content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def login(request):
"""登录视图"""
if request.session.get('is_login',None):
logger.info(request)
return redirect("/index/")
if request.method == "POST":
login_form = UserForm(request.POST)
message = "请检查填写的内容！"
if login_form.is_valid():
username = login_form.c... | b9ea5492bcc9f7224f75e2121a6e8e3e6a1d9827 | 3,614,900 |
def setup_platform(hass, config, add_devices, discovery_info=None):
""" Set up the Visonic Alarm platform. """
hub.update()
visonic_alarm = VisonicAlarm(hass)
add_devices([visonic_alarm])
# Create an event listener to listen for changed arm state.
# We will only fetch the events from the API on... | cd345fec39db4388b06e7efed8cf392e2797fcdc | 3,614,901 |
def pipeline_send_op(node, destination, comm, stream=None, ctx=None):
"""Make a new instance of PipelineSendOp and call the instance.
Parameters:
----
node : Node
The Node to be send.
destination : scalar value
The gpu index for destination.
Returns:
----
A new Node ins... | 29db37670805705032cb293d8606d20bc4bc6bb1 | 3,614,902 |
import signal
import math
def synth(**kwargs):
"""return ricker wavelet synthetic data"""
# defaults
if 'pol' not in kwargs: kwargs['pol'] = 0.
if 'delta' not in kwargs: kwargs['delta'] = 1.
if 'split' not in kwargs: kwargs['split'] = []
if 'noise' not in kwargs: kwargs['noise'] = 0.0... | 8186c37add652e63ecdfe610866abc00d08eefe6 | 3,614,903 |
import yaml
import random
import string
def tmp_config_file(dict_: dict) -> str:
"""
Dumps dict into a yaml file that is saved in a randomly named file. Used to as config file to create
ObservatoryConfig instance.
:param dict_: config dict
:return: path of temporary file
"""
content = yaml... | d4ea42a8dc1824757df7f9823f44f7fc181b29aa | 3,614,904 |
import re
def get_bootstrap_assets(self, platform=None):
"""
:param self:
:param platform: optional, defaults to current build's platform
:return: Asset type requested for the supplied platform in bootstrap.cfg
"""
if platform is None:
platform = self.env['PLATFORM']
bootstrap_cfg ... | 55510ed1d15c3ec7323b257b5596cd601bad2316 | 3,614,905 |
def calc_checksum(packet):
"""
Calculates the checksum of a given packet.
This function is only for use in environments where 16-bit words are used.
:param packet: A list with 16-bit numbers as Integers.
:return: The checksum of the packet as Integer
"""
# validate the input
try:
... | 7fd61f9cd15bf7acc7e87255cd6813aa84216266 | 3,614,906 |
def interpolate_with_degree(nodes, values, deg, use_mp=False):
"""Compute a rational function which interpolates the given nodes/values
with given degree `m` of the numerator and `n` of the denominator.
Args:
nodes (array): the interpolation nodes
values (array): the values at the interpola... | 19f5ffa5ac4f1b18de4d489b68ba7726a4c8851a | 3,614,907 |
def preprocess_input(title, overview, vectorizer):
"""
Extract TF-IDF features from a single title and overview input.
:param title: Str. Movie title.
:param overview: Str. Movie plot.
:param vectorizer: Fitted sklearn.feature_extraction.text.TfidfVectorizer object.
:return: Tf-IDF features matr... | 0de37a8e7c870eef185baa3aa1a497ea8d353201 | 3,614,908 |
def _generate_image_info(im, params):
""""generate url and tokens for image"""
image = ee.Image(im)
if "sld_style" in params:
m = image.sldStyle(params.get("sld_style"))
del params["sld_style"]
elif "palette" in params:
m = image.visualize(
**{
"min":... | 13a6bc4a6ad9eb7dd549682d707b1dd7aabb65fe | 3,614,909 |
import typing
def forced_attribute_type(name: str, type_accessor: typing.Callable[[], typing.Type], may_subclass=False, source_source=None):
"""
Forced a certain data type on an object attribute
Not validated, but allows optimisations to happen!
Can speed up calls by a lot
"""
def annotation... | 2e1d56e5b3d93d392381f008b6acfda6b47ba6d5 | 3,614,910 |
def _setup_fig(ncols, nrows, figsize_width, figsize_height):
"""
Parameters:
-----------
ncols
Number of columns in the figure.
type: int
nrows
Number of rows in the figure.
type: int
figsize_width
Scaler adjustment of figure width
default: 1
... | cf6c75101220620a8bf7c04d59ba9642ba339779 | 3,614,911 |
def unconfirmed():
"""Catch users with unconfirmed emails."""
if current_user.is_anonymous or current_user.confirmed:
return redirect(url_for('main.index'))
return render_template('account/unconfirmed.html') | 04c40e63a48da389fdec7897c8db049cde572228 | 3,614,912 |
import sys
def local_str(arg):
"""
Преобразует arg в unicode, а затем в строку с кодировкой для вывода на текущем терминале
"""
e = sys.stdout.encoding
if not e:
e='cp1251'
return unicode(arg).encode(e, 'ignore') | 4fc08dac4d1da64ad35e47a6c01fc60d5623b0e6 | 3,614,913 |
def computeAlleleFrequency (f_C, f_T):
"""3
f_C = minor allele count
f_T = major allele count
minor_allele_frequency = f_C/ (f_C+f_T)
7"""
minor_allele_frequency = f_C/(f_C+f_T)
return minor_allele_frequency | 984a7364bfd3ff2c724c885dedd97f61f959b7e6 | 3,614,914 |
def update_m(obj, ia, rcut=9.0, pbc=None):
"""
retrieve local structure around atom `ia
for periodic systems (or very large system)
"""
zs, coords, c = obj
v1, v2, v3 = c
vs = ssd.norm(c, axis=0)
nns = []
for i,vi in enumerate(vs):
n1_doulbe = rcut/li
n1 = int(n1_dou... | 5ee6752f1c5cc1274557e523acb12394a9b33f56 | 3,614,915 |
def crext_TruncatedHMAC():
"""Create a Truncated HMAC extension."""
return ExtensionType.truncated_hmac.value + lenprefix(b"") | 4d9dbc4156e4bc1855e241bd493aa7b7149e800a | 3,614,916 |
def microcycle_days(weekly_training_days, weeks):
"""generates indexes of training days during the weeks"""
training_day_indexes = []
for w in range(weeks):
for d in weekly_training_days:
training_day_indexes.append(w * 7 + d.value)
return training_day_indexes | 5c0364b1dc58d2c0205d4e6442d590a23519e5f4 | 3,614,917 |
def reduced_supercell_vectors(ab, n):
"""
Returns all possible reduced in-plane lattice vectors and
transition matrices for the given starting unit cell lattice
vectors(ab) and the supercell size n
"""
uv_list = []
tm_list = []
for r_tm in get_trans_matrices(n):
uv = get_uv(ab, r... | 7c75258e19037ee8e09858793b3232690313add8 | 3,614,918 |
from typing import List
def make_polygon_from_coords(coords: List[float]):
"""
Creates a `Polygon` instance using the passed in coordinates:
`[x1 y1 x2 y2 ... xn yn]`.
It raises a `ValueError` if the coordinates list does't have
an even number of entries.
:param coords: list of the coordinat... | 7aa7c46d9f769f57a1bfdbe962bb2f942ab08e96 | 3,614,919 |
def fibonacciMemoization(n: int):
"""
:param n: range numbers to be visited in fibonacci series
:return: nth value in the fibonacci sequence
"""
global fibb_memo
if n in fibb_memo:
return fibb_memo[n]
if n <= 2:
return 1
fibb_memo[n] = fibonacciMemoization(n - 1) + fi... | affd30d81fc6a0564c4acddb2b676a26fcb9846a | 3,614,920 |
def scatter(data, **kwargs):
"""I dont like this. Viewing code should not reside in model logic."""
fig, ax = plt.subplots(1, 1, figsize=(6, 5))
ax.scatter(*data.cpu().numpy().T[:2], **kwargs)
plt.close()
return fig | b89416ded88c872585a3db75651b393d5d319b79 | 3,614,921 |
def build_training_model_component():
"""
Build training model component
Returns:
training_model_component: training model component
"""
model_training_stage = []
rfor = RandomForestClassifier(featuresCol=FEATURES, labelCol=TARGET, seed=RANDOM_SEED)
model_training_stage.append(rfor)
... | 7bbb6f830bb8f4719e95dd3b18121e3ba8ab23cc | 3,614,922 |
import torch
def cka(k_x: torch.Tensor, k_y: torch.Tensor, centered: bool = False, unbiased: bool = True) -> torch.Tensor:
"""Compute Centered Kernel Alignment (CKA).
:param k_x: n by n values of kernel applied to all pairs of x data
:param k_y: n by n values of kernel on y data
:param centered: whet... | a0abf43f33e79f67a2974d7524730f04ae86dd93 | 3,614,923 |
import os
import logging
import google
def _run_dag_and_wait():
"""Run and wait for the DAG to finish.
Returns:
state: The end state of the DAG.
"""
artifacts_path = os.path.join(prow.get_gcs_output(), "artifacts")
logging.info("Artifacts will be saved to: %s", artifacts_path)
conf = {
"PULL_NUM... | fde39f8665c09c000b354eb280465b88e4f18f21 | 3,614,924 |
from typing import OrderedDict
def columns(table, missing=None):
"""
Construct a :class:`dict` mapping field names to lists of values. E.g.::
>>> import petl as etl
>>> table = [['foo', 'bar'], ['a', 1], ['b', 2], ['b', 3]]
>>> cols = etl.columns(table)
>>> cols['foo']
... | 2938710112da2b8317fda65b8d873f48e1e2dc40 | 3,614,925 |
import sys
def get_output_encoding():
""" Get the output encoding used for output to management commands.
:return: ``sys.stdout.encoding``
"""
return sys.stdin.encoding or sys.getdefaultencoding() or DEFAULT_ENCODING | ef9bf322ced4d4d1d179ebf618cf1965e5934398 | 3,614,926 |
def _project_vertices(v, w, h, cam_r, cam_t):
"""projects vertices onto image plane"""
V = ch.array(v)
U = ProjectPoints(v=V, f=[w * 2, w * 2], c=[w / 2., h / 2.], # camera intrinsics
k=ch.zeros(5), t=cam_t, rt=cam_r)
return U | db7f664a531abb4949c66499ef9ef7bfd3cff047 | 3,614,927 |
import pprint
def check_overlapping(features):
"""Check for elements of `features` with overlapping ranges. In the
case of overlap, print an informative error message and return
names and positions of overlapping features.
"""
features = features[:]
overlapping = []
for i in range(len(fea... | 6a246aca29c01b32091d7890b6a55d66367e8e14 | 3,614,928 |
def predict(x, P, F=1, Q=0, u=0, B=1, alpha=1.):
""" Predict next position using the Kalman filter state propagation
equations.
Parameters
----------
x : numpy.array
State estimate vector
P : numpy.array
Covariance matrix
F : numpy.array()
State Transition matrix
... | fb6002c528489f5d595acd8137f1606416eb6678 | 3,614,929 |
def update_hosts(hosts_list=None, user='root'):
"""
@param_post{hosts_list}
@param_post{user} (optional, default: @val{root})
"""
if user is None:
missing_parameter('user')
if hosts_list is None:
missing_parameter('host_list')
try:
f = open("/etc/hosts", "r")
... | 2e95445363814befe67757d517590d2b112bf871 | 3,614,930 |
def get_file_to_load():
"""Open a popup window to select a file to load"""
return sg.popup_get_file(
'Select a file to open',
EVENT_OPEN,
initial_folder=USER_HOME,
no_window=True,
default_extension=EDITOR_EXTENSION,
) | 3ab90ed642d460dd0db0fbdf63d09dc900d19715 | 3,614,931 |
from operator import concat
def renew(alias, sub_nas, args):
"""
:param alias:
:param sub_nas:
\n:param args [expiration, type]:
\n:returns new expiration if success or False if failed:
\nif sub_nas defined passes call to sub_nas otherwise
we try to renew alias
"""
# handle sub_nas... | c252c72f51c19b798d7af53eb9a064991bbc5a98 | 3,614,932 |
def create_train_op(total_loss,
optimizer,
global_step=_USE_GLOBAL_STEP,
update_ops=None,
variables_to_train=None,
transform_grads_fn=None,
summarize_gradients=False,
gate_gradient... | ad2033022d628c4b82da453b0ba772f72028abd6 | 3,614,933 |
def does_asyncio(func):
"""Simple decorator for running a test inside an asyncio event loop."""
def wrapper(*args, **kwargs):
get_event_loop().run_until_complete(func(*args, **kwargs))
return wrapper | 8f1d9a37400204cfa63ec5edaa25592558219b4d | 3,614,934 |
def correct_baseline(raw_data, mode, smoothing=True, transform=False,
**kwargs):
"""
Calculate baseline data for raw_data with generate_baseline(...).
Takes the same arguments like generate_baseline, for details see
docstring of generate_baseline.
"""
return raw_data - gene... | b9e3b278cfd1e33bb606a32866eea2be5cb75bef | 3,614,935 |
def article(*args, **kwargs):
"""
The HTML <article> element represents a self-contained composition
in a document, page, application, or site, which is intended to be
independently distributable or reusable (e.g., in
syndication). This could be a forum post, a magazine or newspaper
article, a b... | 79405862e88865296aa16ae477f2a6c5d2323ac9 | 3,614,936 |
from typing import Dict
def validate(business: Business, cod: Dict) -> Error:
"""Validate the Change of Directors filing."""
if not business or not cod:
return Error(HTTPStatus.BAD_REQUEST, [{'error': babel('A valid business and filing are required.')}])
msg = []
msg_directors_addresses = val... | 937b74506eb4e3a9d73bc135394f78b42a32e861 | 3,614,937 |
def index():
"""
Basic index view, listing online users.
"""
msg = 'Online: %s' % ', '.join(get_online_users())
return make_response(msg) | a74c95ec7d25f46c3a5c30203ec6ce34260d35ba | 3,614,938 |
def pixel2wave (pix, c, model='linear') :
"""
Inverse function for a given pixel(wave) model.
Converts a pixel position pix into a wavelength w using one of several invertable models:
'linear','quadratic','cubic' w(pix) = invert_polynomial(pix,c) because pix(w) = c[0]+c[1]*w+...
'exp' w(pix) = -ln[(pix-c2)... | e8722d739bcf7fa76a5b8dbda34edddc76915496 | 3,614,939 |
def compute_level(id, tree):
"""
compute the level of an id in a tree
"""
topic = tree[id]
level = 0
while (id != 0):
level += 1
id = topic['parent']
topic = tree[id]
return(level) | fb7fbc1c1f97e85c03abdd453a3deb3411960e45 | 3,614,940 |
import os
def is_db_weather(weather_path):
"""True, if the ``weather_path`` is one of the pre-installed weather files that came with the CEA"""
weather_name = get_db_weather_name(weather_path)
if weather_name in LOCATOR.get_weather_names():
# could still be a custom weather file...
db_weat... | 85dbaa618d5607183169ecca7e671ef30f0ac23f | 3,614,941 |
import csv
def ReadDirectoryFromFile(file_name, hub_map):
"""directory_tools.ReadDirectory
INPUTS:
- file_name -- name of the file containing the MemberHub directory dump
- hub_map -- dictionary that maps hub names to hub IDs
OUTPUTS:
- directory -- list of families read from the MemberHub d... | 3ed042a2b26436f4061e8d0b628f4887a8982a10 | 3,614,942 |
from typing import Sequence
from typing import Any
from typing import Optional
from typing import Union
from typing import List
def flatten(sequence: Sequence[Any], depth: Optional[int] = -1, **kwargs) -> Union[List[Any], Any]:
"""
Receives values, whether arrays of values, regardless of their shape and flatn... | bfdd0ed66d3eaac5ec3b6c17e43f917bfbbadc69 | 3,614,943 |
import random
import sympy
def change_four_variables_in_expr(latex_dict: dict) -> str:
"""
>>> latex_dict = {}
>>> latex_dict['input'] = [{'LHS': parse_latex(''), 'RHS': parse_latex('')}]
>>> latex_dict['feed'] = [parse_latex('')]
>>> latex_dict['output'] = [{'LHS': parse_latex(''), 'RHS': parse_l... | 81385dc30fcd84d1e9e72326383849cc88f1ada3 | 3,614,944 |
def polyglot_1st_pronoun(s):
"""Get first pronoun from the sentence.
Parameters
----------
:param s: string
Sentence
Returns
-------
:returns: string
first pronoun
"""
pronouns = polyglot_pronouns(s)
return pronouns[0] | c0c27ae6bdb5be5b6317cf6751242759538de41c | 3,614,945 |
def filter_by_pvalue_strand_lag(ratios, pcutoff, pvalues, output, no_correction, name, singlestrand):
"""Filter DPs by strang lag and pvalue"""
if not singlestrand:
zscore_ratios = zscore(ratios)
ratios_pass = np.where(np.bitwise_and(zscore_ratios > -2, zscore_ratios < 2) == True, True, False)
... | 394b7b6561c869ba97bbb2ad1d015b2600b71b26 | 3,614,946 |
def write_user_playlist(username, text_file=None):
""" Write user playlists to text_file """
links = get_playlists(username=username)
playlist = internals.input_link(links)
return write_playlist(playlist, text_file) | 2ab684f2f7eec1484d76427fe179fe8620e60da8 | 3,614,947 |
def is_float(db_type):
"""Return True if the database type is a float supported type, False otherwise.
"""
return db_type in ACCEPTED_FLOAT_DB_TYPES | 114657762f76afce67739aac011539b6a0c081e6 | 3,614,948 |
import time
def generate_papernot():
"""
Train the second/distilled model using uncertaity array
:return: distilled model
"""
sigmas = np.load(PROJ_PATH + 'mnist_papernot/sigmas.npz')['sigmas']
start = time()
model_papernot = train_papernot(sigmas)
end = time()
print("Papernot trai... | d526855245b05fcc5f2107952082239e8121674c | 3,614,949 |
def inverse_stft_window_fn(frame_step,
forward_window_fn=window_ops.hann_window,
name=None):
"""Generates a window function that can be used in `inverse_stft`.
Constructs a window that is equal to the forward window with a further
pointwise amplitude cor... | 73a17762231915b35409c05119c1b39eace851b2 | 3,614,950 |
def Vegas(integrand, ndim, userdata=NULL,
epsrel=EPSREL, epsabs=EPSABS, flags=0, ncomp=1, seed=None,
mineval=MINEVAL, maxeval=MAXEVAL, nstart=NSTART,
nincrease=NINCREASE, nbatch=NBATCH,
gridno=GRIDNO, statefile=NULL, nvec=1):
"""
*nstart*: the number of integrand evaluations per iteration to start... | 0762180ec96902b045ff0a16e9f389a7917287ea | 3,614,951 |
def human_annotations(human_file):
"""
Generates JSON from TSV files
"""
zipped_rows = get_rows_from_file(human_file, '\r')
# Too many processes causes the http requests causes the remote to respond with error
pool = mp.Pool(processes=1)
annotations = pool.map(human_single_annotation, zipped... | 965b3f8d1ab557ae79e3f2fa2f0e8e635b568842 | 3,614,952 |
import torch
import math
def eval_gather_inds(len_, num_samples=7):
""" get the gather indices """
inds = torch.arange(0, num_samples, dtype=torch.long)
mul = math.ceil(len_ / num_samples)
output = inds.repeat(mul)[:len_]
return output | 516ca54ff5c3b442bc93becd15d1bdabd8c8025f | 3,614,953 |
def vap_lapserate(temp,pres,dvap=None,chkvals=False,chktol=_CHKTOL,
dvap0=None,chkbnd=False,mathargs=None):
"""Calculate water vapour adiabatic lapse rate.
Calculate the adiabatic lapse rate of water vapour at temperature
and pressure.
:arg float temp: Temperature in K.
:arg float pres... | 6597bd3d0faef483d7db9c46e0c01a4cb3fc9922 | 3,614,954 |
def none_or_valid_float_value_as_string(str_to_check):
"""
Unless a string is "none", tries to convert it to a float and back to check
that it represents a valid float value. Throws ValueError if type
conversion fails. This function is only needed because the MATLAB scripts
take some arguments eithe... | 54f3c63fab0752678cb5a69723aa7790ab11a624 | 3,614,955 |
def hunkify_lines(lines, context=3):
"""
Return a list of line hunks given a list of lines `lines`. The number of
context lines can be control with `context` which will return line hunks
surrounded with `context` lines before and after the code change.
"""
# Find contiguous line changes
rang... | c5acde8c6335b82173af724ba3c8c34058fa23b6 | 3,614,956 |
from typing import Dict
from typing import Union
def _from_node_reqs_to_dask_resources(
node_reqs: NodeRequirements,
) -> Dict[str, Union[int, float]]:
"""Dask resources are set such as {"CPU": X.X, "GPU": Y.Y, "RAM": INT}"""
dask_resources = node_reqs.dict(exclude_unset=True, by_alias=True)
logger.de... | 0aeace41a5a3267e23b1c81406c500db0983e199 | 3,614,957 |
def init_policy(states, Q):
"""
Define initial target policy of off-policy MC method
Parameters
----------
states : list of tuples
States consist of positions and velocity of agent
Q : dict
Dictionary with q values of each action in each state
Returns
-------
pi : d... | 1c354291668c3489695cd5d25ea11bb3d00d5531 | 3,614,958 |
def gaussianFWHM(x, fwhm, norm = 'area'):
"""
Calculate a Gaussian function.
Parameters
----------
x : array_like
Input array
fwhm : scalar
The full-width at half-maximum value.
norm : {'area', 'amplitude'}
The normalization convention. The default is 'area'. See... | 3df6f2b531669862322bc34796d315c1e8d6f2e2 | 3,614,959 |
def S_moving_average_filter(_data_list, _smoothing=1):
"""
Returns moving average data without data lag.
Use the smoothing factor to get required overall smoothing where the smoothing factor is greater than zero.
"""
ma_data = []
ds = len(_data_list)
s = _smoothing
mas = int((ds... | 763bff294c6225260cb67e2e38440eb4d514c126 | 3,614,960 |
def StripKey(key):
"""Returns key with header, footer and all newlines removed."""
key = key.strip()
key_lines = key.split(b'\n')
if (not key_lines[0].startswith(b'-----')
or not key_lines[-1].startswith(b'-----')):
raise OpenSSLException(
'The following key does not appear to be in PEM format... | bed4f367759098fcb001c315791f3cf25328993e | 3,614,961 |
def get_expanse_certificate_context(data):
"""
provide custom context information about certificate with data from Expanse API
"""
return {
"SearchTerm": data['search'],
"CommonName": data['commonName'],
"FirstObserved": data['firstObserved'],
"LastObserved": data['lastOb... | cf5c1d38ae7ed3474171ccff7d437d7b622cbcec | 3,614,962 |
def find_polygon_divisions(line_pts, polygon_pts, angle):
"""
Esta función primero genera una recta, con un ángulo definido por angle, en cada
punto contenido dentro de line_pts. Luego, para cada recta generada, encuentra la intersección
con cada mitad del polígono definido en polygon_pts. R... | 41add86abc9ad47be8cec00a0029d83f067b864b | 3,614,963 |
def factorial(x: i32) -> i32:
"""
Computes the factorial of `x`.
"""
if x < 0:
return 0
result: i32
result = 1
i: i32
for i in range(1, x+1):
result *= i
return result | 31daab3c0e27756346154c6e1d1576363b81e83d | 3,614,964 |
import argparse
def parseargs(): # pragma: no cover
"""Sets up command-line arguments and parser
Parameters:
Returns: parser
Raises:
"""
parser = argparse.ArgumentParser(description='Metrics BeeGFS-Sqlite to elastic')
parser.add_argument("-f", "--cfgfile", help='Specify the config file (.... | bc4a82545fc493c0b386a63b25d393ab0dfdc3cb | 3,614,965 |
from datetime import datetime
def convert_time(time_str):
"""Convert iso string to date time object
:param time_str: String time to convert
"""
try:
dt = datetime.strptime(time_str, "%Y-%m-%dT%H:%Mz")
return dt
except Exception:
return time_str | 4ba3d5b8af4305cc44afb60d02eeb1b1d041fab9 | 3,614,966 |
def get_common_words():
"""Finds all common words in Redis"""
redis_connection = get_redis_connection()
words = redis_connection.keys(get_word_key("*"))
return set([word[2:].decode('utf-8') for word in words]) | 888b6f8e77954ce6ed6f45d647156da53338faf3 | 3,614,967 |
import numpy
def complex_to_amp_phase(lookup_table):
"""
This constructs the function to convert from complex64 or 128 to AMP8I_PHS8I format data.
Parameters
----------
lookup_table : numpy.ndarray
Returns
-------
callable
"""
_validate_lookup(lookup_table)
def converte... | 92acec01b2a166a17b36a6d32352805ae0a6c7ce | 3,614,968 |
def suck_out_formats(reporters):
"""Builds a dictionary mapping edition keys to their cite_format if any.
The dictionary takes the form of:
{
'T.C. Summary Opinion': '{reporter} {volume}-{page}',
'T.C. Memo.': '{reporter} {volume}-{page}'
...
}
In other ... | a0db907839573ca53f7c96c326afe1eac5491c63 | 3,614,969 |
import time
import logging
def tsne_embeddings(X,
include_svd=True, n_svd_components=50,
tsne_params=dict()):
"""
Computes t-SNE embeddings of the tf-idf vectors. By default it first performs
a dimensionaly reduction using truncated SVD, as recommended in the scikit-learn
documentation. This i... | 186d9f67e6142e51b87fdfca2d2f4a6e05a60b7a | 3,614,970 |
def get_expected_return(
rewards: tf.Tensor,
gamma: float,
standardize: bool = True) -> tf.Tensor:
"""Compute expected returns per timestep."""
n = tf.shape(rewards)[0]
returns = tf.TensorArray(dtype=tf.float32, size=n)
# Start from the end of `rewards` and accumulate reward sums
# int... | a8b5a2dbd67eaaf000dba05340239bc0fca1a563 | 3,614,971 |
def cast_bytes(data, encoding='utf8'):
"""
Cast str, int, float to bytes.
"""
if isinstance(data, str) is True:
return data.encode(encoding)
elif isinstance(data, int) is True:
return str(data).encode(encoding)
elif isinstance(data, float) is True:
return str(data).enco... | 01ac5d7cd4a728e401075334900808a6a579deef | 3,614,972 |
from typing import Dict
from typing import Any
from typing import Sequence
from typing import Tuple
def anchormap(refs: Dict[Any, Any] = {}) -> Sequence[Tuple[Location, Location]]:
"""
Return all lexical references
Performs compilation up to and including the type resolution, but doesn't start executing
... | dbf0f3bbee8c071245b0b3f75a348ea0524f9d69 | 3,614,973 |
def deep_access_list(x, keylist, key_value_eq=None):
"""
>>> deep_access_list({"a":2}, ["a"])
2
>>> deep_access_list({"a":[{"a":2, "b":5}, {"a":1, "b":6}]}, ["a", "a"])
3.0
>>> deep_access_list({"a":[{"a":"cat1", "b":"cat2"}, {"a":"cat3", "b":"cat2"}]}, ["a", "a"], "cat1")
1.0
>>> deep_a... | cdc3491c5b99ec02a40fcf518cd9f4e40e743f8a | 3,614,974 |
def plot_roc_curve(y_true_arr, y_pred_proba_arr, labels_arr, pos_label=None, plot_thres_for_idx=None,
log_wandb=False):
"""Function for plotting ROC curve
Args:
y_true_arr (list/np.array): list of all GT arrays
y_pred_proba_arr (list/np.array): list of all predicted probabili... | 46f4e1b3ab25183f72d724e6c13f8e2320125158 | 3,614,975 |
def _pillow2array(img, flag='color', channel_order='bgr'):
"""Convert a pillow image to numpy array.
Args:
img (:obj:`PIL.Image.Image`): The image loaded using PIL
flag (str): Flags specifying the color type of a loaded image,
candidates are 'color', 'grayscale' and 'unchanged'.
... | 70800bd3174a6ab33389ca51c4204d21d19e3d16 | 3,614,976 |
import torch
from typing import Optional
from typing import Tuple
def get_eval_fn(model: torch.nn.Module):
"""Get the evaluation function for server side.
Parameters
----------
model
The model we want to evaluate.
Returns
-------
evaluate
The evaluation function
"""
... | 918b4e62422f0c645ffa68da346aae1c5e588413 | 3,614,977 |
def build_rnn_dataset(dataframes, tokenizer=lambda s: s.split()):
"""
Given an SST reader, return the dataset as (X, y) training pairs.
Parameters
----------
dataframes : pd.DataFrame or list of pd.DataFrame
The dataset or datasets to process, as read in by
`sentiment_reader`.
... | 71feeeed3369a8e6ddc3d2d62b56161da8da336a | 3,614,978 |
def api_user_current_bar():
"""Request endpoint to change a user's current bar
:param int user_id: ID of the user to modity
:param int bar_id: ID of the bar to set as user's current view default
If 0, will use the configured default bar
:param string next: Should be the URL of the current page s... | 5353640a895ab8260d8919609a1ba661cf391d48 | 3,614,979 |
def _default_line_time_factory(self: "Kymo"):
"""Line time in seconds"""
if self.timestamps.shape[1] > 1:
ns_to_sec = 1e-9
return (self.timestamps[0, 1] - self.timestamps[0, 0]) * ns_to_sec
else:
raise RuntimeError(
"This kymograph consists of only a single line. It is no... | 075242606bacac1b9963d62f5e3794a5b276412e | 3,614,980 |
def B(i,j,k):
"""
Tensor B used in constructing ROMs.
Parameters
----------
i : int
j : int
k : int
Indices in the tensor.
Returns
-------
int
Tensor output.
"""
if i == j + k:
return -1
elif j == i + k or k == i + j:
return 1
el... | b4969759fd2f07bd2bd2baed48a2adfd8669987a | 3,614,981 |
def magic(data):
"""Mime-Type anhand eines Datenstroms raten."""
if data[0:2] == '\xff\xd8': # JPEG Start of Image
return 'image/jpeg', '.jpg'
elif data[0:4] == '\x89PNG':
return 'image/png', '.png'
elif data[0:4] == '%PDF':
return 'application/pdf', '.pdf'
else:
LOG... | 16043cee7c05f81973702e624344447c23fe8677 | 3,614,982 |
import os
import json
def read_metadata(input_dir):
"""Read metadata JSON file in +input_dir+ into a dictionary"""
metadata_path = os.path.join(input_dir, METADATA_FILENAME)
with open(metadata_path) as src:
return json.load(src) | fa6a6a4c6c5293ac0438ca596c7bf9784a3e5775 | 3,614,983 |
def logout():
"""登出"""
session.pop("user_id", None)
session.pop("nick_name", None)
session.pop("mobile", None)
# session.pop('user_id', None)
# session.pop('nick_name', None)
# session.pop('mobile', None)
session.pop('is_admin', None)
return jsonify(errno=RET.OK, errmsg="退出登录成功") | 7c0abc3be1c097e63cfb1ae08af13f38dd806cad | 3,614,984 |
def boost_python_pattern_generator(asg, pattern=None, *args, **kwargs):
"""
"""
return boost_python_generator(asg, asg.declarations(pattern=pattern), *args, **kwargs) | 21c6e1f653376a155ea12104b0884e2ac3bdc0c7 | 3,614,985 |
def make_upload_chart(gfunc, yaml_path, json_path, title):
"""Create an upload chart
Args:
gfunc: the group by function
yaml_path: the template path
json_path: the path to write to
title: the title of the chart
Retuns:
the chart JSON
"""
return pipe(
gfunc,
... | db9636700faa099ffe018a9f8b60293c531cca8b | 3,614,986 |
import torch
import time
from re import X
def _yuzu_ism(model, X_0, precomputation, device='cpu', use_layers=use_layers,
ignore_layers=ignore_layers, terminal_layers=terminal_layers, verbose=False):
"""Perform ISM using compressed sensing to reduce the necessary compute.
This function will take a model,... | 5cf32eafc131380609d6f27e4baa9f638a5c3754 | 3,614,987 |
import os
import jsonschema
import json
def check(schema: dict) -> dict:
"""
Validate JADN schema against JSON schema,
Validate JADN schema against JADN meta-schema, then
Perform additional checks on type definitions
"""
# Add empty Fields if not present
schema_types = [TypeDefinition(*t) ... | c545a30f4a59160ba2a1b88559659651023c2a27 | 3,614,988 |
def resmlp_24_224():
"""
ResMLP-24
Paper: ResMLP: Feedforward networks for image classification...
Link: https://arxiv.org/abs/2105.03404
"""
cfg = MLPMixerConfig(
name="resmlp_24_224",
url="[timm]",
patch_size=16,
embed_dim=384,
nb_blocks=24,
mlp_... | d92f9e483ec19a950771e076ba786755ca92469e | 3,614,989 |
import math
def h2abc(h):
"""Returns a description of the cell in terms of the length of the
lattice vectors and the angles between them in radians.
Takes the representation of the system box in terms of an upper triangular
matrix of column vectors, and returns the representation in terms of the
... | aaaf35381bc447398a2339180e39a488530cd313 | 3,614,990 |
def get_joint_distribution(
trials,
mean_prior=lambda: tfd.Uniform(0., 1.),
inverse_concentration_prior=lambda: tfd.HalfNormal(5.)):
"""Returns a joint distribution over parameters and successes."""
param_shape = ps.shape(trials)[:1]
mean = tfd.Sample(mean_prior(), param_shape)
inverse_concentration... | cc1a2eacad8870048d92eb573af13244a3405a8c | 3,614,991 |
import io
def format_data(data, indent):
"""Format a bytestring as a C string literal.
Arguments:
data: Bytestring to write
indent: Indentation for each line, a string
Returns:
A multiline string containing the code, with indentation before every line
including the first. There is... | 260e2b296addeb1113d657b086302197a8e365bb | 3,614,992 |
from re import A
def survey_series_rheader(r):
"""
The series rheader
"""
if r.representation == "html":
db = current.db
s3db = current.s3db
tablename, record = s3_rheader_resource(r)
if not record:
series_id = current.request.vars.series
t... | c4d35cec80f32e575cb505e43113dc656682b9ca | 3,614,993 |
def sample(bn, cond=None):
"""
Sample every variables of a Bayesian Network
:param bn: a Bayesian Network
:param cond: dict, given variables
:return:
"""
g = bn.DAG
cond = cond if cond else dict()
if any(nod not in cond for nod in bn.Exo):
raise ValueError('Exogenous nodes do... | 81606afea08f1e80b73d115ed6a6a2581c13890c | 3,614,994 |
from typing import Any
import json
async def async_get_config_entry_diagnostics(
hass: HomeAssistant, entry: ConfigEntry
) -> dict[str, Any]:
"""Return diagnostics for a config entry."""
# Currently we only support a single device
device = hass.data[DOMAIN][entry.entry_id][VICARE_DEVICE_CONFIG]
da... | cee924ef4bff944a53dfffd7b8aff84b369691bc | 3,614,995 |
import os
def load_image_lists(frame_list_file, prefix="", return_list=False):
"""
Load image paths and labels from a "frame list".
Each line of the frame list contains:
`original_vido_id video_id frame_id path labels`
Args:
frame_list_file (string): path to the frame list.
prefix ... | 82f55d9c13db80f8f07481689640b9eb284e80f3 | 3,614,996 |
from typing import List
def predict_single(classifier: GaussianNB, test_data:List[Text], num: int = 200):
"""
predicts the most probable class value for the given test tokens and model
Parameters
----------
classifier: GaussianNB
model that holds the bag of words model
test_d... | 2f0e136a1bc0c4988219e76e7145c8ba19e29a99 | 3,614,997 |
def psf_to_inhg(psf):
"""Convert lb/ft^2 to inches of mercury."""
return psf * 0.014139030952735 | c1a482c71ad86ae31efece5f1a395fa354db8c3e | 3,614,998 |
def post_request_with_retries(url, json_payload, verify_ssl=True):
"""This function performs a POST request with a total of 5 retries in case of timeouts or connection issues.
.. versionchanged:: 3.2.0
The query URL is now made into an absolute URL as necessary before performing the API request.
..... | b3b37e5819d82cfd1871c614db1b9715ede05fe4 | 3,614,999 |
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