content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def extract_command(text):
"""
Extracts the command from `text` (minus the '/') if `text` is a command (see is_command).
If `text` is not a command, this function returns None.
Examples:
extract_command('/help'): 'help'
extract_command('/help@BotName'): 'help'
extract_command('/search black... | f73e3a01b22ef8bf612c8a06fd2d3636657cba16 | 62,400 |
def get_files_array(path):
"""
get files as array
"""
files = []
for file in files_collect(path):
files.append(file)
return files | 48a8b5b8f89fcf51b8e751f48fa39b8111c7afbb | 62,401 |
def complete_tree_pair(aidx, bidx, adoc, bdoc, ops, adoc_range=None, bdoc_range=None):
"""this function extend the subphrases to their matching subtrees.
Returns:
[Span, Span]: the extended aspan, and bspan
"""
if is_punct_phrase(aidx, adoc) and is_punct_phrase(bidx, bdoc):
return a... | b97cd5623f13c0891b64b33c1858186cdf6a71cf | 62,402 |
import re
def decompose_molecule(molecule, n=1):
"""
Returns the chemical constituents of the molecule, and their number.
Parameters
----------
molecule : str
A molecule in standard chemical notation,
e.g. 'CO2', 'HCO3' or 'B(OH)4'.
Returns
-------
All elements i... | a332f40d5d20c349abe97569ce0129c7e9d03543 | 62,403 |
def sign_metadata(role: str, metadata_proto):
"""Signs a serialized metadata for a given role"""
signed = getattr(tuf_pb2, f'Signed{role.capitalize()}Metadata')()
serialized = metadata_proto.SerializeToString()
setattr(signed, f'serialized_{role}_metadata', serialized)
# TODO(pwbug:456): Generate si... | 9ad59759e1e3eb76fabd9c20536a0cae5dcc424b | 62,404 |
from typing import Union
from typing import Optional
def set_chat_description(token: str,
chat_id: Union[int, str],
description: Optional[str] = None
) -> bool:
"""Use this method to change the description of a group,
a supergroup or a... | b47a1fb2374b73cde21d9a8eece47f2611fd7bc8 | 62,405 |
def converte_int_char(inteiro):
"""Converte um inteiro para um caractere segundo a tabela ASCII
com correção do valor do inteiro, segundo enunciado e uso da função chr(), para que:
0 = '_' = , 1 = 'a' = , 2 = 'b', ..., 26 = 'z' e 27 = '.'
Args:
inteiro (int): inteiro a ser convertido em carac... | e7550dec4aa3e4a82729728befcb566e9d8315d0 | 62,406 |
def create_iterable_dataset(torch_transforms_module, pipeline_results):
"""
Create a PyTorch iterable dataset that loads samples from pipeline results.
:param torch_transforms_module: The imported torch.transforms module.
:param pipeline_results: Pipeline results iterator.
:return: Dataset that has... | 1de2f8be910da07e1a63e177f59d9bf0467edbe1 | 62,407 |
import json
def add_flow(req):
"""
:param req:
:return:
"""
r = {}
post_args=req.POST
f = flowgroup()
f.name = post_args.get('title')
try:
r['msg'] = '%s saved.' % (f.name)
r['status'] = '200'
f.save()
return HttpResponse(json.dumps(r, ensure_ascii... | 6ea4ed871b2b5363fcca519eb0fbc27c4886da5a | 62,408 |
def subset_gctoo(gctoo, row_bool=None, col_bool=None, rid=None, cid=None,
ridx=None, cidx=None, exclude_rid=None, exclude_cid=None):
""" Extract a subset of data from a GCToo object in a variety of ways.
The order of rows and columns will be preserved.
Args:
gctoo (GCToo object)
... | 2513c5449ac294ea9e79ac69f09b58ec9579d154 | 62,409 |
def dtype(request, device):
"""Run a test case in single and double precision."""
return request.param | 8196d76b2edd4bd66253b675f4636b77208f7617 | 62,410 |
import ipdb
def reduce(*event_lists):
"""
intersect all events of multiple sources to one dict of date: summary
"""
result = {}
for cal_items in event_lists:
for item in cal_items:
try:
ref = item['start'].get('date', None) or item['start'].get('dateTime')
... | f247481bb193aebbe8cb9b038347af2b409c2ae4 | 62,411 |
from typing import Dict
from typing import Callable
def is_current_builder() -> Dict[str, Callable]:
"""Inject a function to evaluate whether or not a result is current."""
def is_current(result: dict) -> bool:
"""Determine whether the result is the current version."""
if result['submitted_dat... | 35b44ee27a24ecb09f6e76245aab4619971dc17e | 62,412 |
from io import StringIO
def download_image(session, url):
"""" dumps image into memory """
dl = session.get(url, stream=True)
img = StringIO()
img.write(dl.content)
img.seek(0) # rewind to beginning
return img | ed3ab31b0eb3419e34085585aeb742252713be51 | 62,413 |
def scale_alpha(range=None, name=None, breaks=None, labels=None, limits=None, na_value=None, guide=None, trans=None,
format=None):
"""
Scale for alpha.
Parameters
----------
range : list
The range of the mapped aesthetics result.
name : str
The name of the scale ... | 02626c2f8c347e4cf757a5c08da5bd88674531ed | 62,414 |
def formation_energy_table(
defect_phase_diagram: DefectPhaseDiagram,
chempot_limits: dict = None,
fermi_level: float = 0,
hide_cols: list = None,
show_key: bool = True,
pd_facets: list = None,
):
"""
Prints the formation energy tables for either a single chemical potential limit (i.... | 9ecec1588f3367a8a33241562d1aa9d34da717ba | 62,415 |
def get_attr_info(key, convention, normalized):
"""Get information about the MMD fields.
Input
=====
key: str
MMD element to check
convention: str
e.g., acdd or acdd_ext
normalized: dict
a normalized version of the mmd_elements dict (keys are, e.g.,
'personnel>or... | 53e6d389935fead65173c3fd66d3608daa9c7ebc | 62,416 |
def unpad(x, pad_width):
"""
func to unpad slice (FOR LINUX)
----------
x : ndarray
image array
pad_width : tuple
tuple fed to np.pad
Returns
-------
ndarray
unpadded img
"""
slices = []
for c in pad_width:
e = None if c[1] == 0 else -c[1]
... | bedab5694f287d1ccd84f4240306c9d18cb38b8a | 62,417 |
def hello_world():
"""..."""
jsn = request.json
c = conn.cursor()
c.execute("insert into User values ({},{},{},{},{},{})".format(jsn['user_id'],
jsn['email_address'],
j... | d6187a1fd0a73cff75523ce3d4f45e9987e0c59d | 62,418 |
import os
def ensurePath(root, dir_names):
"""Creates hierarchy of nested folders starting from root, if they did not exist.
Returns resulting path.
"""
path = root
for dir_name in dir_names:
path += str(dir_name) + "/"
if not os.path.exists(path):
os.makedirs(path)
... | 3829c4f17e0b72c06d0130df7ef2d1b35a3dd8db | 62,419 |
from pkg_resources import resource_filename
def get_ffxml_path():
"""
Return the path where OpenMM ffxml forcefield files are stored in this package.
Returns
-------
path : str
The absolute path where OpenMM ffxml forcefield files are stored in this package
"""
filename = resource... | 29b9d3de56560ce6ddd690ffe944fe890c80f0ed | 62,420 |
def evaluate_semeval_monolingual(vectors, lang):
"""
Get a semeval score for a single monolingual test set.
"""
spearman_score = measure_correlation(spearmanr, vectors, read_semeval_monolingual(lang))
pearson_score = measure_correlation(pearsonr, vectors, read_semeval_monolingual(lang))
score = ... | a529d58ad064f84683f1afcc4a6d4a6ca24c5f25 | 62,421 |
def exists_type(curs: Cursor, type_name: str) -> int:
"""Does type exists?"""
schema, name = fq_name_parts(type_name)
q = """select count(1) from pg_namespace n, pg_type t
where t.typnamespace = n.oid
and n.nspname = %s and t.typname = %s"""
curs.execute(q, [schema, name])
re... | fdbfd1670db81ff9317e9ea04d4e4ac4b3db7230 | 62,422 |
import torch
def get_batch(data):
""" Get a batch of data from the data loader, which automatically batches the individual examples
Concatenates necessary data (lm_labels, loss_mask, tgs_mask), which is required for FS/QT variant tasks
Puts data into tensors, and places them onto CUDA
"""
... | b9f1750e348916526015df576e2969abaa51fb5f | 62,423 |
def override(args, overrides):
"""override optional arguments with arguments from the config file"""
args_dict = vars(args)
for key, value in overrides['args'].items():
if key == 'config':
raise utils.FatalException('argument "%s" specified in the config '
'override could... | 4ec582bf506a82852496756bf8e67ee3997ad92a | 62,424 |
def _infer_decision_threshold(y_proba: np.ndarray,
y_true: np.ndarray,
default_dt: float,
results_at_recall: float=None) -> float:
"""infer decision threshold based on given recall value, """
if results_at_recall:
... | f64f1f433c9b74420601961ad69ed2c1bdc17bd5 | 62,425 |
def toggle_doors(doors, skip):
"""Toggle every skip door in doors.
doors is an array of elements where a false value represents a
closed door and a true value represents an open door.
If skip is 1, toggle door #1, #2, #3...
If skip is 2, toggle door #2, #4, #6...
Returns doors
"""
for... | 7631bbc860c4bfa9a7c236a07ebfdb1092bd351c | 62,426 |
def has_year(line):
"""
:type line: FrekiLine
:rtype: bool
"""
return bool(line.search(year_str)) | b24ca4cc25174a62733f49c026f501d1832fac11 | 62,427 |
import math
def presion_vapor_tmed(tmed):
"""
calcula la presión del vapor en saturación a la temperatura media kPa
param: tmed : temperatura media
"""
return 0.6108*math.exp(17.27*tmed/(tmed+237.3)) | 968fc144037e57d688a8f0f5e19a0d7779e5bc9b | 62,428 |
import os
def process_tfr(input_path, data_dir, extract_1_of_N=1):
"""
Process a Waymo tfrecord file by extracting only every N-th frame of the front video camera
images and labels and converting the extracted data items into a tfrecord file using tf object
detection api format. The processed tfrecor... | df5e19a0aaf5112e6a40144d14373c93ca6fe714 | 62,429 |
import subprocess
def dmenu(options, dmenu):
"""Call dmenu with a list of options."""
cmd = subprocess.Popen(dmenu,
shell=True,
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE)
... | be627e15dbb62b017dee2cf707d7810d38d4854e | 62,430 |
from typing import Tuple
def double(user: str, num: int = 0) -> Tuple[str, str, str]:
"""Return JSON Object."""
return ("OK", "text/plain", f"{user}-{num}") | 57a540ff9cd021847dff39f6ee02960c527f0b36 | 62,431 |
def reward_fixture():
""" Reward for 4 state MDP, reward of 1 for single state, 0 elsewhere """
return np.array([0, 0, 0, 1]) | 9cb33d03137d3921da7e8b82403d98f52db020d1 | 62,432 |
import re
def find_first_arg_pos(bracket_offset, curr_line, args=None):
""" find_first_arg_pos(bracket_offset : int, curr_line : str) -> [int, int]
Arguments:
bracket_offset - The position of the bracket in the current line e.g
" ( list 'timey 'wimey )" --> 4
" ( list 'timey 'wimey ... | 33732d7c0141b4d1c5e9942a299e2be9c64f4813 | 62,433 |
def get_col_dim(col):
"""
Get the physical dimension of a column by its name.
Args:
col (str): the name of the column.
Returns:
str: the physical dimensions of the given column.
"""
for dim in DIM_COL.keys():
if col in DIM_COL[dim]:
return dim | ede5df4189caa156a40708292f0c2d838712792c | 62,434 |
def prerank(rnk, gene_sets, outdir='GSEA_Prerank', pheno_pos='Pos', pheno_neg='Neg',
min_size=15, max_size=500, permutation_num=1000, weighted_score_type=1,
ascending=False, processes=1, figsize=(6.5,6), format='pdf',
graph_num=20, no_plot=False, seed=None, verbose=False):
""" Ru... | 5b94e1d52b87671aea9a8090010f1a8040d044c3 | 62,435 |
def metade(valor=0, formatc=False):
"""
-> Dá a metade de um valor.
Parâmetros opcionais
:param valor: Valor que será dobrado.
:param formatc: Booleano que indica se a formatação no valor será feita
:return: Valor dividido em dois com a formatação ou não.
"""
res = valor / 2
return r... | 83b25300b2b476fa0ec7b78ed5390d223b431376 | 62,436 |
import os
import json
from datetime import datetime
import re
def find_comment(anchor, store=None, raise_errors=False, get_time=False):
"""Find the comment in the specified store or any store"""
# Remove anchor hook if it exists
if anchor.startswith(ANCHOR_HOOK):
anchor = anchor[len(ANCHOR_HOOK):]
nth_s... | ebb99c731a1337aebb7b3f05efb1e7603b7f4c87 | 62,437 |
def get_repo_url(mead_tag, nexus_base_url, prefix="hudson-", suffix=""):
"""
Creates repository Nexus group URL composed of:
<nexus_base_url>/content/groups/<prefix><mead_tag><suffix>
:param mead_tag: name of the MEAD tag used to create the proxy URL in settings.xml
:param nexus_base_url: the b... | b422b46da7c039575c9dbfd5ce5bf7157e64f9b4 | 62,438 |
def remove_false_deletes(tokenized, text):
""" Sometimes a statement like 'Removing the 'x' from the end of
paragraph can be confused as removing the paragraph. Ensure that
doesn't happen here. Likely this method needs a little more work. """
contains_delete = bool(matching(tokenized, tokens.Verb, verb=... | 16c7b479ad2d98a15ac9cd9d9f4f678af24dffa4 | 62,439 |
import functools
import warnings
def deprecated(func):
"""This is a decorator which can be used to mark functions
as deprecated. It will result in a warning being emmitted
when the function is used."""
@functools.wraps(func)
def new_func(*args, **kwargs):
warnings.simplefilter('always', D... | 7886ce0db1e81b3856222fb1ea3f6b2080b18474 | 62,440 |
def get_manufacturer(metadata):
"""Extract scanner manufacturer from DICOM tags."""
if [0x8, 0x70] in list(metadata.keys()):
manufacturer = metadata[0x8, 0x70].value
if 'Siemens' in manufacturer or 'SIEMENS' in manufacturer:
manufacturer = 0.0
elif 'Philips' in manufacturer ... | 9814f026d1ce6c8c83dbcd2b6132a80d5ea7fdac | 62,441 |
def count_times(func):
"""
Checks how many times a function repeats.
:param func: dictionary in the format (k, v): (name of brodmann area, name of the functions)
"""
times = dict()
for val in func.values():
for v in val:
inc = 1
v = v.split("\t\t")[1]
... | 0080eaf022f1de61cc9e4a06ffec1a87c5cc8980 | 62,442 |
import itertools
def GetBoundingBoxOfCoordinates(coordinates):
"""Returns smallest box containing all lat/long coordinates in given list.
Args:
coordinates: list of (lat, lon) 2-tuples.
Returns:
BoundingBox object.
"""
# Latitude is easy
north = max(x[0] for x in coordinates)
south = min(x[0] f... | ff5d556831c650c7178a703200d2ea3620b1cf53 | 62,443 |
def trunc_sequence(df: pd.DataFrame, max_len: int = -1) -> pd.DataFrame:
"""
Truncate the length of the passed
in dataframe to the max length.
:param df: pd.DataFrame, The dataframe to truncate.
:param max_len: int, The length to truncate the df to.
:return: pd.DataFrame
"""
return df.truncate(after=(max_len... | 16466e4fef170cd10171d327cc7903862b1deaca | 62,444 |
import typing
async def wait_for_component(
client: discord.Client,
component: typing.Union[str, dict, list] = None,
message: typing.Union[discord.Message, int, list] = None,
check=None,
timeout=None,
) -> ComponentContext:
"""
Helper function - wrapper around 'client.wait_for("component",... | bec60ec84d7ad03318272be30b459eb3e83f9703 | 62,445 |
def max_eigenvalue_constraint(x_vec, max_eigenvalue):
"""
This function defines an inequality constraint on the maximum eigenvalue of a SPD matrix.
The value returned by the function is positive if the inequality constraints is satisfied.
Parameters
----------
:param x_vec: SPD matrix in Mandel... | 02810dbe9f57a11548de123d5278d896002f021f | 62,446 |
def guess_timezone_by_ip(ip, only_name=False):
"""Given an `ip` with guess timezone using geoip2.
Returns a tuple of (tz_offets, tz_name, tz_formated).
`None` is returned if it can't guess a timezone.
For this to work you need to set tz_utils.GEOIP_DATA_LOCATION
You can get this database from http:... | d2be11536a06f5f9b6770b546404bc58e0ba762c | 62,447 |
def get_insert_cmd(insert_fields, table, update_cmd=None):
"""
Creates the insert command to use with an insertion to a PostgreSQL database,
given the table and the fields to be inserted
Parameters
----------
insert_fields: list of strs
Fields of data that will be inserted
table: st... | d026911c0574bc2f8a52ede5bbb72b48d81272f8 | 62,448 |
def XCAFDoc_LayerTool_GetID(*args):
"""
:rtype: Standard_GUID
"""
return _XCAFDoc.XCAFDoc_LayerTool_GetID(*args) | 6afb65fdc6c6da71181a57fb9bc1e34c5abd07f4 | 62,449 |
import os
def get_labels(split='test'):
""" Gets label files of specified dataset split """
label_paths = get_files_from_folder(
os.path.join(dataset_constants.LABELS, split), '.json')
return label_paths | b21cd5587000dd1e825cf14920dad71f0efb76a6 | 62,450 |
def kojak(kojak_txt: str, perc_inter: str, perc_intra: str, out_file: str,
version: str = "2.0-dev", max_charge: int = 8,
decoy_prefix: str = "decoy_", to_pin: bool = False) -> None:
"""
Convert Kojak search results to xenith tab-delimited format.
For conversion, the Kojak searches must... | df709826dbe8e702ae2b362120638d16623caddb | 62,451 |
import logging
def extract_df(dic=input, file=None):
"""
:param dic: global input parameters that can be altered in the config.py file
:param file: str: name of the file containing a sieving sample
:return: dataframe of sieving sample
"""
df = pd.read_excel(file, engine="openpyxl", header=Non... | 5c491074eaac0886313304f14457730495926b28 | 62,452 |
from typing import Dict
from typing import Any
def generate_artificial_data(params_dict: Dict[str, Any]):
"""Generate artificial biomarker data.
Args:
params_dict: Parameters for the data to generate (see
parameters of :func:`generate_artificial_classification_data`).
Returns:
... | e6779756a7d61234dd6b464743bec90e8b1c3f40 | 62,453 |
def serialize(gtp_command, gtp_response):
"""Serialize a GTP response as a string.
Needs the command we are responding to so we can match the sequence
number.
"""
return '%s%s %s\n\n' % (
'=' if gtp_response.success else '?',
'' if gtp_command.sequence is None else str(gtp_command.s... | 32412766b3d1db92a8aae653dbf8b11a761e35b1 | 62,454 |
def create_entry(request):
"""Creates a new entry or shows the create form"""
if request.method == 'POST':
new_entry = EntryForm(request.POST)
if new_entry.is_valid():
# create the entry
util.save_entry(new_entry.cleaned_data['title'], new_entry.cleaned_data['entry'])
... | 0562bbc939e6bdcc5c3fb1bef4a572fc0439bc50 | 62,455 |
import pathlib
import sys
import subprocess
import io
import collections
def shellcmd(bin, args, printOutput=True, returnOut=False):
"""Run the shell command with specified arguments for skopeo/docker
args -- A tuple of arguments.
printOutput -- If True, the output of the command will be send to t... | e9a84bda21e2f77c77b15179992a9af02585b360 | 62,456 |
def after(f, chain=False):
"""Runs f with the result of the decorated function."""
def decorator(g):
@wraps(g)
def h(*args, **kargs):
if chain:
return f(g(*args, **kargs))
else:
r = g(*args, **kargs)
f(*args, **kargs)
... | b4897684320927a86915335084f3da7ae126dec5 | 62,457 |
def fill_template(template_pack, predictions, eoa_id, pad_id, eos_id):
"""
:param template: [batch_size, max_seq_len]
:param mask: [batch_size, max_seq_len]
:param predictions: a list of tensors
:return:
"""
def _transpose(a):
"""
:param a: mask_num * batch_size * undefined_l... | 2d0ff6a31688608755188772ed6b87cac05fa620 | 62,458 |
from kotti.resources import get_root
def root(db_session):
"""returns Kotti's 'root' node."""
return get_root() | 165f71869534832541b292b33512abf70e035f1f | 62,459 |
from typing import Optional
from typing import Dict
from typing import List
from typing import Any
from typing import cast
def call_service(
ctx: Configuration,
domain: str,
service: str,
service_data: Optional[Dict] = None,
) -> List[Dict[str, Any]]:
"""Call a service."""
try:
req = r... | 8eb97e1be3efcddac5f6b982c1bed29f84259c9c | 62,460 |
def list_entries():
"""Return entries to be displayed in rofi."""
return(['']) | 76223be8cc86d9b9592edd1849ac1a8862c4d01c | 62,461 |
import os
import re
def cprnc(model, file1, file2, case, rundir, multiinst_driver_compare=False, outfile_suffix="",
ignore_fieldlist_diffs=False, cprnc_exe=None):
"""
Run cprnc to compare two individual nc files
file1 - the full or relative path of the first file
file2 - the full or relativ... | a2fa6fefcceae55767ad1e34b0b902a74e3e3b79 | 62,462 |
def eval(y_true, y_pred, normalize=False, verbose=3):
"""Evaluate the results in a two-class model.
Parameters
----------
y_true : array-like
True labels of the classes.
y_pred : array-like
Predicted labels.
normalize : bool, optional
Normalize the values in the confusio... | dd26ee9b70af25a11323fa420d5ac4709afa0fd2 | 62,463 |
import copy
def add_missing_fields(og_layout, tab):
"""
Adds missing fields to the layout.
"""
layout = copy.deepcopy(og_layout)
missing_fields = tab.get_missing_fields(layout.get("content"))
if not missing_fields:
return og_layout
tab_data = tab.get_from_tabs(layout.get("content")... | 040f47606c5b89a52ed9defc4a9dbdda56c4cb2a | 62,464 |
def collate_effect_size(counts, powers, alpha):
"""Calculates the effects for power values
Parameters
----------
counts : array
the number of samples used to calculate the power
powers : {list, ndarray}
list of arrays of power values. If there are multiple power arrays,
each... | f8171545e5b7a11a42da081a070be8232dd81199 | 62,465 |
def sample_dirichlet_multinomial(dirichlet_alphas:np.ndarray, num_samples:int) -> np.ndarray:
""" Sample from a Dirichlet-multinomial distribution
Parameters
----------
dirichlet_alphas : numpy.ndarray
The concentration parameters for the Dirichlet distribution
num_samples : int
Th... | 8cfe8a5fd8465d82612e176973c3a23d45eebd04 | 62,466 |
import os
import logging
import pickle
from re import T
def load_data(data_id, path, remove=True, do_pickle=True, silent=False):
""" Read data from disk file """
path = os.path.join(path, data_id)
if not os.path.exists(path):
logging.info("[%s] %s missing", misc.caller_name(), path)
retur... | 6e13a37590fee08999d7ee706abf889de752a00d | 62,467 |
def lift_hand(env_lift, tot_reward):
""" Lift hand with set action velocities
env_lift: Mujoco environment
tot_reward: Total cumulative reward
"""
# action only used to move hand, not recorded in replay buffer and is NOT used to update policy
action = np.array([wrist_lift_velocity, finger_lift_v... | ccba8cee7a92bb60672d4ca09b351cc0666c6083 | 62,468 |
import torch
def get_autoencode_minibatch(
lines, word2ind, index, batch_size,
max_len, add_start=True, add_end=True
):
"""Prepare minibatch."""
if add_start and add_end:
lines = [
['<s>'] + line + ['</s>']
for line in lines[index:index + batch_size]
]
elif ... | 953785f3042e4800e7343c886d84218e6be5b171 | 62,469 |
def read_file(path):
"""
Return the contents of a file
Arguments:
- path: path to the file
Returns:
- contents of the file
"""
with open(path, 'r') as file:
return file.read().rstrip() | 85d64985da7c9ea15b314d25b42ad2bc6491a111 | 62,470 |
def build_scaler_train_and_test_datasets(
label,
train_features,
test_feature,
df,
test_size,
seed,
scaler_cast_to_type="float32",
min_feature_range=-1,
max_feature_range=1):
"""build_scaler_train_and_test_datasets
:param label: log label
... | da94aa27d78c22dfaaa03e441f83519d0c4b179d | 62,471 |
def _entitlements(ctx):
"""Returns the entitlement file to be used for codesigning."""
# Use the entitlements from the internal provider if it's present (to support
# rules that manipulate them before passing them to the bundler); otherwise,
# use the file that was provided instead.
if getattr(ctx.... | d177c53a4d74319203d197fbe3561b5d4de3a6bf | 62,472 |
def dwconv_block(
in_channels: int,
out_channels: int,
kernel_size: int,
stride: int = 1,
padding: int = 1,
dilation: int = 1,
bias: bool = False,
use_bn: bool = True,
bn_eps: float = 1e-5,
activation=(lambda: nn.ReLU(inplace=True))
):
... | 4cf99e00f04a4d8e6fbb2ba75601fd4879898409 | 62,473 |
def test_db():
"""Provide an in-memory database for testing."""
return SqliteDatabase(':memory:') | 97c13d2a6bd3c8cc49349f480be1983b1aa29147 | 62,474 |
def get_venv_packages(venv_path):
# type: (str) -> Set[str]
"""
Returns the packages installed in the virtual environment using the
package index file.
"""
with open(get_index_filename(venv_path)) as reader:
return set(p.strip() for p in reader.read().split('\n') if p.strip()) | 6aae4c5bd8d663a25b41205fd6ae4e3a2b02368d | 62,475 |
def get_roi_ious(rois, gt_boxes):
"""
Get IoU per Reion Proposals (Column 1 == GT Box1, Column 2 == GT Box2 ...)
"""
roi_ious = np.zeros([len(rois), len(gt_boxes)])
for i in range(len(rois)):
for j in range(len(gt_boxes)):
roi_ious[i, j] = get_iou(boxA_pts=rois[i], boxB_pts=... | 0a6b67e18efd16e58b3ae1428cc7bca227d6e5d7 | 62,476 |
import tempfile
import base64
def _setup_conn(**kwargs):
"""
Setup kubernetes API connection singleton
"""
kubeconfig = kwargs.get("kubeconfig") or __salt__["config.option"](
"kubernetes.kubeconfig")
kubeconfig_data = kwargs.get("kubeconfig_data") or __salt__[
"config.option"]("kub... | 95635f66ae1df336c9f725bd281fb8bccac057cb | 62,477 |
from datetime import datetime
import json
def get_co2_latest():
"""
Returns the co2 values for the most recent day.
"""
if request.method == 'GET':
try:
session = co2DB.create_session()
date = datetime.now().replace(hour=0, minute=0)
if date == None:
... | 7e40218227024f7f9e7a53134502361b642cd428 | 62,478 |
def common_options(f):
"""
Common CLI options used by all commands. Ex: --debug
:param f: Callback function passed by Click
:return: Callback function
"""
f = debug_option(f)
return f | 63dc4d1a294f34c1abdd08a96a733d812e309b91 | 62,479 |
def get_default_db_file():
"""Returns default location of db file"""
return DEFAULT_DB_LOCATION | 25f374ea1392a63d7ad557800241ee1ff8b74e7f | 62,480 |
def dashboard_post(request, status='all', category='all', page=1):
"""Dashboard"""
list_count = settings.DASHBOARD_LIST_COUNT
if int(page) < 1:
return redirect('blogs:dashboard_post', status, category, 1)
current_page = int(page) - 1
start_at = current_page * list_count
end_at = start_... | 91620494da8ca1ee766888d78fe04a1a2451dd90 | 62,481 |
import sys
def addMenuItem(caption, link, icon=None, thumbnail=None, folder=False, fanart=None):
"""
Add a menu item to the xbmc GUI
Parameters:
caption: the caption for the menu item
icon: the icon for the menu item, displayed if the thumbnail is not accessible
thumbail: the thumbnail for th... | f2d51b9046e255196c4048aa66a9ecd07f2326e1 | 62,482 |
def next_power_2(x: int) -> int:
"""Return the smallest power of 2 greater than or equal to x"""
return 1 << (x-1).bit_length() | f5361250c1a6ef8228adcfd0aeab478484e7239b | 62,483 |
def ismir2015_evaluate(niter=0, **kwargs):
"""
inputs:
niter - number of permutation test iterations to run [0=none]
**kwargs - key-word arguments for tsne analysis function {harmonic_}tsne_all()
ref_idx - reference audio file, all audio warped to this [9]
dfun - distance function to use [bregma... | 737814eb30bd97fa679134d63e97869893125fb1 | 62,484 |
def create_new_pet(
obj_in: PetCreationForm,
current_user=Depends(get_current_user)
):
"""
Add a new pet to DB
"""
if obj_in.owner != current_user["id"]:
raise HTTPException(
status.HTTP_403_FORBIDDEN,
"You are not authorised for this operation."
)
n... | e48d134f8e8e77fe4abd827dcab65d9af6af0492 | 62,485 |
def get_rnai_essentiality(symbol: str) -> float:
"""Get essentiality of the gene in the RNAi experiments."""
return _get_essentiality(symbol, "rnai") | fde9f7f748c79cb85b15fb649848a574057d5e5a | 62,486 |
def security_group_exists(self, sg_id=None, name=None):
"""
Checks if a security group already exists on this connection, by name or by ID.
:param boto.ec2.EC2Connection self: Current connection.
:param string sg_id: ID of the security group to check. Default : None.
:param string name: Name of the... | 042cd05a550b139b3441613269f59a27ad028ea1 | 62,487 |
def FCS2CorrSplit(data, dwellTime, listOfG=['central', 'sum3', 'sum5', 'chessboard', 'ullr'], accuracy=50, split=10):
"""
Chunk SPAD-FCS trace into different parts and calculate correlation curves
========== ===============================================================
Input Meaning
-------... | 346f0ee5be3f825e593a40276f2228569ff3bfc7 | 62,488 |
import json
import os
def _setup_hparams(args):
""" Wrapper function to get hyperparameters from input args. """
print("Args:")
for k, v in sorted(vars(args).items()):
print("\t{}: {}".format(k, v))
if args.hparams_seed == 0:
hparams = hparams_registry.default_hparams(args.algorithm, ... | 1f6710f7bb397c20e473c77f04002dde772a0293 | 62,489 |
from typing import Optional
from typing import Sequence
def get_log_saved_searches(compartment_id: Optional[str] = None,
filters: Optional[Sequence[pulumi.InputType['GetLogSavedSearchesFilterArgs']]] = None,
log_saved_search_id: Optional[str] = None,
... | d4d8b0b8f8cc38f85fdd8d31e9f596e60a9d1ce8 | 62,490 |
def repeat(x, nTimes, assertAtLeastOneRep=False):
"""
Repeat x nTimes times.
Parameters
----------
x : tuple or Circuit
the operation sequence to repeat
nTimes : int
the number of times to repeat x
assertAtLeastOneRep : bool, optional
if True, assert that nTimes > 0. ... | fd03fa160625d9690aeda6bc5313f5af5999bc4a | 62,491 |
import json
import torch
def load_model(directory, model_version=None):
"""
Returns model, data_loader and mask_descriptor of trained model.
Parameters
----------
directory : string
Directory where experiment was saved. For example './experiment_1'.
model_version : int or None
... | af6799f2b43e666638c44c89a5550ff8357d0b2a | 62,492 |
def load_data(file_name: str) -> dict:
"""Reads all data in h5 file ``file_name`` and returns them as a `dict`."""
with h5py.File(file_name, 'r') as data_file:
q_values = np.array(data_file.get('q_values'))
reflectivity = np.array(data_file.get('reflectivity'))
labels = pd.read_hdf(fil... | f5fc95a47eb7edd039fab3040a18b37d3c8641dc | 62,493 |
def pixel_scale(y):
"""Function (from WFC3 paper),
to determine max and min scale
for given ycen"""
# Add or subtract 150 from y to account for impact
# of vertical scan on y position.
min = 0.0028*(y-150) + 44.68
max = 0.0026*(150+y) + 45.112
out = np.asarray([min,max])
return out | 27845ec93ea212a12df680faba02e515bde048ba | 62,494 |
def image_detail(request):
"""
post:
Post an image.
"""
if request.method == 'POST' and request.FILES:
print(request.FILES['image'])
myfile = request.FILES['image']
# Future TODO: Possibly add it to the DB, but don't have too.
try:
Photo.object... | b3b8dd725507c089384ed463c6a5039189acf0fa | 62,495 |
import os
def get_config(argv, use_argparse=True, cwd=None):
"""
Read sys.argv and parse out repository of migrations and database url.
>>> import os
>>> from configparser import ConfigParser
>>> from shutil import rmtree
>>> from tempfile import mkdtemp
>>> config_dir = mkdtemp()
>>>... | d9decefb76d3775bec5c7d07b07194cf614f6950 | 62,496 |
def sbe43(calib, P, K, T, S, V):
"""NOT TESTED
IS THIS IN ITS-90? DOES IT MATTER?
SBE equation for converting SBE43 engineering units to oxygen (ml/l).
SensorID: 38
Parameters
----------
calib : dictionary
calib is a dict holding Soc, Voffset, Tau20, A, B, C, E
P : array-like
... | 30bc9b73bcef840e045b22dcc67d402a3dca61f7 | 62,497 |
def get_approximate_cloud_underside(qc, z_tol=100.0):
"""
Using 3D condensate field `qc` create a 2D array representing the underside
height of the lowest cloudy point per column
"""
z_cloud_underside = qc.zt.where(qc > 0.0).min(dim="zt")
m = z_cloud_underside < z_tol + z_cloud_underside.min()
... | 5605531095b47e9552ca00b852188f4189bf43fe | 62,498 |
def getDivisionByID(xStarts: [int], yStarts: [int], idDivision: int, divisionSize=1024):
"""
Return x and y starting and ending coordinates for a specific division
:param xStarts: the x-axis starting coordinates
:param yStarts: the y-axis starting coordinates
:param idDivision: the ID of the divisio... | f82fd932eefd2560567117f96fdb7fc165a9bda7 | 62,499 |
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