content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def check_results(results):
"""Examines a list of individual check results and returns an overall
result for all checks combined.
"""
if CheckResults.SCALE_UP in results:
return CheckResults.SCALE_UP
if all(r == CheckResults.SCALE_DOWN for r in results):
return CheckResults.SCALE_DOW... | a7a18caca42c9a6f555110418b96b5cc6b9d203c | 21,700 |
import os
def disk_usage(path):
"""returns disk usage for a path"""
total = os.path.getsize(path)
if os.path.isdir(path):
for filename in os.listdir(path):
child_path = os.path.join(path, filename)
total += disk_usage(child_path)
print(f"{total:<10} {path}")
return ... | 0c4901f94d562d7def81afcef4ffa27fe48c106c | 21,701 |
def edit_route(link_id):
"""edit link"""
link = dynamo.tables[TABLE_NAME].get_item(Key={'id': link_id})['Item']
form = LinkForm(link=link['link'], tags=','.join(link['tags']))
if form.validate_on_submit():
link, tags = form.parsed_data()
dynamo.tables[TABLE_NAME].update_item(
... | b20f22345d3de2b474e04821bdfbee5391f1d493 | 21,702 |
def build_empty_pq():
"""Build empty pq."""
return PriorityQ() | a18dc1ac16ceb2475f47e1f55e0617957c1e0cad | 21,703 |
def add_flags(flags):
"""Add KZC flags"""
def f(test, way):
test.args += flags
return f | 58c6db2bb46c321ce3e3592ac8be2ee6d1feecb6 | 21,704 |
import os
import subprocess
def RunProcess(cmd, stdinput=None, env=None, cwd=None, sudo=False,
sudo_password=None):
"""Executes cmd using suprocess.
Args:
cmd: An array of strings as the command to run
stdinput: An optional sting as stdin
env: An optional dictionary as the environment
... | 6b1f599b6fe601ea8e3ce85757f76ca7b4f707b2 | 21,705 |
def public_jsonp_service(view):
"""
More explicitly named to call attention to the extra little p
"""
return _json_service_wrapper(JSONPResponse, view) | 76588ade3d537a102dc6ca3bf540bc32da928e30 | 21,706 |
def manage_data(xls_file: str) -> list:
"""
转换xls手动标注的数据为待处理的格式
:param xls_file: 目标文件路径
:return: 转换后的字典列表
"""
f = pd.read_excel(xls_file, index=False)
cnt = 0
result = []
while cnt < len(f) - 1:
if f.text[cnt] == f.text[cnt + 1]:
temp_dic = {'text': f.text[cnt], '... | 3198013b713f50b650bc5b3542905d1e860a6871 | 21,707 |
def get_arrival_times(inter_times):
"""Convert interevent times to arrival times."""
return inter_times.cumsum() | 7197fc6315d3eaca118ca419f23aed7c0d7cd064 | 21,708 |
def generate_custom_background(size, background_color, nb_blobs=3000,
kernel_boundaries=(50, 100)):
""" Generate a customized background to fill the shapes
Parameters:
background_color: average color of the background image
nb_blobs: number of circles to draw
ker... | 782883d29cf67dbb33662fbb22b457783320101d | 21,709 |
def rotate_z(domain, nrot=4):
"""take BoxCollection and return equivalent CylinderCollection by
rotating about the second axis. thus, transform coordinates of
points like (x, z) --> (x, 0, z)."""
return rotate(domain, d=1, nrot=nrot) | ca1b197d758a18b86675a14be952065055dea05f | 21,710 |
def filter_roi(roi_data, nb_nonzero_thr):
"""Filter slices from dataset using ROI data.
This function filters slices (roi_data) where the number of non-zero voxels within the ROI slice (e.g. centerline,
SC segmentation) is inferior or equal to a given threshold (nb_nonzero_thr).
Args:
roi_data... | 9e325f77436e152377bee84d7e82d3f80424f288 | 21,711 |
def from_numpy(shape, dt):
"""
Upcast a (shape, dtype) tuple if possible.
>>> from_numpy((5,5), dtype('int32'))
dshape('5, 5, int32')
"""
dtype = np.dtype(dt)
if dtype.kind == 'S':
measure = String(dtype.itemsize, 'A')
elif dtype.kind == 'U':
measure = String(dtype.item... | 249701a885dc01d13fe356ce4117300e79d803a5 | 21,712 |
import optparse
def ParseArgs():
"""Parse the command line options."""
option_parser = optparse.OptionParser()
option_parser.add_option(
'--from', dest='sender', metavar='EMAIL',
help='The sender\'s email address')
option_parser.add_option(
'--to', action='append', metavar='EMAIL', dest='rec... | eb1ee1c5fb66f76882aef0787e2c4716146526f4 | 21,713 |
def pyramidnet110_a84_cifar100(classes=100, **kwargs):
"""
PyramidNet-110 (a=84) model for CIFAR-100 from 'Deep Pyramidal Residual Networks,' https://arxiv.org/abs/1610.02915.
Parameters:
----------
classes : int, default 100
Number of classification classes.
pretrained : bool, default ... | f005c26e80e87536b5032685f27944560e5d8fc7 | 21,714 |
def contains_vendored_imports(python_path):
"""
Returns True if ``python_path`` seems to contain vendored imports from botocore.
"""
# We're using a very rough heuristic here: if the source code contains
# strings that look like a vendored import, we'll flag.
#
# Because Python is dynamic, t... | 90ed6939d7f43cac29eb66c3e27e911b9cc62532 | 21,715 |
def filter_uniq(item):
"""Web app, feed template, creates unique item id"""
detail = item['item']
args = (item['code'], item['path'], str(detail['from']), str(detail['to']))
return ':'.join(args) | 914fa4e3fcdf6bc7e6a30b46c8f33eecd08adcf1 | 21,716 |
import joblib
import time
import logging
import warnings
import pickle
def load_pickle(filename, verbose=2, use_joblib=False):
"""
Note: joblib can be potentially VERY slow.
"""
with open(filename, 'rb') as file:
if verbose >= 2:
start = time.time()
logging.info(f'L... | 680c4b72e47efeb58ec1bd93e4899a3ae6b99709 | 21,717 |
from typing import Match
async def make_match(*args, register=False, **kwargs) -> Match:
"""Create a Match object. There should be no need to call this directly; use matchutil.make_match instead,
since this needs to interact with the database.
Parameters
----------
racer_1_id: int
The DB... | 67346038696558f19b08a65cf45e88646b1186e4 | 21,718 |
def is_anonymous(context: TreeContext) -> bool:
"""Returns ``True`` if the current node is anonymous."""
# return context[-1].anonymous
tn = context[-1].tag_name
return not tn or tn[0] == ':' | 0169a93cada0d371b3b4628ff3fabbbef6ef60f2 | 21,719 |
def expand_to_beam_size(tensor, beam_size):
"""Tiles a given tensor by beam_size."""
tensor = tf.expand_dims(tensor, axis=1)
tile_dims = [1] * tensor.shape.ndims
tile_dims[1] = beam_size
return tf.tile(tensor, tile_dims) | e38adceceeecdab737f89f246125674ac87e4702 | 21,720 |
import ipdb
def get_vignettes(
h5_file,
bed_file,
tmp_dir=".",
importance_filter=True,
rsid_to_genes=None,
ensembl_to_hgnc=None):
"""get the example indices at the locations of interest
"""
# prefix (scanmotifs)
dirname = h5_file.split("/")[-2]
print... | 396d2a5b908c99fd74427f74babc50323820fa36 | 21,721 |
def delete_cluster(access_token, project_id, cluster_id):
"""删除集群"""
url = f"{BCS_CC_API_PRE_URL}/projects/{project_id}/clusters/{cluster_id}/"
params = {"access_token": access_token}
return http_delete(url, params=params) | f48d7f8a6278e528792601938817d883751d7a41 | 21,722 |
def modifMail(depute, mail = MAIL):
"""
modifMail renvoit une chaine de caractères d'un mail personnélisé pour chaque députés des comissions choisies
Prend en entrée : infoDeput : un tableau de tableau avec les données des députés.
mail : l'adresse d'un fichier txt remp... | 0ade624e356bd0cc94fc3312ee1746a8771cb6a4 | 21,723 |
def atoi(s, base=None): # real signature unknown; restored from __doc__
"""
atoi(s [,base]) -> int
Return the integer represented by the string s in the given
base, which defaults to 10. The string s must consist of one
or more digits, possibly preceded by a sign. If base is 0, it
is chos... | 420c9a68c1fe829a665eaba830df757114a81b47 | 21,724 |
def gzip_requested(accept_encoding_header):
"""
Check to see if the client can accept gzipped output, and whether or
not it is even the preferred method. If `identity` is higher, then no
gzipping should occur.
"""
encodings = parse_encoding_header(accept_encoding_header)
# Do the actual co... | a07ca3d77095467791fc97d1a525ee878715e929 | 21,725 |
import logging
def create_logger(name="dummy", level=logging.DEBUG, record_format=None):
"""Create a logger according to the given settings"""
if record_format is None:
record_format = "%(asctime)s\t%(levelname)s\t%(message)s"
logger = logging.getLogger("modbus_tk")
logger.setLevel(level)
... | d7662fa035d7f096820c54b6e3b8403a77ce5769 | 21,726 |
def precip_units(units):
"""
Return a standardized name for precip units.
"""
kgm2s = ['kg/m2/s', '(kg/m^2)/s', 'kg/m^2/s', 'kg m^-2 s^-1',
'kg/(m^2 s)', 'kg m-2 s-1']
mmday = ['mm/day', 'mm day^-1']
if units.lower() in kgm2s:
return 'kg m^-2 s^-1'
elif units.lower() in... | e5f94c3dd41b68d2e7b6b7aa1905fd5508a12fab | 21,727 |
from typing import Union
from typing import List
def enumerate_quantities(
df: pd.DataFrame, cols: Union[List[str], None] = None, qty_col: str = "quantity"
) -> pd.DataFrame:
"""Creates new dataframe to convert x,count to x*count."""
if not cols:
raise ValueError("parameter cols must be an iterabl... | 0defc1575ead9b70f658be5ed6795b22c3b39ac7 | 21,728 |
def calcul_acc(labels, preds):
"""
a private function for calculating accuracy
Args:
labels (Object): actual labels
preds (Object): predict labels
Returns:
None
"""
return sum(1 for x, y in zip(labels, preds) if x == y) / len(lab... | 3dc22c8707c181dda50e2a37f2cd822b2a31590d | 21,729 |
def makeMolFromAtomsAndBonds(atoms, bonds, spin=None):
"""
Create a new Molecule object from a sequence of atoms and bonds.
"""
mol = Molecule(pybel.ob.OBMol())
OBMol = mol.OBMol
for atomicnum in atoms:
a = pybel.ob.OBAtom()
a.SetAtomicNum(atomicnum)
OBMol.AddAtom(a)
... | 570dafe641bbade0d070942ea8e708d7e454e011 | 21,730 |
import sys
def alpha_040(enddate, index='all'):
"""
Inputs:
enddate: 必选参数，计算哪一天的因子
index: 默认参数，股票指数，默认为所有股票'all'
Outputs:
Series：index 为成分股代码，values为对应的因子值
公式:
((-1\* rank(stddev(high, 10)))\* correlation(high, volume, 10))
"""
enddate = to_date_str(enddate)
... | 3c9ac15f617a44699ce568fda2a175b11350c43b | 21,731 |
def get_preprocessor(examples, tokenize_fn, pad_ids):
"""
Input:
examples: [List[str]] input texts
tokenize_fn: [function] encodes text into IDs
Output:
tf input features
"""
def generator():
for example in examples:
tokens = tokenize_fn(example)
yield pad... | 0b2fb2217e04183fee027faedd163a8f8a048e9a | 21,732 |
def is_propositional_effect(eff: BaseEffect):
""" An effect is propositional if it is either an add or a delete effect. """
return isinstance(eff, (AddEffect, DelEffect)) | be440b2192dd6b89fcaff5756e774e7543f408cf | 21,733 |
def read_user(msg):
"""Read user input.
:param msg: A message to prompt
:type msg: ``str``
:return: ``True`` if user gives 'y' otherwhise False.
:rtype: ``bool``
"""
user_input = input("{msg} y/n?: ".format(msg=msg))
return user_input == 'y' | 662e95002130a6511e6e9a5d6ea85805f6b8f0f5 | 21,734 |
import scipy
def frechet_distance(real, fake):
"""Frechet distance.
Lower score is better.
"""
n = real.shape[0]
mu1, sigma1 = np.mean(real, axis=0), np.cov(real.reshape(n, -1), rowvar=False)
mu2, sigma2 = np.mean(fake, axis=0), np.cov(fake.reshape(n, -1), rowvar=False)
diff = mu1 - mu2
... | 55ed2a4f21b8987925083c925e7df6de7b305c06 | 21,735 |
import requests
def get_tenants(zuul_url):
""" Fetch list of tenant names """
is_witelabel = requests.get(
"%s/info" % zuul_url).json().get('tenant', None) is not None
if is_witelabel:
raise RuntimeError("Need multitenant api")
return [
tenant["name"]
for tenant in requ... | 97944d2de2a8dfc2dd50dbea46a135a184e7aa37 | 21,736 |
def ant():
"""Configuration for MuJoCo's ant task."""
locals().update(default())
# Environment
env = 'Ant-v2'
max_length = 1000
steps = 2e7 # 20M
return locals() | 1b99dba9f38b735056055c564e1143c5eb77401a | 21,737 |
def docker_run(task, image, pull_image=True, entrypoint=None, container_args=None,
volumes=None, remove_container=True, **kwargs):
"""
This task runs a docker container. For details on how to use this task, see the
:ref:`docker-run` guide.
:param task: The bound task reference.
:type... | 6ddc61d47c7b78bf532195a8cddd37f3c730b675 | 21,738 |
def get_accuracy(pred, target):
"""gets accuracy either by single prediction
against target or comparing their codes """
if len(pred.size()) > 1:
pred = pred.max(1)[1]
#pred, target = pred.flatten(), target.flatten()
accuracy = round(float((pred == target).sum())/float(pred.numel()) * 100, 3... | f30e57602e4a06b0a0e3cd131bf992cf8f9b514e | 21,739 |
import numpy
def ifourier_transform(F,dt,n):
"""
See Also
-------
fourier_transform
"""
irfft = numpy.fft.irfft
shift = numpy.fft.fftshift
return (1.0/dt)*shift(irfft(F,n=n)) | d068cdbbe95f58d4210d2e799dfaee878fb9bf98 | 21,740 |
def preprocess_labels(labels, encoder=None, categorical=True):
"""Encode labels with values among 0 and `n-classes-1`"""
if not encoder:
encoder = LabelEncoder()
encoder.fit(labels)
y = encoder.transform(labels).astype(np.int32)
if categorical:
y = np_utils.to_categorical(y)
... | 3d92ce70f6ae7f713b27f5a31e92f0aab919584b | 21,741 |
def import_minimal_log(path, parameters=None, variant=DEFAULT_VARIANT_LOG):
"""
Import a Parquet file (as a minimal log with only the essential columns)
Parameters
-------------
path
Path of the file to import
parameters
Parameters of the algorithm, possible values:
... | 530f60799318b90c90d08d427965041e4bda6dba | 21,742 |
def get_input_assign(input_signal, input_value):
""" Get input assignation statement """
input_assign = ReferenceAssign(
input_signal,
Constant(input_value, precision=input_signal.get_precision())
)
return input_assign | 9b3e372423d323af3a718ab909c26f2ba42bfea6 | 21,743 |
def prune_repos(region: str=None, registry_prefix: str=None, repo: str=None, current_tag: str=None, all_tags: str=None):
"""
Pull the image from the registry if it doesn't exist locally
:param region:
:param registry_prefix:
:param repo:
:param current_tag:
:param all_tags:
:return:
... | d5d21230f4440e4909a9ff0288a794471b5fb016 | 21,744 |
def convert_size_bytes_to_gb(size_in_bytes):
""":rtype: float"""
return float(size_in_bytes) / GB | 7d3946dc431aa6a531fa11ef8e5391279f8b553a | 21,745 |
def merge_swab(survey_df, swab_df):
"""
Process for matching and merging survey and swab result data.
Should be executed after merge with blood test result data.
"""
survey_antibody_swab_df, none_record_df = execute_merge_specific_swabs(
survey_df=survey_df,
labs_df=swab_df,
... | 38253b473c45a967dc1aeccdd61e94566014a347 | 21,746 |
def confirm_space(environ, start_response):
"""
Confirm a spaces exists. If it does, raise 204. If
not, raise 404.
"""
store = environ['tiddlyweb.store']
space_name = environ['wsgiorg.routing_args'][1]['space_name']
try:
space = Space(space_name)
store.get(Recipe(space.public... | aff453f96bb85895115dff9796387bc223151c81 | 21,747 |
def find_ppp_device_status(address=None, username=None):
"""Find device status node based on address and/or username.
This is currently only used by the web UI. For the web UI this is the best
guess for identifying the device related to a forced web forward; which
allows the web UI to default username... | 71d44185a5df8f72b1281102faef66ea4f8a1de1 | 21,748 |
def get_L_dash_prm_bath_OS_90(house_insulation_type, floor_bath_insulation):
"""主開口方向から時計回りに90°の方向の外気に面した浴室の土間床等の外周部の長さ (m)
Args:
house_insulation_type(str): 床断熱住戸'または'基礎断熱住戸'
floor_bath_insulation(str): 床断熱住戸'または'基礎断熱住戸'または'浴室の床及び基礎が外気等に面していない'
Returns:
float: 主開口方向から時計回りに90°の方向の外気に面した浴... | 13362e5f035865b38ea6562aa7a836ce95298590 | 21,749 |
import os
def init():
"""Authorize twitter app using tweepy library"""
# ensure environment variables are set
if not os.environ.get("consumer_key"):
raise RuntimeError("consumer_key not set")
if not os.environ.get("consumer_secret"):
raise RuntimeError("consumer_secret not set")
... | fc53f0fe47a689d7a90a43cb1400d69f909c5ded | 21,750 |
import json
def generate_books(request, form):
"""
Returns a list of books.
"""
list_of_books = Book.generate_existing_books(form.cleaned_data['part'])
return HttpResponse(json.dumps(list_of_books), content_type='application/json') | d75deab68c4cb4cdc9f14e4a313ffd060ab01004 | 21,751 |
def window_reverse_4d(windows, window_size, H_q, W_q, H_s, W_s):
"""
Args:
windows: (num_windows*B, window_size, window_size, window_size, window_size, C)
window_size (int): size of window
H_q (int): Height of query image
W_q (int): Width of query image
H_s (int): Height ... | 8ef2743ec15c140807a9c269680f8bd3810703a3 | 21,752 |
import argparse
def parse_arguments():
"""
Function to parse command line arguements
from the user
Returns
-------
opts : dict
command line arguements from the user
"""
info = 'Divides pdb info files for parallelization'
parser = argparse.ArgumentParser(description=info)
... | 8bdc260c1dcb779c7b30927651e26c05a9c0d5f5 | 21,753 |
def numeric(symbols, negative, value):
"""Implement the algorithm for `type: numeric`."""
if value == 0:
return symbols[0]
is_negative = value < 0
if is_negative:
value = abs(value)
prefix, suffix = negative
reversed_parts = [suffix]
else:
reversed_parts = []
... | 4eb41904f1ead6e6f8f6d6a5a7855d917a0029b7 | 21,754 |
from typing import Dict
def scale_value_dict(dct: Dict[str, float], problem: InnerProblem):
"""Scale a value dictionary."""
scaled_dct = {}
for key, val in dct.items():
x = problem.get_for_id(key)
scaled_dct[key] = scale_value(val, x.scale)
return scaled_dct | f7ad0cf51129d7abfb85fdba8d64f1c69bba2bad | 21,755 |
import json
def get_and_log_environment():
"""Grab and log environment to use when executing command lines.
The shell environment is saved into a file at an appropriate place in the Dockerfile.
Returns: environ (dict) the shell environment variables
"""
environment_file = FWV0 / "gear_environ.j... | 2b91378184a442a3a21c8b94a4667dc9ab90290a | 21,756 |
def green(string: str) -> str:
"""Add green colour codes to string
Args:
string (str): Input string
Returns:
str: Green string
"""
return "\033[92m" + string + "\033[0m" | b6bdefe3e467e88c044b9289ea26a59ccf564f1a | 21,757 |
def from_6x6_to_21x1(T):
"""Convert symmetric second order tensor to first order tensor."""
C2 = np.sqrt(2)
V = np.array([[T[0, 0], T[1, 1], T[2, 2],
C2 * T[1, 2], C2 * T[0, 2], C2 * T[0, 1],
C2 * T[0, 3], C2 * T[0, 4], C2 * T[0, 5],
C2 * T[1, 3], C2 ... | 177d766ee251dfb52396f88b4e77d101956afe79 | 21,758 |
def post_add_skit_reply():
""" removes a skit if authored by the current user """
email = is_authed(request)
if email and csrf_check(request):
# same as args, form data is also immutable
request.form = dict(request.form)
request.form['email'] = email
p_resp = proxy(RUBY, requ... | 17b64bba949bb2df57cbdf796c0b895387672018 | 21,759 |
from datetime import datetime
def register(request):
"""Register new account."""
token_int = int(datetime.datetime.strftime(
datetime.datetime.now(), '%Y%m%d%H%M%S%f'))
token = short_url.encode_url(token_int)
if (not request.playstore_url and not request.appstore_url
and not reques... | 649c413011ec76bdb2244bbbfe7f4810230d3202 | 21,760 |
def stringify_parsed_email(parsed):
"""
Convert a parsed email tuple into a single email string
"""
if len(parsed) == 2:
return f"{parsed[0]} <{parsed[1]}>"
return parsed[0] | 6552987fe6a06fdbb6bd49e5d17d5aadaae3c832 | 21,761 |
import math
def standard_simplex_vol(sz: int):
"""Returns the volume of the sz-dimensional standard simplex"""
result = cm_matrix_det_ns(np.identity(sz, dtype=DTYPE))
if result == math.inf:
raise ValueError(f'Cannot compute volume of standard {sz}-simplex')
return result | 1b0d806312ee722f3251e1099e604a18d4e762a7 | 21,762 |
def all_saveable_objects(scope=None):
""" Copied private function in TF source. This is what tf.train.Saver saves if var_list=None is passed. """
return (tf.get_collection(tf.GraphKeys.GLOBAL_VARIABLES, scope) +
tf.get_collection(tf.GraphKeys.SAVEABLE_OBJECTS, scope)) | 4c0b8ec0dd65160a113d4e6151a1a5b6d8454926 | 21,763 |
def base_to_str( base ):
"""Converts 0,1,2,3 to A,C,G,T"""
if 0 == base: return 'A'
if 1 == base: return 'C'
if 2 == base: return 'G'
if 3 == base: return 'T'
raise RuntimeError( 'Bad base: %d' % base ) | f1c98b7c24fae91c1f809abe47929d724c886168 | 21,764 |
import argparse
def parse_args(args):
"""
function parse_args takes arguments from CLI and return them parsed for later use.
:param list args : pass arguments from sys cmd line or directly
:return dict: parsed arguments
"""
parser = argparse.ArgumentParser()
required = parser.add_argument... | e3783dc173696b5758d8fc90bc810841e043be0a | 21,765 |
def attr(accessing_obj, accessed_obj, *args, **kwargs):
"""
Usage:
attr(attrname)
attr(attrname, value)
attr(attrname, value, compare=type)
where compare's type is one of (eq,gt,lt,ge,le,ne) and signifies
how the value should be compared with one on accessing_obj (so
compare=gt me... | 8b3944ee8ef64938314766cc21e893ccbf48d9e1 | 21,766 |
def group_connected(polygon_map, mask=None):
"""Group all connected nodes."""
# Wrap :c:`group_connected()` from ``polygon_map.c``.
polygon_map = mask_polygon_map(polygon_map, mask)
queue = Queue(len(polygon_map) + 1)
group_ids = np.full(len(polygon_map), -1, np.intp, order="C")
groups_count:... | 2239feab1ef914156e01ab430f0c561609de0b18 | 21,767 |
def dictmask(data, mask, missing_keep=False):
"""dictmask masks dictionary data based on mask"""
if not isinstance(data, dict):
raise ValueError("First argument with data should be dictionary")
if not isinstance(mask, dict):
raise ValueError("Second argument with mask should be dictionary")... | d18f6effb4367628ba85095024189d0f6694dd52 | 21,768 |
import subprocess
import time
from pathlib import Path
def connect(file=None, port=8100, counter_max=5000):
"""Open libreoffice and enable conection with Calc.
Args:
file (str or pathlib.Path, optional): Filepath. If None, a
new Calc instance will be opened.
port (int, optional): ... | a82386b0eff1c8665f056d705a8a65913beecdf4 | 21,769 |
from dallinger.config import default_keys
from dallinger.config import Configuration
def stub_config():
"""Builds a standardized Configuration object and returns it, but does
not load it as the active configuration returned by
dallinger.config.get_config()
"""
defaults = {
u'ad_group': u'T... | 57820943883411f7e1081d1ff39ac5677d91f41d | 21,770 |
def _prepare_policy_input(
observations, vocab_size, observation_space, action_space
):
"""Prepares policy input based on a sequence of observations."""
if vocab_size is not None:
(batch_size, n_timesteps) = observations.shape[:2]
serialization_kwargs = init_serialization(
vocab_size, observatio... | 9799357e00453a1259551c3af1b5bf5b58603186 | 21,771 |
def RGB2raw(R, G, B):
"""Convert RGB channels to Raw image."""
h, w = R.shape
raw = np.empty(shape=(2*h, 2*w), dtype=R.dtype)
raw[::2, ::2] = R
raw[1::2, 1::2] = B
raw[1::2, 0::2] = G
raw[0::2, 1::2] = G
return raw | 7adb2ccef65c85c7e5d1ac223f397ef2f90dd9d3 | 21,772 |
def get_algs_from_ciphersuite_name(ciphersuite_name):
"""
Return the 3-tuple made of the Key Exchange Algorithm class, the Cipher
class and the HMAC class, through the parsing of the ciphersuite name.
"""
tls1_3 = False
if ciphersuite_name.startswith("TLS"):
s = ciphersuite_name[4:]
... | cc2ab3fcae87feeb7877bad091446fb2d20be6b0 | 21,773 |
def centroid(window):
"""Centroid interpolation for sub pixel shift"""
ip = lambda x : (x[2] - x[0])/(x[0] + x[1] + x[2])
return ip(window[:, 1]), ip(window[1]) | e1cf0398261637f682c74340f99566d19e342b66 | 21,774 |
def _format_warning(message, category, filename, lineno, line=None):
"""
Replacement for warnings.formatwarning that disables the echoing of
the 'line' parameter.
"""
return "{}:{}: {}: {}\n".format(filename, lineno, category.__name__, message) | 8267150c5890759d2f2190ccf4b7436ea8f55204 | 21,775 |
from typing import List
def precision_at_k(predictions: List[int], targets: List[int], k: int = 10) -> float:
"""Computes `Precision@k` from the given predictions and targets sets."""
predictions_set = set(predictions[:k])
targets_set = set(targets)
result = len(targets_set & predictions_set) / float(... | 4c6e566db7c488416139545f5f845ff80b7af434 | 21,776 |
def wordify_open(p, word_chars):
"""Prepend the word start markers."""
return r"(?<![{0}]){1}".format(word_chars, p) | 8b267aaca897d6435a84f22064f644727ca6e83c | 21,777 |
def Mt_times_M(M):
"""Compute M^t @ M
Args:
M : (batched) matrix M
Returns:
tf.Tensor: solution of M^t @ M
"""
if isinstance(M, tf.Tensor):
linop = tf.linalg.LinearOperatorFullMatrix(M)
return linop.matmul(M, adjoint=True)
elif isinstance(M, (tf.linalg.LinearOper... | cfb8023711186821faf0ff8bfa1277d6585d40de | 21,778 |
import typing
def make_values(ints: typing.Iterable[int]):
"""Make datasets.
"""
return [
('int', ints),
('namedtuple', [IntNamedTuple(i) for i in ints]),
('class', [IntObject(i) for i in ints]),
] | 700bbd4a43bff38a0154bbc595c1cd10cc2ec9d9 | 21,779 |
import collections
def attach_trans_dict(model, objs):
"""Put all translations from all non-deferred translated fields from objs
into a translations dict on each instance."""
# Get the ids of all the translations we need to fetch.
try:
deferred_fields = objs[0].get_deferred_fields()
except... | 933e87b050eac0dfbead141c0c3c56a2add9751f | 21,780 |
def list_known_protobufs():
"""
Returns the list of known protobuf model IDs
"""
return [k for k in proto_data_structure] | a4b80f948792a4d2a965eac507a118719fa106f5 | 21,781 |
def hash_value(*args):
"""
hash_value(NodeConstHandle t) -> std::size_t
hash_value(BufferConstHandle t) -> std::size_t
hash_value(FileConstHandle t) -> std::size_t
"""
return _RMF.hash_value(*args) | c85277fec7f329eeba26d053a43205bf1eda0662 | 21,782 |
import re
def read_examples(input_file):
"""Read a list of `InputExample`s from an input file."""
examples = []
unique_id = 0
# with tf.gfile.GFile(input_file, "r") as reader:
with open(input_file, "r") as reader:
while True:
line = tokenization.convert_to_unicode(reader.readli... | 82380f9409bd91e16fc4324fc345d335fa9e96dc | 21,783 |
from datasets import load_dataset
def get_finance_sentiment_dataset(split: str='sentences_allagree') -> list:
"""
Load financial dataset from HF: https://huggingface.co/datasets/financial_phrasebank
Note that there's no train/validation/test split: the dataset is available in four possible
... | 9f83d4c501ed16e5e617c32090787d1377ec70fd | 21,784 |
def list_databases():
"""
List tick databases and associated aggregate databases.
Returns
-------
dict
dict of {tick_db: [agg_dbs]}
"""
response = houston.get("/realtime/databases")
houston.raise_for_status_with_json(response)
return response.json() | d2ba438a0496f5863ad1c16cb8e694b54276d01e | 21,785 |
def nice_range(bounds):
"""
Given a range, return an enclosing range accurate to two digits.
"""
step = bounds[1] - bounds[0]
if step > 0:
d = 10 ** (floor(log10(step)) - 1)
return floor(bounds[0]/d)*d, ceil(bounds[1]/d)*d
else:
return bounds | 66f538649b8f1c55d301b2a0e293a4968b3665d9 | 21,786 |
def connect_to_portal(config):
"""
The portal/metadata schema is completely optional.
"""
if config.portal_schema:
return aws.connect_to_db(**config.rds_config, schema=config.portal_schema) | 2aa76ae2ad8d9ea16ea7ba227627f02d3c044d70 | 21,787 |
import json
def get_words_for_source():
""" Gets JSON to populate words for source """
source_label = request.args.get("source")
source = create_self_summary_words(source_label)
return json.dumps(source) | 2a2fc02a6f77cd109f3e0fded026676109ae014c | 21,788 |
def raster(event_times_list):
"""
Creates a raster plot
Parameters
----------
event_times_list : iterable
a list of event time iterables
color : string
color of vlines
Returns
-------
ax : an axis containing the raster plot
"""
color='k'
ax = plt.gca()
for ith... | 3c5b485bdc3992602a7c7bb227329b2e74c611d9 | 21,789 |
def FindOneDocument(queryDocument, database='NLP', collection="Annotations", host='localhost', port='27017'):
"""
This method returns the first document in the backing store that matches the criteria specified in queryDocument.
:param queryDocument: [dict] A pymongo document used to query the MongoDB insta... | fb5f683f4451144ae3cbe374162bef36918130ba | 21,790 |
def user_info(context, **kwargs):
"""
Отображает информацию о текущем авторизованом пользователе, либо ссылки на авторизацию и регистрацию
Пример использования::
{% user_info %}
:param context: контекст
:param kwargs: html атрибуты оборачивающего тега
:return:
"""
request = co... | 20321056fd5fdf8f51e79fb66d335272e85ada0d | 21,791 |
from functools import reduce
from datetime import datetime
def transactions(request):
"""Transaction list"""
tt = TimerThing('transactions')
# Get profile
profile = request.user.profile
characters = Character.objects.filter(
apikeys__user=request.user,
apikeys__valid=True,
... | 46585859baa2a665f30d6abd48455c9abefa1c1e | 21,792 |
def to_bytes(val):
"""Takes a text message and return a tuple
"""
if val is NoResponse:
return val
val = val.replace('\\r', '\r').replace('\\n', '\n')
return val.encode() | 9f5a45d9c69a18eec22c85c6691f8b3d46742af4 | 21,793 |
def _create_fake_data_fn(train_length=_DATA_LENGTH, valid_length=50000, num_batches=40):
""" Creates fake dataset
Data is returned in NCHW since this tends to be faster on GPUs
"""
logger = _get_logger()
logger.info("Creating fake data")
data_array = _create_data(_BATCHSIZE, num_batches, (_HEI... | 33533cc4b1d43aaeba48db8470c93cbc058ad3dc | 21,794 |
def watershed(src):
"""
Performs a marker-based image segmentation using the watershed algorithm.
:param src: 8-bit 1-channel image.
:return: 32-bit single-channel image (map) of markers.
"""
# cv2.imwrite('{}.png'.format(np.random.randint(1000)), src)
gray = src.copy()
img = cv2.cvtColo... | 6915b6a924e64d12340e02b28085290685dddc9b | 21,795 |
def sub(x, y):
"""Returns the difference of compositions.
Parameters
----------
x : NumPy array, shape (n,) or (k,n)
The composition that will be subtracted from.
y : NumPy array, shape (n,) or (k,n)
The composition to be subtracted.
Returns
-------
z : NumPy array, sha... | c9e1fb31abb22a6efb9903c6e9f7cdc06cc110d0 | 21,796 |
def _broadcast_concatenate(arrays, axis):
"""Concatenate arrays along an axis with broadcasting."""
arrays = _broadcast_arrays(arrays, axis)
res = np.concatenate(arrays, axis=axis)
return res | 5032ec0a90dde25d74906dbf661248086c785485 | 21,797 |
def get_final_bmi(data_dic, agex_low, agex_high, mrnsForFilter=[], filter=True):
"""
Function to get the distinct bmi percentile readings for predictions.
Returns outcome percentiles and labels
#### PARAMETERS ####
data_dic: dictionary of patient data
agex_low: low age range for outcome predicti... | e9793adf7470a695bd730f66817b735451df71a2 | 21,798 |
import sqlite3
def add_group_sub(uid:int, group_id:int) -> bool: #添加订阅信息
"""
向已存在的表中插入群记录, 如果群已经存在则什么都不做
:param uid: 唯一标识用户的数字uid
:param group_id: 监听该用户的群id
"""
connection = sqlite3.connect(DB_PATH)
cursor = connection.cursor()
success = True
group_exist = cursor.execute(
f... | de71f03aa56bf4ae963877281e7e70876f5e72ff | 21,799 |
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