content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import gdata.gauth
def credentials_to_token(credentials):
"""
Transforms an Oauth2 credentials object into an OAuth2Token object
to be used with the legacy gdata API
"""
credentials.refresh(httplib2.Http())
token = gdata.gauth.OAuth2Token(
client_id=credentials.client_id,
clie... | 549b1041c275c542d96e1d048832f71969d727d7 | 3,632,500 |
def solve2x2(lhs, rhs):
"""Solve a square 2 x 2 system via LU factorization.
This is meant to be a stand-in for LAPACK's ``dgesv``, which just wraps
two calls to ``dgetrf`` and ``dgetrs``. We wrap for two reasons:
* We seek to avoid exceptions as part of the control flow (which is
what :func:`nu... | 2f773a0e452ce1401dc5fb5c17256b662614c366 | 3,632,501 |
def fetch_global_notifications(count=0) -> dict:
"""
Always returns notifications in user view.
"""
cfg = get_config()
if count == 0:
count = cfg.default_max_notes
global_feed = get_global_feed()
global_notes = global_feed.get_notifications(count=count, user_view=True)
return glo... | 661232b2477eabd0c5a3b706b8253e4956e1aabd | 3,632,502 |
def getClusterPositionsRedshift(hd_clu, cluster_params, redshift_limit):
"""
Function to get the positions and redshifts of the clusters that pass the required criterion
@hd_clu :: list of cluster headers (each header ahs info on 1000 clusters alone)
@cluster_params :: contains halo_mass_500c and centra... | 4b30bb44a82daa3f2f113c14b7f044ac22d20c6c | 3,632,503 |
def lark_to_field_definition_node(tree: "Tree") -> "FieldDefinitionNode":
"""
Creates and returns a FieldDefinitionNode instance extracted from the
parsing of the tree instance.
:param tree: the Tree to parse in order to extract the proper node
:type tree: Tree
:return: a FieldDefinitionNode ins... | f00d0ed11d3ff61d8017cecbb0226b88accb9854 | 3,632,504 |
def variant_wraps(vfunc, wrapped_attributes=VARIANT_WRAPPED_ATTRIBUTES):
"""Update the variant function wrapper a la ``functools.wraps``."""
f = vfunc.__main_form__
class SentinelObject:
"""A unique sentinel that is not None."""
sentinel = SentinelObject()
for attr in wrapped_attributes:
... | 4143a0e2cb5676c80314096575c9d33fbdcdb788 | 3,632,505 |
from typing import Iterable
def gradient_activity(activity, periods=1, append=True, columns=None):
"""Compute the gradient for all given columns.
Read more in the :ref:`User Guide <gradient>`.
Parameters
----------
activity : DataFrame
The activity to use to compute the gradient.
pe... | fd05c9323d406b9f0c5089f7715b8ec55ceeaae2 | 3,632,506 |
def password_validators_help_texts(password_validators=None):
"""
Return a list of all help texts of all configured validators.
"""
help_texts = []
if password_validators is None:
password_validators = get_default_password_validators()
for validator in password_validators:
help_t... | 3df7b1a669ee7ef01b1e28645d3d7fca5816cf8d | 3,632,507 |
import torch
def spherical_schwarzchild_metric(x,M=1):
""" Computes the schwarzchild metric in cartesian like coordinates"""
bs,d = x.shape
t,r,theta,phi = x.T
rs = 2*M
a = (1-rs/r)
gdiag = torch.stack([-a,1/a,r**2,r**2*theta.sin()**2],dim=-1)
g = torch.diag_embed(gdiag)
print(g.shape)... | 4e65d520a88f4b9212bab43c7ebc4dfc30245bd3 | 3,632,508 |
def _get_pathless_grib_file_names(
init_time_unix_sec, model_name, grid_id=None, lead_time_hours=None):
"""Returns possible pathless file names for the given model/grid.
:param init_time_unix_sec: Model-initialization time.
:param model_name: See doc for `nwp_model_utils.check_grid_name`.
:para... | 6435348fa760b5bd36e8c54df192b024210dcf4f | 3,632,509 |
def get_picard_mrkdup(config):
"""
input: sample config file output from BALSAMIC
output: mrkdup or rmdup strings
"""
picard_str = "mrkdup"
if "picard_rmdup" in config["QC"]:
if config["QC"]["picard_rmdup"] == True:
picard_str = "rmdup"
return picard_str | 87e24c0bf43f9ac854a1588b80731ed445b6dfa5 | 3,632,510 |
import random
def ChoiceColor():
""" 模板中随机选择bootstrap内置颜色 """
color = ["default", "primary", "success", "info", "warning", "danger"]
return random.choice(color) | 15779e8039c6b389301edef3e6d954dbe2283d54 | 3,632,511 |
import platform
def filter_command_line(line):
"""Returns and updates the command line starting with the flag"""
line_flag = line.strip().split(":")[0].strip()
new_line = line.strip()[len(line_flag) + 1:].strip().lstrip(":").strip()
if line_flag == EXEC_FLAG:
return new_line
elif line_flag... | ff5560b1ba23544902e0904bc08030b2d24a40e4 | 3,632,512 |
def load_image(path: str):
"""
Return a loaded image from a given path.
:param path: (str) relative path of the iamge.
:return: PIL image.
"""
image = Image.open(path)
return image | 8c9d96d5cea2fdac67ba937b7d01bc01a860d1d7 | 3,632,513 |
from operator import concat
def mergeSeries(sdata, resetIdx=False):
"""
Merge Series
Inputs:
> sdata: Either a list of dictionary of Series data
> resetIdx (False by default): should we reset the indices?
Output:
> The merged Series
"""
if isinstance(sdata, list):... | dc0382581d3e14dc46abe9c5b40d685f3d80ec20 | 3,632,514 |
def ranking_overview(request):
"""
Show history of rankings for top N teams in current ranking
"""
# Check which rounds are complete
rnd_complete = get_completed_rounds()
# Calculate ranking after each of these rounds
increment_rnds = []
ranking_matrix = []
round_names = []
... | c68505833f72d529d4ea1617d4d8455120c5321d | 3,632,515 |
def release_lock(lock_name, identifier):
"""
:param lock_name: 锁名称
:param identifier: uid
:return: True or False
"""
lock = "string:lock:" + lock_name
pip = redis_client.pipeline(True)
while True:
try:
pip.watch(lock)
lock_value = redis_client.get(lock)
... | 8df9f174d11a36ffad9ed2310c2293630669dc4c | 3,632,516 |
def add_user():
""" Add a user"""
payload = request.json
for required_key in users_schema:
if required_key not in payload.keys():
return jsonify({"message": f"Missing {required_key} parameter"}), 400
user = db.users.find_one({"email": payload["email"]})
if user is not None:
... | 1c674dbb70caa0ae43819391c97694d3dd82a235 | 3,632,517 |
import hashlib
def __get_str_md5(string):
"""
一个字符串的MD5值
返回一个字符串的MD5值
"""
m0 = hashlib.md5()
m0.update(string.encode('utf-8'))
result = m0.hexdigest()
return result | 1d55cd42dc16a4bf674907c9fb352f3b2a100d6c | 3,632,518 |
from typing import List
def create_optimizers() -> List[OptimizationProcedure]:
"""Creates a list of all optimization procedures"""
optimizers: List[OptimizationProcedure] = []
ordering_rules = TaskOrderingRule.__subclasses__()
for rule in ordering_rules:
optimizers.append(StationOriented... | f5cade59c03b017435c18a97423eb059418a6e20 | 3,632,519 |
import urllib
def command_get_file_list(ip_addr, directory):
"""command.cgi?op=100: Get list of files in a directory. Not recursive.
:raise FlashAirBadResponse: When API returns unexpected/malformed data.
:raise FlashAirDirNotFoundError: When the queried directory does not exist on the card.
:raise F... | 40f8c9b84113be84358959f246a868424d382947 | 3,632,520 |
def axml_content(d):
"""
OwcContent dict to Atom XML
:param d:
:return:
"""
# <owc:content type="image/tiff" href=".."
if is_empty(d):
return None
else:
try:
content_elem = etree.Element(ns_elem("owc", "content"), nsmap=ns)
mimetype = extract_p(... | c35c266d4ae7c5026958cbb271598f76369ecc6f | 3,632,521 |
def average_water_consumed(wn):
"""
Compute average water consumed at each node, qbar, computed as follows:
.. math:: qbar=\dfrac{\sum_{k=1}^{K}\sum_{t=1}^{lcm_n}qbase_n m_n(k,t mod (L(k)))}{lcm_n}
where
:math:`K` is the number of demand patterns at node :math:`n`,
:math:`L(k)` is the number o... | bf88a45035b993d00fb31ff7151e48a0a1d59c83 | 3,632,522 |
def _shuffle(arr1, arr2):
"""
Shuffles arr1 and arr2 in the same order
"""
random_idxs = np.arange(len(arr1))
np.random.shuffle(random_idxs)
return arr1[random_idxs], arr2[random_idxs] | 785ecd0b9e92d5695cd2466fec6649d463f55feb | 3,632,523 |
from datetime import datetime
import pytz
def assign_output(request):
"""assigns the given files as version outputs for the given entity
"""
logger.debug('assign_output')
logged_in_user = get_logged_in_user(request)
full_paths = request.POST.getall('full_paths[]')
original_filenames = reques... | 7a0a6f0131a4bee9cc3248ee8e695980b5850024 | 3,632,524 |
def make_pipeline(tfidf_vectorizer, model):
""" Creates sklearn NLP pipeline
:param vectorizer: Vectorizer object
:param model: Model object
:return: Pipeline object
"""
tfidf_vectorizer = tfidf_vectorizer
model = model
pipeline = Pipeline([("tfidf", tfidf_vectorizer),
... | 423b59d2635bf34169091c7456e71eca2dbdf5d6 | 3,632,525 |
def pnf_peeling_mechanism(item_counts, k, epsilon):
"""Computes epsilon-DP top-k counts by the permute-and-flip peeling mechanism.
The peeling mechanism (https://arxiv.org/pdf/1905.04273.pdf) adaptively uses
the counts as a utility function for the exponential mechanism. Once an item
is selected, the item is ... | 2c2fe9e59addc4905211ca70efd1f88bdeb5a976 | 3,632,526 |
from datetime import datetime
def format_date(timestamp):
"""Reusable timestamp -> date."""
return datetime.date.fromtimestamp(timestamp).isoformat() | 0f735dc18700332238ab4441677c786f9accc069 | 3,632,527 |
import sys
def getpwuid(uid):
"""
getpwuid(uid) -> (pw_name,pw_passwd,pw_uid,
pw_gid,pw_gecos,pw_dir,pw_shell)
Return the password database entry for the given numeric user ID.
See pwd.__doc__ for more on password database entries.
"""
if uid > sys.maxint or uid < 0:
... | e2917351bb23ece2fabb5274391bf2939df590c6 | 3,632,528 |
import time
def train(model, optimizer, loader, epoch):
"""
Train the models on the dataset.
"""
# running statistics
batch_time = AverageMeter("time", ":.2f")
data_time = AverageMeter("data time", ":.2f")
# training statistics
top1 = AverageMeter("top1", ":.3f")
top5 = AverageMet... | 3d65714a50f1842c32c85fe0cd3c02d7069a88f9 | 3,632,529 |
import functools
def ResidualBlock(name, input_dim, output_dim, filter_size, inputs, resample=None, he_init=True):
"""
resample: None, 'down', or 'up'
"""
if resample == 'down':
conv_shortcut = functools.partial(lib.ops.conv2d.Conv2D, stride=2)
conv_1 = functools.partial(
l... | 1b78b86ea42dd225f5a2bde6bcb6ed47b055ec00 | 3,632,530 |
def run_uGLAD_direct(
Xb,
trueTheta=None,
eval_offset=0.1,
EPOCHS=250,
lr=0.002,
INIT_DIAG=0,
L=15,
VERBOSE=True
):
"""Running the uGLAD algorithm in direct mode
Args:
Xb (np.array 1xMxD): The input sample matrix
trueTheta (np.array 1xDxD): The corresp... | 5b362abfec18a217c768bbe45bce3059ece8be22 | 3,632,531 |
def twitter_api():
"""Returns an authenticated tweepy.API instance.
Returns None on failure.
"""
try:
auth = tweepy.OAuthHandler(TWITTER_API_KEY, TWITTER_API_KEY_SECRET)
auth.set_access_token(TWITTER_ACCESS_TOKEN,
TWITTER_ACCESS_TOKEN_SECRET)
ap... | 5f0e748740025d4065c6317fdf03eead25e7ba95 | 3,632,532 |
def as_general_categories(cats, name="cats"):
"""Return a tuple of Unicode categories in a normalised order.
This function expands one-letter designations of a major class to include
all subclasses:
>>> as_general_categories(['N'])
('Nd', 'Nl', 'No')
See section 4.5 of the Unicode standard fo... | 391185d75dce63df7deb724f8dea035389122b94 | 3,632,533 |
from pathlib import Path
import glob
def upload_directory(
directory: str = './',
upsert=False,
ignore_duplicate_error=False,
recursive=False,
pattern='*'):
"""
Upload files in a directory to the database.
:param directory: [Optional] The root directory to upload. ... | d156c44f511182958172ba30bfb5422bb5da8dcd | 3,632,534 |
def tExtract(rft, T_INDEX):
"""T_INDEX is either of T_WL, T_SPEC, T_COM """
tdat = [dat[T_INDEX] for dat in rft[RFT_T] if (dat[T_WL] >= rft[RFT_R][R_WL] and dat[T_WL] <= rft[RFT_R][R_WH])]
return tdat | c1cdf75b377851316a5da050b8f248f14cfd34e5 | 3,632,535 |
from typing import Union
from pathlib import Path
from typing import Optional
def open_txt(path: Union[str, Path], cf_table: Optional[dict] = cmor) -> xr.Dataset:
"""Extract daily HQ meteorological data and convert to xr.DataArray with CF-Convention attributes."""
meta, data = extract_daily(path)
return t... | 3a77ed5a501c1d455299504e4dd36e55cea580e9 | 3,632,536 |
def dc_coordinates():
"""Return coordinates for a DC-wide map"""
dc_longitude = -77.016243706276569
dc_latitude = 38.894858329321485
dc_zoom_level = 10.3
return dc_longitude, dc_latitude, dc_zoom_level | c07812ad0a486f549c63b81787a9d312d3276c32 | 3,632,537 |
import argparse
def get_arguments():
"""
Obtains command-line arguments.
:rtype: argparse.Namespace
"""
parser = argparse.ArgumentParser()
parser.add_argument(
'--clusters',
type=argparse.FileType('rU'),
required=True,
metavar='CLUSTERS',
help='read c... | 32ce1446d8ac04208a4387bcd2ac31a2609580a3 | 3,632,538 |
def request_id_to_key(request_id):
"""Converts a request id into a TaskRequest key.
Note that this function does NOT accept a task id. This functions is primarily
meant for limiting queries to a task creation range.
"""
return ndb.Key(TaskRequest, request_id ^ task_pack.TASK_REQUEST_KEY_ID_MASK) | a5c3ef9939390d43264ba397e4c123af44758471 | 3,632,539 |
from typing import Optional
def get_web_app_premier_add_on_slot(name: Optional[str] = None,
premier_add_on_name: Optional[str] = None,
resource_group_name: Optional[str] = None,
slot: Optional[str] = None,
... | 764101a407305b1f6e03fe8b1ccb17cb2ecbd86f | 3,632,540 |
from typing import Callable
from typing import Iterable
from typing import List
def lmap(f: Callable, x: Iterable) -> List:
"""list(map(f, x))"""
return list(map(f, x)) | 51b09a3491769aafba653d4198fde94ee733d68f | 3,632,541 |
import ImportPathHelper as imports
from editor_python_test_tools.utils import Report
from editor_python_test_tools.utils import TestHelper as helper
import azlmbr.legacy.general as general
import azlmbr.bus
import azlmbr.physics as phys
import azlmbr.math as mathazon
def C4925577_Materials_MaterialAssignedToTerrain()... | 45b527c1b413c33be81fecf7babd4d11de513a8f | 3,632,542 |
def fallible_to_exec_result_or_raise(
fallible_result: FallibleExecuteProcessResult, description: ProductDescription
) -> ExecuteProcessResult:
"""Converts a FallibleExecuteProcessResult to a ExecuteProcessResult or raises an error."""
if fallible_result.exit_code == 0:
return ExecuteProcessResult(
fal... | 774cf9e89fd383a37992fff0b2e1b72ff96bddc8 | 3,632,543 |
def cumprod_np(a: np.ndarray, mod: int) -> np.ndarray:
"""Compute cumprod over modular not in place.
the parameter a must be one dimentional ndarray.
"""
n = a.size
assert a.ndim == 1
m = int(n**0.5) + 1
a = np.resize(a, (m, m))
for i in range(m - 1):
a[:, i + 1] = a[:, i + 1] *... | b5b1635000bf82b563c350341c8c56edbb0eb9fb | 3,632,544 |
def table_of_contents(df_documentation=''):
"""
Function::: table_of_contents
Description: brief description here (1 line)
Details: Full description with details here
Inputs
doc_csv_file: FILE csv file with documentation of functions
Outputs
tab_contents: STR Table of content... | fa5c26b729278bcc312a07fc6822ecf4837e2828 | 3,632,545 |
def mock_get_location_business_from_sam(client, duns_list):
""" Mock function for location_business data as we can't connect to the SAM service """
columns = ['awardee_or_recipient_uniqu'] + list(update_historical_duns.props_columns.keys())
results = pd.DataFrame(columns=columns)
duns_mappings = {
... | 61c9d0c0ee18a3840f7b2c0b70c504c388e83343 | 3,632,546 |
def repeat(N, fn):
"""repeat module N times
:param int N: repeat time
:param function fn: function to generate module
:return: repeated loss
:rtype: MultiSequential
"""
return MultiSequential(*[fn() for _ in range(N)]) | da20e6af56fd227d6eb2c6e083ac21d5c65e71e3 | 3,632,547 |
import numpy
def dense_to_one_hot(labels_dense, num_classes):
"""Convert class labels from scalars to one-hot vectors."""
num_labels = labels_dense.shape[0]
index_offset = numpy.arange(num_labels) * num_classes
labels_one_hot = numpy.zeros((num_labels, num_classes))
labels_one_hot.flat[index_offset + labels... | dc4c717a03624708be6b09b040acb5a901d1e8f0 | 3,632,548 |
from typing import Set
from typing import Mapping
def parse_input(data: str) -> (Set[str], Mapping[str, Mapping[str, int]]):
"""Extract the names and associated happines changes from data."""
names = set()
happiness_changes = {}
for line in data.splitlines():
match = INPUT.fullmatch(line)
... | 147cc6a19160b6e472249e59c5a8a41fb73f6cde | 3,632,549 |
def main(argv):
"""The program.
Returns an error code or None.
"""
try:
# Build an environment from the list of arguments.
env, writer = make_env_and_writer(argv)
try:
cmd = COMMANDS[env.options.command](env, writer)
cmd.execute()
finally:
... | 00063921703fea4ef21e8767ccdb1156f3c45911 | 3,632,550 |
import pandas
def merger(primary_path:str, secondary_path:str, desired_columns:list, shared_column="time"):
"""
--> Primary path is the global analysis file produced by analyzing NMR spectra
--> Secondary path is the raw-data file recorded by the DAQ.
--> Desired columns is a list of columns that you want to MIG... | 8db087622b691bb0b36505e038c8aa5ed5902121 | 3,632,551 |
import unicodedata
import re
def slugify_ref(value: Text, allow_unicode: bool = False) -> Text:
"""
Convert to ASCII if 'allow_unicode' is False. Convert spaces to hyphens.
Remove characters that aren't alphanumerics, underscores, or hyphens. Convert to lowercase.
Also strip leading and trailing whit... | 1ce3893436f1590e55679248290aadc486f0d717 | 3,632,552 |
import json
def user_search():
"""UserSearch"""
value = request.args.get('search')
cur = MY_SQL.connection.cursor()
cur.execute(
'''SELECT id, username FROM accounts.users WHERE
username LIKE '%%%s%%';''',
(value)
)
users = json.dumps(cur.fetchall())
return users | 774234ee4cb4bae2b77a0c469037c695660d250e | 3,632,553 |
def graphcut(img1, img2, mask):
"""
Inputs:
Mask:
The 80px area out of the boundary. 2 dims.
Pixels on the edge of Img1 are marked with 1 and same for Img2. Internal pixels are marked with 3.
Img1 & Img2:
Here Img1 means source img, aka. the input img. Img2 is... | a6d113e714191015f446cf1e687d925258dfb06f | 3,632,554 |
def lutForTBMap():
""" produce a look up table for a red-black-blue colormap"""
cmap=mpl.colors.LinearSegmentedColormap.from_list('my_colormap',
['blue','black','red'],
256)
#I'm not entirely sure what this lower is for. Its use... | 1017d2fc7c7279ac3baa1393286244586d0e30c8 | 3,632,555 |
import typing
import tqdm
def val_one_epoch(model: Module, dataloader: DataLoader, criterion,
device: str) -> typing.Tuple[typing.Union[np.ndarray, None],
dict]:
"""
Validate the given model for one epoch.
:param model: model to evaluate
... | d51a5fbb064d00de1a48d30927cb1695db0a3168 | 3,632,556 |
def multiply_something(num1, num2):
"""this function will multiply num1 and num2
>>> multiply_something(2, 6)
12
>>> multiply_something(-2, 6)
-12
"""
return(num1 * num2) | 1a726c04df146ab1fa7bfb13ff3b353400f2c4a8 | 3,632,557 |
def post_shift_dp(train_set, vali_set, test_set, logreg_model):
"""Post-shifts log. regression model for demographic parity using vali_set.
Returns the train, validation and test sets with the group attribute appended
as an additional feature, and the post-shifted linear model for the expanded
datasets.
Arg... | 03cfcf5060e6419398042ff08fbb991c34551726 | 3,632,558 |
def determine_acknowledgement(record, report, ignore_string):
"""Mark report for output unless ignored"""
if record[COMMENT_TEXT]:
comment = record[COMMENT_TEXT].lower()
else:
comment = ""
if ignore_string in comment:
report["should"] = False
return True
report["shou... | 8fd4d0d2623a0183953a21cb2029da0fadc95bff | 3,632,559 |
def estimate_infectious_rate_constant_vec(event_times,
follower,
t_start,
t_end,
kernel_integral,
count_events... | 207833e1b32885fe39a209bfef227665c8c59ad1 | 3,632,560 |
import urllib
import json
def cotacaoBRL():
"""
Retorna a última cotação do Bitcoin em BRL - Mercado Bitcoin via API BitValor
"""
with urllib.request.urlopen("https://api.bitvalor.com/v1/ticker.json") as url:
data = json.loads(url.read().decode())
last = data['ticker_24h']['exchanges... | a6c96aa8c8cff46ab4b410a81d1ef19ac912fcbb | 3,632,561 |
from typing import List
def adder(journal: Journal) -> List[JournalEntry]:
"""A task that requires previous phases to have recorded journal entres with tags 'x' and 'y', which it will sum.
Returns a new journal entry, titled 'x+y', containing the sum of the existing journal entries 'x' and 'y'
"""
x... | 03303cd74dffa0631dbb120280666701268871e7 | 3,632,562 |
def find(word,letter):
"""
find letter in word , return first occurence
"""
index=0
while index < len(word):
if word[index]==letter:
#print word,' ',word[index],' ',letter,' ',index,' waht'
return index
index = index + 1
return -1 | bdeb0f0993fb4f7904b4e9f5244ea9d7817fa15f | 3,632,563 |
def subsample_ind(n, k, seed=32):
"""
Return a list of indices to choose k out of n without replacement
"""
rand_state = np.random.get_state()
np.random.seed(seed)
ind = np.random.choice(n, k, replace=False)
np.random.set_state(rand_state)
return ind | 958ddcf3122bc8c8f9cab0539896bfc624d1901f | 3,632,564 |
def HA2(credentails, request):
"""Create HA2 md5 hash
If the qop directive's value is "auth" or is unspecified, then HA2:
HA2 = md5(A2) = MD5(method:digestURI)
If the qop directive's value is "auth-int" , then HA2 is
HA2 = md5(A2) = MD5(method:digestURI:MD5(entityBody))
"""
if crede... | 94f9a6b6e6371f1d7c1c6606577cbbced201facf | 3,632,565 |
from typing import Dict
from typing import Any
import hashlib
def name_to_scope(
template: str,
name: str,
*,
maxlen: int = None,
params: Dict[str, Any] = None,
) -> str:
"""Return scope by given template possibly shortened on name part.
"""
scope = template.format(name=name, **params)... | cd6759da406b6072565f693cdffe8eb16107c074 | 3,632,566 |
def bootstrap_idxs(n, rng: np.random.Generator = None):
"""
Generate a set of boostrap indexes of length n, returning the pair (in_bag, out_bag) containing the in-bag and
out-of-bag indexes as numpy arrays
"""
if rng is None or type(rng) is not np.random.Generator:
rng = np.random.default_rn... | 3d76cfea110c91a228bc8bc3ec5698c9a94676b8 | 3,632,567 |
def run(argv=None):
"""Main entry point; defines and runs the wordcount pipeline."""
parser = argparse.ArgumentParser()
parser.add_argument('--input',
dest='input',
default='$GTFS_BUCKET/at/20190429120000/at.zip',
help='Input file to p... | d4bacf3a16dc53e3e8b6213e6dbbb2be9a7df2b0 | 3,632,568 |
def check_skyscrapers(input_path: str):
"""
Main function to check the status of skyscraper game board.
Return True if the board status is compliant with the rules,
False otherwise.
>>> check_skyscrapers("check.txt")
True
"""
lst = read_input(input_path)
if check_columns(lst) and\
... | ff57e649bbd87563fe97e870e304259041f0582f | 3,632,569 |
from typing import Dict
from typing import Any
import importlib
def load_preprocessor(preproc_params: Dict[str, Any], device: str) -> Module:
"""Load preprocessor from module preprocessors.name"""
preproc = None
if preproc_params is not None:
preproc_module = importlib.import_module(
f... | a6ea8dc293c883f5bcd1841bd1d483b97d393dab | 3,632,570 |
def get_image_ground_truth(image_id, dataset):
"""Load and return ground truth data for an image (image, mask, bounding boxes).
Args:
image_id:
Image id.
Returns:
image:
[height, width, 3]
class_ids:
[instance_count] Integer class IDs
bbo... | 3894e5714ceb64c7b414f100e69ac5c3b2b36fb8 | 3,632,571 |
import html
def update_stream_metadata(stream_names):
"""
Updates the sidebar with metadata from a board live stream
"""
if not stream_names[0]:
return html.P("Metadata will appear here when you pick a stream"),
print(f"Getting metadata for {stream_names[0]}")
metadata = cfg.redis_ins... | f0db85b232d00deebc9f970c9ab92a472e717288 | 3,632,572 |
def nested_field_map(name: str) -> Mapper:
"""
Arguments
---------
name : str
Name of the property.
Returns
-------
Mapper
Field map.
See Also
--------
field_map
"""
return field_map(
name,
python_to_api=lambda x: [[x]],
api_to_... | 7af0a3e8df4f4bc8228a3473d75bbab527bf0eee | 3,632,573 |
def socket_state(realsock, waitfor="rw", timeout=0.0):
"""
<Purpose>
Checks if the given socket would block on a send() or recv().
In the case of a listening socket, read_will_block equates to
accept_will_block.
<Arguments>
realsock:
A real socket.socket() object to check for.
... | fc2fa9162d3228021c6738e0e2453cabae907899 | 3,632,574 |
def wrap_with_threadpool(obj, worker_threads=1):
"""
Wraps a class in an async executor so that it can be safely used in an event loop like asyncio.
"""
async_executor = ThreadPoolExecutor(worker_threads)
return AsyncWrapper(obj, executor=async_executor), async_executor | 744a428535aa70d7b130e12bb9c144aac3df4d96 | 3,632,575 |
import re
def file_read(lines):
""" Function for the file reading process
Strips file to get ONLY the text; No timestamps or sentence indexes added so returned string is only the
caption text.
"""
# new_text = ""
text_list = []
for line in lines:
if re.search('^[0-9]', line) is No... | 7d37bb79c6b1cdd43d7b813e03bf3d8b18f5a6ed | 3,632,576 |
from sys import exc_info
def ipn(request):
"""PayPal IPN (Instant Payment Notification)
Cornfirms that payment has been completed and marks invoice as paid.
Adapted from IPN cgi script provided at http://aspn.activestate.com/ASPN/Cookbook/Python/Recipe/456361"""
payment_module = config_get_group('PAYM... | d04e6b8a5bf08a59c081d912e531be2b7e7539ab | 3,632,577 |
def has_file_ext(view, ext):
"""Returns ``True`` if view has file extension ``ext``.
``ext`` may be specified with or without leading ``.``.
"""
if not view.file_name() or not ext.strip().replace('.', ''):
return False
if not ext.startswith('.'):
ext = '.' + ext
return view.fil... | 043edf03874d1ec20e08fcb5795fd205206f7194 | 3,632,578 |
def balanced_accuracy_score(y_true: np.array, y_score: np.array) -> float:
"""
Calculate the balanced accuracy for a ground-truth prediction vector pair.
Args:
y_true (array-like): An N x 1 array of ground truth values.
y_score (array-like): An N x 1 array of predicted values.
Returns:... | 4c7a17e5a5706b8b8cf65d15db51283d7873aca0 | 3,632,579 |
import re
def VOLTS(text):
""" Parse all voltages in tegrastats output
[VDD_name] X/Y
X = Current power consumption in milliwatts.
Y = Average power consumption in milliwatts.
"""
return {name: {'cur': int(cur), 'avg': int(avg)} for name, cur, avg in re.findall(VOLT_RE, text)} | f79934a037b2d995974e833c8b7b045e195637d4 | 3,632,580 |
from typing import Union
async def get_team_id(user_id: int) -> Union[int, None]:
"""Return the team id of a user based on their user id."""
data = await users.find_one(
{"user_id": user_id},
{"team_id": 1, "_id": 0},
)
if data:
team_id = data.get("team_id")
else:
... | e0905e65edc6ff84d35d25ec43eb98f3898295af | 3,632,581 |
def _clone_static_fields(ex: TensorDict,) -> TensorDict:
"""Clone static fields to each ray.
Args:
ex: A single-camera or multi-camera example. Must have the following fields
-- frame_name, scene_name.
Returns:
Modified version of `ex` with `*_name` features cloned once per pixel.
"""
# Identi... | 126d564e4704ee3a7c878630cadcd3adcb58eeaf | 3,632,582 |
def get_atom_types_selected(smi_file, database):
""" Determines the atom types present in an input SMILES file.
Args:
smi_file (str) : Full path/filename to SMILES file.
"""
# list of atom types to be selected
if database == "GDB-13":
atom_types = ['H', 'C', 'N', 'O', 'Cl']
p... | 26a92a44db7c4f187f21e6dfe8dd64694fabc29a | 3,632,583 |
def run_profile(times, schedule, msid, model_spec, init, pseudo=None):
""" Run a Xija model for a given time and state profile.
:param times: Array of time values, in seconds from '1997:365:23:58:56.816' (cxotime.CxoTime epoch)
:type times: np.ndarray
:param schedule: Dictionary of pitch, roll, etc. va... | 92ffe057738183d50aac40693d572a232354e621 | 3,632,584 |
def extract_optimized_structure(out_file, n_atoms, atom_labels):
"""
After waiting for the constrained optimization to finish, the
resulting structure from the constrained optimization is
extracted and saved as .xyz file ready for TS optimization.
"""
optimized_xyz_file = out_file[:-4]+".xyz"
... | 203dfd85987c29ec4f2479ca47be0d497a230480 | 3,632,585 |
def get_genes(exp_file, samples, threshold, max_only):
"""
Reads in and parses the .bed expression file.
File format expected to be:
Whose format is tab seperated columns with header line:
CHR START STOP GENE <sample 1> <sample 2> ... <sample n>
Args:
exp_file (str): Name... | 62b27eef9c863078c98dee0d09bada5e058909e2 | 3,632,586 |
def conv_name_to_c(name):
"""Convert a device-tree name to a C identifier
This uses multiple replace() calls instead of re.sub() since it is faster
(400ms for 1m calls versus 1000ms for the 're' version).
Args:
name: Name to convert
Return:
String containing the C version of this... | 150af670d8befea7374bbb5b13da9d6e0734863e | 3,632,587 |
from typing import Tuple
from typing import Optional
from typing import List
import io
from re import I
import textwrap
def generate(
symbol_table: intermediate.SymbolTable, namespace: csharp_common.NamespaceIdentifier
) -> Tuple[Optional[str], Optional[List[Error]]]:
"""
Generate the C# code of the visit... | 53e905a0ad37b5f6e47220439747a004db7f8203 | 3,632,588 |
def get_account_id(role_arn):
"""
Returns the account ID for a given role ARN.
"""
# The format of an IAM role ARN is
#
# arn:partition:service:region:account:resource
#
# Where:
#
# - 'arn' is a literal string
# - 'service' is always 'iam' for IAM resources
# - 'regi... | 623eb66eefd59b9416deb478c527062ae4454df7 | 3,632,589 |
def retrieve_context_topology_node_total_potential_capacity_total_potential_capacity(uuid, node_uuid): # noqa: E501
"""Retrieve total-potential-capacity
Retrieve operation of resource: total-potential-capacity # noqa: E501
:param uuid: ID of uuid
:type uuid: str
:param node_uuid: ID of node_uuid
... | 5a4cdee9e14783598ad622fd7faacc5c11b2ed70 | 3,632,590 |
def GHP_Op_max(Q_max_GHP_W, tsup_K, tground_K):
"""
For the operation of a Geothermal heat pump (GSHP) at maximum capacity supplying DHN.
:type tsup_K : float
:param tsup_K: supply temperature to the DHN (hot)
:type tground_K : float
:param tground_K: ground temperature
:type nProbes: float... | 3025a70d8d32030cb098b2087e0d9e0eef16b315 | 3,632,591 |
def attention_lm_decoder(decoder_input,
decoder_self_attention_bias,
hparams,
name="decoder"):
"""A stack of attention_lm layers.
Args:
decoder_input: a Tensor
decoder_self_attention_bias: bias Tensor for self-attention
(see c... | 90ff631cdf8898dfde86e965ad70c317936f0b1c | 3,632,592 |
from typing import Any
def list_to_dict(data: list, value: Any = {}) -> dict:
"""Convert list to a dictionary.
Parameters
----------
data: list
Data type to convert
value: typing.Any
Default value for the dict keys
Returns
-------
dictionary : dict
Dictionary ... | 1e73bb6ca98b5e2d9b1e0f8d4cb19fc044a9ce63 | 3,632,593 |
def Routing_Meta():
"""Routing_Meta() -> MetaObject"""
return _DataModel.Routing_Meta() | f5fc17eb8dc8e428e03ec6fe37cb9dec2c32f355 | 3,632,594 |
def get_tag_name(tag):
"""
Extract the name portion of a tag URI.
Parameters
----------
tag : str
Returns
-------
str
"""
return tag[tag.rfind("/") + 1:tag.rfind("-")] | e24f0ae84ed096ec71f860291d1e476c75bf8370 | 3,632,595 |
import requests
def create_user(token, user_name, maps_to_id):
"""
Creates the user account in Keycloak
"""
users_url = '{keycloak}/auth/admin/realms/{realm}/users'.format(
keycloak=KEYCLOAK['SERVICE_ACCOUNT_KEYCLOAK_API_BASE'],
realm=KEYCLOAK['SERVICE_ACCOUNT_REALM'])
headers = {... | e7a4b9cce99343156dc3933d7726cbc8ff5a1597 | 3,632,596 |
import os
def construct_url(test):
"""Construct URL for the REST API call."""
server_env_var = test["Server"]
server_url = os.environ.get(server_env_var)
if server_url is None:
log.error("The following environment variable is not set {var}".format(var=server_env_var))
return None
... | 2623313d9c34170b87bfb756905da2802cc1b805 | 3,632,597 |
def view_profile(request, username=None):
"""view a user's profile
"""
message = "You must select a user or be logged in to view a profile."
if not username:
if not request.user:
messages.info(request, message)
return redirect("collections")
user = request.user
... | 5ab171f5d1f414100b8c8e36b652511b3df37a9b | 3,632,598 |
import torch
def bf_shannon_entropy(w: 'Tensor[N, N]') -> 'Tensor[1]':
"""
Compute the Shannon entropy of w.
Warning: this method is very inefficient.
It should only be used on small examples, e.g., for testing purposes.
"""
Z = torch.zeros(1).double().to(device)
H = torch.zeros(1).double(... | b606c97cd43ead270b82d73bf9af2a0aed2b9a08 | 3,632,599 |
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