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def pratt(Ea,Ed):
"""
Created on Tue Oct 12 09:58:15 2021
@author: kondow_a
Converted from
Vivek Bhadouria (2021). Pratt's Figure of Merit
(https://www.mathworks.com/matlabcentral/fileexchange
/60473-pratt-s-figure-of-merit),
MATLAB Central File Exchange. Retrieved October 1... | c1af52d4384756f5fd1bf409d9f53d2ceae60c91 | 3,608,500 |
import requests
def get_weather(furl):
"""
Get the weather of a city given API call.
:param furl: URL of the API call.
:return: JSON response with weather data.
req = requests.get(furl)
"""
req = requests.get(furl)
return req.json() | 7aa9c484c368fb61b9b6bf360dffa732e661b037 | 3,608,501 |
import nose
def import_nose():
""" Import nose only when needed.
"""
nose_is_good = True
minimum_nose_version = (1, 0, 0)
try:
except ImportError:
nose_is_good = False
else:
if nose.__versioninfo__ < minimum_nose_version:
nose_is_good = False
if not nose_is... | 8828c6911423094c38df79e0e31df4d4f0ffd266 | 3,608,502 |
def curry(f, *args, _curry_force_call=False, _curry_allow_uninspectable=False, **kwargs):
"""Decorator: curry the function f.
Essentially, the resulting function automatically chains partial application
until the minimum positional arity of ``f`` is satisfied, at which point
``f``is called.
Also m... | 7f47c0826fba89262e99eeef92c62a5c29885751 | 3,608,503 |
import torchvision
import torch
import argparse
def choose_network(model_type, pre_trained_flag):
"""
选取特征提取器
使用官方的实现，但是所有网络都去掉全链接层
"""
if model_type == 'alexnet':
model = torchvision.models.alexnet(pretrained=pre_trained_flag)
new_classifier = nn.Sequential(*list(model.classifier.... | dcc4247ada208868aefc8e81a0bde5e115e4358f | 3,608,504 |
def checkpoint_list_objects_command(client: Client, limit: int, offset: int, filter_search: str,
ip_only: bool, object_type: str) -> CommandResults:
"""
Retrieve data about objects.
Args:
client (Client): CheckPoint client.
limit (int): The ma... | d776c3dd26656379349f860b830b2ae54e1a821f | 3,608,505 |
import os
def mimic_path_relativity(path, other, default_dir):
"""If 'other' file is relative, make 'path' relative, otherwise make it
absolute.
"""
if os.path.isabs(other):
return os.path.join(default_dir, path)
if os.path.isabs(path):
return os.path.relpath(path, default_dir)
... | 5a8243446db11cf13f8fa8f47bac4f05f032c30c | 3,608,506 |
def polyglot_2nd_number(s):
"""Get second number from the sentence.
Parameters
----------
:param s: string
Sentence
Returns
-------
:returns: string
second number
"""
numbers = polyglot_numbers(s)
if len(numbers) > 1:
return numbers[1]
else:
... | e0131b2742e20673d2561cdb7014cb803e157f60 | 3,608,507 |
def string_set_intersection(set_a, set_b, ignore_case=True, sep=","):
"""
Return intersection of two coma-separated sets
:type set_a str
:type set_b str
:type ignore_case bool
:type sep str
:rtype set
"""
if set_a is None or set_b is None:
return set()
if ignore_case:
set_a = set_a.lower(... | bd444273c17dc747f6856531c12d0b7280fb5aa3 | 3,608,508 |
def Main(a, b, c, d):
"""
:param a:
:param b:
:param c:
:param d:
:return:
"""
m = 0
if a > b:
if c > d:
m = 3
else:
if b > c:
return 8
else:
return 10
else:
if c > d:
... | d3e12e98bda3109f31e9286b8e95c92bb3e416c0 | 3,608,509 |
def ldns_verify_rrsig(*args):
"""LDNS buffer."""
return _ldns.ldns_verify_rrsig(*args) | 20095cd97e5067ec55d53460ff1fd501ac4eba3c | 3,608,510 |
def load_obj(name, folder ):
"""
To load a .pkl object from a desired folder
Parameters
----------
name : string
name of the object to be loaded
folder: string
name of the folder where the object is.
Returns
-------
returns the .pkl object to b... | 5025a82d0f2ecebfe4c36f223bea3b2f0b561fdf | 3,608,511 |
def load_data_from_days_mat(mat_data_path_name,mat_variable_name,get_meta=False):
"""
mat
"""
mat_data=sio.loadmat(mat_data_path_name)
data=mat_data[mat_variable_name].astype('float32')
if get_meta:
meta=compute_data_meta(data,axis=(0,1,2))
return data,meta
else:
return data | 0cf19c0c94f185e6e68b93def00576226ec75cbd | 3,608,512 |
def c1Dtochi(c1D, box_size, r_min=None, r_max=None):
"""
For the cylindrically-averaged 1D correlation function c1D(r), this
function returns the 2D susceptibility of the square box system of length
L, defined as chi = 2\\pi/L^2 \\int_{r_min}^{r_max} dr c1D(r).
NOTE: for displacement-related correlations, this sus... | 47849480ae7cb7e060c40e88cf556fd8fca8d641 | 3,608,513 |
def traverse_file_structure(current, function, **inner_function_args):
"""Recursively traverses the given folder and applies the function to every file that it finds.
:param current: Source folder
:type current: stibnite.file_operations.FolderType
:param function: The function that will be applied to f... | 93312cb2792a27c1441a3794ca261bc67c22171a | 3,608,514 |
def compute_mt_attention(model, inputs, targets, task=None, device=0):
"""
"""
inputs = place_on_gpu(inputs, device=device)
model = model.to(device=device)
model.eval()
for task_head in model.decoder.task_heads.values():
task_head.region_aware = True
model_output = model(inputs, targ... | 96769a496f63c6554363fce1fbeff2e111eb742a | 3,608,515 |
import time
def my_model_file():
"""
根据我自己训练的NER模型进行提取
Returns:
"""
time.sleep(2)
try:
if request.files:
file = request.files["file"]
msg_dict = extract_data_from_file(file)
return jsonify({"code": 200, **msg_dict})
else:
return ... | d26efd0c963856026ed181a5811568c9523749e9 | 3,608,516 |
def discreteOperatorToPreconditioner(op):
"""
Create a preconditioner from a discrete boundary operator.
*Parameters:*
- op (DiscreteBoundaryOperator)
A discrete operator, which acts as preconditioner, e.g. an ACA
approximate LU decomposition or a sparse inverse.
*Returns*... | 8dde3df2e5ac076dbd6d4ddbeae18b8b7d50ce3a | 3,608,517 |
from typing import Dict
from typing import List
def find_input_layers(node_layer_map: Dict) -> List[tf.keras.layers.InputLayer]:
"""
helper to find the input layers of the model.
:param node_layer_ref: dictionary includes node_ref as a key, in_layers and out_layer as value
:return: return list of inp... | b4ce3ef67a4ffa952b8775ac66c87e70a7009292 | 3,608,518 |
def findDissimilar(index, minibatch1, minibatch2, actions, rewards):
"""
check which samples should be dissimilar
because they lead to different rewards after the same actions
:param index: (int)
:param minibatch1: (np.ndarray)
:param minibatch2: (np.ndarray)
:param actions: (np.ndarray)
... | 20c5cdcab1f0ebacd38e63e1f29be42ded37baa8 | 3,608,519 |
def med_blur(img, ksize=3, flag=False):
"""
Median filter for input image
:param img: input image
:param ksize: size of filter
:return: image after median filter
"""
if img.dtype is not np.uint8:
img = img.astype(np.uint8)
new_img = cv.medianBlur(img, ksize)
if flag:
... | 19992aed9a4834cb7610894af45f60ff51b4a09b | 3,608,520 |
def plot_source_type_histogram(docs, **kwargs):
""" Plot histogram of the number of documents by publication source
type. """
default = dict(title='Publication source type', limit=25)
return wrapper(docs, compute_source_type_histogram, default, **kwargs) | ae90f7a7140c4b63e34445c0a5623b243ddc8cea | 3,608,521 |
def gyy(lons, lats, heights, tesseroids, dens=None, ratio=2.5):
"""
Calculate the yy (East-East) component of the gravity gradient tensor
due to a tesseroid model.
"""
return SI2EOTVOS * _optimal_discretize(tesseroids, lons, lats, heights,
_gyy, ratio, dens... | 20df89dc3b5bead73a68f850f071d723139eff88 | 3,608,522 |
def extract_text(dom, name, wrapper=None):
"""
Function tries to extract text data from the first tag
with a given name and wrapps it in a give function / class.
"""
elements = dom.getElementsByTagName(name)
if elements:
text = elements[0].lastChild.data
else:
text = ""
r... | 19edcf8daad4438fc2096cc19dc7091df46bcdc0 | 3,608,523 |
def FMetisShad2(fGHz,r,D,sign=1):
""" F Metis shadowing function
Parameters
----------
fGHz : np.array(Nf)
frequency GHz
r : np.array(Nseg,)
distance between Tx and Rx
D : np.array(Nseg,Nscreen)
indirect distance between Tx and Rx (screen effect)
sign : np.array(Nse... | be8c9cad7dd69dfbca4fa945edf6cb4a6b38b724 | 3,608,524 |
def get_app_settings() -> AppSettings:
"""
This function returns a cached instance of the AppSettings object.
Returns certain settings depending on the set APP_ENV environment variable.
Caching is used to prevent re-reading the environment every time the API settings
are used in an endpoint. If y... | 01057df01cf56914d8f092241e9fbbe0da305714 | 3,608,525 |
def AddDefaultLocationToAllocationEndpointRequest(ref, unused_arguments, req):
"""Python hook to set default global location in allocation endpoint requests."""
del ref
project = properties.VALUES.core.project.Get(required=True)
# Use global for the location value
location = 'global'
req.parent = PARENT_TEM... | 1b6a3557ac329316022812119cf01378e73ea688 | 3,608,526 |
def parse_args():
"""Parse arguments"""
usage = ('usage: %prog'
+ ' [--no-personals]'
+ ' [--protocol=zephyr|zulip]'
+ ' [--zulip-rc]'
+ ' [--default-classes]'
+ ' [--class=class ...]')
parser = OptionParser(usage=usage)
parser.add_option(... | 4159b804cf710f3f7573e1e348cd5fb7e79fcad1 | 3,608,527 |
def loading_matfile(file_name, key, key2=''):
"""
@ param: string: file_name
@ param: string: key
return: key data in numpy.array form
"""
if file_name is None:
print("Invalid file name!")
# res = loadmat(file_name)[key]
f = h5py.File(file_name, 'r')
res = f.get(key + "/" + k... | e6a902add48c141145627feec3ed15c0f0bab12d | 3,608,528 |
def center_elevation_map(elevation, width, height):
"""Translate the map horizontally and vertically to put as much ocean as possible at the borders."""
miny = None
ymin = None
minx = None
xmin = None
for y in xrange(height):
sumy = 0
for x in xrange(width):
sumy += ... | 143dfdbec7e5e26e8208f57965d53633f14b7494 | 3,608,529 |
def multilingual(request):
"""
Returns context variables containing information about available languages.
"""
codes = sorted(get_language_code_list())
return {'LANGUAGE_CODES': codes,
'LANGUAGE_CODES_AND_NAMES': [(c, LANG_DICT.get(c, c)) for c in codes],
'DEFAULT_LANGUAGE_C... | a04d9ab287ddf774a701e920778abbcc5e899e62 | 3,608,530 |
from typing import Optional
def curie_lookup(curie: str) -> Optional[str]:
"""
Given a CURIE, find its label.
This method first does a lookup in predefined maps. If none found,
it makes use of CurieLookupService to look for the CURIE in a set
of preloaded ontologies.
Parameters
---------... | 5e6428852619e55d2f5cb025644d72ed5ca7c4eb | 3,608,531 |
import os
def get_eessi_envvar(eessi_envvar):
"""Get an EESSI environment variable from the environment"""
eessi_envvar_value = os.getenv(eessi_envvar)
if eessi_envvar_value is None:
raise EasyBuildError("$%s is not defined!", eessi_envvar)
return eessi_envvar_value | e87865813a1ef9a8a07884bafb589d7266250a73 | 3,608,532 |
def write_all_output_csv(out_dict, org_list, csv_rbh_output_filename, csv_strict_output_filename,
csv_ns_output_filename, DEBUG, debug, good_tax_list):
"""
Writes formatted final output to CSV.
:param out_dict: a dictionary of dictionaries
:param org_list: a list of organisms
... | 9e15b9ab739693c517f69e8621fa2a53c7c053c9 | 3,608,533 |
def youden_onecut(data, pred_col, duration_col, event_col, pt=None):
"""Cutoff maximize Youden Index.
Parameters
----------
data : pandas.DataFrame
full survival data.
pred_col : str
Name of column to reference for dividing groups.
duration_col : str
Name of column indic... | a96f83c14494cf27afb981f3f5dbd99628c5b412 | 3,608,534 |
import itertools
def make_multislice_graph(net_list, w):
"""Makes a multislice representation of a list of separate networks.
Creates a single network object representing the specified multislice
structure. Every vertex appears once for each network where it is present.
Multislice connections occur b... | cdd08acdf6c1faae13685d718d9d7ccff71a1f10 | 3,608,535 |
import functools
def SupplyImpliedArguments(fn, namespace):
"""!
@brief Supply values from namespace to keyword-only no-default arguments.
@param[in] fn A function.
@param[in] namespace A dict(str => ..)
@return fn wrapped to get arguments from namespace.
"""
iargs = ImpliedArguments(fn)
... | e9d39458b3b61ea1a7816ac678a9af57ea4940eb | 3,608,536 |
def node_neighbors_average(
node,
nodes,
values,
n: int = 50):
"""
:param node: objective node
:param nodes: grid nodes
:param values: values calculated in nodes
:param n: number of neighbors
:return value: averaged value
Find the the average value for a node... | 1c6724a73df0781b2013d8262c3033254c7687d5 | 3,608,537 |
def layout(response: mara_page.response.Response) -> str:
"""Renders a complete html page for the response"""
return '<!DOCTYPE html>\n' + str(
_.html(lang='en')[
_.head[
head_elements(response)
],
_.body(class_='navigation-collapsed')[
... | 9204be7df1edb002357bfe05ece1eeec792d3ce9 | 3,608,538 |
import argparse
def get_args():
"""
Get arguments of the program
:return: arguments parsed
"""
parser = argparse.ArgumentParser(
"Split a video in several images"
)
parser.add_argument("--path_video", type=str, help="Path to the input video", default="")
parser.add_argu... | 59c8e728930e534b95e07d0c03fa9c8932fb31de | 3,608,539 |
def map_enum_fields(field: tp.Any, enum: tp.Enum, **kwargs) -> tp.Any:
"""Map fields to values.
See `vectorbt.utils.mapping.apply_mapping`."""
mapping = to_mapping(enum, reverse=True)
return apply_mapping(field, mapping, **kwargs) | 5e8592d3cf3584d62e902e0f50b7572d645cc8c0 | 3,608,540 |
def _to_xy(df, target):
"""Converts a Pandas dataframe to the x,y inputs that TensorFlow needs"""
return df.loc[:, df.columns != target].values.astype(np.float32),\
df.loc[:, target].values.astype(np.float32) | 941516cd0c2c5ba4a8e311b4d5f4851d686b0938 | 3,608,541 |
import torch
def affine(data: dict, matrix: torch.tensor, visualize: bool = False) -> dict:
"""
Applies affine transformation to the data
:param data dict of elements to be transformed
:param matrix: matrix of transformation
:param visualize: if true it activates the display tool to debug the ... | dfc2bb71587d29d01ee4fecac9364d61068b04ee | 3,608,542 |
from typing import Optional
import types
def make_reverb_dataset(
server_address: str,
batch_size: Optional[int] = None,
prefetch_size: Optional[int] = None,
table: str = adders.DEFAULT_PRIORITY_TABLE,
num_parallel_calls: int = 12,
max_in_flight_samples_per_worker: Optional[int] = None,
po... | a23b01852148d1f86012d717bd0630fd9b887bab | 3,608,543 |
def unmask(data):
""" transform masked array into regular numpy array """
data_out = {}
for k in data.keys():
if type(data[k]) is np.ma.core.MaskedArray:
data_out[k] = data[k].data
else:
data_out[k] = data[k]
return data_out | 3d9a25a56614b03b51138365a568ecb4450e9c2c | 3,608,544 |
def get_locale():
"""how to get the locale is defined by you.
Match by the Accept Language header::
match = app.config.get('BABEL_SUPPORTED_LOCALES', ['en', 'zh'])
default = app.config.get('BABEL_DEFAULT_LOCALES', 'en')
return request.accept_languages.best_match(match, default)
"""... | 351a8ca65820d3169de694d44919f610d3faea98 | 3,608,545 |
import math
def R_2vect(vector_orig, vector_fin):
"""
Taken from:
https://github.com/Wallacoloo/printipi/blob/master/util/rotation_matrix.py
Calculate the rotation matrix required to rotate from one vector to another.
For the rotation of one vector to another, there are an infinit series of
ro... | bbb9edb627ac438bddd87e9e49e5595ba78bce95 | 3,608,546 |
def create_numpy_image(dtype_name, nchannels, order='c'):
"""
Create a numpy image with 'nchannels' channels of major ordering
of 'order'
:param: nchannels: The number of channels the created image is to have
:param: order: major ordering of created image. Default: column major ordering
:return:... | c3dc9f92612625fa4eac1b6f4c0a5334e8e0d053 | 3,608,547 |
import random
def buildModel():
"""
Поток заявок поступает в накопитель с допустимой ёмкостью, равной 3 единицам, равномерно каждые 5+/-1 мин. Если заявки после накопителя застают 2-й канал (устройсто) занятым, то они поступают на обработку во второй канал. Время обработки 1-го канала равно 13+/-1 мин, 2-го 9... | 9a91844942efb4d1e75547a4c21a474b95d70ccb | 3,608,548 |
def uniform_random_sample(H,persis_info,gen_specs,_):
"""
Generates ``gen_specs['gen_batch_size']`` points uniformly over the domain
defined by ``gen_specs['ub']`` and ``gen_specs['lb']``.
:See:
``libensemble/tests/regression_tests/test_6-hump_camel_uniform_sampling.py``
"""
ub = gen_sp... | 837994b5bb5ae3d833997bff9158e47effa9a3d4 | 3,608,549 |
import json
def handle_callback(request):
"""Check the token and save it as a cookie if correct."""
if request.args.get("error"):
return request.args["error"]
discord = make_session(request, state=request.ctx.session.get("oauth2_state"))
try:
token = discord.fetch_token(
"https://discordapp.com/... | 0ef0df0b846507250a707c526fcc773a38dd5464 | 3,608,550 |
def get_cache_manager():
"""Returns an instance of CacheManager."""
cache_manager = cache.CacheManager()
cache_manager.initialize(cache.MemCache())
return cache_manager | 8895e03119f4b0f68ef31ddb76813aabb10674fa | 3,608,551 |
def normal_map(tensor, shape):
"""
Generate a tangent-space normal map.
.. image:: images/normals.jpg
:width: 1024
:height: 256
:alt: Noisemaker example output (CC0)
:param Tensor tensor:
:param list[int] shape:
:return: Tensor
"""
height, width, channels = shape
... | edc19b6c300696ed6445793839c5fa763f00458e | 3,608,552 |
import functools
from typing import Any
def _generate_class_wrapper(obj: RealClass) -> WrappedClass:
"""Function decorators"""
fn: RealFunction = obj.__init__
@functools.wraps(fn)
def new_init(*args: Any, **kwargs: Any) -> None:
setattr(args[0], RAW_KEY, kwargs) # set the raw data on self
... | f212a07e834ae605d4a258d1ea7bed9a88faa502 | 3,608,553 |
import re
def get_source(cell):
"""
Returns the source code of a cell in a way that works for both nbformat and JSON
Args:
cell (``nbformat.NotebookNode``): notebook cell
Returns:
``list`` of ``str``: each line of the cell source stripped of ending line breaks
"""
sou... | c8d61cd66ed7eb00a38d6e3f9bccf58495de69bf | 3,608,554 |
import datasets
from pydantic import BaseModel # noqa: E0611
def load_model(masks: np.ndarray, dataset: datasets.BaseDataset, iou: float,
backbone: str, **kwargs) -> BaseModel:
"""load the model for the training
Arguments:
masks {np.ndarray} -- the mask used
dataset {datas... | 2b004922c660602998fe759d8de6f0f8a6123980 | 3,608,555 |
def app():
"""Test server"""
# Instance of Flask server for test suite
app = create_app()
# Grab FLASK_ENV and format it into a config name, then add that config to our app
app.config.from_object("config.TestConfig")
return app | 43f136cd9744f60ed810d8df320641d11f6de0f0 | 3,608,556 |
def parse_ea_from_binary(mode: int, register: int, size: OpSize, is_source: bool, data : bytearray) -> (EAMode, int):
"""
Takes in the paramaters and returns a newly constructed EAMode and the amount of
words of data that it used. If the paramaters were illegal in any way then
(None, 0) is returned
... | 4306389c81051ab4906dc1b1ae615fa616090e2f | 3,608,557 |
def subplots(nrows=1, ncols=1, width_ratios=None, height_ratios=None, **fig_kw):
"""Create a figure and a set of subplots.
Parameters
----------
nrows, ncols : int, default: 1
Number of rows/columns of the subplot grid.
width_ratios : array-like of length *ncols*, optional
Defines ... | cad6fab1a9f31529d00bca88edaa1e615153db12 | 3,608,558 |
import requests
import re
def get_dimension_values(dimension_code='YEAR', search_for=''):
"""
Allows user to inspect, and run a case-insensitive search through the values of a specific dimension.
Parameters
----------
dimension_code : str
The GHO database unique identifier for each dimen... | 0b04c73bec23d682d872ee4d0a24ef5a8700f10f | 3,608,559 |
import torch
def sgd_step(self, closure=None):
"""Performs a single optimization step.
Args:
closure (callable, optional): A closure that reevaluates the model
and returns the loss.
"""
loss = None
if closure is not None:
with torch.enable_grad():
loss = cl... | 97bcd84075290281ce30a73d82300f9b03c384c8 | 3,608,560 |
def dedup_whoopsies(sortedWhoopsies):
""" Take whoopsies sorted first by qid, then
magnitude, then return the worst whoopsie
by query """
mergedWhoopsies = iter(sortedWhoopsies)
whoopsies = []
whoopsie = None
lastQid = -1
try:
while True:
# Read ahead to next... | dfac3eda077e544df39539c4ea10d0a0eb7c6b7e | 3,608,561 |
import string
def processPDF(dictionary):
"""
Process the PDFs that can be found in the dictionary, created by the readPDF function.
This includes removing stopwords, punctuations, digits, whitespaces, line breaks, and lemmatizes and stems all the words.
Parameters:
dictionary: dictionary
... | 07faf21ccf53c0ad101cb3d9fb83675f3d391611 | 3,608,562 |
def prioritize_nodes(graph, where_conditions):
"""Assign high priority to nodes mentioned in where conditions."""
priorities = {}
for node in graph.keys():
priorities[node] = 1
return priorities | 60ef01d7bba9b03925a35e9fae602118207a208a | 3,608,563 |
import random
def _place_image(canvas, image):
"""
Returns the x and y co-ordinate the "image" should be placed at on the
"canvas".
"""
global objects
moments = _color_moments(image)
if len(objects) == 0:
x_val = int((canvas.size[0] - image.size[0]) / 2)
y_val = int((canv... | 9238255bc57f13a8914674c6b0aa1a3f48f80b7e | 3,608,564 |
def read_file_pdf():
"""pdf files
---
parameters:
- name: input_file
in: formData
type: file
required: true
responses:
200:
description: Output
"""
pdfReader = PyPDF2.PdfFileReader(request.files.get("input_file"))
text = ""
for page in range(pdfReader.numPages):
text = text + pdf... | 623817577d5fde8042bf3e9648010960782e71bc | 3,608,565 |
def jissue_field_prepare_dummy_s(project, inst):
""" This method returns a dummy string, it is a reference to understand how the issues
are created and are working in jira, each field has specific attributes, depending
on the field type. To get the attributes one easy whay is to check an issue direc... | 16ef7c7e94c82d5d752577e270f121b16e903bc3 | 3,608,566 |
def no_of_passwords(k=0):
"""
All are lowercase english alphabet. So for each position we have 26 possibilities.
length_of_passwords = 5
each_position_no_of_possibilities = 26
"""
n = 26
k = 5
return n**k | 01898ae8eda0234858d2be1ff767a13ddb466a31 | 3,608,567 |
def get_shape_ids(conn, roi_id, across_groups=True):
"""Get IDs of shapes associated with an ROI
Parameters
----------
conn : ``omero.gateway.BlitzGateway`` object
OMERO connection.
roi_id : int
ID of ``ROI``.
across_groups : bool, optional
Defines cross-group behavior o... | a657326e6a84f3e80a5c89235daf9da1d52ac3ba | 3,608,568 |
def env_start():
""" returns numpy array """
global maze, current_position
start_position = [0,3] #maze[0][3] # start [x,y]
current_position = start_position
return start_position | a12f2ea46c8ea41923842fd79e9ae91f0441a8ea | 3,608,569 |
import logging
async def prover_get_credential(wallet_handle: int,
cred_id: str) -> str:
"""
Gets human readable credential by the given id.
:param wallet_handle: wallet handler (created by open_wallet).
:param cred_id: Identifier by which requested credential is store... | 87f5d47942410b9f2653be26b52c61cd55ef32ad | 3,608,570 |
def rdist(x, y):
"""Reduced Euclidean distance.
Parameters
----------
x: array of shape (embedding_dim,)
y: array of shape (embedding_dim,)
Returns
-------
The squared euclidean distance between x and y
"""
result = 0.0
for i in range(x.shape[0]):
result += (x[i] - ... | 3caa871145b8ca68c0cd2bd23a183967b7b5b7cc | 3,608,571 |
import logging
import torch
def evaluate_dev_set(model, data, criterion, data_loader, device):
"""
Evaluates the model performance on dev data
"""
logging.info('Evaluating accuracy on dev set')
y_true = list()
y_pred = list()
total_loss = 0
for batch, targets, lengths, raw_data in dat... | 4f61eaf29b42477e7e01aa74cd020053ebff5698 | 3,608,572 |
def _handle_time(time_label, time_unit, times):
"""Handle time label string and units."""
_validate_type(time_label, (None, str, 'callable'), 'time_label')
if time_label == 'auto':
if times is not None and len(times) > 1:
if time_unit == 's':
time_label = 'time=%0.3fs'
... | 5b894aadd3997aff8b91c1a1e5908d1faa9160de | 3,608,573 |
def argmax_decode(prediction):
""" Decode a prediction using the highest probable character at each
timestep. Then, simply convert the integer sequence to text
Params:
prediction (np.array): timestep * num_characters
"""
int_sequence = []
for timestep in prediction:
int_seque... | 082baa4a5401353f1237d9a469970d5afc495bd3 | 3,608,574 |
def quality_of_life(state, time, config, intervention=None):
"""Get the world2 quality of life metric derived from a state.
Parameters
----------
state: whynot.simulators.world2.State or iterable representing a state.
State of the dynamics
time: float
config: world2.C... | 60e09bd475e785dfe788ae203e6c3da5f0d11ff3 | 3,608,575 |
def get_face_encoding(image, detected_face):
"""
Encode face into 128 measurements using a neural net
:param image: picture numpy array
:param detected_face: face detector object with one detected face
:return: measurement (128,) numpy array
"""
pose_landmarks = face_pose_predictor(image, d... | aa8ebda712dea3dfc20c30ba8912ffad77d5a0aa | 3,608,576 |
def reject_task_create(events, **kw):
"""Possible argument to attr_handler()"""
events = [e for e in events if type(e) is not ThreadTaskCreate]
if len(events) == 1:
return events[0]
else:
return events | aa3d6f1b29f72111488018527696a11e25d1d836 | 3,608,577 |
def list_products():
""" Returns all of the Products """
app.logger.info("Request for Product list")
products = []
category = request.args.get("category")
name = request.args.get("name")
if category:
products = Product.find_by_category(category)
elif name:
products = Product.... | 5a257c2dfddb777fcd3b016f80320d4348cbed11 | 3,608,578 |
def preprocess_obs(obs, imsize):
""" function to preprocess observation from env """
c = obs['images']
# image
c = preprocess_image(c)
return c | e69915f4b1148f6e9d8d4856285e150eeffdd6e6 | 3,608,579 |
def quadratic_approximation(x_list, y_list):
"""
Аппроксимация квадратичной функцией
Parameters
----------
x_list : [float, float, ...]
Список координат х.
y_list : [float, float, ...]
Список координат у.
Returns
-------
x_koef : [float, float, float]
Список... | 331a52c06aea40f5600897dbba389b3d5962744c | 3,608,580 |
import os
def task_exist(project_name, task_name):
"""
Checks existence of task.
:param project_name: name of project whose task we are going to be looking for
:param task_name: name of task that we are looking for
:return: boolean
"""
if '.' in task_name:
task_name = os.path.spli... | 0e88146f69cfdc99710acc10c0af7ce9517f8430 | 3,608,581 |
def rref(m):
"""Row reduced echelon form of matrix"""
n = len(m)
M = len(m[0])
if n == M:
for row in m:
row.append(0)
_rref(m,n,M)
for row in m:
row.pop()
elif n != M:
_rref(m,n,M)
return m | 2e75fe50bb9dcfb57fff5a64c741e4f4779996f2 | 3,608,582 |
import glob
def find_file(path):
"""
Search file
Parameters
----------
path : str
Path and pattern to find files.
Returns
-------
str or list of str
List of files.
"""
file_path = glob.glob(path)
if len(file_path) == 0:
raise ValueError("!!! No fil... | a5176d5caa5cef6ca2724c79e3f920cfc96aea0c | 3,608,583 |
def set_updated_site(site_id, ttl=2*3600):
"""
设置站点更新标记，2 小时
"""
key = settings.REDIS_UPDATED_SITE_KEY % site_id
return R.set(key, '1', ttl) | 955ae942baff8d3346eb633cb3c215a2b7ab4d10 | 3,608,584 |
import numpy
def compute_ivectors(gmm_stats, ivector_machine):
"""
Given :py:class:`bob.learn.em.GMMStats` and an T matrix, get the iVectors.
"""
ivectors = []
for g in gmm_stats:
ivectors.append(ivector_machine(g))
return numpy.array(ivectors) | 26d25ebd1acfd65571aa91a292c05ec70c35fc58 | 3,608,585 |
from typing import OrderedDict
def data_preparation_be(country_attributes,reversed_dates=True):
"""
Creates an sorted dictionary of dates, new cases and tests for the Belgian Covid-19 data
Parameters
----------
country_attributes : dict
A dictionary containing country attributes
rever... | a0a2389c7f1ad81e79e42217b2855bf81f8663a9 | 3,608,586 |
from pathlib import Path
from datetime import datetime
import os
def RunPipeline(config, start_population_size):
""" Run the daedalus Microsimulation pipeline
Parameters
----------
config : ConfigTree
Config file to run the pipeline
start_population_size: int
Size of the starting p... | f837699367a7038b2f568a3ab6c97863d52f761a | 3,608,587 |
import os
def get_html_theme_path():
"""Return list of HTML theme paths."""
cur_dir = os.path.abspath(os.path.dirname(__file__))
return [cur_dir] | 9041e859b786d33257ac3e972c223474261bceca | 3,608,588 |
def invert_hiearchy(hierarchy):
"""Method to return the inverted hierarchy (1-res_seq)
:param :py:obj:`~gemmi.Structure` hierarchy: pdb hierarchy to be inverted
:returns: the :py:obj:`~gemmi.Structure` hierarchy corresponding with the inverted sequence (1-res_seq)
"""
inverted_model = gemmi.Model(... | cde371da9c512cd98dd38c129995ec854d9061d2 | 3,608,589 |
def __minimaxav_bruteforce(profile, committeesize):
"""Brute-force algorithm for computing Minimax AV (MAV)"""
opt_committees = []
opt_mavscore = profile.num_cand + 1
for comm in combinations(list(range(profile.num_cand)), committeesize):
score = scores.mavscore(profile, comm)
if score <... | e97d1bf465bfcc0dbe117a714986173210e173bf | 3,608,590 |
import re
def get_potential_dois_from_text(text):
"""use multiple different regexes to get a list of potential dois,
it uses a very generic regex first which only checks for the bare minimum start to the end of line,
this result will than be searched for possible endings generating possible dois
... | 2a5d8af511fa13bd28c06c1715a1adbd787ee70b | 3,608,591 |
def my_getrss():
""" See http://stackoverflow.com/questions/669438/how-to-get-memory-usage-at-run-time-in-c """
fp = None
try:
fp = open("/proc/self/stat")
parts = fp.read().split()
return int(parts[23]) * _sc_page_size / 1024
finally:
if fp:
fp.close() | 8c073b9e06c57bbd2fc3c7aa7829e6f40da61ef2 | 3,608,592 |
import scipy
def hindered_rotor_d_heat_capacity_d_barr(T, freq, barr):
"""
Return the first derivative of the heat capacity with respect to the
hindered rotor frequency in J/mol*K/cm^-1 at the given set of temperatures
`Tlist` in K, evaluated at the frequency `freq` in cm^-1 and a barrier
height `... | 138149a65c80d04d909cfe480427628adbdbd046 | 3,608,593 |
import torch
import time
def predict(image, checkpoint_path, topk, use_gpu):
"""
Loads a model from the given checkpoint file and predicts what
flower the given image is and the related probability.
Parameters:
image - A NumPy array representing the desired image
checkpoint_path -... | 852a802616f35cf3d09f22a2336a781559bfe1c6 | 3,608,594 |
import time
def get_new_items(ticker: str, channel='@newswire', max_iterations = 60, until = 0):
"""Gets news items from ceo using ticker
Parameters:
ticker - stock ticker, for example APHA
channel - can be @newswire, @thenewswire
max_iterations - max number of reques... | 1d9fb1396907fd4936145adb9de18f8a03bd428c | 3,608,595 |
from pathlib import Path
def get_file_info(dataset: Dataset,
file_path: MetadataPath) -> FileInfo:
"""
Get information about the file in the dataset or
None, if the file is not part of the dataset.
"""
# Convert the metadata file-path into a system file path
path = Path(file... | 443fddb515f6ce6f8f439dd89cb7b79887d0012b | 3,608,596 |
def is_json(request):
"""Indicates if this request is JSON or not. By default a request
is considered to include JSON data if the mimetype is
``application/json`` or ``application/*+json``.
.. versionadded:: 0.11
"""
mt = request.mimetype
app.logger.info("Mime Type: %s" %mt);
if mt == ... | 3d81d11b068f5d2c09693279f15c0ca39c2eeaba | 3,608,597 |
from typing import List
from typing import Callable
import tqdm
import pickle
import math
def _build_query_ann_index(
bucket_filenames: List[str], process_spectrum: Callable,
vectorize: Callable, n_probe: int, batch_size: int, n_neighbors: int,
n_neighbors_ann: int, precursor_tol_mass: float,
... | 644469888045b9c4dd65bb4fec50b2d2f1993e29 | 3,608,598 |
import hashlib
import json
def _hasher(obj):
"""Computes non-cryptographic hash of an object."""
h = hashlib.md5(json.dumps(obj).encode())
return h.hexdigest() | 14262878ac53af8f49f7fef4c028be36e4370725 | 3,608,599 |
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