content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def flatten(obj: JSONObject) -> FlatJSON:
"""
Flattens a JSON object to a dict with a single level of mapping. Key become tuples that store the
path from the top-level object down to the value. Object keys are stored as str, Array index as int
Arguments:
obj: json object to flatten
Returns... | e71511826e4b74bc40bdec257ce761902ee91300 | 81,335 |
import random
from datetime import datetime
import uuid
def get_product():
"""
Returns a random product generator function based on
shared/resources/schemas.yaml
Usage:
from fixtures import get_product
product = get_product()
"""
PRODUCT_COLORS = [
"Red", "Blue", "Gree... | df608e8aa124792f8ed6baff92a04d01fa8aaa32 | 81,336 |
def b58encode(v):
""" encode v, which is a string of bytes, to base58."""
long_value = 0
for c in v:
long_value = long_value * 256 + c
result = ""
while long_value >= __b58base:
div, mod = divmod(long_value, __b58base)
result = __b58chars[mod] + result
long_value = ... | d1643703e3bee0e9a1d83fe7d5a71eeaf1fecc06 | 81,338 |
def resize_smallest(frames: tf.Tensor, min_resize: int) -> tf.Tensor:
"""Resizes frames so that min(height, width) is equal to min_resize.
This function will not do anything if the min(height, width) is already equal
to min_resize. This allows to save compute time.
Args:
frames: A Tensor of dimension [tim... | 8a064e78986bbb81f0107042063b8bbfe05ce438 | 81,339 |
def centerxywh_to_topleftxywh(boxes):
"""
args:
boxes:list of center_x,center_y,width,height,
return:
boxes:list of x,y,x,y,cooresponding to top left and bottom right
"""
x_top_left = boxes[0] - boxes[2] / 2
y_top_left = boxes[1] - boxes[3] / 2
width = boxes[2]
height = b... | d5ea2716e982369b0052df6ee9f757e13e32c779 | 81,341 |
def compute_posture(df_dict):
"""
Computes posture, or bounding volume, of the body on a per frame basis.
Args:
df_dict (dict): dict of data frames, indexed by body parts
Returns:
DataFrame: resulting data frame comprising frame-level bounding volume
values
"""
list_X = []
list_Y =... | 1fbcf3c00fcce4c51c566a11bb44aa8e92cad5ea | 81,342 |
from typing import Optional
def _old2new_label(old_label: str) -> Optional[str]:
"""
Converts old-style BigEearthNet label to the
new labels.
> Note: Some labels were removed! This function
will return `None` if the label was removed and
raise a `KeyError` if the input label is unknown.
"... | a99d978ebebc0fa2fa093e1ee7d9adde106a284b | 81,344 |
def parts(a, b):
"""https://stackoverflow.com/a/52698110"""
q, r = divmod(a, b)
return [q + 1] * r + [q] * (b - r) | f6bffd65b39b83532d7105966a503e7e8c96db55 | 81,345 |
def is_parameterized_generic(type_, raising=True):
"""
Returns whether ``type_`` is a generic type with some
type arguments supplied, for example ``List[int]``
or ``List[T]`` (but not ``List``) - in other words, a
:class:`types.GenericAlias`.
If ``type_`` is not a type as defined by :func:`~int... | 67edef470ac351038034626b9e27190d5bc340af | 81,346 |
def sine_offset(tee, location, alpha):
"""Return sine of angle between position of sun at
local time tee and when its depression is alpha at location, location.
Out of range when it does not occur."""
phi = latitude(location)
tee_prime = universal_from_local(tee, location)
delta = declination(t... | 682894b3b94ab5c300748dca84610934307e592f | 81,347 |
def reverse_looping_deconvolution_data_reuse_patterns(upsampling_factor, height, in_channels, kernel_size, original_operator="D-SP", width:int = None):
"""
input:
upsampling_factor:int - the upsampling factor
height:int - the height of the input image
width:int - the width of the input i... | ecba08ec1fa15002dbff849c520ae7be0a1d3c74 | 81,348 |
def murphy_skill(xmodel,xobs,xref=None,ignore_nan=True):
"""
Murphy Skill metric
"""
if ignore_nan:
sel=np.isfinite(xmodel+xobs)
else:
sel=slice(None)
m=xmodel[sel]
o=xobs[sel]
if xref is None:
xref=o.mean()
ms=1 - np.mean( (m-o)**2 )/np.mean( (xref-... | ff5b894a2513949db0490e20a263aac1499ad40a | 81,349 |
def project_to_cameras(poses_set, cams, ncams=4):
"""
Project 3d poses using camera parameters
Args
poses_set: dictionary containing 3d poses
cams: dictionary containing camera parameters
ncams: number of cameras per subject
Returns
t2d: dictionary with 2d poses
... | 3ee7eeb0ae3dca5ccbeb219de77cb1416d6cee6e | 81,350 |
def exclude(items, excludes):
"""Exclude removes all items in a list that is in the excludes list (for dirs)"""
for ex in excludes:
items = [x for x in items if not ex in x]
# return items
return items | 5a9de305dbfc804b06e6533dd20030b8cbca00f8 | 81,351 |
def get_pathway_kegg_url(specie_id):
"""Get patwhway URL for A SINGLE specie."""
return urljoin(KEGG_PATHWAYS_URL, get_pathways_kegg_id(specie_id)) | 8fb792d51917ba346f3599dada9df490cc527d16 | 81,352 |
import numpy
def calculate_migration_time(vms, bandwidth):
"""Calculate the mean migration time from VM RAM usage data.
:param vms: A map of VM UUIDs to the corresponding maximum RAM in MB.
:param bandwidth: The network bandwidth in MB/s.
:return: The mean VM migration time in seconds.
"""
re... | 83881d08c457924a7770fb072d401578a53d04b4 | 81,354 |
import math
def get_path(s1, s2):
""" runs astar on the map"""
def distance(n1, n2):
"""computes the distance between two stations"""
latA, longA = n1.position
latB, longB = n2.position
# convert degres to radians!!
latA, latB, longA, longB = map(
lambda d:... | f712c7aff3e1da0bc58b687fb5ab97fcb2418233 | 81,355 |
def chord_symbol_root(figure):
"""Return the root pitch class of a chord.
Args:
figure: The chord symbol figure string for which the root is computed.
Returns:
The pitch class of the chord root, an integer between 0 and 11 inclusive.
Raises:
ChordSymbolError: If the given chord symbol cannot be i... | dd66b1ddfea6589d651bb209b3c8a3a126fabcb9 | 81,356 |
def flatten_entrypoints(ep):
"""Flatten nested entrypoints dicts.
Entry points group names can include dots. But dots in TOML make nested
dictionaries:
[entrypoints.a.b] # {'entrypoints': {'a': {'b': {}}}}
The proper way to avoid this is:
[entrypoints."a.b"] # {'entrypoints': {'a.b': {}}... | 2b8e600c1932f0b2f3a64e5d7cdccb841bc82030 | 81,357 |
def elslib_CylinderValue(*args):
"""
:param U:
:type U: float
:param V:
:type V: float
:param Pos:
:type Pos: gp_Ax3
:param Radius:
:type Radius: float
:rtype: gp_Pnt
"""
return _ElSLib.elslib_CylinderValue(*args) | 3ef438f3e8c3bc2ff1fddf29911d9994512d1053 | 81,358 |
def Get_random_valid_grid(size):
"""Returns a single valid raw grid out of 9! possible combiantions"""
#getting size values and shuffling them
values_to_set = [i for i in range(size)]
shuffle(values_to_set)
#assigning them to a size x size board on the main descending diagonal, by doing so, the init... | 0ca8ffe41cada0b18cef4cf4367a9c3225c39d29 | 81,359 |
def enframe(data, window_size, hop_size):
"""Divide 1D data in frames"""
if data.ndim != 1:
raise TypeError('Input must be a 1-dimensional array.')
n_frames = 1 + (len(data) - window_size) // hop_size
framed = np.empty((n_frames, window_size))
for i in range(n_frames):
framed[i] = da... | ba8729c76641495f1900a3d9bcd46c37f8f2d2ad | 81,360 |
import decimal
def get_decimal_count(value, is_drop_trailing_zeros=True) -> int:
"""Return decimal count.
https://stackoverflow.com/a/6190291/2402577
See https://stackoverflow.com/a/11227878/2402577
for drop the trailing zeros from decimal.
"""
value = str(value)
if is_drop_trailing_zero... | ac0272c74eb5ed14694af7c13fcfb287d1eeea4c | 81,361 |
def valid_timezone(x: str) -> bool:
"""
Retrun ``True`` if ``x`` is a valid human-readable timezone string,
e.g. 'Africa/Abidjan'; otherwise return ``False``.
"""
return x in TIMEZONES | e9d88334130e7b9f7513f1e5d0813573f2c3357d | 81,362 |
from turbinia.client import TASK_MAP
import copy
def validate_recipe(recipe_dict):
"""Validate the 'recipe' dict supplied by the request recipe.
Args:
recipe_dict(dict): Turbinia recipe in need of validation
submitted along with the evidence.
Returns:
Tuple(
bool: Whether the recipe has a va... | e504d7cec9e133b856057e4c73e38adde476d4bf | 81,363 |
def hello_world():
"""Main landing page"""
return render_template('index.html') | 8c9cdb3d6d1b4fd55985b604bf1fa4ca297da1fc | 81,364 |
def plot_verified_region_control_set_point(verification_model, control_set_point, power_reference_points):
"""
Plot for a given control set point and (multiple) power reference points.
:param verification_model: The verification model
:param control_set_point: A fixed control set point
:param power_... | 1d3e7863aae8b87c05eb8a6c49b076a893e2babc | 81,365 |
import ctypes
def encrypt(cert_or_certlist, msg, algo=szOID_NIST_AES256_CBC, initvector=geninitvector):
"""Encrypt ``msg`` one or many :class:`Certificate` using ``algo`` with the initial
vector ``initvector``.
If ``geninitvector`` is left as it is, it will generate a random one.
Algorithms... | 2430a0991155f2652dae028f5c032e3224a3d569 | 81,367 |
import torch
import math
def get_log_p_and_kl_(generative_model, inference_network, obs, obs_id, num_particles):
"""Compute log weight and log prob of inference network.
Args:
generative_model: models.GenerativeModel object
inference_network: models.InferenceNetwork object
obs: tensor... | 18c076cb06b9490b2b5c8674727efa6c37c1446c | 81,368 |
def _GenerateEstimatorConstructor(estimator_class_name, variable_types, variable_names, extension_class_name):
"""
Generates the consructor for the estimator class.
"""
code = ["\n\npublic {0}(IHostEnvironment env".format(estimator_class_name)]
# Generate the Constructor parameters
for variable_... | 19366e1e25befa2e0723604d31f0f59b602b9b51 | 81,369 |
def getExt(fileName, allowedExts=None):
"""Returns the extension from the given file name.
If ``allowedExts`` is ``None``, this function is equivalent to using::
os.path.splitext(fileName)[1]
If ``allowedExts`` is provided, but the file does not end with an allowed
extension, a :exc:`Path... | 5385ce1fb6376acfeef6b08f9682948080ffdee2 | 81,370 |
import json
from typing import cast
from typing import Type
def dump(obj, fp, *, indent=None, sort_keys=False, core: "Core" = None, **kw):
"""
Dumps an object into a Writer with support for HomeControl's data types
"""
return json.dump(
obj, fp, cls=cast(Type[JSONEncoder], partial(JSONEncoder,... | cb7162b9b58c99d11d3beec4bb3a8554d8f9a8c7 | 81,371 |
def mXZpm_HB(mu,P,mXZj,mXZtot,eps_s):
"""
Calculates the upper and lower bounds on the number of errors in the
sifted X or Z basis, for each pulse intensity, using the Hoeffding bound.
Defined after Eq. (4) in [1].
mXplus[j] and mXmin[j], or mZplus[j] and mZmin[j]; j = {1:3}
Parameters
... | 8f9cbeb4642bfc5efcf6e27a55244aefb2bb7b2b | 81,372 |
from typing import Any
def is_born_in(Subject, Object):
"""
Ex: Xu is born in 1902 or 1903 in a family of farmers in Hubei (China RRB)
"""
anything = Star(Any())
return Subject + Token("is born in") + Object + anything | 0d38a92ba7c47ece4b46aff9f61f212d1a5a04e5 | 81,373 |
def get_project_single_branch_links(request, project_id, branch_id):
""" Display single branch links """
if request.method != 'GET':
return res.get_template_data(request, 'presenter/not_found.html', {})
project_entry = GitProjectEntry.objects.filter(id=project_id).first()
if project_entry is No... | 81f5984f7d0b9e9c24e63434680838bddb00209a | 81,375 |
def cpi(token="", version="stable", filter="", format="json", **timeseries_kwargs):
"""Economic data
https://iexcloud.io/docs/api/#economic-data
Args:
token (str): Access token
version (str): API version
filter (str): filters: https://iexcloud.io/docs/api/#filter-results
fo... | 9eac6e15daaf99393817ee1a25e805d3f39ffadf | 81,376 |
def make_universal_sf(config):
"""Generate a symmetry function applied to all elements."""
kind, inner = parse_config(config)
if kind == "rad":
return _make_universal_rad(**inner)
if kind == "ang":
return _make_universal_ang(**inner)
else:
raise ValueError(
f"... | 3603bed8cfd8db35c40f0d25aa2be585dfeec5c2 | 81,378 |
def format_bootstrap_metrics_to_dataframe(
metrics: dict,
decimals: int,
) -> pd.DataFrame:
"""
Format a dictionary of metrics into a dataframe for easier logging and printing.
"""
# Convert dictionary to dataframe
df = pd.DataFrame(metrics).transpose()
# Reorder columns and round colum... | 452c5ba883d2d31bac56e89779fcbafec59d39fb | 81,379 |
def get_classification(random_state = 42):
"""
Creates a classification dataset.
Wrapper for sklearn's make_classification.
:param random_state: Specifies a random seed
:return: A tuple of X,y values.
"""
X, y = sklearn.datasets.make_classification(
n_samples = 1000,
n_class... | 043b19ed3adf48bc2c8be86d7d1e8632a723e6c3 | 81,380 |
from typing import Optional
async def get_asset_digest(genome: str = g, asset: str = a, tag: Optional[str] = tq):
"""
Returns the asset digest. Requires genome name asset name and tag name as an input.
"""
tag = tag or DEFAULT_TAG
try:
return Response(
content=rgc[CFG_GENOMES_K... | 7ef505fa39d6f50c53662e825295276ef9bdc15c | 81,381 |
import nlopt
def acq_max_with_tracing(ac,gp,bounds):
"""
A function to find the maximum of the acquisition function using
the 'DIRECT' library.
Input Parameters
----------
ac: The acquisition function object that return its point-wise value.
gp: A gaussian process fitted to the relevant d... | b4ba813f0199e7e43ad7e35a261d04e2870ee5f7 | 81,382 |
def delete_cert(account_number, cert):
"""
Delete a certificate from AWS
:param account_number:
:param cert:
:return:
"""
return assume_service(account_number, 'iam').delete_server_cert(cert.name) | a776f34445c61426af8ee982785fdd6a126cdb6c | 81,383 |
import math
def calculations_6(q_coppelia):
"""!
Builds the 6 dof Jacobian by computing the transformation matrices,
extracting the geometric vectors from the results and finally building the matrix.
@param q_coppelia: vector of the joint positions
@return Js: Jacobian matrix
"""
p = np.p... | 637feab7c015d14585a41428076f2929a9786f6c | 81,384 |
def predict_sequence_class(sequence, vectorizer_model, classifier_model, class_labels):
"""
inputs: DNA sequence, model and class labels (dictionary)
Function takes in a DNA sequence returns its class amongst:
[G protein coupled receptors', Tyrosine kinase', 'Tyrosine phosphatase', 'Synthetase', 'Syntha... | 7760662355f7039a075b190256e0b11e364959ea | 81,386 |
from functools import reduce
def replace(names_to_check, non_valid=None, rmap=None):
"""
Removes characters defined in non_valid from strings defined in names_to_check
Does not mutate strings in names_to_check, but returns new strings with invalid
characters replaced by a single space
:param nam... | 67702fd88e0085d886d680eebe320549b031a6de | 81,387 |
def get_bmi_category_df():
"""
Get the dataframe for the bmi category
:return: data and schema for the data frame
"""
data = [("Male", 171, 76, 1.71, 25.99, "Overweight", "Enhanced risk"),
("Female", 151, 96, 1.51, 42.1, "Very severely obese", "Very high risk")]
schema = StructType([... | 9f031724797f3308df891fec8dfdf351957f7b21 | 81,388 |
def sense_predictor(word_rnn_outputs, tag_feats, target_senses, num_senses, words_count,
predict_sense, sense_smoothing):
"""Network for predicting sense separately"""
if predict_sense:
sense_features = word_rnn_outputs
sense_features = tf.concat([sense_features, tag_feats], ... | e0962a5dda4ca81b49897868c76625682eebf4c3 | 81,389 |
def showscal(data, property="ke", **kwargs):
"""
showf(data, var, units)
Arguments:
data : xarray.DataSet that contains dimensions of t,x,y
and a variable w (scalar)
"""
data.piv.vec2scal(property=property)
fig, ax = contour_plot(data, **kwargs)
return fig, ax | 435f434a22ce6da1cf48157d812799279823f8c5 | 81,390 |
import requests
def download_torrent_file(torrent_file_url):
"""
Функция скачает по ссылке торрент файл и вернет его название.
Если не получится, вернет None
"""
user_agent = 'Mozilla/5.0 (compatible; Googlebot/2.1; +http://www.google.com/bot.html)'
rs = requests.get(torrent_file_url, heade... | 41f7ef4a03266b16a7a1d8e1add4b13ecc2e0ea6 | 81,391 |
def run(*datasources, **options):
"""Executes given Robot data sources with given options.
Data sources are paths to files and directories, similarly as when running
pybot/jybot from command line. Options are given as keywords arguments and
their names are same as long command line options without hyph... | 755b7b35ffb13df1f2dc6badfbbaf354aa4dc985 | 81,392 |
def get_new_session():
"""
获取新Session
"""
session = session_factory()
return session | 7e04843aefa1b250d0808a700ed3c3addc6feb70 | 81,393 |
def get_download_mode():
"""Return the mode used to download references and mappings, either normal
"http" file transfer or json "rpc" based. In theory HTTP optimizes better
with direct support for static files from Apache, but RPC is more flexible
and works through firewalls. The key distinction... | 19a76bae07679bd6272b2b70ed11fdc99c3a4a61 | 81,394 |
import numpy
def complex_to_int(data):
"""
This converts from complex64 or 128 data to int16 data.
Parameters
----------
data : numpy.ndarray
Returns
-------
numpy.ndarray
"""
new_shape = _validate_input(data)
if data.dtype.name == 'complex128':
view_dtype = num... | 3e068373fa31d6a636de3b1b1fc71928c20b2788 | 81,395 |
def _binary_method(op):
"""Implement a forward binary method with a noperator, e.g., __add__."""
def func(self, other):
self, other = coerce([self, other])
if isinstance(other, Image):
return Image(
op(self._value, other._value), copy=False
).merge_proper... | 19cb264d4897277537650e4c829bcdeb3775bead | 81,396 |
def point_copy(p):
"""Utility function to coerce a list or tuple into Point3 format"""
return Point3(p[0], p[1], p[2]) | 11d05c444e3ec856f163eb2f568c9bfe0debf65d | 81,397 |
def get_new_lp_file(test_nr):
""" Get name of new LP file """
return "test/{0}-new.lp".format(test_nr) | f7527a053a640d080f3aecd9db24623d5563b250 | 81,400 |
def readQueue():
"""
Description: Reads SQS Queue for processing
Links:
https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/sqs.html#SQS.Client.receive_message
Expects:
Nothing
Returns: message array, each in JSON
"""
sqs = boto3.client('sqs',region_n... | 6221e08b9b2d7339f2c6579ce73f80775badea0e | 81,402 |
def comments_listing(request,option=None):
"""
Generate Comment Listing template.
:param request: Django request object (Required)
:type request: :class:`django.http.HttpRequest`
:param option: Whether or not we should generate a CSV (yes if option is "csv")
:type option: str
:returns: :cla... | b45a494a0bfd02562ae52e3e5aaa49931c8961b2 | 81,403 |
def get_auth_instance(credentials, auth_type):
"""
Returns an *Auth instance suitable for the requests package
"""
model = AUTH_TYPE_MAP[auth_type]
if model is None:
return None
username = credentials.username
if auth_type == NTLM and credentials.type == credentials.EMAIL:
us... | 52ed597ee191781fe996e44db67529e5fd272141 | 81,404 |
def transmit(message: str) -> str:
"""
Convert a message to a NATO code word transmission.
"""
result = []
for char in ALPHANUM_RE.findall(message.upper()):
result.append(ALPHANUM_TO_NATO[char])
return " ".join(result) | d67d27ff400b131a62d405ba0391461b8b7ad31c | 81,405 |
import PIL
def pilshow_imageobject_vscode(image_object: PIL.Image.Image):
"""When used with a VS Code "Interactive Window", displays the referenced image object.
Args:
image_object (PIL.Image.Image): Reference an existing Image object
"""
#
if isinstance(image_object, PIL.Image.Image):
... | 7556e791e5cdc5a0a8a10701a3ddac0e5c37b46f | 81,406 |
def calculate_bmu_indexes():
"""Create a tensorflow graph for calculating the best matched indexes in a SOM."""
mapdata = tf.placeholder(tf.float32, shape=(None, None), name="som")
fcsdata = tf.placeholder(tf.float32, shape=(None, None), name="fcs")
squared_diffs = tf.pow(tf.subtract(
tf.expand_... | b028351b20d8bcfd18d1f29aafece07a140488d9 | 81,407 |
def tokenize(tokenizer, data, max_length = 128):
"""
Iterate over the data and tokenize it. Sequences longer than max_length are trimmed.
:param tokenizer: tokenizer to use for tokenization
:param data: list of sentences
:return: a list of the entire tokenized data
"""
tokenized_data = []
... | 30b3786c1299bc42cd2698eae83ce1c6bdc3cfbe | 81,408 |
import torch
def empty_like(input_, dtype):
"""Wrapper of `torch.empty_like`.
Parameters
----------
input_ : DTensor
Input dense tensor.
dtype : data-type
Data type of output.
"""
return torch.empty_like(input_._data, dtype=dtype) | 6f2a8b5392cb854fd7bb782fe8de0766653bb3b5 | 81,409 |
def remove_host(host, service_instance):
"""
Removes host from vCenter instance.
Returns connection state of host
host
Name of ESXi instance in vCenter.
service_instance
The Service Instance Object from which to obtain host.
"""
host_ref = utils_common.get_mor_by_property(... | fc00ce2806c575c60745ee5d1335b3489a51e1d9 | 81,411 |
def unbind_slot_luks1(module, device, slot):
"""Unbind slot in a LUKS1 device. This involves removing both the clevis
metadata in LUKSMeta as well as its associated keyslot.
Return <result> <error>"""
_unused, err = get_jwe_luks1(module, device, slot)
if err:
errmsg = "{0}:{1} is not bound t... | 14db4d116a3ae121f047cbe5f2710d7a99a574fe | 81,412 |
def detect_peaks_1d(timeseries, delta_peak, threshold, peak_width=5):
"""
detect_peaks_1d
Starting from the largest burst event in the time series at hand, we identify a set of
disjunct sub records, placed symmetrically around the peak of burst events which exceed
a given amplitude threshold until ... | 7d30d9ed9d9c68c36d843939c18110ebe0162ef0 | 81,413 |
def __calculate_always_decrease_rw_values(
table_name, gsi_name, read_units, provisioned_reads,
write_units, provisioned_writes):
""" Calculate values for always-decrease-rw-together
This will only return reads and writes decreases if both reads and writes
are lower than the current provisi... | c25985b74e91794151b2c193f2b9cceae911d805 | 81,415 |
def _compute_residuals(X, column_index, alpha, gram, max_iter=5000,
tol=1e-3, method='lasso'):
"""Compute the residuals of the regression of a given column of the
design matrix against the other columns"""
n_samples, n_features = X.shape
i = column_index
X_new = np.delete(X,... | 5bb915536fa54d6a3861f6b0d3572f6674dbe2d9 | 81,416 |
def load_imagenet_targets() -> np.ndarray:
"""
Returns the ground-truth labels of the ImageNet valdation set.
"""
_check_imagenet_folder()
return tv_datasets.ImageFolder(root=ImageNetValidationData).targets | 75962488b547c0a0788ebd9dc3158340447c47c8 | 81,417 |
def create_dataset(number_of_input):
"""Create new dataset
:rtype: str
"""
dataset = models.Dataset(number_of_input=number_of_input)
dataset.save()
return str(dataset) | 666e75c723a7033bb3978ba07c118e8430aa7522 | 81,419 |
import logging
def find_log_path(lg):
"""
Find the file paths of the FileHandlers.
"""
out = []
for h in lg.handlers:
if isinstance(h, logging.FileHandler):
out.append(h.baseFilename)
return out | efab0cb7eafd0491e1365224dc83f816c7bb1b51 | 81,420 |
def apply_packaged_translation(pkg, input_text, translator, num_hypotheses=4):
"""Applies the translation in pkg to translate input_text.
Args:
pkg (Package): The package that provides the translation.
input_text (str): The text to be translated.
translator (ctranslate2.Translator): The... | e476e20a73348959e22466f94cf4033782cc791e | 81,421 |
def _shuffling_queue(shuffling_queue_capacity, min_after_dequeue, dtypes, fields_as_list):
"""Creates a shuffling queue with enqueue/dequeue pair. Always a single writing thread."""
# Named tuples loose the 'named' part when going via queue
shuffling_queue = tf.RandomShuffleQueue(shuffling_queue_capacity, min_af... | 37c832eb72dfbf8365963abacd125394f4e7612b | 81,422 |
from datetime import datetime
def json_serial(obj):
"""JSON serializer for objects not serializable by default json code"""
if isinstance(obj, datetime):
serial = obj.isoformat()
return serial
raise TypeError ("Type not serializable") | 287b7e3396bba08f001ee658e1d3adf0b4b4b12a | 81,424 |
import requests
def send_proms_pingback(pingback_target_uri, payload, mimetype='text/turtle'):
"""
Generates and posts a PROMS pingback message
:param pingback_target_uri: a URI, to where the pingback is sent
:param payload: an RDF file, in one of the allowed formats and conformant with the PROMS pin... | 09ecff1835352f08e7fc5f4bce545585798e688c | 81,426 |
def sal_structure(
prediction, observation, thr_factor=None, thr_quantile=None, tstorm_kwargs=None
):
"""
Compute the structure component for SAL based on :cite:`WPHF2008`.
Parameters
----------
prediction: array-like
Array of shape (m,n) with prediction data. NaNs are ignored.
obse... | 2b6ae019ca2aaab8ec0243f2fc5aa24f6f3c1e97 | 81,427 |
import re
def expand_zoo_variables(custom_env, string_to_process):
"""
развернуть в строке переменные окружения zoo
поискать в строке '%KEY%' если есть то заменить на соответсвующее значение из словаря
и так для каждого ключа в словаре
:param string_to_process:
:return... | 14064b112f3c46f4c22f3959aeff5cd6d02e3634 | 81,428 |
async def async_unload_entry(
hass: HomeAssistant, config_entry
): # pylint: disable=unused-argument
"""Handle integration unload"""
for cancel_handle in hass.data[DOMAIN].get("cancel_handlers", []):
if cancel_handle:
cancel_handle()
if hass.services.has_service(DOMAIN, "report"):
... | b0e0cf7a907c6106ccd17ea8705afb07f59f4041 | 81,430 |
def repeated_KFold_cv(estimator,X,y,repeat,sample_weight=None,n_splits=5,pipeline_learner_step='auto',pred_int=0,random_state=None):
"""
Perform k-fold cross-validation with multiple random splits
Args:
estimator: sklearn estimator instance
X: data matrix (nxm)
y: response (n-vector)
repeat: number of time... | 7d5dcc2a86447ae9cf576b18ce034a600d220992 | 81,431 |
from datetime import datetime
def status_summary(request):
"""Return number of recent errors as json."""
fmt = getparam(request, "fmt", "html", options=["html", "json"])
num_mins = getintparam(request, "window", 5, minimum=1, maximum=100, fmt=fmt)
mins_ago = datetime.datetime.now() - datetime.timedel... | d6ba8d1cad37f6a4b0e40d593dbc682667d97f3c | 81,432 |
import re
def split_host_port(address, default_host=None, default_port=None):
"""Split address to host port
The format of address like:
host1, host1:8888, 1.1.1.1, 1.1.1.1:8888, :8888
>>> split_host_port('host1:8888')
('host1', '8888')
>>> split_host_port('host1')
('host1', None)
... | dc75fa033d02664d47c1a62259a2e30c9a489a56 | 81,433 |
def keywords(text):
"""Get the top 10 keywords and their frequency scores ignores blacklisted
words in stopwords, counts the number of occurrences of each word, and
sorts them in reverse natural order (so descending) by number of
occurrences.
"""
text = split_words(text)
# of words before re... | 66e2cfe4af9dea6440763602b81bfc6cfb3133b7 | 81,434 |
def extract_latregion_rectilinear(cube, lat_bounds):
"""Extract region of interest from a regular lat/lon grid.
Returns subset of the original cube that contains only the latitude range of interest.
"""
southern_lat, northern_lat = lat_bounds
lat_constraint = iris.Constraint(latitude=lambda cell... | a8195d1444ca6dbfb0a2a03e5b586176d790200f | 81,436 |
from typing import Dict
def get_detail_context(workflow: models.Workflow) -> Dict:
"""Create the context to render the details page.
:param workflow: Workflow being manipulated
:return: Dictionary to render the details page
"""
context = {
'workflow': workflow,
'table_info': None}... | e1e644c6a801d7e41d7657ddc09c8b412a3b6143 | 81,437 |
def transpose2(x, dim1, dim2):
"""Transpose two axes `dim1` and `dim2` of a tensor."""
perm = list(range(len(x.shape)))
perm[dim1] = dim2
perm[dim2] = dim1
return tf.transpose(x, perm) | 710d04740f07355603225cbcd0dce2b03f8d7f7e | 81,438 |
def is_pmap(pmap):
"""Check this here so people don't mistake pmap and PMap.
Parameters
----------
pmap : obj
An object
Returns
-------
bool
Returns True if it is a pyrsistent.pmap
"""
return isinstance(pmap, PMap) | f8a28218681b445b9f7534db29654d28fcd91e9f | 81,439 |
import torch
def estimate_grad_moments(xloader, network, criterion, steps=None):
"""Estimates mean/sd of gradients without any training steps inbetween - this gives the total_XXX kind of estimators which are only evaled once per epoch on the whole dataset"""
with torch.set_grad_enabled(True):
network.eval()
... | 7bb57bd5db63270c162e6c3801bba39f2bfeba4b | 81,440 |
def register( request ):
"""
Uses the user registration form to display form, create user account from
valid data (on POST), or show errors if data is invalid. If the change is
successful, user is logged in and redirected to their homepage.
:param request: request object
:return: HttpRes... | ec9bb390f407248414db35ae4a7c8055f1508401 | 81,441 |
import requests
def public_ip():
"""
Pytest fixture for current public IP-address.
:return: Public IP-address.
:rtype: str
"""
assert PROXY_HOST is not None
r = requests.get(URL_HTTP)
assert r.status_code == 200
return r.json()['origin'] | a0614e4958356a1251432f201fc00e86d2e58dbd | 81,443 |
import torch
def patch_label_2d(
model, img, pre_processing, output_processing, patch_size, stride, batch_size, device, num_classes,
):
"""Processes a whole section"""
img = torch.squeeze(img)
h, w = img.shape[-2], img.shape[-1] # height and width
# Pad image with patch_size/2:
ps = int(np.f... | c2eee8c2c9d63b26cf3e544dfe19e90e081ec4d0 | 81,446 |
def to_2d(arg, raw=False, expand_axis=1):
"""Reshape argument to two dimensions.
If `raw` is `True`, returns NumPy array.
If 1-dim, will expand along axis 1 (i.e., Series to DataFrame with one column)."""
if raw or not checks.is_array(arg):
arg = np.asarray(arg)
if arg.ndim == 2:
r... | bdff16165384395b2cae0b244f86d8ed4c6e3efb | 81,447 |
import random
def generate_fake_ohlc_data(data_df):
"""
Generates fake ohlc data for each row of twitter sentiment dataframe. Used for testing
without creating database or making api calls to finnhub.
Args:
data_df: Dataframe containing time and twitter sentiment socres for each currency
... | 5b6608765a7a8300a17c9cda3a4dab3a2c18327b | 81,448 |
def index(request):
"""View function for Home page site"""
# Generate counts of some of the main objects
num_bloggers = BlogAuthor.objects.count()
num_blogs = Blog.objects.count()
num_comments = Comment.objects.count()
context = {
'num_bloggers': num_bloggers,
'num_blogs': num_bl... | 2918cd4d2f4793beaddb88713d24e18346cec797 | 81,449 |
def handle_accept(current_request=None):
"""处理C端 accept"""
url_prefix = "http://" + current_request.host
c_path = current_request.path
#类似 /v1/h5/house/info
url_suffix = c_path.replace(url_prefix, "")
a = my_config.getAccept(url_suffix)
logger.info("Accept is %s", a)
return a | d5469dec08602610f3922fa9acb09e78e1c2989d | 81,450 |
def simple_doctor_alarm_generators(update_vals=None):
"""A function for returning Doctor alarm event generators.
Returns generators for a given number of Doctor alarms.
:param update_vals: preset values for ALL update events
:return: generators for alarms as specified
"""
return _simple_alarm_... | 236d01f23ed3c3095488d2de6343285f0e8ae301 | 81,451 |
def open_acqusition(c3d_file):
""" Opens a c3d file with BTK """
reader = btk.btkAcquisitionFileReader()
reader.SetFilename(c3d_file)
reader.Update()
return reader.GetOutput() | c961b7581c7347ec537429c50277e99e3b5697df | 81,452 |
def merge_wordpiece_tokens(paired_tokens):
"""
Combine tokens that have been broken up during the wordpiece tokenization process
The weights of the merged token is the average of their wordpieces
:param paired_tokens: A list of tuples with the form (wordpiece_token, attention_weight)
:return: A list... | f33edbcb48e54277d7bc4132c0cfa67aa1170cf0 | 81,453 |
def home():
"""List all available api routes."""
return (
f"Welcome to Honolulu, Hawaii's Climate Home Page:<br/>"
f"Available Routes:<br/>"
f"<br/>"
f"List of Precipitation Data with Corresponding Dates:<br/>"
f"/api/v1.0/precipitation<br/>"
f"<br/>"
f"Li... | 08cb0c5ae57d3dd672459aef018c7de9d1cbab56 | 81,454 |
def index():
"""
Redirect to the root of the swagger docs
"""
return redirect('/apidocs/') | 480b106ab557c3957add6c10752ef41d0065a3cc | 81,455 |
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