content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def filter_sides(segmentation):
"""Remove hedges on left and right hand side.
Also remove anything from the edge of the hedge
to the closest edge of the image.
"""
ydim, xdim = segmentation.shape
mid_point = xdim // 2
for i in segmentation.identifiers:
region = segmentation.region_b... | 4d02903b4cadc39fb3461fdc13916cc7233ad39d | 3,610,219 |
from datetime import datetime
def log_file_name(extension):
"""
Create a file name in the logfiles directory, based on current data and time
Requires the computer to have an RTC or synched clock
"""
now = datetime.now()
# Linux
file_name = '%0.4d%0.2d%0.2d-%0.2d%0.2d%0.2d' % (now.year, now... | 795ab0623ee6a563cfc4e2531cd8745f0ff2fac3 | 3,610,220 |
def arc(data: bytes) -> int:
"""
Compute a CRC-16 checksum of data with the arc algorithm.
:param bytes data: The data to be computed
:return: The checksum
:rtype: int
:raises TypeError: if the data is not a bytes-like object
"""
_ensure_bytes(data)
return _crc_16_arc(data) | 1ce9de456d04b1a8b060a1cb83ffd1b457bdae86 | 3,610,221 |
def check_replication(master_vals, slave_vals, options):
"""Check replication among a master and a slave.
master_vals[in] Master connection in form: user:passwd@host:port:socket
or login-path:port:socket
slave_vals[in] Slave connection in form user:passwd@host:port:socket
... | dde3878a9afde2bd12209da20da5681fd64ba77c | 3,610,222 |
def _incremental_mean_and_var(X, last_mean, last_variance, last_sample_count):
"""
Note. Most of this script is taken from scikit-learn, except for the last line.
--- Original doc ---
Calculate mean update and a Youngs and Cramer variance update.
last_mean and last_variance are statistics compute... | 55eacfc7905eae1b2608314a651c25f2707a3ac7 | 3,610,223 |
def _calculate_expected_result(
dist_per_cell, numeric_values, numeric_values_scale, input_mask_float, logits_aggregation, config
):
"""
Calculates the expected result given cell and aggregation probabilities.
Args:
dist_per_cell (`tfp.distributions.Bernoulli`):
Cell selection distr... | b282c538b495989b6c4066b8f99d72fc4810845e | 3,610,224 |
def fit_unbinned(f_likelihood, data, start_guess, min_method=None, bounds=None):
"""
unbinned max likelihood fit to data with given likelihood func
"""
if method is None:
method="L-BFGS-B" # minimization method, see docs
result = minimize(
neg_log_like, # function to minimize
... | ac20d2fe30aae1922190fee7a38d204a1612a2ad | 3,610,225 |
def load_data(n_pca=3):
"""Data Loader
:param n_pca: number of pca components, defaults to 3
:type n_pca: int, optional
"""
path = f'../dataRBC/RBC_r28L_T100R100_pca{n_pca}_enc_data.txt.gz'
traj_data = pd.read_csv(path, header=None).values
traj_data = traj_data.reshape(-1, 200, n_pca)
... | e7e7c454da1aebb2af83f800e488cfab3296b110 | 3,610,226 |
def delete_attachment(self, request, form):
""" Delete a notice attachment. """
layout = Layout(self, request)
notice = self.linked_official_notices[0]
if notice.state == 'accepted' or notice.state == 'published':
if not request.is_secret(self):
request.message(
_("... | 6715c1079dfabd4e43e97a88ff4b5c75c563b00c | 3,610,228 |
def geoloc(ip_address: str) -> dict:
""" Return {'lat':, 'lon':} values for {ip_address} """
ip_details = method_ipinfo(ip_address)
return {'lat': ip_details['latitude'], 'lon': ip_details['longitude']} | 1f98d69dd9d239f27c85e490cc69d5a27aac9184 | 3,610,229 |
def TreeImportanceArray(reg):
"""Get important array if `reg` is tree regression."""
return reg.feature_importances_ | 59f3b0bcc9a4c60af71b62163e3e087137c64f49 | 3,610,230 |
def _get_test_stats_with_mi(feature_names):
"""Get stats proto for MI test."""
result = statistics_pb2.DatasetFeatureStatistics()
for feature_name in feature_names:
feature_proto = text_format.Parse(
"""
custom_stats {
name: "max_sklearn_adjusted_mutual_information"
... | d5ebdd6a55ca0af03b1076ecc5fd4741f296ec19 | 3,610,231 |
def ride(self: Client, riders_or_rides: str) -> RideProxy:
"""Delegates to a
:py:class:`mcipc.rcon.be.commands.ride.RideProxy`
"""
return RideProxy(self, 'ride', riders_or_rides) | 209f5804eaf7a6e566fd13acc484abf73802d47c | 3,610,232 |
def process_data(event_id, st, sampling_rate, pre_filt=(1.2, 2, 8, 10), water_level=100,
folder_name="default_folder", save_processed=True):
"""
Function to process the raw data stream
Args:
event_id (str): Event ID -> Ideally should be time stamp YYYY-MM-DDTHH:MM:SS.000
st ... | bf2b1f829bb0211d9d1729d8feb4534cb01b236e | 3,610,233 |
from typing import Any
from typing import Dict
def _check_headers(headers: Any) -> Dict:
"""Check headers format an validate content type.
:param headers: configured headers
:return Dict: request headers
"""
if headers is None:
headers = {}
if 'Content-Type' not in headers.keys():
... | f7dc965ffd740ea94ca3485f455cf6427ebc16d8 | 3,610,234 |
def average_test_disorder(data, test_classifier, target_classifier):
"""Given a list of points, a feature-test Classifier, and a Classifier
for determining the true classification of each point, computes and returns
the disorder of the feature-test stump."""
test_disorder = 0
test_classifications = ... | 555b55c58cfa956642d6b4f53afca07a999a33b1 | 3,610,235 |
import signal
def seed_initial_offsets_peaks(y, noise, rect_area=500, prominence_knockdown_factor=0.03):
"""
Generate the locations of the seeds for the initial fit. Place a seed at each of the peaks.
Determine peak location from smoothed version of signal. Smooth signal by cross correlating it with rect.... | e7b4f572cedf5ef37e5bc0c3a6f724704c212f16 | 3,610,237 |
def ReadNetString(fp):
"""Reads a net string from the File object fp, returning the string in
unicode.
A net string has the format <len>:<str>,
where <len> is decimal of the length of <str>, and comma ends the string.
Returns:
The unicode string contained in the netstring, or '' if... | 9805367388fea261df94209482f3d496ef6e749b | 3,610,238 |
def to_str(obj):
"""Attempts to convert given object to a string object
"""
if not isinstance(obj, str) and PY3 and isinstance(obj, bytes):
obj = obj.decode('utf-8')
return obj if isinstance(obj, string_types) else str(obj) | 1123f73fff9b0eebe3a6d29f2768f0459e0d83f2 | 3,610,239 |
def get_middle_value(my_list):
"""Return the middle value from a list after sorting.
:param list my_list: List of sortable values"""
return sorted(my_list)[len(my_list) // 2]
"""Convert an integer resolution in base-pairs to a nicely formatted string.
:param int window_size: Integer resolution ... | 53e8724f1709429707766db45c34ebd0db62a686 | 3,610,240 |
import math
def ll2m(lat, lon):
"""Lat/lon to meters"""
x = lon * 20037508.34 / 180.0
y = math.log(math.tan((90.0 + lat) *
math.pi / 360.0)) / (math.pi / 180.0)
y = y * 20037508.34 / 180
return (x, y) | f998cb7af707d56c9dd6e7a26b8d165f392e07f3 | 3,610,241 |
def bilinterp(x, y, nx_tuple, ny_tuple, x_tuple, y_tuple, fxy):
"""
Bilinear interpolation: Given nx-tuple + 1 x-points,
ny-tuple + 1 y-points, x_tuple and y_tuple,
routine finds f(x, y) = fxy at (x, y) in (x_tuple, y_tuple).
Assumes x_tuple and y_tuple are increasing arrays.
"""... | ee6ffb312cb0a7af3cff524aa366e71f176158f8 | 3,610,242 |
def get_version():
"""Return version of the dynamic link library.
Wraps:
int DWGetVersion();"""
return _get_version() | a99b2c66124f14b04c476b888663ffd7b38a61ff | 3,610,243 |
def edu_plotter(func):
"""Decorator to apply to all plotting functions in OGGM-Edu.
Parameters
----------
func : function
the function or method to decorate
Returns
-------
the decorated function
"""
@wraps(func)
def context_wrapper(
*args,
sns_context=... | d44a63d1c62f5107eb9cbedd89b3c3634bc60a00 | 3,610,244 |
def load_sample_data(name):
"""
Load an example dataset from the GMT server.
The data are downloaded to a cache directory (usually ``~/.gmt/cache``) the
first time you invoke this function. Afterwards, it will load the data from
the cache. So you'll need an internet connection the first time around... | 73ffa2caa4106f97d88766214756fbf6347f4787 | 3,610,245 |
def rip_svgi(content: str, embed_styles: bool = False) -> str:
"""
Rips SVG content (single diagram) and scripts for interaction out of HTML
:param content: HTML page content in text format
:param embed_styles: If specified as True then mentioned styles would be downloaded and embedded into SVG
... | d5472b86be70e138128ff527f388a9b1ffa2602d | 3,610,246 |
def get_info(request):
"""
Obtiene
"""
info = "Backend"
if UserToken.get_headquar_id(request.session):
try:
sede = Headquar.objects.get(
id=UserToken.get_headquar_id(request.session))
info = "%s-%s" % (sede.enterprise.name, sede.name)
except:... | fbfdf8ce2a802af374b0004bb0e6029849c38b9d | 3,610,247 |
from typing import Sequence
def prune_by_lbh(seq_list: list, seq_length: int, q: Sequence, kim_reduction: float = 0.75,
keogh_reduction: float = 0.25):
"""
Prune the sequences based on LB_Kim and LB_Keogh lower bound. First the sequences are pruned using LB_Kim
reduction factor and then u... | c2ed7e88f9597e9f27ed1902fca858a35e028ff3 | 3,610,248 |
def keyDataIdsInit():
"""
Initializes the key data klasses. This function is called from the init
function and the application should not call it directly.
Returns : 0 on success or a negative value if an error occurs.
"""
return xmlsecmod.keyDataIdsInit() | a2f254c8b0655cea68f6a91092ac0b7697f99df2 | 3,610,249 |
import numpy
def _image_to_ground_plane_perform(r_tgt_coa, r_dot_tgt_coa, arp_coa, varp_coa, gref, uZ):
"""
Parameters
----------
r_tgt_coa : numpy.ndarray
r_dot_tgt_coa : numpy.ndarray
arp_coa : numpy.ndarray
varp_coa : numpy.ndarray
gref : numpy.ndarray
uZ : numpy.ndarray
R... | d325471ce2f21562dfd38e536ce77eb215069349 | 3,610,251 |
def encode_string_text(text):
"""Replace special symbols with corresponding entities or magicwords."""
text = text.replace("<", "<")
text = text.replace(">", ">")
text = text.replace("[", "[")
text = text.replace("]", "]")
text = text.replace("{", "{")
text = text.replace(... | c7887934983efda3a0d1e06451ccd85cab529a30 | 3,610,252 |
def compute_input_planes(input_channels, merging_strategy, inputs, abs_nodes):
"""Compute the number of input planes."""
if len(inputs) == 0: # this is an input node
return input_channels
inplanes = 0
for i in inputs:
if merging_strategy == EdgeMerge.CAT:
inplanes += abs_nod... | a6f163a9891f77ba58e06905d3ed03fe9e7259eb | 3,610,253 |
def test_01_setup():
"""
sample init init attr, state, action space
:return:
"""
names = ['gender', 'age']
vals = {'gender': ['M', 'F', 'U'],
'age': ['0-19', '20-29', '30-39', '40-49', '50-59', '60-69', '70-*']}
attr_set = AttrSet(names, vals)
state_set = StateSet(['date', '... | ce487a5287859ea1502aea0090df90f5a0769036 | 3,610,254 |
def make_aware(value, timezone=None):
"""
Make a naive datetime.datetime in a given time zone aware.
:param value: datetime
:param timezone: timezone
:return: localized datetime in settings.TIMEZONE or timezone
"""
if timezone is None:
timezone = TIMEZONE
# Check that we won't... | 8012d14a84bf44f14454f5bf02f4ec93d31668cf | 3,610,255 |
from typing import Tuple
def parse_reflections_array(array: np.array) -> Tuple:
"""
Helper method for parsing reflections without exporting to ".CSV"
Parse an reflection array of GSASII defined as:
index explanation
0,1,2 h,k,l (float)
3 (int) multiplicity
4 (float) d-space, Å
5 (floa... | a20e11499b6baba9c6c6631441cd457a88bac5b9 | 3,610,256 |
def get_dbconn(db_dsn):
"""Connects to the MongoDB server and returns a database handler."""
def _ensure_indexes(db):
"""
Ensures that an index exists on specified collections.
Definitions:
index_by_collection = {
'collection_name': [
('field_name_1'... | f4b074547ce539865f17cee302feae0ca4bbd0d2 | 3,610,257 |
def _params_to_ints(qs):
"""Convert a (string) list of string ids to a list of integers"""
return [int(str_id) for str_id in qs.split(',')] | 7568eeb6cf28f1c8e696e2fab6e7a89dcbbc07fc | 3,610,258 |
import typing
import json
def _prepare_hyperparams(free_hyperparams: typing.Sequence, hyperparameter_values: typing.Dict) -> typing.Tuple[typing.Sequence, typing.Set[str]]:
"""
Values in ``hyperparameter_values`` should be serialized as JSON, as obtained by JSON-serializing
the output of hyper-parameter's... | 90a42428d33c6931622258691d92e82642dfa49e | 3,610,259 |
from typing import List
def est_croissante2(l : List[float]) -> bool:
""" ... cf. ci-dessus ...
"""
# Résultat
b : bool = True
# Indice courant
i : int = 0
while (i < len(l) - 1) and b:
b = l[i] < l[i + 1]
i = i + 1
return b | 74357fe91d42b3cb0d95e09346504b0701ab7164 | 3,610,260 |
def compose(f, g):
"""
Compose two filter f and g.
:param f: Outer filter function.
:type f: filter function.
:param g: Inner filter function.
:type g: filter function.
:return: lambda x: f(g(x))
:rtype: filter function.
"""
def filter_fn(df):
df = g(df)
if len... | d90cda63eb365219ce5f454265036c7d977da216 | 3,610,261 |
def Device(device_name):
"""Returns the taurus device for the given device name
It is a shortcut to::
import taurus.core.taurusmanager
manager = taurus.core.taurusmanager.TaurusManager()
factory = manager.getFactory()
device = factory.getDevice(device_name)
:param device_... | 834baf071ab408e9150cc803a317f151554950cb | 3,610,262 |
def load_data(self, name):
"""Load data given a data path.
This is a low level method that will search through the various
search paths until it's able to load a value. This is typically
only needed to load *non* model files (such as _endpoints and
_retry). If you need to load model files, you sho... | 94e75787fa72b91ea5e27e8cd076b36037044962 | 3,610,263 |
def stop_list_to_link_list(stop_list):
"""
[a, b, c, d] -> [(a,b), (b,c), (c,d)]
"""
return list(zip(stop_list[:-1], stop_list[1:])) | 49046e60664cd9c19ab55c1254684932d937531a | 3,610,264 |
from typing import Union
def compare(A: Mv, B: Mv) -> Union[Expr, int]:
"""
Determine if ``B = c*A`` where c is a scalar. If true return c
otherwise return 0.
"""
if isinstance(A, Mv) and isinstance(B, Mv):
Acoefs, Abases = metric.linear_expand(A.obj)
Bcoefs, Bbases = metric.linea... | 830dfaa97cf042278278b5c1aff8da77d5ee8f5a | 3,610,265 |
def get_enum_size(*args):
"""get_enum_size(enum_t id) -> size_t"""
return _idaapi.get_enum_size(*args) | 58024506d567e6d07d420233a16c1bd1e2f7750e | 3,610,266 |
def _martin_luther_king_holiday(year):
"""Martin Luther King's birthday (third Monday in January)"""
if year < 1983:
return None
for day in range(15, 22):
d = dt.date(year, 1, day)
if d.weekday()==0:
return d
raise Exception('Should never get there') | 06cfb37660a8b7034bad3cadc329bca84694acb6 | 3,610,267 |
def random_bivariate_anisotropic_Gaussian(kernel_size,
sigma_x_range,
sigma_y_range,
rotation_range,
noise_range=None,
... | add17263e4bc7c1b99bf55bf032e40cc093d7079 | 3,610,268 |
def validate_guess(number) -> str or None:
"""
:param number: the number to guess
:return: the valid guessed number or None if user gives up
"""
number_size = len(number)
while True:
guess = easygui.enterbox(f"Please guess the {number_size}-digit number: ")
if guess is None:
... | 41cfc02f97f33365389bd27dcd42d65c31ccdb57 | 3,610,269 |
def excel_radiosonde(request, form):
"""
Reads the radiosonde form and converts the data into a excel file
"""
start = form.cleaned_data['start_date_radiosonde']
end = form.cleaned_data['end_date_radiosonde']
time = form.cleaned_data['time_radiosonde']
fields = form.cleaned_data['fields... | 371736b8f6c0eb0b84a46bc4aa36060bf85b3db4 | 3,610,270 |
def compare_metrics(best_eval_result, current_eval_result):
"""Compares two evaluation results."""
return best_eval_result["exact_match"] < current_eval_result["exact_match"] | ce3880c2cc271d9c8c766a2dfbd95d31f5fb651c | 3,610,271 |
import importlib
def import_module(filename):
"""Import a module given a full path to the file."""
spec = importlib.util.spec_from_file_location("doc_filter", filename)
module = importlib.util.module_from_spec(spec)
spec.loader.exec_module(module)
return module | 924f19b96d98290dabfda1aef70cb7f67455f553 | 3,610,272 |
def set_target_bits(targs, sourcemask):
"""Apply bright source mask to targets, return desi_target array.
Parameters
----------
targs : :class:`recarray`
A recarray of targets as made by, e.g., :mod:`desitarget.cuts.select_targets`.
sourcemask : :class:`recarray`
A recarray containi... | 156a45e5c79a02321a3de05081ec429f5a4c325d | 3,610,273 |
def get_checksum_value(checksum):
"""
Return the checksum value.
The given checksum might either be a standard ad32 or md5 string, or a dictionary with the format
{ checksum_type: value } as defined in the `FileSpec` class. This function extracts the checksum value from this
dictionary (or immediate... | bc5a3a506a53970217a32fc0be79378e85787c18 | 3,610,274 |
def construct_bibfile_data(*paths):
"""
List of data corresponding to individual bib files
:param pathlib.Path *paths: Path to file possibly containing BibTeX data.
:rtype: list
"""
bibs = [reffile_factory(path) for path in paths]
return bibs | 7b0ddfd615e8cb54ce905d52a756e689824454a1 | 3,610,275 |
def check_shell_pipes(cmd):
"""
Determine whether a command appears to contain shell pipes.
:param str cmd: Command to investigate.
:return bool: Whether the command appears to contain shell pipes.
"""
return "|" in strip_braced_txt(cmd) | ad91661727e42fef6c95428b524c0178e23642ec | 3,610,276 |
from typing import Dict
import requests
from bs4 import BeautifulSoup
import re
def scrap_allrecipes_recipe(url: str) -> Dict:
"""This function scraps a recipe of Allrecipes, given its URL,
and prepare a JSON file to index in Elasticsearch.
:param url: the URL of the recipe
:return: the recipe as a J... | 0c060ba40e784b7dad6ab2af40dd6f0aa4600173 | 3,610,277 |
def waitTargetUpdate(omni_robot, timeout):
"""
Wait for target updating
:param omni_robot: (OmniRobot)
:param timeout: (time to wait for updating)
"""
omni_robot.target_pos_changed = True
time = 0.0 # second
while time < timeout and not rospy.is_shutdown():
if not omni_robot.tar... | c9be8516640667a758ef1a3fc62b881fc4bedec3 | 3,610,278 |
def known_references(request):
"""
List all known references witht he option of removing the contact date
"""
user = request.user
if 'remove_known_ref' in request.POST and \
request.POST['remove_known_ref'].isdigit():
try:
application = CredentialApplication.objects.get(
... | e22424641306f0020006f233cfea2b169a4c17c6 | 3,610,279 |
def get_plugin():
"""Return the filter."""
return IpynbFilter | 991dead0a95e97526736e3cf06bd76138be46cf2 | 3,610,280 |
def __ensure_paragraphs(text):
""" Checks if paragraph break in text else adds it and returns """
if "\n\n" in text:
# Paragraph break detected just return it
return text
# If not detected add it ourselves
new_text = "\n\n".join(__cut_text(text, length=500))
return new_text | 5b79021021c4a89bc12901ac12c29257e16d3409 | 3,610,283 |
def main(path, task, representation):
"""
:param path: str specifying path to dataset.
:param task: str specifying the task. Always e_iso_pi in the case of the human performance comparison
:param representation: str specifying the molecular representation. One of ['fingerprints, 'fragments', 'fragprints... | 732f96bc4697ce11f3665584799c608b8c0096ae | 3,610,284 |
def region_of_interest(img, vertices):
"""
区域选择
Only keeps the region of the image defined by the polygon
formed from `vertices`. The rest of the image is set to black.
"""
# defining a blank mask to start with
mask = np.zeros_like(img)
# defining a 3 channel or 1 channel color to fill... | a0b3741b135a9a9c2356b6b63061ee784c0a6b98 | 3,610,286 |
def segformer_b5(pretrained=False, progress=True, num_classes=150):
"""Create a SegFormer-B5 model.
Args:
pretrained: Download backbone weights pretrained on ImageNet data if true.
progress: Display the download progress of pretrained weights if true.
num_classes: Number of output class... | 39bc9c36fd26a49856848d8ba08076a0a9205334 | 3,610,287 |
def expand_codes(df=None,
codes=None,
cols=None,
sep=None,
codebook=None,
hyphen=True,
star=True,
colon=True,
regex=None,
del_dot=False,
case_sensitiv... | e2e6132cf94a6b19c9d6294c36ffc8fa412401a0 | 3,610,288 |
import math
def compute_roce(fpr, preds, real):
"""
Calculate the ROC enrichment (ROCE) score - i.e., the y value divided by
the x value on an ROC curve, at a fixed predetermined x value (i.e.
a fixed false positive rate).
Args:
fpr (float): pre-set false positive rate
preds (np.ar... | 89190c89b4faa0d2025da578b06ba94906e7bfe8 | 3,610,289 |
def segmentPlaneIntersection(s0 = "const Dim<3>::Vector&",
s1 = "const Dim<3>::Vector&",
point = "const Dim<3>::Vector&",
normal = "const Dim<3>::Vector&",
tol = ("const double", "1.0e-8")):
"""Inters... | eb68974937de575702069565fc3ee34dfadf89cc | 3,610,291 |
def get_host_data(root):
"""Traverses the xml tree and build lists of scan information
and returns a list of lists.
"""
host_data = []
hosts = root.findall('host')
for host in hosts:
addr_info = []
# Ignore hosts that are not 'up'
if not host.findall('status')[0].attrib[... | 6f4967da12edd496df613b210083745c5c137578 | 3,610,293 |
import concurrent
def with_progress_bar(target):
"""
Adapted from ipywidgets progress bar example
:param target: Function to run. Function must take progress bar as argument.
:return: None
Try it out with::
a = []
def work(progress):
total = 3
for i in ran... | 0d814c035363c14cff98de798781129b42a2858a | 3,610,294 |
def incident_beam(*, source_chopper: sc.Variable,
sample_position: sc.Variable) -> sc.Variable:
"""
Compute the incident beam vector from the source chopper position vector,
instead of the source_position vector.
"""
return sample_position - source_chopper.value['position'].data | 2f6b5502e336ed02b4c733808bb446f5e0310689 | 3,610,295 |
import math
def arrhenius (A: float, E: float, T: float, R: float = R) -> float:
"""
Args:
A: Pre-exponential (frequency) factor.
ValueError raised if not > 0.
E: Activation energy.
T: Temperature in Kelvins.
ValueError raised if not >= 0.
R: Universal g... | 8f5d43bb659070fed34274db36fb9e5ec79343d1 | 3,610,296 |
def xoai_contributor(source, *args, **kwargs):
"""
CZ:
EN:
"""
value = []
for person_role in source:
role = person_role["@name"]
field = person_role["element"]["field"]
if isinstance(field, list):
for person in field:
value.append(
... | a17ab90aee1326c66cdc546b726666b86039cc3f | 3,610,297 |
def http_endpoint(
flask_entity,
flask_rule,
method: HttpMethod = HttpMethod.GET,
returns_json_response: bool = True,
):
"""
Decorator factory used to easily register a Transiter HTTP endpoint.
:param flask_entity: either the Flask app or a Flask blueprint
:param flask_rule: the URL rel... | a33c4a24466ce8ebaa96e243714ae045ce1f22fa | 3,610,298 |
from typing import Any
from typing import List
import torch
def all_gather_cuda(data: Any) -> List[bytes]:
"""
Run all_gather on arbitrary picklable data (not necessarily tensors)
Args:
data: any picklable object
Returns:
list[data]: list of data gathered from each rank
"""
world_size = global_world_size()
... | 763c64ee2f5efe129be1a292acb81461ba395bf5 | 3,610,299 |
def from_array(array, copy=True):
"""Convert a NumPy array to a tensor.
Initializes a taco tensor from a NumPy array and copies the array by default. This always creates a dense
tensor.
Parameters
------------
array: numpy.array
A NumPy array to convert to a taco tensor
copy: boo... | 189e5be32db3f411e0a649357a9f8a4e164093ac | 3,610,300 |
def maybeName(obj):
""" Returns an object's __name__ attribute or it's string representation.
@param obj any object
@return obj name or string representation
"""
try:
return obj.__name__
except (AttributeError, ):
return str(obj) | 2b83918c49fc6cd19a027c1d2db07fcb0d57166a | 3,610,301 |
def compare(attr_a, attr_b=0, operation=0):
"""Create math_Compare-node to get boolean of logical comparison between given attrs.
Args:
attr_a (NcNode or NcAttrs or string): Maya node attribute.
attr_b (NcNode or NcAttrs or float): Maya node attribute.
operation (NcNode or NcAttrs or in... | 54d94c30984c52daf250e9bed83fba3d56844938 | 3,610,303 |
import inspect
def gc_nc_60_79(mqc):
"""
Analogous to gc_nc_0_19.
"""
k = inspect.currentframe().f_code.co_name
try:
d = next(iter(mqc["multiqc_picard_gcbias"].values()))
v = d["GC_NC_60_79"]
v = np.round(v, DECIMALS)
except KeyError:
v = "NA"
return k, v | cb3febae5450c3662e8ce91175b5e8ecc42f52b1 | 3,610,305 |
import math
import random
def generate_random_pose():
"""
generate a random rod pose in the room
with center at (0, 0), width 10 meters and depth 10 meters.
The robot has 0.2 meters as radius
Returns:
random_pose
"""
def angleRange(x, y, room, L):
"""
Compute rod an... | 81c26bbabb6b4386b4086b20a09fe8691add2fed | 3,610,306 |
import logging
def version_description(project_arn: str, version_name: str = None):
"""[Describes a Project on Rekognition in AWS]
Args:
project_arn (str): [Unique Identifier for a Project on Rekognition in AWS]
version_name (str, optional): [Display Name]. Defaults to None.
Raises:
... | 3af2244c502a2599ad5c283b3e9147d785ef3a51 | 3,610,307 |
def feature_importance(residuals, analysis_type="collective", date_from=None, date_till=None, weigh=True):
"""Feature importance calculation
Parameters
----------
residuals : pandas.DataFrame()
analysis_type : str, "single"/"collective", "single" by default
date_from : str in format 'yyyy-mm-... | 45c66fa9ddae1b8e81e68c055de94a72a311c83f | 3,610,308 |
def utest(a, b):
"""
MannWhitney U statistic
scipy.stats.mannwhitneyu tests for a != b
Use only when the number of observation in each sample is > 20 and yo
have 2 independent samples of ranks.
Mann-Whitney U is significant if the u-obtained is LESS THAN or equal to
the critical value of U.... | 4628ef64e3a3aaf60dc88f750976b7f0147852bd | 3,610,309 |
from typing import Callable
from typing import Any
import asyncio
import time
async def run_async(func: Callable[..., Any], *args, **kwargs) -> Any:
"""
Runs a callable on the database thread pool executor using the current thread's
I/O loop instance.
Usage:
def blocking_task(arg1, arg2, ar... | 69f7bf02daa77bff85baa34139c8771b20660f1e | 3,610,310 |
def constant_schedule_with_warmup(epoch, warmup_epochs=0, lr_start=1e-4, lr_max=1e-3):
""" Create a schedule with a constant learning rate preceded by a warmup
period during which the learning rate increases linearly between {lr_start} and {lr_max}.
"""
if epoch < warmup_epochs:
lr = (lr_max - ... | e780c3946f0207f94065c3ce8333896c3513f25a | 3,610,311 |
def gen_lc(x,p0,struct,pmax=85.):
""" From gen_lc.pro """
#p0 = m0i, m0v, m0b, period, phase shift, tbreak1, tbreak2
p = np.array(p0).copy()
if len(p) < 11: # use the poly fits to fill in the pca1-pca4 coeffs
c_need = 11 - len(p0)
poly_fits = struct["POLY_FITS"][0]
new_coeffs = [... | 6a211bad9280dd2d78cc70ee95bd57e6c2d0439b | 3,610,312 |
def create_embed(author, level, ascendency_name, class_name, main_skill: Skill, is_support):
"""
Create the basic embed we add information to
:param author: of the parsed message - str
:param level: of the build
:param ascendency_name: to display
:param class_name: to display if no ascendency ha... | 4a116384d1507909addce61b51151c12f0d2a24b | 3,610,313 |
def get_cluster_name():
"""
Retrieves the current cluster name from the CLUSTERNAME environment variable
This should probably be in conf.py, but it creates dependency issues with ZMQ
:return: str cluster name
"""
return environ.get('CLUSTERNAME') | 25ce09ffce1654c5d316ee06b70187ed7d4dd9c0 | 3,610,315 |
def ml_ssl(stft, sv, compression=0, eps=1e-8, norm=False, mask=None):
"""
Maximum likelihood SSL
Arguments:
stft: STFT transform result, M x T x F
sv: steer vector in each directions, A x M x F
norm: normalze STFT or not
mask: TF-mask for source, T x F x (N)
Return:
... | aef6117f45de1f64b15449ae872e9ddc96455578 | 3,610,316 |
def vonMisesStressUtilization(axial_stress, hoop_stress, shear_stress, gamma, sigma_y):
"""combine stress for von Mises"""
# von mises stress
a = ((axial_stress + hoop_stress)/2.0)**2
b = ((axial_stress - hoop_stress)/2.0)**2
c = shear_stress**2
von_mises = np.sqrt(a + 3.0*(b+c))
# stress ... | 3b62b0c6e91eb6f244a70b60ab8b74fb712fac82 | 3,610,317 |
def bar_chart(data2):
"""
A bar chart, like the one above but with small custom alterations title and size
"""
Chart2 = alt.Chart(data2).mark_bar().encode(
alt.X ('movies', title="My Favorite Movies"),
alt.Y ('num_oscars', title="# of Academy Awards"),
color='movies',
).... | aca1fd668a529b82b9293d54f99fa662a8da72b4 | 3,610,319 |
def nSpecies():
""" Returns the total number of species in the model. """
return 62 | b9e77841cb46bba4faa1fab3c1ea00875753aaf1 | 3,610,320 |
def plot_convergence(*args, **kwargs):
"""Plot one or several convergence traces.
Parameters
----------
* `args[i]` [`OptimizeResult`, list of `OptimizeResult`, or tuple]:
The result(s) for which to plot the convergence trace.
- if `OptimizeResult`, then draw the corresponding single t... | 81ad36bd5e1efeddee70e5899aed547a63909e7d | 3,610,321 |
def server_player_id(player_id):
"""Serve player ID endpoint.
This endpoint is used to indicate a buzzer has been triggered, or register
a buzzer.
Args:
player_id: Player identifier.
"""
gameshow = flask.current_app
gameshow.state_machine.process(
state_machine.Events.TRIGG... | 39220e2c66aeafbeb52d5176adcba8ead7faf91b | 3,610,322 |
import math
def crt(cong):
"""Use the Chinese Remainder THeorem to solve the given system of
congruences, cong = [(mod1, rem1), (mod2, rem2), ...] where
val = rem1 mod mod1
val = rem2 mod mod2
...
The val satisfying the congruences is returned.
"""
result = 0
nprod = math.prod([v[0... | 1b63975b769c8d8cf9e5dcf65b102a6a03a7e3c5 | 3,610,323 |
import base64
def compose_message(body, subject, contacts):
"""
composes message
using message text, subject, contacts
and returns it encoded
"""
message = MIMEMultipart()
message['subject'] = subject
message['from'] = me
message['to'] = contacts
plaintext_body = html_to_text(... | 77926afa9ac8d95f83b47a9d1a978008d2a5100d | 3,610,324 |
def getFileList(dbid, fnr, printi=0, type='A'):
""" Get list of Sdicfile objects from Predict file
:param dbid: dbid of Predic file
:param fnr: file number of Predic file
:param printi: print file list if True
:param type: select by file type ('A' is Adabas file)
:returns: list of Sdicfile na... | 09aba2798337b337981fcf8885e774b87ea00409 | 3,610,325 |
def insertWarnings(lines, badCommand):
"""Insert warnings after a command that is probably to be checked.
The text is to be given as a list of lines.
A command in this sense can be any text that is not to be
followed by an asciiletter
"""
lineNumber = 0
while lineNumber < len(lines):
... | 0b8dfb35f818cd74dea54846d9aca9abb9c42efe | 3,610,326 |
def rho_p(rank_vector):
"""Compares each element in the vector to its corresponding value in the null distribution
vector, using the probability mass function of the binomial distribution.
Assigns a p-value to each element in the vector, creating the betaScore vector.
Uses minimum betaScore as rho
... | ba35368b14c2ee0635ffd70e0a243b634698dda2 | 3,610,327 |
import copy
def occupy_seats(data, seat_tolerance, only_adjacent):
""" Occupies seats according to rules.
:param data: seat map (2d array)
:param seat_tolerance: number of discovered seats that can be occupied to still make the person occupy the seat
:param only_adjacent: boolean, if True only check ... | ab86082b0e6c0b4f453c7af2e6dfe383ed6b3054 | 3,610,328 |
def get_orthogonal_grid_edges(pix_x, pix_y, scale_aspect=True):
"""calculate the bin edges of the slanted, orthogonal pixel grid to
resample the pixel signals with np.histogramdd right after.
Parameters
----------
pix_x, pix_y : 1D numpy arrays
the list of x and y coordinates of the slanted... | 11f79e53b021c8744f047f47fb4699c277a3f3ab | 3,610,329 |
def rom(a, b,f, eps = 1e-8):
"""Approximate the definite integral of f from a to b by Romberg's method.
eps is the desired accuracy."""
R = [[0.5 * (b - a) * (f(a) + f(b))]] # R[0][0]
#print_row(R[0])
n = 1
while True:
h = float(b-a)/2**n
R.append((n+1)*[None]) # Add an empty r... | 3dfd00652837b999187a30ace3c3143fa381cb2a | 3,610,330 |
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