content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def get_matching_s3_keys_as_set(bucketname, suffix="") -> set:
"""
Generate the keys in an S3 bucket as set.
:param bucket: Name of the S3 bucket.
:param prefix: Only fetch keys that start with this prefix (optional).
"""
result = set()
for obj in get_matching_s3_objects(bucketname):
... | 8b1c3ece7cecee91fad170663e3963b4909fbcf4 | 41,438 |
def scaled_up_roi(roi, scale: int, shape=None):
"""
Compute ROI for a scaled up image.
Given a crop region in the original image compute equivalent crop in the upsampled image.
:param roi: ROI in the original image
:param scale: integer scale to get scaled up image
:return: ROI in the scaled u... | 24f160bde7f995861aee3f0c20001ce4093aa58a | 41,441 |
def get_rotation(tracker: TrackerComponent):
"""Returns the Euler rotation of the tracker."""
# Data is [0]=side-side [1]=flat [2]=forward-back
if tracker.is_hardware:
torso_state = tracker.get_state('torso')
return torso_state.rot_euler
return (0, 0, 0) | c352c51513abccdbc716cd02d2d04a057a164cfd | 41,442 |
import torch
def lowpass_filtering_in_frequency_domain(
image_grad: torch.Tensor, lowpass: torch.Tensor
) -> torch.Tensor:
"""Applies lowpass filtering in the frequency domain as descibed in Walker
et al. 2019.
Args:
grad (torch.Tensor): gradient
lowpass (torch.Tensor): losspass tenso... | 847d89f9f0078838b594b61df9dd4544cb2bd062 | 41,443 |
def review_detection_html(ibs, image_uuid, result_list, callback_url, callback_method='POST', include_jquery=False):
"""
Returns the detection review interface for a particular image UUID and a list of
results for that image.
Args:
image_uuid (UUID): the UUID of the image you want to review det... | c155f48e2ebc930f9ee9181107ac65ba0b2ea637 | 41,444 |
def mask_label_image(labels: np.ndarray, bg_mask: np.ndarray, bg_label: int = 0):
"""
Mask an input label image and rearrange the label numbers so that
they form the continuous range [0, numlabel].
Note that there is not relabelling of the components, just a
renumbering.
Args:
:param labe... | 3bcc9fb1e65884856105048d42756e03f5062237 | 41,445 |
import torch
def compute_accuracy(
x: Tensor, y: Tensor, m: int, nx: int, c1: int, w: Tensor, b: Tensor
) -> float:
"""Compute accuracy using the given parameters and data.
Args:
x (Tensor): The input tensor (MNIST images)
y (Tensor): The output tensor (a column vector of zeros and ones)
... | eededcbedbf4b0137e16428ab0ed566cb5e6e102 | 41,446 |
def modal(item_id):
"""
Return the information of the specified 'item_id'.
This is so that users can open the correct modal item through AJAX
"""
return jsonify({
"id": item_id,
"name": mysqlcommands.get_item(item_id)[1]
}) | 2f7edf7a7ed61b7ad2e6223b4dc8e267bc2fa8a0 | 41,447 |
import warnings
def get_download_url(data_product_uri):
"""(Deprecated) Get URL for downloading data product identified by data_product_uri."""
warnings.warn("Use user_storage.get_download_url instead.", DeprecationWarning)
return (reverse("django_airavata_api:download_file") + "?" +
urlencode... | c095a2dfe43ffb984d3eb6bbecc64106dd29c5fe | 41,448 |
import re
def get_remote_version_string():
"""
Get the current cvd string from the clamav DNS TXT entry
"""
resolver = Resolver()
resolver.timeout = 5
nameserver = CVDUPDATE_NAMESERVER
record = str(resolver.resolve(CVDUPDATE_NAMESERVER, "TXT").response.answer[0])
versions = re.searc... | c58415d26378a804d0b536d7218f14744a673d93 | 41,449 |
def lit(val):
"""Accept a single item and return the given value."""
return lambda seq: ([val], seq[1:], Status.succeed(where='lit')) | 3cf40630a20ef53e25e67ffe1e0279e9bfafa24e | 41,450 |
def average(data, axis, n):
"""
Averages data along the given axis by combining n adjacent values.
:param data: Data to average along a given axis.
:type data: numpy array
:param axis: Axis along which to average.
:type axis: int
:param n: Factor by which to average.
:type n: int
... | 2f958f48dbf4e14cdcce4c0c06904b7c48007a25 | 41,452 |
def _left_operator(func):
"""Function decorator to treat a method as the left operator."""
def inner(self, other):
"""Decorator wrapper."""
left = self.value
if isinstance(other, NumericType):
right = other.value
else:
right = other
return to_aiid... | 252cd5b7e9031f0598c998b69cc7157dcd747661 | 41,453 |
from typing import Any
def normalize_data_values(type_string: TypeStr, data_value: Any) -> Any:
"""Decodes utf-8 bytes to strings for abi string values.
eth-abi v1 returns utf-8 bytes for string values.
This can be removed once eth-abi v2 is required.
"""
_type = parse_type_string(type_string)
... | 17e4c3342a8d7dbc5a1274b5368357cb66a9b8e0 | 41,454 |
def update_bpt(*args):
"""update_bpt(bpt_t bpt) -> bool"""
return _idaapi.update_bpt(*args) | e02507ec02b11a3fb30fe10d6da584bf9535a65d | 41,456 |
def generate_test_data():
"""
生成测试样本数据，来自函数y=sin(2 * pi * x)
:return: 生成的测试数据集的X向量和Y向量
"""
test_X = np.linspace(0, 1, 4 * data_number)
test_Y = np.sin(2 * np.pi * test_X)
return test_X, test_Y | 9b8e0abbb5b0a68b3fa20105e0e96e9bf40fee6a | 41,457 |
def usaf_station_to_lat_lng(station):
"""Return the latitude and longitude coordinates of the given USAF station.
Parameters
----------
station : str
String representing a USAF Weather station ID
Returns
-------
lat_lng : tuple of float
Latitude and longitude coordinates.
... | 591615783f859be3efe36bb754e8142430d69069 | 41,459 |
def generate_kwargs(gt, m_vir_thresh, SSPs_in=None, SSP_kwargs={}, **extra_kwargs):
"""
Generate kwargs for a GAMMA run.
Example usage:
## Generate tree and SSP input to GAMMA
gt = caga.gamma_tree.load("my_gamma_tree.npy")
mvir_thresh = 1e7
SSPs_in = caga.precompute_ssps... | c9b03fb003d778890f8183b2bf4dd7e5ccfb4dca | 41,460 |
def increase_vectors(vectors):
"""accelerate so that pieces move faster in earlier frames"""
new_vecs = []
for vec in vectors:
new_vecs.append((vec[0]*VEC_GROWTH, vec[1]*VEC_GROWTH))
return new_vecs | 0eaeaa193722b7a135fa7f0d37605d7bf3a7db9e | 41,461 |
def Validate(ciffile,dic = "", diclist=[],mergemode="replace",isdic=False):
"""Validate the `ciffile` conforms to the definitions in `CifDic` object `dic`, or if `dic` is missing,
to the results of merging the `CifDic` objects in `diclist` according to `mergemode`. Flag
`isdic` indicates that `ciffile` is ... | d3828279f9cdfae69690122c82ab50cb40fb9662 | 41,462 |
def tapis_client(x_tapis_token: str = Depends(tapis_token)) -> Tapis:
"""Returns a user Tapis client for the provided token"""
try:
client = _client(x_tapis_token)
except BaseTapyException as exc:
raise HTTPException(
status_code=status.HTTP_401_UNAUTHORIZED,
detail="... | cf9b7a70819c8b1f19da9ae4a40e07417032e0ef | 41,463 |
def default_exchange():
"""Return a default :class:`kombu.Exchange` created from configuration.
Scope: function
This fixture offers a default :class:`kombu.Exchange`.
"""
return Exchange("test-exchange", type="direct") | efff24cd68f6b5bcd2d7628a2bfc399969b64a10 | 41,464 |
from ._array import GeoArray
def to_geo(values):
"""Convert values to GeoArray
Parameters
----------
values : WKT, GeoJSON or Esri JSON in a list
Returns
-------
addresses : GeoArray
Examples
--------
Parse strings
>>> to_geo(['{"x" : -118.15, "y" : 33.80, "spatialRefere... | f0eaa16589489c998109fb9d38df96d82435ac32 | 41,465 |
def build(name, ask=True, **kwargs):
"""
Build the malicious mote to its target hardware.
:param name: experiment name (or absolute path to experiment)
:param ask: ask confirmation
:param path: expanded path of the experiment (dynamically filled in through 'command' decorator with 'expand')
:pa... | 3d1e82946779f298aecb2e90f481588172bbf051 | 41,466 |
def cor(y, z):
"""Compute Pearson's correlation coefficient."""
return np.corrcoef(y, z)[0, 1] | bb7dac07c5070430a2160c85a87fba1a657e0785 | 41,467 |
import torch
def ldot(u, v, keepdim=False):
"""Lorentzian scalar product"""
uv = u * v
uv.narrow(-1, 0, 1).mul_(-1)
return torch.sum(uv, dim=-1, keepdim=keepdim) | 59c26e622ef5ffe94d92a2e8c0fc40d316b58f5b | 41,468 |
def print_qa(questions, answers_gt, answers_gt_original, answers_pred, era, similarity=dirac, path=''):
"""
In:
questions - list of questions
answers_gt - list of answers (after modifications like truncation)
answers_gt_original - list of answers (before modifications)
answers_pr... | b1379067f4677626522989ea5c2888678b50e8dc | 41,469 |
def thumbiconurl(public_path):
"""Get the URL of an icon for filename.
"""
return mimetypeurl(mimetype(public_path)) | 590f1d75f5bb27aed0f0a81dc2b70b940ad9a677 | 41,470 |
def test_depends(func):
"""Decorator to prevent a test being executed in individual mode"""
def invalid(self, test):
if self.test_individual:
test.description = "Invalid"
return test.DISABLED("This test cannot be performed individually")
else:
return func(self... | 4b2db29fc8c0a30ec3a4ec6c3fb93ed958f0094e | 41,471 |
def load(
phono3py_yaml=None, # phono3py.yaml-like must be the first argument.
supercell_matrix=None,
primitive_matrix=None,
phonon_supercell_matrix=None,
is_nac=True,
calculator=None,
unitcell=None,
supercell=None,
nac_params=None,
unitcell_filename=None,
supercell_filename... | ed2c4b2eceb0a7979ab864b8ff357663086dbc5e | 41,472 |
def pluralize(
*, with_quantity: bool = True, with_indicative: bool = False, **word
) -> str:
"""Pluralize a single kwarg's name depending on the value.
``with_indicative`` must be used with ``with_quantity``.
Example
-------
>>> pluralize(object=2)
"2 objects"
>>> pluralize(object=1)... | 9dc4fbe280f4794599f57e7af645d9cac51d655e | 41,473 |
def move_bounds(box, ovl_box, padding=0, axis=None):
"""
given two boxes, return the x and y deltas needed to move the first box to avoid the second.
for simplicity, we chose only one axis, whichever is shorter. Also, only allow positive moves.
can choose axis with axis='y' or axis='x'
""... | 4b3275d97987a95f9962e975ead5f03af3964348 | 41,474 |
def ensure_f(func: Function) -> F:
"""wrap the given function into a F instance"""
if not isinstance(func, F):
return F(func)
return func | 7ea54909bac42c2ade1d1a82ec00c9aff3af7cb6 | 41,475 |
import re
def compiler_call(executable):
""" A predicate to decide the entry is a compiler call or not. """
compilers = [
re.compile(r'^([^/]*/)*([^-]*-)*c(c|\+\+)$'),
re.compile(r'^([^/]*/)*([^-]*-)*g(cc|\+\+)(-\d+(\.\d+){0,2})?$'),
re.compile(r'^([^/]*/)*([^-]*-)*clang(\+\+)?(-\d+(\.... | d8fa6fa22f13b13154579e19a4ab18e016a56caf | 41,476 |
def month_and_year(m=None, y=None):
"""Creates a string from month and year data, if available."""
if y is None:
return "present"
if m is None:
return str(y)
m = month_to_int(m)
return "{0} {1}".format(SHORT_MONTH_NAMES[m], y) | 6c09800c7b7649c983462b0f1d09829d897c4e1b | 41,478 |
def to_bool(a):
"""
a: a str or bool object
if a is string
'true', 't', 'yes', 'y', '1', 'ok' ==> True
'false', 'f', 'no', 'n', '0' ==> False
"""
if isinstance(a, bool):
return a
elif a is None:
return False
elif isinstance(a, (int, float)):
return b... | 00cb99d07ba6dc2b149f52930e9916cabb7fb872 | 41,479 |
import six
def find_nova_host(address, config):
"""See if a nova instance has the supplied address."""
nova = client.Client(config['username'],
config['password'],
config['tenant_id'],
config['authurl'],
region... | 11dc70d022996f8134d57a4507f8b495a7b23402 | 41,480 |
from typing import Iterable
def camera_matrix(fov=const.CAMERA_FOV, resolution=const.CAMERA_RESOLUTION, alpha=0):
"""Returns camera matrix [1] from Field-of-View, skew, and offset.
Parameters
----------
fov : float, Iterable
Field-of-View angle (degrees), if type is Iterable it will be interp... | 3817ea4f890b423757fb4c29715697f9df5decf4 | 41,481 |
import random
def LoadUserAgents(uafile):
"""
uafile : string
path to text file of user agents, one per line
"""
uas = []
with open(uafile, 'rb') as uaf:
for ua in uaf.readlines():
if ua:
uas.append(ua.strip()[1:-1-1])
random.shuffle(uas)
return ... | 3942f92c11e16ff979c1ef80552a1340bc149c16 | 41,482 |
def comment_threads_list(key, part, allThreadsRelatedToChannelId=None,
channelId=None, id=None, videoId=None,
maxResults=None, moderationStatus=None, order=None,
pageToken=None, searchTerms=None, textFormat=None):
"""Returns a list of commen... | 74ca3da4aee410ed38916ed4193860715ea01614 | 41,483 |
def gaussianBlur(img):
"""Applies gaussian filter to a grayscale image"""
return cv2.GaussianBlur(img, (5, 5), 0) | e0a28f50c792ec09a6660beedc2d9e6e1df0d59b | 41,484 |
def fix_month(bib_str: str) -> str:
"""Fixes the string formatting in a bibtex entry"""
return (
bib_str.replace("{Jan}", "jan")
.replace("{jan}", "jan")
.replace("{Feb}", "feb")
.replace("{feb}", "feb")
.replace("{Mar}", "mar")
.replace("{mar}", "mar")
.r... | 9bdcb06dc43a6d6748af20d5279ca38ec6aa1d0a | 41,485 |
def multipart_form_message(media, form_data={}):
"""Return a MIMEMultipart message to upload encoded media via an HTTP form POST request.
Args:
media: a list of (encoded_data, filename) tuples.
form_data: dict of name, value form fields.
"""
message = MIMEMultipart('form-data', None)
if form_data:
... | e8c27c3baf0e0692a017de2bfb3a08755cecfb4a | 41,486 |
def make_well2file_dict(data):
"""Create a dictionary mapping wells to image files.
Parameters
----------
data : pandas data frame
A data frame from feature computation.
Returns
-------
well2file : dictionary, {(int, string): string}
A dictionary keyed by a (plate, well) tu... | 0baaed068a9b84596749a89bc37cae10f8e3950d | 41,487 |
from typing import Optional
def create_balloon(
x: units.Distance = units.Distance(m=0.0),
y: units.Distance = units.Distance(m=0.0),
center_lat: float = 0.0,
center_lng: float = 0.0,
pressure: float = 7_000.0,
power_percent: float = 0.95,
date_time: Optional[dt.datetime] = None,
time_... | e776684b8aa648acfd18f1e026aec296e4c39329 | 41,488 |
def calculate_reference_sample(experiment: FCSExperiment,
exclude_samples: list) -> str:
"""
Given an FCS Experiment with multiple FCS files, calculate the optimal reference file.
This is performed as described in Li et al paper (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5... | 0058d26f7331b5fc1075af1a3a394bc6c64ba2b2 | 41,490 |
def get_visibles(photos, user):
"""
get only photos visible for user
"""
return photos.filter(
Q(owner=user) |
Q(shared=user)
) | 657c336244d2d34b76c12f8964389be4a8d1a300 | 41,491 |
import asyncio
async def changeTeam(team, member):
"""enleve tous les rôles d'un utilisateur sauf '@everyone' et '@modo' puis place le member dans la team appropriée
return 1 si le changement est effectif 0 sinon"""
team = teamName(team)
assert team
assert isinstance(member, discord.Member)
f... | a6accb214e1e09bae59fc4b495f95d019444ac01 | 41,492 |
def dataqc_spiketest(dat, acc, N=5, L=5, strict_validation=False):
"""
Description:
Data quality control algorithm testing a time series for spikes.
Returns 1 for presumably good data and 0 for data presumed bad.
The time series is divided into windows of len L (an odd integer
... | c2c496c6260095b8887b5105ec4305af74959c17 | 41,493 |
def pad(text: str, width: int, align: str = '<', fill: str = ' '):
"""
pad the string with `fill` to length of `width`
:param text: text to pad
:param width: expected length
:param align: left: <, center: ^, right: >
:param fill: char to fill the padding
:return:
"""
assert align in ... | 74befd22927438961b85e370ed16239d7df52707 | 41,494 |
def coins_to_numpy(game):
"""Game coins info to numpy array
Parameters
----------
game : camel up game
Camel up game class
Returns
-------
array
Numpy array
"""
return np.array(
[(key[0], key[1]["coins"]) for key in [*game.player_dict.items()]],
dty... | 2c0614d008f43bbb33e66e6cad169e4e512a6cd9 | 41,495 |
import select
def edit_mode(obj):
"""
Select the object and change to edit mode
:param obj: string, name of object
:return: bpy data object
"""
bpy.ops.object.mode_set(mode='EDIT')
o = select(obj)
bpy.ops.object.mode_set(mode='EDIT')
bpy.ops.object.mode_set(mode='EDIT')
return ... | 046c65e6b2beda097776cecb35e25fa8b64314e5 | 41,496 |
async def test_cli(
aiohttp_client,
otupdate_config,
monkeypatch,
version_file_path,
mock_name_synchronizer,
):
"""
Build an app using dummy versions, then build a test client and return it
"""
app = buildroot.get_app(
name_synchronizer=mock_name_synchronizer,
system_... | 616c900b2f122ec04cfd3586d9de2937bf9c0d6d | 41,497 |
def check_xform(path_to_xform):
"""
Returns an array of warnings if the form is valid.
Throws an exception if it is not
"""
# provide useful error message if java is not installed
if not _java_installed():
raise EnvironmentError("pyxform odk validate dependency: java not found")
#re... | ac31946110fefc462ebc0e9bc9763840f19a77bb | 41,498 |
import torch
def slerp(val, low, high):
"""
val, low, high: bs x frames x coordinates
if val == 0 then low
if val == 1 then high
"""
assert low.dim() == 3, low.dim()
assert val.dim() == 3, val.dim()
assert high.dim() == 3, high.dim()
low_norm = low / torch.norm(low, dim=2, keepdim=... | 96a74c366139f3f617676e5e011884f698569b97 | 41,499 |
def canonical_version(versionstr, release_type='python-service'):
"""Given a version string verify it is in the canonical form."""
errors = list(validate_version(versionstr, release_type))
if errors:
raise ValueError(errors[-1])
return versionstr | caa578f41b7046e88a9a174221d9d1af9b378955 | 41,500 |
def CircAperture(Fin, R, x_shift = 0.0, y_shift = 0.0):
"""
*Inserts a circular aperture in the field.*
:param R: radius of the aperture
:type R: int, float
:param x_shift: shift in x direction (default = 0.0)
:param y_shift: shift in y direction (default = 0.0)
:type x_shift: int, floa... | bad700cd1e1c8f8767ab52b1444d4088ca30f6b2 | 41,501 |
import re
def extract_access_token(request):
"""
Get the access token using Authorization Request Header Field method.
Or try getting via GET.
See: http://tools.ietf.org/html/rfc6750#section-2.1
Return a string.
"""
auth_header = request.META.get('HTTP_AUTHORIZATION', '')
if re.compi... | 6c6d36bdd4965796bacdca7d13a2fc6ef2189299 | 41,502 |
def param_is_numeric_and_simple(p):
"""
Test whether a parameter is numeric and, if it is a string, that it doesn't
contain scientific or uncommon notation.
:param p: An input parameter
:return:
"""
if isinstance(p, str):
return str_is_numeric(p)
else:
return param_is_num... | 3e85671d84d865767c306199c98f1c1c2b151a29 | 41,503 |
def DefineNor(height, width):
"""
Generate Nor module
I0 : Array(width, Bit), I1 : Array(n, Bit) -> O : Array(n, Bit)
"""
T = Array(width, Bit)
class _Nor(Circuit):
assert height > 1 and height <= 4
name = 'Nor%dx%d' % (height, width)
if height == 2:
IO ... | b7de2c1f5af67d96aed3e840f20bcce9d3ac4023 | 41,504 |
def HMA(data, period=16):
"""
Hell's Moving Average
HMA indicator is a common abbreviation of Hull Moving Average.
The average was developed by Allan Hull and is used mainly to identify the current market trend.
Unlike SMA (simple moving average) the curve of Hull moving average is considerably s... | 604bc4da85d3cb5220db6460caf84f90ff8cc401 | 41,505 |
import torch
def create_input(shape):
"""Create a random input tensor."""
return torch.rand(shape).float() | 88a907bae19882a4a7c1a0b819eb0deccb065752 | 41,506 |
def input_thing():
"""输入物品信息"""
name_str, price_str, weight_str = input('物品名称，价格，重量: ').split()
return name_str, int(price_str), int(weight_str) | d48452a942263ae522e93474c6cc4a5cdd9e097c | 41,507 |
def perpendicular_vector(R, max_alt):
"""
Generates a viewing and tangent vectors
perpendicular to a sphere of radius R
"""
return np.array([0, R+max_alt*2, 0]).reshape(3, 1), \
np.array([0.0, 0, 0]).reshape(3, 1) | 5a08c9d935d05ccee99666627a359ee5c6163147 | 41,508 |
import base64
import time
def enroll(video):
"""
Params:
video: base64 encoded data
"""
try:
setup_directories()
content = base64.b64decode(video)
filename = frappe.session.user+".mp4"
OUTPUT_VIDEO_PATH = frappe.utils.cstr(frappe.local.site)+"/private/files/user/"+filename
with open(OUTPUT_VIDEO_PATH,... | 6bc989f656f123613b85d61f3217f39a0a5d993f | 41,509 |
def nonzero_maximum_box(input: Image, flag_dst: Image, destination: Image = None) -> Image:
"""Apply a maximum filter (box shape) to the input image.
The radius is fixed to 1 and pixels with value 0 are ignored.
Note: Pixels with 0 value in the input image will not be overwritten in the
output im... | a28e2fe91e712ca95ed66670465e72033d756a7e | 41,510 |
def linear_layer(input_tensor, classes, train,
summary=False, rf=1, data_format="NCHW"):
"""Builds a logit layer that we apply the softmax to, with variables
Args:
input_tensor: input tensor
classes: Number of classes to classify in the output
train: If we want to train this layer or no... | d297314d5af49065f19fda689939d6216fe34734 | 41,511 |
def get_information(key):
"""
Obtains a variety of runtime information about CMSElemental.
"""
key = key.lower()
if key not in __info:
raise KeyError(f"Information key '{key}' not understood.")
return __info[key] | bfe75ac86a9231629fbf3472cbdddfd1e4015787 | 41,513 |
import string
import random
def gene_text(number=6):
"""生成随机字符"""
source = string.ascii_letters+string.digits
return ''.join(random.sample(source,number)) | 40970c8b938797243d7626ebad48e78116df657a | 41,514 |
def gen_snippet(snippet, config):
"""Renders a config snippet.
"config" represents the portion of the YAML
file applicable to this snippet"""
template = ENV.get_template(snippet + ".j2")
return template.render(config=config) | cb740b483204b7c49647414ae24145475a0d9b6f | 41,516 |
import requests
from bs4 import BeautifulSoup
from datetime import datetime
def get_info_from_notice(notice):
"""
# 글 제목, 글 작성자
if(str(notice).find('font')!=-1):
print('정상작동')
title = notice.find('font').text
else:
print('에러')
writer = notice.find('td', attrs={'class'... | a063bc6cbbcc18dc49c5141d235373e65deed810 | 41,517 |
def thead(content, accesskey:str ="", class_: str ="", contenteditable: str ="",
data_key: str="", data_value: str="", dir_: str="", draggable: str="",
hidden: str="", id_: str="", lang: str="", spellcheck: str="",
style: str="", tabindex: str="", title: str="", transl... | aa288162d200733761d3b84f81234fb1b05dfe7d | 41,519 |
from typing import Union
from typing import Type
def get_msf_session_id(session_name: str, plan_execution_id: Union[Type[int], int]) -> str:
"""
Get a Metasploit session ID by the defined session name
:param str session_name: Session name provided in input file
:param int plan_execution_id: ID of the... | 27ba07da3c7330cf752a02b9737f153e258d3a25 | 41,520 |
def compute_margin(
input_fn, root_dir, model_config, sess=None,
batchsize=50, dataset_size=50000):
"""Compute the margins of a model on all input data.
Loads a given model from given directory and load the parameters in the given
scope. Iterates over the entire training dataset and computes the upper bo... | 717e9a3cf03ab4f7594a4f082a7cc2699b0bd75b | 41,521 |
def in_notebook():
"""Determine whether code is running in a Jupyter Notebook shell.
Returns
-------
ip : bool
True if running in a notebook shell, False otherwise
"""
try:
# See https://stackoverflow.com/questions/15411967
shell = get_ipython().__class__.__name__
... | f3b77ecb41c40b8bc8f558441374fc35949c331d | 41,522 |
import tokenize
from operator import getitem
import math
def groupby_agg(
ddf,
gb_cols,
aggs_in,
split_every=None,
split_out=None,
dropna=True,
sep="___",
sort=False,
as_index=True,
):
""" Optimized groupby aggregation for Dask-CuDF.
This aggregation algorithm only sup... | 67635be47d6495f75e57649ca565dd454143853a | 41,523 |
def put_op(form):
"""Annotation for a callable function specifying that it is a PUT :class:`Op`."""
return op.Put(form) | c90562f01a64bed25a576ea503f65e93feb0f7aa | 41,524 |
def str_to_tstamp(time_value):
""" Convert date string to timestamp
Args:
time_value (Union[str, int]): date string in any format supported by dateutils.parser.parse
Returns:
int: timestamp
"""
if type(time_value) is int:
# If we got int - consider it being timestamp already
... | 758216ec302d87adff5be5673c89476f164c053f | 41,525 |
def merge_UserInput_with_SourceDF(user_df: pd.DataFrame, source_df: pd.DataFrame):
"""
Reads the user feature dataset and merges that to the end of the source dataset. Removes the duplicates
found in the source with the users dataset. It returns a tuple. first element is the merged dataset
and the secon... | a5c16112a43985ae9c56ff017a825ea126e2ad52 | 41,526 |
from datetime import datetime
def get_effective_data_length(user_code, span_min=10, best_effort=False, exclude_capped=False,
start_time=None, end_time=None, min_num_samples=100):
"""
To compute the length of the data by the user, based on `ActionLog`. Our system establishes
a connection (from app ... | 9307e0b142775430f088249f9ae37ef3b549c875 | 41,527 |
def lorenz_curve(data: pd.Series) -> pd.Series:
"""
Calculates the values for the lorenz curve of the data.
For more information see online `lorenz curve
<https://en.wikipedia.org/wiki/Lorenz_curve>`_.
Args:
data: sorted series to calculate the lorenz curve for
Returns:
the va... | 0a430c60f61addb286d0d29c9358906d810bae12 | 41,528 |
from typing import Iterable
def cut_solid(solid, cutter):
"""
Performs a boolean cut of a solid with another solid or iterable of solids.
Args:
solid Shape: the Shape that you want to cut from
cutter Shape: the Shape(s) that you want to be the cutting object
Returns:
Shape: the... | 44f2f039a4bbeba986f4195f9294369f11f59531 | 41,529 |
def _find_stub_degree(branch, bus_id):
"""Find degree of stubbiness, and stub branches.
:param pandas.DataFrame branch: branch DataFrame from Grid object.
:param int bus_id: index of bus to find subbiness of.
:return: (*tuple*) -- tuple containing:
stub_degree (*int*) -- How stubby (non-negativ... | 4036fb131674401441ac5387923a78a37378ace2 | 41,531 |
def add_data_to_list(twitter_return):
"""
Extract the data from the twitter_return dictionary and place in a list
"""
twitter_dict = twitter_return ['response_dict']
# Grab the twitter data
twitter_data_list=twitter_dict['data']
return twitter_data_list | 9e2a2a5e22926b604856c1ec1ae20ebf765b8610 | 41,532 |
def get_issue_by_url_seg(url_seg, url_seg_issue):
"""
Retorna um número considerando os parâmetros ``iid`` e ``kwargs``.
- ``url_seg``: string, contém o seguimento da URL do Journal;
- ``url_seg_issue``: string, contém o seguimento da URL do Issue,.
"""
journal = get_journal_by_url_seg(url_seg... | 8b7f167a0bebf7cd4484a4da24df142e70c60cad | 41,533 |
def negentropy(p):
"""
Entropy which operates on vectors of length N.
"""
# This works fine even if p is a n-by-1 cvxopt.matrix.
return np.nansum(p * np.log2(p)) | 90b271589ba25d86420ad8413cd83fa304d75d24 | 41,534 |
def check_n_files(subject, collector, keep, n_file=1):
"""
Organise download path per subject for the two sessions.
If the number of total file is not the same as expected, drop the subject.
Parameters
----------
subject: str
Subject ID.
collecter: dict
Dictionary collecti... | 56e9ec830d573b8fc8f5c50c1b6bc126a44653a7 | 41,535 |
def create_resource_id_tag(**kwargs):
""" create tag via resource id """
session = kwargs.get('session', {})
resource_id = kwargs.get('resource_id', {})
tag_name = kwargs.get('tag_name', {})
tag_value = kwargs.get('tag_value', {})
try:
tag_session = session.get_client_session(service='ec... | 2eef38417ce22520267f31b1b24297f914e2392a | 41,538 |
def ErrorReset(*args):
"""ErrorReset()"""
return _gdal.ErrorReset(*args) | ea013beb93eed6f2d7f91f1a9d1cab5e6692769f | 41,539 |
from typing import Dict
def get_noise_range_pcts(db_range_exps: dict, length: float) -> Dict[int, float]:
"""Calculates percentages of aggregated exposures to different noise levels of total length.
Note:
Noise levels exceeding 70 dB are aggregated and as well as noise levels lower than 50 dB.
Re... | 723c7e45a24c149df6f5f19b3f8aabb1f8d5b184 | 41,540 |
def update_info():
"""
用户信息更新
"""
username = request.get_json()['username']
email = request.get_json()['email']
password = request.get_json()['password']
words_book = request.get_json()['words_book']
words_num = request.get_json()['words_num']
words_num = int(words_num) if words_num ... | d997cf23ec0320b4b583f35431df11877116ecd2 | 41,541 |
def read_terminals(terminals_file=DEFAULT_TERMINALS_FILE):
"""Returns all terminals in order that they are coded in file_train. """
terminals = read_json(terminals_file)[:50000 - 1]
return [EMPTY_TOKEN] + terminals + [UNKNOWN_TOKEN] | 6514a760f4ed2a49be97230ce6315c0d8bc27d8c | 41,542 |
def _sync_engagement_db_dataset_to_coda(engagement_db, coda, coda_config, dataset_config, cache, dry_run=False):
"""
Syncs messages from one engagement database dataset to Coda.
:param engagement_db: Engagement database to sync from.
:type engagement_db: engagement_database.EngagementDatabase
:para... | e56e967a96348760119e9194909fdbd2ae65d6fb | 41,543 |
def group_by_first(pairs):
"""Return a list of pairs that relates each unique key in the [key, value]
pairs to a list of all values that appear paired with that key.
this documentation should state why this should normally be used; what should this func normally be used for?
Arguments:
pairs -- a se... | 430f6cb9c8c3fc0b6f6b5078f383c5bbb7420dfe | 41,544 |
def accepts_environment(func):
"""Allows defining an action function that accepts only theTrailEnvironment and doesn't accept a context.
Example:
@accepts_environment
def action_function_taking_only_environment(trail_env):
# Do something with trail_env
pass
"""
@wraps(func)
... | 8d6ce250e6bd22e6ec110aded195dfd63e4fe286 | 41,545 |
def film_layer(incoming, gamma, beta, name='film'):
"""
FiLM layer
:param incoming: incoming tensor
:param gamma: incoming gamma
:param beta: incoming beta
:param name: (string) name scope
:return:
"""
with tf.name_scope(name):
# get shape of incoming tensors:
in_shap... | 0617da38dabe08cdbde762b20f2f1d9f75d9256c | 41,546 |
def _score_lcs(target_tokens, prediction_tokens):
"""Computes LCS (Longest Common Subsequence) rouge scores.
Args:
target_tokens: Tokens from the target text.
prediction_tokens: Tokens from the predicted text.
Returns:
A Score object containing computed scores.
"""
if not target_tokens or not pr... | 666cc0761d0bbd221ccd09106d16073c323d42d1 | 41,547 |
def reshape_t(x, shape):
"""Work around fact that x.reshape(()) doesn't work"""
if shape != ():
return x.reshape(shape)
else:
return x[0] | 579a63afd05ff86093903e160db16266e2bb2125 | 41,548 |
import ctypes
def make_shared_array(np_array: np.ndarray) -> mp.Array:
""" shared array"""
flat_shape = int(np.prod(np_array.shape))
shared_array_base = mp.Array(ctypes.c_float, flat_shape)
shared_array = np.ctypeslib.as_array(shared_array_base.get_obj())
shared_array = shared_array.reshape(np_arr... | 4b1f7ff98c82506c5f04631f4d2211d4e8ca990c | 41,549 |
def _create_core_state_space(optim_paras, options):
"""Create the core state space.
The state space of the model are all feasible combinations of the period,
experiences, lagged choices and types.
Creating the state space involves two steps. First, the core state space is created
which abstracts f... | 6f33032212e61d69e11a616f132961f6f70ae373 | 41,550 |
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