content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def _to_system(abbreviation):
"""Converts an abbreviation to a system identifier.
Args:
abbreviation: a `pronto.Term.id`
Returns:
a system identifier
"""
try:
return {
'HP': 'http://www.human-phenotype-ontology.org/'
}[abbreviation]
except KeyError:
... | f43942b242e67866028a385e6614133dc25b31b0 | 16,600 |
from typing import Union
def apply_gate(circ: QuantumCircuit, qreg: QuantumRegister, gate: GateObj,
parameterise: bool = False, param: Union[Parameter, tuple] = None):
"""Applies a gate to a quantum circuit.
More complicated gates such as RXX gates should be decomposed into single qubit
ga... | 0babd68efb8bae67c5f610bcca3eb9f3b67630ad | 16,601 |
from typing import Tuple
import codecs
def preprocess_datasets(data: str, seed: int = 0) -> Tuple:
"""Load and preprocess raw datasets (Yahoo! R3 or Coat)."""
if data == 'yahoo':
with codecs.open(f'../data/{data}/train.txt', 'r', 'utf-8', errors='ignore') as f:
data_train = pd.read_csv(f, ... | 78a7bfe7968ad47f797728ffb43c804ab8af6298 | 16,602 |
def loadSentimentVector(file_name):
"""
Load sentiment vector
[Surprise, Sorrow, Love, Joy, Hate, Expect, Anxiety, Anger]
"""
contents = [
line.strip('\n').split() for line in open(file_name, 'r').readlines()
]
sentiment_dict = {
line[0].decode('utf-8'): [float(w) for w in li... | 5d0d1f4598eeed455d080236720adcae357b6485 | 16,603 |
def unique_boxes(boxes, scale=1.0):
"""Return indices of unique boxes."""
v = np.array([1, 1e3, 1e6, 1e9])
hashes = np.round(boxes * scale).dot(v)
_, index = np.unique(hashes, return_index=True)
return np.sort(index) | fc9ab64356192828659f025af6aa112205fc838c | 16,604 |
import os
def compscan_key(compscan):
"""List of strings that identifies compound scan."""
# Name of data set that contains compound scan
path = compscan.scans[0].path
filename_end = path.find('.h5')
dataset_name = os.path.basename(path[:filename_end]) if filename_end > 0 else os.path.basename(pat... | f66caa4da5ab6ba51d6167bc1638324233a21ec2 | 16,605 |
def HEX2DEC(*args) -> Function:
"""
Converts a signed hexadecimal number to decimal format.
Learn more: https//support.google.com/docs/answer/3093192
"""
return Function("HEX2DEC", args) | b4741d02acae7169854d1193ae5b43f6736257dc | 16,606 |
def find_edges(mesh, key):
""" Temp replacement for mesh.findEdges().
This is painfully slow.
"""
for edge in mesh.edges:
v = edge.vertices
if key[0] == v[0] and key[1] == v[1]:
return edge.index | 98247b64a0e5671a7dbbf314f314cef2c5c8aae3 | 16,607 |
def thumbnail(link):
"""
Returns the URL to a thumbnail for a given identifier.
"""
targetid, service = _targetid(link), _service(link)
if targetid:
if service in _OEMBED_MAP:
try:
return _embed_json(service, targetid)["thumbnail_url"]
except (ValueEr... | 9ca78af2a65a41a70fef73c35383ae9214fb2d96 | 16,608 |
def valve_gas_cv(m_dot, p_1, p_2, m_molar, T):
"""Find the required valve Cv for a given mass flow and pressure drop.
Assumes that a compressible gas is flowing through the valve.
Arguments:
m_dot (scalar): Mass flow rate [units: kilogram second**-1].
p_1 (scalar): Inlet pressure [units: p... | 07bd3f45392e03eb6744b98a3fde022aa517c4fc | 16,609 |
def frequency_based_dissim(record, modes):
"""
Frequency-based dissimilarity function
inspired by "Improving K-Modes Algorithm Considering Frequencies of Attribute Values in Mode" by He et al.
"""
list_dissim = []
for cluster_mode in modes:
sum_dissim = 0
for i in range(len(recor... | 80e21763d6f90ddc5a448f46247fd12253de5dbb | 16,610 |
def _process_create_group(event: dict) -> list:
""" Process CreateGroup event. This function doesn't set tags. """
return [event['responseElements']['group']['groupName']] | 978b3ffc3c4aa72165914b79dc06cb7691c5c5a5 | 16,611 |
from typing import Any
from typing import List
def tree_labels(t: Node):
"""Collect all labels of a tree into a list."""
def f(label: Any, folded_subtrees: List) -> List:
return [label] + folded_subtrees
def g(folded_first: List, folded_rest: List) -> List:
return folded_first + folded_r... | 7ad1703a090cd761a99cd5323c9258e8d2d551b8 | 16,612 |
def find_best_split(rows):
"""Find the best question to ask by iterating over every feature / value
and calculating the information gain."""
best_gain = 0 # keep track of the best information gain
best_question = None # keep train of the feature / value that produced it
current_uncertainty = gini(... | 9b197c99b41e64e37b499b5d4b3c7758cda3b56e | 16,613 |
def pad_data(data, context_size, target_size, pad_at_begin= False):
"""
Performs data padding for both target and aggregate consumption
:param data: The aggregate power
:type data: np.array
:param context_size: The input sequence length
:type context_size: int
:param target_size: The target... | 1b698a849a4ca82d87ce6c5711220b61cd21252b | 16,614 |
import os
def create_callbacks(path):
"""
Creates the callbacks to use during training.
Args
training_model: The model that is used for training.
prediction_model: The model that should be used for validation.
validation_generator: The generator for creating validation data.
... | d19b10e51bd5f2e90cf900a8a044c8d2dbe404e8 | 16,615 |
import os
def SaveAsImageFile(preferences, image):
"""Save the current image as a PNG picture."""
extension_map = {"png": wx.BITMAP_TYPE_PNG}
extensions = extension_map.keys()
wildcard = create_wildcard("Image files", extensions)
dialog = wx.FileDialog(None, message="Export to Image",
... | feaf05ab7a94f958c066a656901f86e01536edac | 16,616 |
def egg_translator(cell):
"""If the cell has the DNA for harboring its offspring inside it, granting it additional food
and protection at the risk of the parent cell, it is an egg.
Active DNA: x,A,(C/D),x,x,x
"""
dna = cell.dna.split(',')
if dna[1] == 'A' and dna[2] == 'C':
return True
... | af0d9097c8a0b5002722c79d6ec8262a66cc375d | 16,617 |
def all_different_cst(xs, cst):
"""
all_different_cst(xs, cst)
Ensure that all elements in xs + cst are distinct
"""
return [AllDifferent([(x + c) for (x,c) in zip(xs,cst)])] | dfc75a54a92a4c8c2ef76af74250b9125c9bb647 | 16,618 |
def processing(task, region: dict, raster: str, parameters: dict):
"""
Cuts the raster according to given region and applies some filters
in order to find the district heating potentials and
related indicators.
Inputs :
* region : selected zone where the district heating potential is studi... | 63a5548e886b575011e716e05a589715f027c316 | 16,619 |
import random
def randbit():
"""Returns a random bit."""
return random.randrange(2) | 4b47101df7368b7cb423920e6a5338b76ab4ecaa | 16,620 |
def calc_points(goals, assists):
"""
Calculate the total traditional and weighted points for all
players, grouped by player id.
Author: Rasmus Säfvenberg
Parameters
----------
goals : pandas.DataFrame
A data frame with total goals and weighted assists per player.
assist... | 1801cf2602a473bdf532e1c0ee58b883dc3e79d1 | 16,621 |
def get_links(browser, elemento):
"""
Pega todos os links dentro de um elemento
- browser = a instância do navegador
- element = ['aside', main, body, ul, ol]
"""
resultado = {}
element = browser.find_element_by_tag_name(elemento)
ancoras = element.find_elements_by_tag_name... | dc28e71452bd0c1ede651981e88ba26815a491dd | 16,622 |
import io
import base64
def file_to_base64(path):
"""
Convert specified file to base64 string
Args:
path (string): path to file
Return:
string: base64 encoded file content
"""
with io.open(path, 'rb') as file_to_convert:
return base64.b64encode(file_to_convert.read()) | 0c942f8f4d29943c5a3aac6c954d9e2b1b2898a3 | 16,623 |
def get_simverb(subset=None):
"""
Get SimVerb-3500 data
:return: (pairs, scores)
"""
simverb = []
if subset == 'dev':
name = '500-dev'
elif subset == 'test':
name = '3000-test'
else:
name = '3500'
with open('../data/SimVerb-3500/SimVerb-{}.txt'.format(name)) a... | 5cec49bd232a883836029b8b011f09f360176910 | 16,624 |
def sample_image(size, min_r, max_r, circles, squares, pixel_value):
"""Generate image with geometrical shapes (circles and squares).
"""
img = np.zeros((size, size, 2))
loc = []
if pixel_value is None:
vals = np.random.randint(0, 256, circles + squares)
else:
vals = [pixel_value... | 25ab1afcd7256bc07ee55ac2e12cf9d834cb798c | 16,625 |
def host_allocations(auth):
"""Retrieve host allocations"""
response = API.get(auth, '/os-hosts/allocations')
return response.json()['allocations'] | 505eeb0502f6480445ec5dff1cd3203eda96d475 | 16,626 |
def rosenbrock_grad(x, y):
"""Gradient of Rosenbrock function."""
return (-400 * x * (-(x ** 2) + y) + 2 * x - 2, -200 * x ** 2 + 200 * y) | c7acf0bbe11a6d1cbb38b6853eb1b508e3846657 | 16,627 |
import os
def get_file(
fname,
origin,
untar=False,
cache_subdir="datasets",
extract=False,
archive_format="auto",
cache_dir=None,
):
"""Downloads a file from a URL if it not already in the cache.
By default the file at the url `origin` is downloaded to the
cache_dir `~/.keras`... | 7098b0ffbf70c8b7468c22637045068d32b71390 | 16,628 |
def extractYoujinsite(item):
"""
"""
vol, chp, frag, postfix = extractVolChapterFragmentPostfix(item['title'])
if '[God & Devil World]' in item['tags'] and (chp or vol):
return buildReleaseMessageWithType(item, 'Shenmo Xitong', vol, chp, frag=frag, postfix=postfix)
if '[LBD&A]' in item['tags'] and (chp or vol):... | 11463288cdcc7268b0b4657934dd8872a7d36580 | 16,629 |
import os
import glob
def get_patient_dirs(root_dir):
"""
Function used to get the root director for all patients
:param root_dir: root director of all image data
:return patient_paths: list of all patient paths, one for each patient
"""
search_path = os.path.join(root_dir, '[0-1]', '*')
p... | d0d38f02214175b867fd8bf8b1e13db8ee8a83f2 | 16,630 |
import os
import torch
import logging
import wget
def _download(path: str, url: str):
"""
Gets a file from cache or downloads it
Args:
path: path to the file in cache
url: url to the file
Returns:
path: path to the file in cache
"""
if url is None:
return None
... | 941f494e8d01817e61d11b83aa51816ca1459449 | 16,631 |
def get_logger() -> Logger:
""" This function returns the logger for this project """
return getLogger(LOGGER_NAME) | 33e11a06c357552c35f9ef089fd303ad15db0884 | 16,632 |
import json
def write_guess_json(guesser, filename, fold, run_length=200, censor_features=["id", "label"], num_guesses=5):
"""
Returns the vocab, which is a list of all features.
"""
vocab = [kBIAS]
print("Writing guesses to %s" % filename)
num = 0
with open(filename, 'w') as outfil... | 9f0055289ff462b0b3c067ea1e0a68c66a74136c | 16,633 |
def upgrade_to_4g(region, strategy, costs, global_parameters,
core_lut, country_parameters):
"""
Reflects the baseline scenario of needing to build a single dedicated
network.
"""
backhaul = '{}_backhaul'.format(strategy.split('_')[2])
sharing = strategy.split('_')[3]
geotype = region['... | 947afef6d550b9022109c665fc311511f428e9f8 | 16,634 |
import hmac
def get_url(request):
"""
Use devId and key and some hashing thing to get the url, needs /v3/api as input
"""
devId = DEV_ID
key = KEY
request = request + ('&' if ('?' in request) else '?')
raw = request + f"devid={devId}"
raw = raw.encode()
hashed = hmac.new(key, ... | 57e6d8dc6c0f282b227559aed5cd9c1f96f7d5b7 | 16,635 |
def _is_mapped_class(cls):
"""Return True if the given object is a mapped class,
:class:`.Mapper`, or :class:`.AliasedClass`."""
if isinstance(cls, (AliasedClass, mapperlib.Mapper)):
return True
if isinstance(cls, expression.ClauseElement):
return False
if isinstance(cls, type):
... | 7f09c1f4908bb62977de07ad4366fb8e6cc84cc2 | 16,636 |
from bs4 import BeautifulSoup
def get_all_links_in_catalog(html) -> list:
"""Получает список всех ссылок на пункты из каталога."""
_soup = BeautifulSoup(html, 'html.parser')
_items = _soup.find('div', class_='catalog_section_list').find_all('li', class_='name')
links_list = []
for item in _items:
... | 53e4fd9aaad8755ddd19328ae5d5f972cfbcdc3c | 16,637 |
def digitize(n):
"""Convert a number to a reversed array of digits."""
l = list(str(n))
n_l = []
for d in l:
n_l.append(int(d))
n_l.reverse()
return n_l | e4355b68da41e4be87ce18b53afb2a406eb120c7 | 16,638 |
import matplotlib.pyplot as plt
import time
def run_example(device_id, do_plot=False):
"""
Run the example: Connect to the device specified by device_id and obtain
impedance data using ziDAQServer's blocking (synchronous) poll() command.
Requirements:
Hardware configuration: Connect signal out... | 9d3306fdac3084622e175a1ce9243a7bcf976daa | 16,639 |
def _available_algorithms():
"""Verify which algorithms are supported on the current machine.
This is done by verifying that the required modules and solvers are available.
"""
available = []
for algorithm in ALGORITHM_NAMES:
if "gurobi" in algorithm and not abcrules_gurobi.gb:
... | cd9310cb78d780154c56763cdf14573bc67ae7b5 | 16,640 |
import re
def symbols(*names, **kwargs):
"""
Emulates the behaviour of sympy.symbols.
"""
shape=kwargs.pop('shape', ())
s = names[0]
if not isinstance(s, list):
s = re.split('\s|,', s)
res = []
for t in s:
# skip empty strings
if not t:
continue
... | bcaf1827ccee67098e619c3ec825f3b1aeb3f798 | 16,641 |
def create_intent(intent, project_id, language_code):
"""Create intent in dialogflow
:param intent: dict, intent for api
:param project_id: str, secret project id
:param language_code: event with update tg object
:return:
"""
client = dialogflow.IntentsClient()
parent = client.project_ag... | 59a150d4456d26f4cd8fa93a2cbfc131278d3ba0 | 16,642 |
from typing import List
def construct_object_types(list_of_oids: List[str]) -> List[hlapi.ObjectType]:
"""Builds and returns a list of special 'ObjectType'
from pysnmp"""
object_types: List[hlapi.ObjectType] = []
for oid in list_of_oids:
object_types.append(hlapi.ObjectType(hlapi.ObjectIdentit... | 24eeb7dbd0de49e702acc574c9264d3e7bcdf904 | 16,643 |
def base_sampler(models, nevents, floating_params=None):
"""
Creates samplers from models.
Args:
models (list(model)): models to sample
nevents (list(int)): number of in each sampler
floating_params (list(parameter), optionnal): floating parameter in the samplers
Returns:
... | af575d4a175239c2af4fe0e61658005a12225e5a | 16,644 |
def menu_maker():
"""Top Menu Maker In each html page
"""
result = "<center>"
for i,item in enumerate(page_name):
if item == "Home":
targets_blank = ""
else:
targets_blank = 'target="blank"'
# Hyper Link To Each Page In HTML File
result += '\t... | 6f9b38926d3eab31d1e5d32a49564f083df4f3cc | 16,645 |
import http
def project_generate_private_link_post(auth, node, **kwargs):
""" creata a new private link object and add it to the node and its selected children"""
node_ids = request.json.get('node_ids', [])
name = request.json.get('name', '')
anonymous = request.json.get('anonymous', False)
if ... | bd006f64d02bf36509297b1a0778e3488093c682 | 16,646 |
def access_token_old_api(authen_code):
"""
通过此接口获取登录用户身份（疑似是一个旧接口）
:param authen_code:
:return:
"""
# 先获取app_access_token
app_access_token = _get_app_access_token()
if not app_access_token:
return None
access_token_old_url = cfg.access_token_old_url
headers = {"Content-T... | efb34044bc07aee817050ef39e8d8a72da7611fd | 16,647 |
def denoising(image):
"""improve image quality by remove unimportant details"""
denoised = cv2.fastNlMeansDenoisingColored(image, None, 10, 10, 7, 21)
return denoised | b5407c1fcd84b49afe5c17e6a221d9da423444f6 | 16,648 |
def teams():
"""Redirect the to the Slack team authentication url."""
return redirect(auth.get_redirect('team')) | 7ea84c5319c7f64a24c7ae42bd0b7467934d8cba | 16,649 |
def _clarans(metric):
"""Clustering Large Applications based on RANdomized Search."""
# choose which implementation to use, hybrid or cpu
get_clusters = _get_clusters(metric, method='cpu')
@jit(nopython=True)
def clarans(data, k, numlocal, maxneighbor):
"""Clustering Large Applications base... | a56321ba094b78eaa6df18917b7c3ad32a3a6bec | 16,650 |
def create_outlier_mask(df, target_var, number_of_stds, grouping_cols=None):
"""
Create a row-wise mask to filter-out outliers based on target_var.
Optionally allows you to filter outliers by group for hier. data.
"""
def flag_outliers_within_groups(df, target_var,
... | 95a7e3e5a0cb8dcc4aa3da1af7e9cb4111cf6b81 | 16,651 |
import contextlib
def closing_all(*args):
"""
Return a context manager closing the passed arguments.
"""
return contextlib.nested(*[contextlib.closing(f) for f in args]) | 075056e1a92c63d5c1db0cda68d7cb447868653b | 16,652 |
def _non_max_suppression(objects, threshold):
"""Returns a list of indexes of objects passing the NMS.
Args:
objects: result candidates.
threshold: the threshold of overlapping IoU to merge the boxes.
Returns:
A list of indexes containings the objects that pass the NMS.
"""
if len(... | 9952386f5a6c6f11b1fdbd37eaca6c273ea4b506 | 16,653 |
def binary_search(x,l):
""" Esse algorítmo é o algorítmo de busca binária, mas ele retorna
qual o índice o qual devo colocar o elemento para que a lista
permaneça ordenada.
Input: elemento x e lista l
Output: Índice em que o elemento deve ser inserido para manter a ordenação da lista
"""
lo... | 457c403ffeb2eb5529c2552bdbe8d7beee9199f2 | 16,654 |
def check_abrp(config):
"""Check for geocodio options and return"""
try:
abrpOptions = config.abrp.as_dict()
except:
return {}
options = {}
abrp_keys = ["enable", "api_key", "token"]
for key in abrp_keys:
if key not in abrpOptions.keys():
_LOGGER.error(f"Miss... | fa9c0f1643ae2793cf66498dbb8f27a033edeafd | 16,655 |
import click
def connect(config, job, attach):
"""
Connect to job.
JOB may be specified by name or ID, but ID is preferred.
"""
jobs = config.trainml.run(config.trainml.client.jobs.list())
found = search_by_id_name(job, jobs)
if None is found:
raise click.UsageError("Cannot find ... | 8a572a92eb9a0cd31af05218dec3ab369109cb31 | 16,656 |
def convert_magicc7_to_openscm_variables(variables, inverse=False):
"""
Convert MAGICC7 variables to OpenSCM variables
Parameters
----------
variables : list_like, str
Variables to convert
inverse : bool
If True, convert the other way i.e. convert OpenSCM variables to MAGICC7
... | 952bca9f07f8e032b33328c1b03470fd3150eabd | 16,657 |
import asyncio
import aiohttp
async def fetch_disclosure(start, end):
"""期间沪深二市所有类型的公司公告
Args:
start (date like): 开始日期
end (date like): 结束日期
Returns:
list: list of dict
"""
start, end = pd.Timestamp(start), pd.Timestamp(end)
start_str = start.strftime(r'%Y-%m-%d')
... | efb6b7706ed73c09c65e5d05567b3fdf38aee887 | 16,658 |
from re import T
def get_loader(
image_dir,
attr_path,
selected_attrs,
crop_size=178,
image_size=128,
batch_size=16,
dataset="CelebA",
mode="train",
affectnet_emo_descr="emotiw",
num_workers=1,
):
"""Build and return a data loader."""
transform = []
if mode == "trai... | 082d1b81b73df7c817fad024911fe431f8cf4a74 | 16,659 |
import json
def remove_samples(request, product_id):
"""Removes passed samples from product with passed id.
"""
parent_product = Product.objects.get(pk=product_id)
for temp_id in request.POST.keys():
if temp_id.startswith("product") is False:
continue
temp_id = temp_id.sp... | e9d0f112f17af463cfe7ddba2bd606d78fb50b3f | 16,660 |
def csu_to_field(field, radar, units='unitless',
long_name='Hydrometeor ID',
standard_name='Hydrometeor ID',
dz_field='ZC'):
"""
Adds a newly created field to the Py-ART
radar object. If reflectivity is a masked array,... | c8052f51bbed2c16c744201b862fa43868d7d527 | 16,661 |
import os
import requests
def get_port_use_db():
"""Gets the services that commonly run on certain ports
:return: dict[port] = service
:rtype: dict
"""
url = "http://www.iana.org/assignments/service-names-port-numbers/service-names-port-numbers.csv"
db_path = "/tmp/port_db"
if not os.pat... | 4462ef74b5575905b75980827d5a5bb5ed05aee8 | 16,662 |
def calculate_com(structure):
"""
Calculates center of mass of the structure (ligand or protein).
Parameters
----------
structure : biopython Structure object
PDB of choice loaded into biopython (only chains of interest).
Returns
-------
A list defining center of mass of th... | 35d6ed62d3943dff0aa1ef0c3a0d04b9235b84ac | 16,663 |
def generate_config(context):
""" Generate the deployment configuration. """
resources = []
name = context.properties.get('name', context.env['name'])
resources = [
{
'name': name,
'type': 'appengine.v1.version',
'properties': context.properties
}
... | 9a997b87a8d4d8f46edbbb9d2da9f523e5e2fdc6 | 16,664 |
def check_regs(region_df, chr_name=None, start_name=None, stop_name=None,
strand_name=None, sample_name=None):
""" Modifies a region dataframe to be coherent with the GMQL data model
:param region_df: a pandas Dataframe of regions that is coherent with the GMQL data model
:param chr_name: (o... | ea00a9b755c8dc2943717254ecdb3390bbefe288 | 16,665 |
from typing import List
from typing import Optional
from typing import Sequence
from typing import Union
from typing import Dict
from typing import Any
from typing import cast
def build_assets_job(
name: str,
assets: List[OpDefinition],
source_assets: Optional[Sequence[Union[ForeignAsset, OpDefinition]]] ... | 8e2353677e5085f0c1eb53ee24687e020912b2e5 | 16,666 |
def createBinarySearchTree(vs):
"""
Generate a balanced binary search tree based on the given array.
Args:
vs - an integer array
{4, 5, 5, 7, 2, 1, 3}
4
/ \
2 5
/ \ / \
1 3 5 7
"""
def _help... | 5e1f7723a4b218d980d7d72ca8f949160ff8042d | 16,667 |
def remove_end_same_as_start_transitions(df, start_col, end_col):
"""Remove rows corresponding to transitions where start equals end state.
Millington 2009 used a methodology where if a combination of conditions
didn't result in a transition, this would be represented in the model by
specifying a trans... | f4b3ddca74e204ed22c75a4f635845869ded9988 | 16,668 |
from typing import Dict
from typing import Any
import os
import re
import sys
from typing import cast
from typing import List
def read_config(path: str) -> Dict[str, Any]:
"""Return dict with contents of configuration file."""
newconf = {
"setup": False,
"servers": [],
"okurls": [],
... | 4d0f020ad37eb7ff4a599afdcedc85b4ac5cc934 | 16,669 |
def sieve(iterable, inspector, *keys):
"""Separates @iterable into multiple lists, with @inspector(item) -> k for k in @keys defining the separation.
e.g., sieve(range(10), lambda x: x % 2, 0, 1) -> [[evens], [odds]]
"""
s = {k: [] for k in keys}
for item in iterable:
k = inspector(item)
... | 6ebb76dfb3131342e08a0be4127fba242d126130 | 16,670 |
def get_model(config: BraveConfig) -> embedding_model.MultimodalEmbeddingModel:
"""Construct a model implementing BraVe.
Args:
config: Configuration for BraVe.
Returns:
A `MultimodalEmbeddingModel` to train BraVe.
"""
init_fn, parameterized_fns = _build_parameterized_fns(config)
loss_fn = _build_... | eceff13cf9ec5bd5cdd126af52bbd4eb6fad6ebe | 16,671 |
def upilab6_1_5 () :
"""
6.1.5. Exercice UpyLaB 6.2 - Parcours vert bleu rouge
(D’après une idée de Jacky Trinh le 19/02/2018)
Monsieur Germain est une personne très âgée. Il aimerait préparer une liste de courses à faire à l’avance. Ayant un
budget assez serré, il voudrait que sa liste de courses soit dans ses cap... | 198a11e4059c39550bb398a473711073677a41d4 | 16,672 |
import torch
def construct_filtering_input_data(xyz_s, xyz_t, data, overlapped_pair_tensors, dist_th=0.05, mutuals_flag=None):
"""
Prepares the input dictionary for the filtering network
Args:
xyz_s (torch tensor): coordinates of the sampled points in the source point cloud [b,n,3]
xyz_t (to... | ca316834cc87e1527e4563407138aa92a46b92a3 | 16,673 |
def rmean(x, N):
""" cutting off the edges. """
s = int(N-1)
return np.convolve(x, np.ones((N,))/N)[s:-s] | eb34bd21523e685184155e65ccddc34e2eb6a428 | 16,674 |
def add_variant_to_existing_lines(group, variant, total_quantity):
"""
Adds variant to existing lines with same variant.
Variant is added by increasing quantity of lines with same variant,
as long as total_quantity of variant will be added
or there is no more lines with same variant.
Returns q... | 1e958db4c684f0bf3f2d821fc06f422cc60d0168 | 16,675 |
def calculate_position(c, t):
"""
Calculates a position given a set of quintic coefficients and a time.
Args
c: List of coefficients generated by a quintic polynomial
trajectory generator.
t: Time at which to calculate the position
Returns
Position
"""
retu... | 927737b41006df13e7bf751b06756eea02542491 | 16,676 |
def get_dqa(df):
"""Method to get DQA issues."""
try:
df0 = df[(df.dob == '') | (df.dqa_sex != 'OK') |
(df.dqa_age != 'OK') | (df.case_status == 'Pending')]
df1 = df0[['cpims_id', 'child_names', 'age', 'case_category',
'dqa_sex', 'dqa_dob', 'dqa_age', 'case_st... | f2c30e87937ce4fac1dd00cd597ee52946d80d07 | 16,677 |
import pickle
def get_3C_coords(name):
"""
Formatted J2000 right ascension and declination and IAU name
Returns the formatted J2000 right ascension and declination and IAU name
given the 3C name.
Example
>>> ra,dec,iau = get_3C_coords('3C286')
>>> print ra,dec,iau
13h31m08.287984... | 1e48ca0535c6cdb5eb2330f3dcfd666e40eef33f | 16,678 |
import json
def get(player):
"""Get the cipher that corresponding to the YouTube player version.
Args:
player (dict): Contains the 'sts' value and URL of the YouTube player.
Note:
If the cipher is missing in known ciphers, then the 'update' method will be used.
"""
if DIR.exists(... | dd658d8aad775fa7871e3efa642b0aad89f8f801 | 16,679 |
def divide(x, y):
"""A version of divide that also rounds."""
return round(x / y) | 1bf9e5859298886db7c928613f459f163958ca7b | 16,680 |
def create_root_ca_cert(root_common_name, root_private_key, days=365):
"""
This method will create a root ca certificate.
:param root_common_name: The common name for the certificate.
:param root_private_key: The private key for the certificate.
:param days: The number of days for which the certific... | 5bf83b8ba56c6dde9f6c2ed022c113350425aa33 | 16,681 |
def hist1d(arr, bins=None, amp_range=None, weights=None, color=None, show_stat=True, log=False,\
figsize=(6,5), axwin=(0.15, 0.12, 0.78, 0.80),\
title=None, xlabel=None, ylabel=None, titwin=None):
"""Makes historgam from input array of values (arr), which are sorted in number of bins (bins) in... | c74771de0df0e9f4d65490a09346d2af18d53cc7 | 16,682 |
def format_validate_parameter(param):
"""
Format a template parameter for validate template API call
Formats a template parameter and its schema information from the engine's
internal representation (i.e. a Parameter object and its associated
Schema object) to a representation expected by the curre... | 4ed21c80bf567beca448065089bfe22fef6cfb17 | 16,683 |
import string
def get_template(name):
"""Retrieve the template by name
Args:
name: name of template
Returns:
:obj:`string.Template`: template
"""
file_name = "{name}.template".format(name=name)
data = resource_string("pyscaffoldext.beeproject.templates", file_name)
return... | 933e597b48b5ed01a29d191fd0fe04371b1baeb6 | 16,684 |
def box3d_overlap(boxes, qboxes, criterion=-1, z_axis=1, z_center=1.0):
"""kitti camera format z_axis=1.
"""
bev_axes = list(range(7))
bev_axes.pop(z_axis + 3)
bev_axes.pop(z_axis)
# t = time.time()
# rinc = box_np_ops.rinter_cc(boxes[:, bev_axes], qboxes[:, bev_axes])
rinc = rotate_iou... | 45aa39e9f55f8198ccbe5faf6a00cf27279057fa | 16,685 |
def _apply_graph_transform_tool_rewrites(g, input_node_names,
output_node_names):
# type: (gde.Graph, List[str], List[str]) -> tf.GraphDef
"""
Use the [Graph Transform Tool](
https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/
graph_transforms/README... | 15d9609357d45fd164fd1569d35669148e66acd8 | 16,686 |
def big_bcast(comm, objs, root=0, return_split_info=False, MAX_BYTES=INT_MAX):
"""
Broadcast operation that can exceed the MPI limit of ~4 GiB.
See documentation on :meth:`big_gather` for details.
Parameters
----------
comm: mpi4py.MPI.Intracomm
MPI communicator to use.
objs: objec... | 341591b207ef793b32e6b727f14533dbe119312d | 16,687 |
def get_task(appname, taskqueue, identifier):
"""Gets identified task in a taskqueue
Request
-------
```
GET http://asynx.host/apps/:appname/taskqueues/:taskqueue/tasks/:identifier
```
Parameters:
- appname: url param, string, the application name
under wh... | c11aadab178776a6246163f2146e9a91d949e3bc | 16,688 |
def GetBuiltins(stdlib=True):
"""Get the "default" AST used to lookup built in types.
Get an AST for all Python builtins as well as the most commonly used standard
libraries.
Args:
stdlib: Whether to load the standard library, too. If this is False,
TypeDeclUnit.modules will be empty. If it's True, ... | 68b6ad916e4a2ab50774e5f1e8da7b1106cdb2e5 | 16,689 |
def assign_style_props(df, color=None, marker=None, linestyle=None,
cmap=None):
"""Assign the style properties for a plot
Parameters
----------
df : pd.DataFrame
data to be used for style properties
"""
if color is None and cmap is not None:
raise ValueErr... | 93bd50e81a988594a42bce26a48d9d24e0e9c6ba | 16,690 |
def to_dbtext(text):
"""Helper to turn a string into a db.Text instance.
Args:
text: a string.
Returns:
A db.Text instance.
"""
if isinstance(text, unicode):
# A TypeError is raised if text is unicode and an encoding is given.
return db.Text(text)
else:
try:
return db.Text(text, ... | 74704f42e8cb05be24df3b32e8964382da9c488e | 16,691 |
import zmq
import time
def zmq_init(pub_port, sub_port_list):
"""
Initialize the ZeroMQ publisher and subscriber.
`My` publisher publishes `my` data to the neighbors. `My` subscriber listen
to the ports of other neighbors. `sub_port_list` stores all the possible
neighbors' TCP ports.
... | fcde81e7387d49e99cd864cea233b1ba02ac679c | 16,692 |
from typing import Dict
from typing import Tuple
import tqdm
def get_all_match_fractions(
residuals: Dict[str, np.ndarray],
roi_mask: np.ndarray,
hypotheses: np.ndarray,
parang: np.ndarray,
psf_template: np.ndarray,
frame_size: Tuple[int, int],
n_roi_splits: int = 1,
roi_split: int = 0... | 65e0da2634dc0f5870fa1c8620ab064f82ffc81a | 16,693 |
def dot(u, v):
"""
Returns the dot product of the two vectors.
>>> u1 = Vec([1, 2])
>>> u2 = Vec([1, 2])
>>> u1*u2
5
>>> u1 == Vec([1, 2])
True
>>> u2 == Vec([1, 2])
True
"""
assert u.size == v.size
sum = 0
for index, (compv, compu) in enumerate(zip(u.store,v.st... | e431800750c8f7c14d7412753814e2498fdd3c09 | 16,694 |
def isvalid(number, numbers, choices=2):
"""Meh
>>> isvalid(40, (35, 20, 15, 25, 47))
True
>>> isvalid(62, (20, 15, 25, 47, 40))
True
>>> isvalid(127, (182, 150, 117, 102, 95))
False
"""
return number in sums(numbers, choices) | c32ee0fe1509c0c1f48bdf8f6b9f8fe5b00fb8f8 | 16,695 |
def from_rotation_matrix(rotation_matrix: type_alias.TensorLike,
name: str = "quaternion_from_rotation_matrix"
) -> tf.Tensor:
"""Converts a rotation matrix representation to a quaternion.
Warning:
This function is not smooth everywhere.
Note:
In the fol... | 2eab1984206c57ec64c4be2b3652008773d9c037 | 16,696 |
def mark_text(text):
"""Compact rules processor"""
attrs = {}
rules = []
weight = 0
attrs['len'] = len(text)
text = text.replace('.', ' ').replace(',', ' ').replace(u'№', ' ').strip().lower()
words = text.split()
textjunk = []
spaced = 0
attrs['wl'] = len(words)
attrs['junkl'... | 7287535d3a9c3bb302f9cc98ca6e7fa2ec4c9a40 | 16,697 |
def create_faucet(client):
"""Create a wallet using the testnet faucet"""
test_wallet = generate_faucet_wallet(client, debug=True)
return test_wallet | a9cfb7e3287f30e49c741e7e0f9ac919d429a396 | 16,698 |
def model_flux(t_dec,B,P_max,R,Ne,d_l,z,mp,me,e,c,sigma_t,time,nu,Gamma,E_k,
n,eps_b,eps_e,p,j_ang):
""" Function for deriving the flux for the spectrum or light curve at
given times and frequencies """
# calculate lorentz factors, characteristic frequencies and
# jet break time
gamma_m = Gamma*eps_e*((p-2)/(p-... | 15658d57ae5d837d416731427e1227eb304b4b75 | 16,699 |
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