content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def resnet101(rate=1, class_num=10, index=None):
"""
Get ResNet101 neural network.
Args:
class_num (int): Class number.
Returns:
Cell, cell instance of ResNet101 neural network.
Examples:
>>> net = resnet101(1001)
"""
return ResNet(rate,
ResidualB... | dfc706eb4bd8ce205692d1c031b650f434ba605c | 3,616,500 |
import typing
import math
def _smart_ceil(x: typing.Union[int, float], order: int = None) -> int:
"""Smart ceil to the nearest round integer.
The 'nearest' is chosen based on the order of the given number
"""
order = int(order) if order else len(str(math.ceil(x)))
if order <= 0:
raise... | 5a93521630b3241844d958eb07b738a62816b7ad | 3,616,501 |
def get_file_storage_impl(request):
"""
Retrieves correct **IFileStorage** instance from the registry.
:param request: Pyramid Request instance
"""
registry = getattr(request, 'registry', None)
if registry is None:
registry = request
return registry.getUtility(IFileStorage) | 2bd3a98728bea03b0870b36f982f019b473cf9c7 | 3,616,502 |
def norm_observation(mat, axis=-1, eps=EPSILON):
"""
L2 normalization for observation vectors
"""
denorm = np.linalg.norm(mat, axis=axis, keepdims=True)
denorm = np.maximum(denorm, eps)
return mat / denorm | 1a931600f139ff5b66f780f3be3b021d64ae2f3a | 3,616,503 |
def get_commercial_from_lowertext(transcript, video_desp):
"""
Get region with lower case transcript
"""
def is_lower_text(text):
lower = [c for c in text if c.islower()]
alpha = [c for c in text if c.isalpha()]
if len(alpha) == 0:
return False
if 1. * len(lo... | 898b4605a769b62e3c9fbd1b9aa8b446a1cf54c2 | 3,616,504 |
async def circuit_sat_prover(
generators, code, x, gf, pivot_choice=cs.PivotChoice.compressed
):
"""Non-interactive implementation of Protocol 8, prover-side,
including Nullity using compressed pivot (Protocol 5).
"""
logger_cs_mpc.debug(f"Enter circuit_sat_prover. pivot_choice={pivot_choice}")
... | 38f6c19ddc59c1b28620a1d9b1c520a57e79ed79 | 3,616,505 |
def rl_modelrl_breakout_ae_medium():
"""Medium set for testing Breakout with an autoencoder."""
hparams = rl_modelrl_ae_medium()
hparams.game = "wrapped_breakout"
return hparams | bb1a54ebf5a2706fb29c85873e10e0052f4872e0 | 3,616,506 |
def layer_norm(inputs,
center=True,
scale=True,
activation_fn=None,
reuse=None,
variables_collections=None,
outputs_collections=None,
trainable=True,
begin_norm_axis=1,
begin_params_axi... | c53b552d8726d619be04ae27c9d0f9a61cd44518 | 3,616,507 |
def get_dependency_type(dependency):
"""Get dependency type from dependency name"""
if dependency.startswith("."):
return RELATIVE
for internal in INTERNAL_ALLOWED_ORDER:
if dependency.startswith(internal+"/"):
return internal
return EXTERNAL | 80ed3a46c7740b573e849c11503e08a7509f0564 | 3,616,508 |
import random
def generate_paired_images_to_inspect_three_different_ways(dataset_to_use, yhat):
"""
Try pairing images by KLG; by all image features (basically we take the max over feature categories); and by invididual and side. In all cases, the
"high pain" image is on the right, although the way we de... | 4101f0366ec96a2facd963367370d484e19baebc | 3,616,509 |
def reducejson(j):
"""
Not sure if there's a better way to walk the ... interesting result
"""
authors = []
for key in j["data"]["repository"]["commitComments"]["edges"]:
authors.append(key["node"]["author"])
for key in j["data"]["repository"]["issues"]["nodes"]:
auth... | 90e50ff58e830fbe902a42c4256b19d9c6c46ff0 | 3,616,510 |
from typing import Tuple
def vis_mask(img: np.ndarray, mask: np.ndarray, col: Tuple[int, int, int], alpha: float = 0.4):
"""
Visualizes a single binary mask by coloring the region inside a binary mask
as a specific color, and then blending it with an RGB image.
Args:
img: Numpy array, represe... | 1abfd847a2882f99072f2668f62f86070c13e0c3 | 3,616,511 |
async def async_setup(hass, hass_config):
"""Set up the Plaato component."""
return True | b2c620c58aabcf788310e3aaf9cdf836f9be15ba | 3,616,512 |
from typing import Union
from typing import Dict
def _get_upstream_seqs(
ica_data: IcaData,
imodulon: Union[str, int],
seq_dict: Dict,
upstream: int,
downstream: int,
):
"""
Get upstream sequences for a table of operons
Parameters
----------
ica_data: IcaData
IcaData o... | ef7264f427849c51808494b06881393e78771e63 | 3,616,513 |
from sys import path
def get_view():
"""Responds with the form for the example"""
return render_template(
"eg015_envelope_tab_data.html",
title="Envelope information",
envelope_ok="envelope_id" in session,
source_file=path.basename(path.dirname(__file__)) + "/controller.py",
... | e98246f15825c037d30d485d03ccd8ee3caa55dc | 3,616,514 |
def json_value(obj):
"""Format obj in the JSON style for a value"""
if type(obj) is bool:
if obj:
return '*true*'
return '*false*'
if type(obj) is str:
return '"' + obj + '"'
if obj is None:
return '*null*'
assert False | fc34c619d550af029536437c0eec7163e3ce673c | 3,616,515 |
def exp(node) -> Node:
"""Exponential of the node, using np.exp(x)"""
return Node(node, None, np.exp(node.value), 'exp' ) | e24d6fffe24fde099ba1f1588aff20a4d848b975 | 3,616,516 |
def bias_variable(shape):
"""Generates a bias variable of a given shape."""
initial = tf.constant(0.1, shape=shape)
return tf.Variable(initial, name='bias') | cd71c9e0e36ea144cc30498fba03189b5c2d03b4 | 3,616,517 |
from . import kerneldll
import os
def precompile_dlls(path, dtype="double"):
# type: (str, str) -> List[str]
"""
Precompile the dlls for all builtin models, returning a list of dll paths.
*path* is the directory in which to save the dlls. It will be created if
it does not already exist.
Thi... | 566088c8f8dbaca077b54235d03fb8393d13245d | 3,616,518 |
import subprocess
def main() -> int:
"""Main"""
# TODO(pwbug/456): Refactor the code so that each test bundle generation
# is done in a separate function or script.
# pylint: disable=too-many-locals
args = parse_args()
test_bundle = Bundle()
dev_signed_root = test_bundle.generate_dev_sig... | 76039cb9ef6978ffc40ab6aa6944c1ddee1432c7 | 3,616,519 |
def padmat(input_mat,left_pad=0,right_pad=0,up_pad=0,down_pad=0):
"""
Helper function to pad zeros to image matrices to edges don't get cut off.
"""
new_mat = np.zeros((input_mat.shape[0]+up_pad+down_pad,input_mat.shape[1]+left_pad+right_pad))
new_mat[up_pad:new_mat.shape[0]-down_pad,left_pad:new_m... | 3e7c23bdc38c8b2a4e2e83229c8d7a9b70f459a6 | 3,616,520 |
def calc_E_M_C_hs_d_t():
"""冷房設備機器のその他の燃料による一次エネルギー消費量（MJ/h）(22d, 23d)を計算する
Args:
Returns:
ndarray: 冷房設備機器のその他の燃料による一次エネルギー消費量（MJ/h）
"""
return calc_E_M_C_hs_MR_d_t() + calc_E_M_C_hs_OR_d_t() | 0766106006545b36b97ca4cbbf980b27779e3d01 | 3,616,521 |
def load_adjacency_list(file: str, bipartite: bool = False, comment: str = '%#',
delimiter: str = None, ) -> Bunch:
"""Parse Tabulation-Separated, Comma-Separated or Space-Separated (or other) Values datasets in the form of
adjacency lists.
Parameters
----------
file : str
... | 256c3ec7515c54ac93f5d81df3b9d413752fadfa | 3,616,522 |
import numpy
def _check_input_args_many_predictors(
predictor_matrix, predictor_names, cmap_object_by_predictor,
cnorm_object_by_predictor, min_colour_value_by_predictor,
max_colour_value_by_predictor, plot_wind_barbs):
"""Error-checks input arguments for `plot_many_predictors*`.
:par... | 303565534f8693cbf27bf99d63017aea9343f5cc | 3,616,523 |
def sim_real_change(request):
""" Return a dummy YATSM model container with a real change
"Real change" dataset is simply a timeseries drawn from samples of two
normal distributions with greatly different mean values.
"""
np.random.seed(123456789)
dates = np.arange(dt.strptime('2000-01-01', '%Y... | a4f42d1235569da39375909f8db01cf7816ca17f | 3,616,524 |
def plugin_reconfigure(handle, new_config):
""" Reconfigures the plugin
it should be called when the configuration of the plugin is changed during the operation of the South service;
The new configuration category should be passed.
Args:
handle: handle returned by the plugin initialisation cal... | 9626575a4ab1c82d6c6eccae56fa0158ab8da008 | 3,616,525 |
from operator import concat
def homogenise_dates(d: DataFrame):
"""
Parameters
----------
d
Returns
-------
"""
d.date = to_datetime(d.date, format="%Y-%m-%d")
col_names = d.columns
date = date_range(
start=to_datetime(d.date).min(),
end=to_datetime(d.date)... | 4b556291b4322121d64234df5ee17a8b7d14e844 | 3,616,526 |
def compute_x_in_set(x, s):
"""Check if elements in tensor x are in set s.
Args:
x: batch_size, num_candidate
s: batch_size, k (padded with -1)
Returns:
boolean tensor with shape of x
"""
s = tf.expand_dims(s, axis=2)
# batch_size, k, 1
k = tf.shape(s)[1]
x = tf.tile(tf.expand_dims(x, axis... | c20b29d4e1ec63e0bb12f582401a0b044025542a | 3,616,527 |
def checkunique (uniquerules, rule) :
"""check if rule already exists
Parameters
uniquerules : list of unique rules
rule : rule to check
Returns
True or False
"""
for r in uniquerules :
if samerule (r, rule) :
return True
return False | 0e803c007747dc997c5b9cda42997b375b180e43 | 3,616,528 |
def global_to_body(q, vec):
"""
Convert a vector from global to body coordinates.
Parameters:
-----------
q: quaternion
The rotation quaternion
vec: ndarray
The vector in global coordinates
Returns:
vec: ndarray
The vector in body coordinates
"""
# quate... | 1aa3aedba92fdb513856477b8c9b7de6a7812a9d | 3,616,529 |
import re
def get_hostmask_regex(mask):
"""Get a compiled regex pattern for an IRC hostmask
:param str mask: the hostmask that the pattern should match
:return: a compiled regex pattern matching the given ``mask``
:rtype: :ref:`re.Pattern <python:re-objects>`
"""
mask = re.escape(mask)
ma... | 6e46d907d51e32139168d6f6405ca45ca38bbb98 | 3,616,530 |
def create_map(template_id, report_id, created_by):
"""Submits a request to CARROT's template_report create mapping"""
return request_handler.create_map(
"templates",
template_id,
"reports",
report_id,
[("created_by", created_by)],
) | 83335f2dc06dcfd7661e51df30e79b8ca9e3e231 | 3,616,531 |
from typing import Any
import yaml
from typing import List
def read_yaml(file: Any) -> dict:
"""Read yaml file. Return dict."""
if isinstance(file, str) and any(file.endswith(x) for x in ('.yml', '.yaml')):
with open(file, "r", encoding='utf-8') as fp:
return yaml.load(fp, Loader=yaml.Full... | d696372cb5fb0b494d257b296dd6ac7946e296ff | 3,616,532 |
def pass_alignment_qc(alignment, barcodes):
"""
Check high quality mapping, QC-passing barcode and UMI of alignment.
alignment :
aligned bam segment
barcodes : list
List of cellular barcode strings
Returns
-------
pass_qc : boolean
true if a high quality, QC passing ... | 2e75a6d66c1bbf4afed9f4fa1a3f9d21fcc6a853 | 3,616,533 |
def _netid_admin_url(netid):
"""
Return UWNetId resource for provided netid supported
resources
"""
return "{0}/{1}/admin.json".format(url_base(), netid) | ab62b99efc92c20eda62e6c2fffc0f761cebd15c | 3,616,534 |
def retrieve(customer, sub_id):
"""
Retrieve a subscription object from Stripe's API
Args:
customer: a legacy argument, we check that the given
subscription belongs to the given customer
sub_id: the Stripe ID of the subscription you are fetching
Returns:
the data fo... | ee348999090a14b3a7adf9b97a83ecbcd92605eb | 3,616,535 |
import os
def read_file(fname):
""" Read a file and return the raw data. Create a new file if necessary. """
if not os.path.isfile(fname):
with open(fname, mode='w', encoding='utf-8') as f:
#TODO: Um. Something more professional perhaps
print('NEWFILE!!!!')
f.write(... | cce26ca3f0c6ddd26461a7b52d6f3637a9e5eeb8 | 3,616,536 |
from typing import List
def get_total_innocent_reds(executions: List[RevisionResults]) -> int:
"""
Get number of innocent red commits from a given list of execution results.
:param executions: list of execution results
:return: number of innocent red commits
"""
count = 0
previous_fails =... | 7fce0016664485154a03d5ef6996957c7dad472e | 3,616,537 |
def read_ffindex(file):
"""Read a ffindex and return a list of all the lines in the file .
Args:
file (string): path to the ffindex
Returns:
list of string: The file read line by line
"""
fh = open(file, "r")
index = []
for line in fh:
index.append(line.rstrip(... | fae6494ddbda63abae1161f9fd22c8a94f506407 | 3,616,538 |
def load_ppi(fname='bio-decagon-ppi.csv'):
"""
Returns networkx graph of the PPI network and a dictionary that maps each gene ID to a number
:param fname:
:return:
"""
fin = open(fname)
print('Reading: %s' % fname)
fin.readline()
edges = []
for line in fin:
gene_id1, gene... | b482c86f1409caeb059fedee167b899529c094be | 3,616,539 |
def get_field_from_args_or_session(config, args, field_name):
"""
We try to get field_name from diffent sources:
The order of priorioty is following:
read_default_contract_address - command line argument (--<field_name>)
- current session configuration (default_<filed_name>)
"""
rez = getattr... | 8979a90814bcab9c72f54835a31d69971f8b1437 | 3,616,540 |
def scrape_all_songs():
""" Gets all lyrics from all available songs on the wiki. """
print('Scraping all songs from {}'.format(URL))
soup = scrapekit.handle_url(URL)
song_elements = []
tables = soup.findAll('table')
for t in tables:
field_index = scrapekit.get_col_index(t, field_name=... | be061ee05ee3873ce87f8c846213e92560162e1f | 3,616,541 |
import networkx
def load(filepath):
"""
:param filepath:
A str or :class:`pathlib.Path` object gives a path of network graph
data ({'nodes': ..., 'links': ...}) in JSON or YAML formats
:param ac_args: keyword arguments given to anyconfig.load
:return: An instance of networkx.Graph
... | bbab216df470d805f0b8b8f78cd856e167082ebb | 3,616,542 |
import hashlib
import os
def calculate_patch_digest(target, hash=hashlib.md5):
"""Calculate the digest of the entire project based on the files listed
in the esky_filelist. This will ensure that patches don't break if any
superfluous files have been added to the application folder"""
filelist = load_f... | b9437f51dc4e2e782521e6aeadf3dbcb2a3acd77 | 3,616,543 |
def pdf_from_template(html_template, data):
"""
!Requirement: make sure that wkhtmltopdf is installed in your system
For more configuration info: https://pypi.org/project/pdfkit/
Generate a pdf file from html template
:param html_template str: html template with jinja template strings
:param d... | 71dc765c90b43a79b6d9ce5a1b76393b47da2bf7 | 3,616,544 |
import logging
def get_db():
"""Opens a new database connection if there is none yet for the
current application context.
"""
logging.info("g %s, %s", g, hasattr(g, 'sqlite_db'))
if not hasattr(g, 'sqlite_db'):
g.sqlite_db = connect_db()
return g.sqlite_db | 2f3867693b15adab25cc9aeafbf34e05b02eacf7 | 3,616,545 |
import functools
def log_header(header=None):
# pylint: disable=R0912
"""Flask decorator to log headers or a specific header
:param header:
This can be a string as to which header to log
"""
def decorator(func):
"""Function decorator to log header(s)"""
def wrapped_functio... | ddf00ee6cdb809ee7fb7c2631f802984a4828d1e | 3,616,546 |
def show_abs_oovs(abstract, vocab, article_oovs):
"""Returns the abstract string, highlighting the OOVs.
"""
unk_id = vocab._word2id(UNKNOWN_TOKEN)
words = abstract.split()
vwords = []
for w in words:
if vocab._word2id(w) == unk_id:
if article_oovs is None:
vw... | 15c234f422f08e6ef5fd129bbc170923bb9abf02 | 3,616,547 |
import logging
import os
import glob
import re
import shutil
def compute_rq_name(rq_type, oslevel):
"""
Compute rq_name.
if oslevel is a complete SP (12 digits) then return RqName = oslevel
if oslevel is an incomplete SP (8 digits) or equal Latest then execute
a metadata suma request t... | daeeba2e5b491f202b62fc096ff0558184549728 | 3,616,548 |
import urllib
import json
def score_paper(arxiv_id):
"""
Sum up the 'influentialCitationCount' (Semantic Scholar) from each author
"""
if arxiv_id in paper_scores:
return paper_scores[arxiv_id]
# request data
base_url = 'https://api.semanticscholar.org/v1/paper/arXiv:'
try:
... | 91fef478bf286cac8254d932bb4b1db99e207bc6 | 3,616,549 |
import importlib
def resolve(module_name, obj_name):
"""
Resolve a named object in a module.
"""
return getattr(importlib.import_module(module_name), obj_name) | 87ccef3456d28615b82a89a8e4ce405403eaade9 | 3,616,550 |
def mock_read_narrative(style):
"""
Mocks the NarrativeIO.read_narrative() function.
Style should be one of "good", "bad", or "private".
A "good" narrative will just return the valid read_narrative()
results by loading and returning the given file. (will raise a
ValueError if file is None).
... | 5be8930591c3612b24784ba562d60a7731f7a43f | 3,616,551 |
def normalize_query_parameters(query_string):
"""
normalize_query_parameters(query_string) -> dict
Converts a query string into a dictionary mapping parameter names to a
list of the sorted values. This ensurses that the query string follows
% encoding rules according to RFC 3986 and checks for dup... | ea45fe96d0b22cde8677354769b764687a53f2bb | 3,616,552 |
def _match(token: bytes, request: HttpRequest) -> bool:
"""
Calculate signature and return True if it matches header.
Args:
token: string, the webhook_token.
request: an HttpRequest object from which the body content and
X-Signature header will be extracted and matched.
Ret... | ee57fe8230290c91b3a0caa526078feba8c55ed9 | 3,616,553 |
def read_in(fn):
"""Read in data to header and data"""
with open(fn,'r') as f:
data=[]
start_right=0
for line in f:
words = line.strip().split()
words = [word.strip() for word in words]
if words[0] == "#" or words[0]=='ID':
start_right ... | a885b3031ff37ba6361cd8be342b585cb3d32ad2 | 3,616,554 |
import argparse
from typing import TextIO
from typing import List
from pathlib import Path
def arg_filtered_tests(pav_cfg, args: argparse.Namespace,
verbose: TextIO = None) -> List[Path]:
"""Search for test runs that match based on the argument values in args,
and return a list of match... | b1af83c5c1a04e31aec46fbfcbe87d06b97a9ed1 | 3,616,555 |
def get_users(token, include_locale=False, presence=False):
"""
Get user list
"""
params = {
"token": token,
"include_locale": include_locale,
"presence": presence
}
r = get("https://slack.com/api/users.list", params=params)
if r.ok:
rparsed = r.json()
... | aff2dcdb83a3a624e960ede3b36d73737d8c0982 | 3,616,556 |
def convertScene(convertContext, data):
"""
Converts a Scene. The data is expected to contain the following elements:
- sharedItems: an optional array of shared item lists. Each element of the array is itself an
array with the following members:
- type: the name of the item list type.
- name: the name of th... | fe840e525a84e88ae30ee26008849076f60c953c | 3,616,557 |
def valid_rfc5737(network: str) -> bool:
"""
Verify an IP Address is in RFC5737
"""
answer = False
if IPNetwork(network) in IPNetwork('192.0.2.0/24'):
answer = True
elif IPNetwork(network) in IPNetwork('198.51.100.0/24'):
answer = True
elif IPNetwork(network) in IPNetwork('2... | a2b46f16cbf54c822a5ab193f671976ecdcc7d6c | 3,616,558 |
def create_noisy_signal(signal_fp, snr, noise_fp=None, offset=None):
"""
Create a noisy signal of a specified SNR.
Parameters
----------
signal_fp : string
File path to clean input.
snr : float
SNR in dB.
noise_fp : string
File path to noise. Default is to use randoml... | d7176fc1a2ffb40d79aa71e921d4e9d833e843f0 | 3,616,559 |
def number_size (N):
"""size(N:long) : int
Returns the size of the number N in bits.
"""
bits, power = 0,1L
while N >= power:
bits += 1
power = power << 1
return bits | a8bbb68e836bb5a6b93cc6296ce8edc20ff7e6cc | 3,616,560 |
import time
import hashlib
def default_login():
"""View with login form."""
if len(request.access_route) > 1:
ip = request.access_route[-1]
else:
ip = request.access_route[0]
login_attempt = LoginAttempt()
previous_attempts = login_attempt.get_failed_attempts_count(
ip,
... | a74743cec37ef6a93f00ed3406c43151b95d4cf1 | 3,616,561 |
def mnist_1_5():
"""
train: (12163, 784), test: (2027, 784)
"""
eps_dataset = 0.3
classes = [1, 5] # 2 is 1, 6 is -1 in the binary classification scheme
(X_train, y_train), (X_test, y_test) = mnist_keras.load_data()
X_train, X_test = (
X_train.astype(np.float64) / 255.0,
X_... | 91ed5897e29665b08891a838b6213ed83247763a | 3,616,562 |
import logging
def standardize_team_name(team: str) -> str:
"""Standardizes team name across sites
Args:
team (str): the code or team name
Returns:
str: team name, Atlanta Falcons, Baltimore Ravens, etc.
"""
matches = _standardize(team, TEAM_NAMES)
if not matches:
lo... | 718f93d08f70575b259d5546760fa7486156a7e6 | 3,616,563 |
def get_num_shorts(string_list):
""" Returns the number of occurences of 'Short' in an input string list.
Args:
string_list(list of string objects)
Returns:
numShorts(int): Number of occurences of 'Short'
"""
numShorts = 0
for marker in string_list:
if (marker == '... | b8e9da454590a8b29965696be3265053cfc78729 | 3,616,564 |
def get_saved_artists(auths=None, offset=0, limit=20):
"""
Extracts and returns a list containing the IDs for all artists followed by any of the accounts defined in 'sources'.
:param auths: dict() being the 'sources'-tree of the auth object as returned by authorize()
:param offset: int() defining at whi... | 38611e27821a466421dc3d21d59eb53443136626 | 3,616,565 |
import pandas
def _try_to_date(x):
"""Wrapper around :func:`pandas.to_datetime` that returns
the input unaltered if it's not a date.
Don't attempt converting numeric or boolean arrays.
"""
if x.dtype.kind != 'U': # unicode string
return x
try:
# In case of ambiguity, prefer Eu... | 01d296b0578933954a3b6593fd52fc15620cc1cd | 3,616,566 |
def at_2_Pa(value):
"""
converts pressure in at (technical atmosphere) to Pa
:param value: pressure value in at (technical atmosphere)
:return: pressure value in Pa
"""
return value * const_at | 30b514cf97205ec7bb9dd5f6c8bd2d7cacdfbc6b | 3,616,567 |
def evaluate(results, annotations, checkpoint, iou_threshold=0.5, save_path=None):
""" Evaluate a given dataset using a given retinanet.
# Arguments
results : detection results
annotations : original data
iou_threshold : The threshold used to consider when a detection is po... | c0d2b5779d243600abed56c3690baf1d84b3c1c2 | 3,616,568 |
async def get(request: Request, organization_id: UUID) -> services.organization.Organization:
"""Organization get """
return await services.organization.get(
organization_id=typeof.OrganizationID(organization_id),
member=request.app.state.member,
) | 9e8a862c1c3c9a59d49265c5746bfc8f92fb8a3b | 3,616,569 |
def w_quest_class(sentence):
"""
process what question about classification
Input=sentence Output=class Sentence
"""
analysis = y_n_ques(W_QUESTION, 'classification' + '+' + sentence[4], sentence[5:])
if analysis.sn:
#The d... | 98a3ef03bbd32f81262d663401d84e637ca7d8eb | 3,616,570 |
def exp_so3(v):
"""
Grassia, F. S. (1998).
Practical parameterization of rotations using the exponential map
"""
angle = np.linalg.norm(v)
if angle < np.power(np.finfo(float).eps, 0.25):
na = 0.5 + angle * angle * 1.0 / 48.0
else:
na = np.sin(angle * 0.5) / angle
ct = n... | aee158e66024d9445757a066d12350794a33f284 | 3,616,571 |
from typing import Callable
from typing import Iterable
def choose(chooser: Callable[[TSource], Option[TResult]]) -> Projection[TSource, TResult]:
"""Choose items from the sequence.
Applies the given function to each element of the list. Returns
the list comprised of the results x for each element where ... | aa8f7008c3590c0a25100cb851e59f5efe6a3440 | 3,616,572 |
import jinja2
def create_j2env(template_dir) -> jinja2.Environment:
"""
Create a Jinja2 enviornment instance used when template building the containerlab
topology file.
Parameters
----------
template_dir: str
The file path where the Jinja2 template file is located.
Returns
--... | 1d6559eae0346c0b9fd6171c18da5f2d94e1db86 | 3,616,573 |
import ast
def _unpack_lists(input_list):
"""Unpacks a list of strings containing sublists of strings
such as provided by the data table in the 2d U-net training pipeline card
Args:
input_list (list): list of strings which contain sublists
Returns:
list: list of hidden items from the... | e80cd60e46b0ec5b5dd9b4a88ebe7193c0645f48 | 3,616,574 |
from astropy.table import vstack
from .API_PS1_DR2 import ps1cone
import math
def cross_match_PS1_DR2(wcs_data, SE_catalog, image_bounds,
band='g', radius=None, clean_catalog=True,
pixel_scale=2.5, mag_thre=15, sep=2.5*u.arcsec,
verbose=True):
... | 8b595d4e583785ea9e04483cb4fe0be9ba14405e | 3,616,575 |
def get_raw_column(table_name, column_name):
"""
Get a wrapped, registered column.
This function cannot return columns that are part of wrapped
DataFrames, it's only for columns registered directly through Orca.
Parameters
----------
table_name : str
column_name : str
Returns
... | cab069c220836a0de4a8cdbb3189b01d94c0b5f7 | 3,616,576 |
def conv_shape_tuple(lhs_shape, rhs_shape, strides, pads, batch_group_count=1):
"""Compute the shape tuple of a conv given input shapes in canonical order."""
if isinstance(pads, str):
pads = lax.padtype_to_pads(lhs_shape[2:], rhs_shape[2:], strides, pads)
if len(pads) != len(lhs_shape) - 2:
msg = "Wrong ... | a159092252a6159c3156107254b6134b0a557bb0 | 3,616,577 |
def shapes_chunks_maxmem(draw, ndim=3, itemsize=4, max_len=10_000):
"""Generate the data we need to test rechunking_plan."""
shape = []
source_chunks = []
target_chunks = []
for n in range(ndim):
sh = draw(st.integers(min_value=1, max_value=max_len))
sc = draw(st.integers(min_value=1... | 3df6a7a0bc74e74ececc3349c4a947996e6bf5f9 | 3,616,578 |
import os
import time
def db_insert_filename_mutagen(conn, cursor, filename, size, metadata, filehash):
# print ("Scanning file {}".format(filename))
""" insert data into database
:param conn: connection
:param filename: filename to insert
:param size of file
:param metadata object
:param ... | 6aa4280118e65cffb549b211a88e70c680380fc7 | 3,616,579 |
def vhat(train_position):
"""
Define the maximum speed of the train in (m/s) as a function of the
position.
"""
# Take desired profile speed and add some buffer only if lower than 100
speed_profile = np.minimum(vbar(train_position) + 30 / 3.6,
np.ones(train_positio... | a93f20b84d9f880385dfb569bfbbef76dc9de68c | 3,616,580 |
def get(a_map, name):
"""Return a _DescriptorInspector around the attribute, or None."""
try:
value = a_map[name]
except KeyError:
return None
else:
return DescriptorInspector(value) | ac346c1a964f2884c5d7a4c62a628240696b2a44 | 3,616,581 |
def jaccard(gt_bbox, bbox_list):
"""Compute the jaccard overlap of two sets of boxes. The jaccard overlap
is simply the intersection over union of two boxes. Here we operate on
ground truth boxes and default boxes.
E.g.:
A ∩ B / A U B = A ∩ B / (area(A) + area(B) - A ∩ B)
Args:
box... | 1b1f8bf381fc521fcf60ff0bf636a0058103c48e | 3,616,582 |
import torch
def cc_sample(shape, sigma, alpha, mu=None, repeats=1, **backend):
"""Sample random fields with a constant correlation.
This function computes the square root of the covariance matrix by SVD.
Parameters
----------
shape : sequence[int]
Shape of the image / volume.å
sigma... | 2fd23cf054b96cdf590f919f7afda9ea9bbd71b7 | 3,616,583 |
def get_KKP_mech_from_eqn_file_as_df(folder=None, Mechanism='Tropchem',
filename=None, verbose=True,
debug=False):
"""
Get KPP mechanism as a pandas DataFrame
"""
# Set the filename if not provided
if isinstance(filename, type... | e932fede2f784b7c40a9249d0cf558894a7d0a9f | 3,616,584 |
def _ActivationParams(op, inexpr, etab):
"""Get activation parameters"""
whichActivation = op.WhichOneof('NonlinearityType')
par = getattr(op, whichActivation)
if whichActivation == 'linear':
alpha = _expr.const(par.alpha, dtype='float32')
beta = _expr.const(par.beta, dtype='float32')
... | afd3ec77f4940b6c727201cb9bcf324bb54fa53a | 3,616,585 |
import argparse
def parse_arguments(argv):
"""Parse command line arguments
Args:
argv (list): list of command line arguments including program name
Returns:
The parsed arguments as returned by argparse.ArgumentParser
"""
parser = argparse.ArgumentParser(description='Preprocessing')
parser.add... | 9a94c3b8ee7a0cdf98581fc7bf19fd0503dd8de8 | 3,616,586 |
import torch
def ln2float(module):
"""Batchnorm to Float."""
if isinstance(module, torch.nn.LayerNorm):
print('Warning: Casting LayerNorm to fp32 ...')
module.float()
for child in module.children():
ln2float(child)
return module | 42bb1769a42a722f5332c0d4f1e635cdca2d6451 | 3,616,587 |
def error_view(template_dir=None):
"""
Create the Error view
Must be instantiated
import error_view
ErrorView = error_view()
:param template_dir: The directory containing the view pages
:return:
"""
if not template_dir:
template_dir = "Pylot/Error"
template_page = "%s/... | ec3fb650283c4879d981f1359328012e57ec9db3 | 3,616,588 |
from typing import Union
import logging
def supply_backend(optional: Union[callable, bool]=False, index_exists: bool=True):
"""
Decorator to pass the initialized backend to the decorated callable. \
Used by command line entries. If the backend cannot be created, return 1.
:param optional: Either a de... | 950d18ae4765acc71dd7272d2f444e4105f65ff3 | 3,616,589 |
def task_detail(request, structure_slug, ticket_id, task_id,
structure, can_manage, ticket, office_employee=None):
"""
View task details
:type structure_slug: String
:type ticket_id: String
:type task_id: String
:type structure: OrganizationalStructure (from @has_admin_privilege... | dbb6b16e708ea455075817738d24df27770f725b | 3,616,590 |
import ctypes
def isOutputFileClosed(path):
"""Returns true if target output file is closed, else false.
Shows popup if file already in use.
Clears contents, so only usable for mode 'w'"""
try:
f = open(path, "w")
f.close()
return True
except PermissionError:
... | 32d7b50b40d9fb50e0466740efa3cb7baeeed6e4 | 3,616,591 |
from datetime import datetime
def convert_time(timestring, date='1990-01-01'):
"""Convert time string to have leading zeros.
:param timestring: Byte array in '%H:%M:%S' without leading zeros.
:param date: Date of the timestamp (defaults to 1990-01-01)
:return: time object
"""
return datetime... | 118e205396118e7e64c7b368dc4347d0a6daab63 | 3,616,592 |
def compute_t_shift(metadata, i, t_p_interp, p_interp, p_file, date_ref,
time_ref, dpdt_thresh=10, plot_pressure=True):
"""
***OBSOLETE***: I determined that a multiplicative factor more accurately
adjusts the Belsorp time than a time shift. See compute_t_multiplier.
Computes number... | 2a7d5cfd9ba2026b4179cb4629ca5d2f7b8409d9 | 3,616,593 |
def quickHBar(ax, xticks, values, colors="b", lw=None):
"""
This function draws an horizontal bar graph
:Arguments:
:type ax: matplotlib Axis2D
:param ax: Axis on which bar graph will be drawn
:type xticks: list
:param xticks: Listo of labels for the bars
:type val... | 15bdcb7b7c78682419af6d53ef103527f434c553 | 3,616,594 |
from datetime import datetime
def exportFromNotebook(notebookPath, outFNames, outFPath=None, encoding='utf-8') :
"""
Routine to auto-generate a python script from Jupyter notebook cells.
Exports code cells that start with
# export name1 name2 ...
where one of the names is in the supplied list ... | 332597f76c692080ffc561775ee2b837dbc1720b | 3,616,595 |
from re import T
def enable_train_mode(mod: T) -> T:
"""Return a module in training mode."""
return mod.train() | f72448d7b4bc908b8f6fe58b52993d546698e8fd | 3,616,596 |
def train_step(real_image, label, noise):
"""
:param real_image:
:param fake_image:
:return:
"""
with tf.GradientTape() as gen_tape, tf.GradientTape() as disc_tape:
generated_image = generator(noise, label, training=True)
real_output = discriminator(real_image, label, training=... | 6323a5fa0e4982b004151844b84d41b3d557348b | 3,616,597 |
import torch
def compute_accuracy(logits, labels, mask):
"""Compute the accuracy"""
logits = logits[mask]
labels = labels[mask]
_, indices = torch.max(logits, dim=1)
correct = torch.sum(indices == labels)
return correct.item() * 1.0 / len(labels) | a7ee234837024598fc95fa9c54c55802ea411577 | 3,616,598 |
import random
import string
import traceback
def run(ceph_cluster, **kw):
"""
pre-requisites:
1. Create a volume with a name
2. Create a subvolume with a name
3. Create a subvolume group with a name
Test operation:
1. Try to create a volume with the same name
2. Try to create a subvol... | e11dad62bac4033954848050c5f8a1b9c3588e3e | 3,616,599 |
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