content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def _is_new_prototype(caller):
"""Check if prototype is marked as new or was loaded from a saved one."""
return hasattr(caller.ndb._menutree, "olc_new") | 1282db1ce6ae2e5f0bb570b036d7166a53287229 | 69,900 |
def rotate_from(points, rotation_transform):
"""Rotate an ndarray of given points(x,y) from a given rotation"""
if type(points) != np.ndarray:
raise TypeError("rotate_from: takes an numpy.ndarray")
new_points = []
for point in points:
point_mat = np.mat([[point[0]],[point[1]],[0]], dtype... | 42f04a44a527a74b8a447d284a7484823c57b17f | 69,901 |
from typing import Union
def pix_rad_to_physical(im_prod: Union[Image, RateMap, ExpMap], pix_rad: Quantity, out_unit: Union[UnitBase, str],
coord: Quantity, z: Union[float, int] = None, cosmo=None) -> Quantity:
"""
Pure convenience function to convert a list of pixel radii to whatever ... | fdac0d35890acee58ab786d0c5fad953cc8c2721 | 69,902 |
import sys
import re
import random
def non_aminoacid_converter(seq, amino_con):
""" Converts Non amino acid characters from protein sequence """
if amino_con == '':
sys.stderr.write("usage: Provide a choice for replacing non amino acid characters\n")
sys.exit(-1)
flag = 0
if len(ami... | 3575aaa6ecf6c8457197ab5c14b82c6eb19d6a0c | 69,903 |
def _ms_dalt_ind(item):
"""
Sorts elements in a sign-alternating descending order and returns a list
of their previous indices compared to their current ones.
\> Parameters:
`item` : *array-like*
"""
if type(item) == np.ndarray:
raise TypeError('numpy.ndarray not yet supported for... | 31d6836227300415c2b59679150966bcb49e4ded | 69,904 |
def wmt_affine_base_trueadam_longer():
"""Set of hyperparameters."""
hparams = wmt_affine_base_trueadam()
hparams.learning_rate_constant = 4.0
hparams.learning_rate_warmup_steps = 20000
return hparams | a57f749c73288ffd6c397d555844574b63f508a5 | 69,905 |
import os
def check_pack_content_directory_exists(pack, content_type):
"""
Check if a provided pack exists in one of the pack paths.
:param pack: Pack name.
:type pack: ``str``
:param content_type: Content type (actions, sensors, rules).
:type content_type: ``str``
:rtype: ``bool``
... | d705280164036a46ed43641057562c53f80f9228 | 69,906 |
def leave(playerName):
""" Permet de supprimer un joueur dans la partie en cours
...
"""
plId = func.recupIdFromName(playerName)
# Je le passe a 'false' dans la table Participate
db.execute("""UPDATE Participate par SET present = 'false' WHERE par.pl_id = '"""+ str(plId) +"""';""")
return "",200 | 920bc31cb3bfcd9fc6828b65ed930fa2b94ccd72 | 69,907 |
def generator(noise_dim=NOISE_DIM, seed=None):
"""Generate images from a random noise vector.
Inputs:
- z: TensorFlow Tensor of random noise with shape [batch_size, noise_dim]
Returns:
TensorFlow Tensor of generated images, with shape [batch_size, 784].
"""
if seed is not None:
... | 1fc14099e8656fa820446c6698a3de44f60ec5d8 | 69,908 |
def get_route_map_entry_by_search(search=dict()):
"""Return a list of RouteMapEntry's by dict."""
try:
objects = RouteMapEntry.objects.filter()
object_map = build_query_to_datatable_v3(objects, search)
except FieldError as e:
raise ValidationAPIException(str(e))
except Exception... | a144abaee91ce3a564a9e6fb25e1d3c62867d76b | 69,909 |
def generate_slug(obj, slug_length):
""" A function to generate a slug with a given length and make sure it's unique. """
slug = get_random_string(slug_length)
slug_is_not_unique = True
while slug_is_not_unique:
slug_is_not_unique = False
other_objs_with_slug = type(obj).objects.filter(id=slug)
if... | 1913d7e888a2ffa3be02faa88db03f0544ae6991 | 69,910 |
from typing import List
import math
def diversity(individuals:List[Individual]) -> float:
"""Computes the diversity of a population. Higher diversity value the better.
Citations:
J. Hu, J. Zeng, and Y. Tan, ‘‘A diversity-guided particle swarm optimizer for dynamic environments,’’ in Bio-Inspired Com... | 339d00261961a1458faea1e412170b8c2ee21020 | 69,911 |
import os
import random
import torch
def test_it(fsdp_config, input_cls):
"""Test FSDP with input being a list or a dict, only single GPU."""
if torch_version() < (1, 6, 0):
pytest.skip("older pytorch doesn't support reduce_scatter")
# Random port in case the next test run quickly, same port woul... | f634b23d73f1ff8ee51263e0ba38ac278b8f1466 | 69,912 |
import uuid
def submit_job(function_name, kwargs, queue_name='default'):
"""
Parameters
----------
function_name: string
Name of the function that will be expected
by the waiting process.
kwargs: dict
Keyword arguments to pass to the function.
queue_name: string ['defau... | e1455a62ec699c1b293149bd4727a682cf7a1b1a | 69,913 |
def read_md_file(filepath):
"""Reads an md file and returns the string."""
with open(filepath, "r", encoding="utf-8") as md_file:
md_file_str = md_file.read()
return md_file_str | 35ad658f850be903b6b183e8970c86c894530c62 | 69,914 |
def regression_loss(pred_boxes, gt_boxes, weights):
"""
Regression loss (Smooth L1 loss: also known as huber loss)
Args:
pred_boxes: [# anchors, 4]
gt_boxes: [# anchors, 4]
weights: Tensor of weights multiplied by loss with shape [# anchors]
"""
loss = tf.losses.huber_loss(pr... | e380c9b91269ac6583c1a89b85d2deea3c2db5aa | 69,915 |
def countObjectTypes(objects):
"""Given a list of objects, returns a count of how many of each type there are."""
results = {"rootgroup": 0, "group": 0, "job": 0}
for obj in objects:
if isJob(obj):
results["job"] += 1
elif isGroup(obj):
results["group"] += 1
e... | ab44060e6581d8cbfc8e83d9bb16e308789c6e13 | 69,916 |
def input_fn(split, mode, data_dir, batch_size, cutout_size, num_epochs=1):
"""Input_fn using the tf.data input pipeline for CIFAR-10 dataset.
Args:
mode: train, valid or test.
data_dir: The directory containing the input data.
batch_size: The number of samples per batch.
num_epochs: The number of ... | 6937c6613868f8b852c0c29b17837dac493b9c31 | 69,917 |
import array
from pathlib import Path
def get(java, name):
"""Returns the value of a Java node property as a Python data type."""
datatype = java.getValueType(name)
if datatype == 'Boolean':
return java.getBoolean(name)
elif datatype == 'BooleanArray':
return array(java.getBooleanArray... | aa70914ffe3180de22d7edea0f3c06c9482cdd4c | 69,918 |
def grid(gdf):
"""
sampling the GNSS data by grids
Parameters
----------
gdf: geodataframe
geodataframe of all gnss data(population)
Returns
-------
list:
list of each grid which contains all related gnss data
"""
#create new column to... | f613359a0061fd2975607044ffcaa8b25b53dcfc | 69,919 |
def convertColorTable(table):
"""Converts a Kaitai Struct-parsed color table to a list of matplotlib color maps"""
cdict = {
"red": [],
"green": [],
"blue": []
}
countOfColors = len(table.colors)
maxColorIndex = countOfColors - 1
for i, col in enumerate(table.colors):
for compName in cdict:
comp = geta... | 2a513a4ecaf60a81c7bf650ba524af29ff51e96f | 69,920 |
def _filter_label_set_to_most_specific(
label_set,
reversed_normalizer):
"""Filters label set to most specific.
Args:
label_set: set of all labels given to protein.
reversed_normalizer: output of reverse_map(label_normalizer). Helps this
function run fast.
Returns:
Filtered set of labe... | 84397b8a6c208b88c13456805be592d9f2e9a505 | 69,921 |
def get_tasks_for_weekly_report(model_obj, company, date_from, date_to):
"""Отдает отфильтрованный кверисет с уникальными датой и описанием"""
return model_obj.objects.select_related(
'tag', 'employees').filter(
date__gte=date_from).filter(
date__lte=date_to).filter(
... | 3b46205d3c1bb5b5d472b350371561167aa2fb5b | 69,922 |
from re import T
def local_op_of_op(node):
"""
Prod(Prod()) -> single Prod()
or
Sum(Sum()) -> single Sum()
"""
if isinstance(node.op, T.elemwise.Prod) or isinstance(node.op, T.Sum):
opt_type = T.Sum if isinstance(node.op, T.Sum) else T.elemwise.Prod
node_inps, = node.inputs
... | 59c795e03d5ec26dff8d32aafd5310fb1ab6ccb3 | 69,923 |
def detectFallingSeq(points_list):
"""Find falling temperatures sequences in given list and stores beginnings and ends of them in list.
Always with format [seq1 start index, seq1 end index, seq2 start index, seq2 end index, ...]
:param points_list: list of pipe temperatures
:return: list of indexes
... | e940497b72745af1669062373a6aca025ac0626c | 69,924 |
async def find_app(hass: HomeAssistantType, api):
"""Find an existing SmartApp for this installation of hass."""
apps = await api.apps()
for app in [app for app in apps if app.app_name.startswith(APP_NAME_PREFIX)]:
# Load settings to compare instance id
settings = await app.settings()
... | 57787205e3fd9ea94607d2c4cc62e60d8bd48257 | 69,925 |
def count_symbols(atoms, exclude=()):
"""Count symbols in atoms object, excluding a set of indices
Parameters:
atoms: Atoms object to be grouped
exclude: List of indices to be excluded from the counting
Returns:
Tuple of (symbols, symbolcount)
symbols: The unique symbols in... | 31f7c116f07788171828f0e116ef28a43eb0e313 | 69,926 |
def extract_bboxes(mask):
"""Compute bounding boxes from masks.
Args:
mask [height, width, num_instances]:
Mask pixels are either 1 or 0.
Returns:
bounding box array [num_instances, (y1, x1, y2, x2)].
"""
boxes = np.zeros([mask.shape[-1], 4], dtype=np.int32)
for i i... | f303ba362be567d8b981630201ba913c4b987bf0 | 69,927 |
import functools
def ignore_transport(transport):
"""
If test function is wrapped into this decorator then
it should not be tested if test is performed for
specified transport
"""
def wrapper(func):
@functools.wraps(func)
def test_method(*args, **kwargs):
if GRAB_T... | b39d1b7db2b82722e39159cdf7b529d5f88caa65 | 69,928 |
import ntpath
def lookup_folder(event, filesystem):
"""Lookup the parent folder in the filesystem content."""
for dirent in filesystem[event.parent_inode]:
if dirent.type == 'd' and dirent.allocated:
return ntpath.join(dirent.path, event.name) | e18df4610bba9cf71e85fe0038a5daf798822bd3 | 69,929 |
import json
def parse_response(func):
"""Parse receive response to json format."""
def wrapper(*args, **kwargs):
response = func(*args, **kwargs)
try:
return response.json()
except json.JSONDecodeError:
return {
"success": False
}
... | 7ad55e524c52cf151e2de8c29d6c2ea786b21a9a | 69,930 |
def ret (numerator,denominator,code):
"""
Divides two dataframes by transposing and using linear algebra rules
"""
df_tradingret = numerator.T / denominator -1
df_tradingret = df_tradingret.T
df_tradingret = pd.concat ([df_tradingret, code], axis=1)
return df_tradingret | 243ab30c44cda82ff7bbf8174a3644efbc22811b | 69,931 |
def read_xyz(filedesc):
"""Takes a xyz-style file and creates an Atoms object.
Args:
filedesc: An open readable file object from a xyz formatted file.
Returns:
An Atoms object with the appropriate atom labels, masses and positions.
"""
natoms = filedesc.readline()
if natoms == "":
... | 44444a452bc364ac9df76674ed60e0482666a34d | 69,932 |
import hashlib
def create_unique_shape_id(line_string: LineString):
"""
Creates a unique hash id using the coordinates of the geomtery
Args:
line_string: Line Geometry as a LineString
Returns: string
"""
x1, y1 = list(line_string.coords)[0] # first co-ordinate (A node)
x2, y2 = lis... | afb57e4bef7baab401467e073d484a4131a1d32e | 69,933 |
import logging
import sys
def initialize_logger(log_file, logAppName):
"""Set up logging.
Returns:
logger (:obj:`logging object`): log with file and stream handlers
"""
logger = logging.getLogger(logAppName)
logger.setLevel(logging.DEBUG)
file_handler = logging.FileHandler(log_file)
... | 433e575edece0262d3b48ad923fe2ecec36bf7ae | 69,934 |
def p27():
""" a and b s.t n*n + a*n + b produces the longest sequence of primes """
maxLen, res = 0, 0
for a in xrange(-999, 1000):
for b in xrange(-999, 1000):
seqLen = getLen(a, b)
if seqLen > maxLen:
maxLen = seqLen
res = a*b
return res | 1db5ad6cc2d8484f5494aab5234d3b88e7c97f2f | 69,935 |
def gate_expand_2toN(U, N, control, target):
"""
Create a Qobj representing a two-qubit gate that act on a system with N
qubits.
Parameters
----------
U : Qobj
The two-qubit gate
N : integer
The number of qubits in the target space.
control : integer
The index ... | 3501a6b785092b95ce9f95d8b1b617a78c5d8863 | 69,936 |
import html
def test_cdcb003_dict_callback_strict_true(dash_duo):
""" Test if strict is True an extra output keys in output dictionary causes a KeyError
At this point I don't know how to write an assertion for this
"""
lock = Lock()
app = dash.Dash(__name__, plugins=[DashCallbackPlugin()])
ap... | 044b8ee80d8eebcd32d67aae8494aacfdf532c14 | 69,937 |
def extract_user(ops, json_data):
""" Extract user from JSON data.
"""
if json_data is None:
return None
if 'required_posting_auths' not in ops or 'required_auths' not in ops:
return None
if ops['required_posting_auths'] is None or ops['required_auths'] is None:
return None
... | 0722afa2f174628670658fbbc0f1a0ab80cd36fe | 69,938 |
from itertools import izip
def _slow_pivot(index, columns, values):
"""
Produce 'pivot' table based on 3 columns of this DataFrame.
Uses unique values from index / columns and fills with values.
Parameters
----------
index : string or object
Column name to use to make new frame's inde... | f5eab1b016424c0cd4922b537aa573b66f0a663d | 69,939 |
def calculate_adjusted_elo_rating(player_one_rating: int, player_two_rating: int, player_one_win: bool, k_factor=32) -> (int, int):
"""
Calculates new elo scores for two players
:param player_one_rating: first player's original rating
:param player_two_rating: second player's origin rating
:param player_one_... | 2792981c6b50836897c5c2396e35bcce7026a716 | 69,940 |
import io
def usgs_lead_call(*, resp, year, **_):
"""
Convert response for calling url to pandas dataframe, begin parsing
df into FBA format
:param url: string, url
:param resp: df, response from url call
:param year: year
:return: pandas dataframe of original source data
"""
df_ra... | 500e8a61c287b4311f6abd8fe32362b55ac5b544 | 69,941 |
def ParseDeviceBlocked(blocked, enable_device):
"""Returns the correct enabled state enum based on args."""
if enable_device is None and blocked is None:
return None
elif enable_device is None or blocked is None:
# In this case there are no default arguments so we should use or.
return blocked is True... | 4554ca5e33194fea77516e910516f3937cd61f3a | 69,942 |
import random
def blobs(
width=8,
height=8,
k=3,
min_extend=0,
max_extend=1,
random_seed=None):
"""Generates a 1 to k number of blobs on a 2D grid
Args:
width: width of grid generated
height: height of grid generated
k: number of random ... | 44fa440913dbf5ecfc16e03972a48c6713d47406 | 69,943 |
import torch
from re import T
import pickle
import os
def get_data(
data_type,
train_fraction=1,
added_edge_fraction=0,
feature_noise_ratio=0,
**kwargs):
"""Get the pytorch-geometric data object.
Args:
data_type: Data type. Choose from "Cora", "Pubmed", "citeseer". If want the... | ace3dd2bdf9a879c07d8fc6c83a4f0b08ee028ea | 69,944 |
def load_env() -> Environ:
"""Load environment variables and expand hierarchy as namespace."""
return Environ(prefix='PLOT').expand() | abda28d07ac2205f9bbf45b8dea8c2c6b03ec697 | 69,945 |
def squared_pearson_correlation_r2(results, labels, pos=1, neg=0):
"""
Citation: MITTLBÖCK, M. and SCHEMPER, M. (1996), EXPLAINED VARIATION FOR LOGISTIC REGRESSION. Statist. Med., 15: 1987-1997.
doi:10.1002/(SICI)1097-0258(19961015)15:19<1987::AID-SIM318>3.0.CO;2-9.
https://pdfs.semanticscholar.org/39f1... | b12de91d6c2e781fe5681f3ac58b07d32bfbe493 | 69,946 |
from typing import Dict
from typing import Any
def grains_filter_by(
salt_mock: SaltMock,
lookup_dict: Dict[str, Any],
grain: str = "os_family",
**kwargs: Any,
) -> Any:
"""Read grains from a SaltMock instance to implement grains.filter_by.
See https://github.com/saltstack/salt/blob/v3002.5/s... | bcbf632adf2b5397f67c2b5d223f8cb215884b81 | 69,947 |
def exists(reader_name: str) -> bool:
"""Check whether the given reader exists
Args:
reader_name: Name of reader.
Returns:
True if reader exists, False otherwise.
"""
return plugins.exists(package_name=__name__, plugin_name=reader_name) | 99ff673a4110a601500ae4c3e3367c64c21b4d0d | 69,948 |
import os
def get_dask_Client(timeout=30, n_workers=None, threads_per_worker=1, processes=True, create_cluster=True):
""" Get a Dask.distributed Client for the scheduler defined externally, otherwise create
The environment variable ARL_DASK_SCHEDULER is interpreted as pointing to the scheduler.
and a cli... | 054d660565fab7baf28c95227f98552ed2c22c65 | 69,949 |
def is_broken_link(url):
"""Determine whether the link returns a 404 error."""
try:
request = urllib_request.Request(
url, headers={'User-Agent': 'Mozilla/5.0'})
urllib_request.urlopen(request).read()
return False
except urllib_request.URLError:
return True
ex... | 12afac7aec8b8465a968e6bb7a2df9e9bdb0de8d | 69,950 |
def get_education_degrees(education_counts, educations):
"""
Gets a map count of the formal educations that was provided in the survey
"""
education_degrees = defaultdict(int)
for e in educations:
for idx in education_counts.index:
if idx in educations[e]:
educati... | c9f4948fd19de12ab08f988472e5892e7406b92a | 69,951 |
import re
def getNormform(synonym):
"""
"""
a = re.sub("[^a-z0-9]", "", synonym[0:255].lower())
return " ".join(a.split()) | 36d60ad20ff8adee5e4d6f009119026db8a1b874 | 69,952 |
from typing import Union
import json
async def session_remove_all(
handle: SessionHandle,
category: str,
tag_filter: Union[str, dict] = None,
) -> int:
"""Remove all matching rows in the Store."""
category = encode_str(category)
if isinstance(tag_filter, dict):
tag_filter = json.dumps(... | 3a5a02328ac40273b3efaa27c7091af0fd07bab9 | 69,953 |
def tarjans(complexes, products):
""" Tarjans algorithm to find strongly connected components.
Dirctly from the peppercornenumerator project.
"""
stack, SCCs = [], []
def strongconnect(at, index):
stack.append(at)
at.index = index
at.llink = index
index += 1
... | 1f81bb8734ad0383dc7aa60e116ac1ac0c20da78 | 69,954 |
def verifyNodesValueMatch (datafile, pnode, cnode, cvalue, rnode, rvalue, bnode, bvalue, dnode=None, dvalue=None):
"""
Searches XML file for the parent node. Finds the 1st child node and checks its value
if value is a match, then search for second child and check if its value matches
datafile = xml file... | a8b5e014ce2993431544025d6b9b558da7e8ba23 | 69,955 |
def conjugate_gradient_ok(f_ax, b_vec, cg_iters=10, callback=None, verbose=False, residual_tol=1e-10):
"""
conjugate gradient calculation (Ax = b), bases on
https://epubs.siam.org/doi/book/10.1137/1.9781611971446 Demmel p 312
:param f_ax: (function) The function describing the Matrix A dot the vector x... | c8815023562b58214584f7f13fd8efe91835f00e | 69,956 |
def parse_grid(rb):
""" Parse grid location
:param _RawBinaryData rb: Binary data describing the location
:returns: Grid location
:rtype: GridLocation
"""
assert rb.location_type == LocationType.GRID
bl = _parse_absolute_coordinates(rb)
if rb.num_bytes == LARGE_GRID_SIZ... | 8c1d047e50d47ebed33ebf891ee690c36afff5e9 | 69,957 |
from typing import Sequence
from typing import MutableMapping
from typing import List
def _parse_cell(
source: Sequence[str],
cell_number: int,
temporary_lines: MutableMapping[int, Sequence[NewMagicHandler]],
command: str,
) -> str:
"""
Parse cell, replacing line magics with python code as pla... | f5cb8ba019852db89608e50de34415ff6acdc55a | 69,958 |
def draw_prediction_on_image(
image, keypoints_with_scores, crop_region=None, close_figure=False,
output_image_height=None):
"""Draws the keypoint predictions on image.
Args:
image: A numpy array with shape [height, width, channel] representing the
pixel values of the input image.... | e295c8ae1d44b854fba4d8dd19bc85c9b0195c97 | 69,959 |
def process_spectrum(spectrum: MsmsSpectrum, is_library: bool) -> MsmsSpectrum:
"""
Process the peaks of the MS/MS spectrum according to the config.
Parameters
----------
spectrum : MsmsSpectrum
The spectrum that will be processed.
is_library : bool
Flag specifying whether the s... | ebad54e42ff763d7e27a1e7dd84e8e8e8abce766 | 69,960 |
def generate_sensors(k = 7, d = 2):
"""
Generate sensor locations.
Input:
k: The number of sensors.
d: The spatial dimension.
Output:
sensor_loc: k * d numpy array.
"""
sensor_loc = 100*np.random.randn(k,d)
return sensor_loc | c7e3d71e565b2d7fd1462f5cdeef69a6cb665910 | 69,961 |
import cmd
import re
def parse_csr (csr):
"""parse the CSR to find all domains"""
out = cmd(["openssl", "req", "-in", csr, "-noout", "-text"], err=f"error loading {csr}")
domains = set([])
# Find Common Name in CSR
cn = re.search(r"Subject:.*? CN\s?=\s?([^\s,;/]+)", out.decode("utf-8"))
if cn... | deb8035c3f4b8fa2929ccae1aa09f01789afc6cb | 69,962 |
import functools
def return_as_coroutine(return_value=None):
"""Creates a function that behaves like an asyncio coroutine and returns the given value.
Typically used as a side effect of a mocked coroutine like this:
# in module mymod:
async def my_coro_under_test():
await asyncio... | 92011e2fd12e85cd8afc4bc3a1f98d23e2d38160 | 69,963 |
import torch
def unscale_transform(x: torch.Tensor, lower: torch.Tensor, upper: torch.Tensor) -> torch.Tensor:
"""
Denormalizes a given input tensor from range of [-1, 1] to (lower, upper).
@note It uses pytorch broadcasting functionality to deal with batched input.
Args:
x: Input tensor of ... | 86aa3a1ac0e15b9f19f5970ece2388de2de3f54d | 69,964 |
def save(
name: str,
model: "xgb.core.Booster",
*,
booster_params: t.Optional[t.Dict[str, t.Union[str, int]]] = None,
metadata: t.Optional[t.Dict[str, t.Any]] = None,
model_store: "ModelStore" = Provide[BentoMLContainer.model_store],
) -> Tag:
"""
Save a model instance to BentoML modelst... | 8f60a8c00345c997262955e87693cba8c5f949e4 | 69,965 |
def defaultformatter(default_factory):
"""The default factory is called without arguments to produce
a new value when a field value is not present.
All remaining field are treated the same as if they were
passed to the str.format, including keyword arguments.
"""
return DefaultFormatter(default... | 800244382025a84583b2cdac6454eb18a105d2ea | 69,966 |
def sigmoid_derivative(x):
"""
Compute the gradient (also called the slope or derivative) of the sigmoid function with respect to its input x.
You can store the output of the sigmoid function into variables and then use it to calculate the gradient.
Arguments:
x -- A scalar or numpy array
... | 0dbc00a502a3eea4d99739a98c541af28264ea76 | 69,967 |
def hidden_digits(time_string):
""" converts time with unknown digits to max time with respect to hours and minutes given starting digits
Args:
time_string (str): a string representing an unknown time
Returns:
max_time_string (str): a string with filled in missing digits for max time
"""... | 15fdefb340ab5fe66b562f0fa642210db138c590 | 69,968 |
def is_valid_target(url, request):
"""
Take a URL string and check if the path component
seems to exist on the current site.
Returns False if the URL raises a 404, and a UrlResolver object
if the URL seems to exist.
"""
# First, set up a variable for the tentative status:
accepts_webmen... | 7592979c9e71c186f71a419875617ac86bd27498 | 69,969 |
def find_tuple_with_max_vl(base, T, key):
"""
Scan through the whole table T, and find the i-th tuple that maximizes VL(base, i).
Returns
-------
:return best: int
Unique Id of the found tuple
"""
max_vl = 0
best = None
for k in T.keys():
if k != key:
v... | 89b0a2b9334c9faeef6065e9e1d92854e6f221e2 | 69,970 |
def classification_signature_fn(examples, unused_features, predictions):
"""Creates classification signature from given examples and predictions.
Args:
examples: `Output`.
unused_features: `dict` of `Output`s.
predictions: `Output` or dict of tensors that contains the classes tensor
as in {'class... | 54802e9846d8604729e7ec134c05b5a07da3d182 | 69,971 |
def static_graph(*args, **kwargs):
"""Decorator to mark a Chain's ``__call__()`` as a static sub-graph.
This decorator marks the define-by-run code inside the `__call__()`
method of a Chain instance as corresponding to a static computation
graph or sub-graph. Such a chain will be referred to as a 'stat... | 7fee1141ccd09b7ab7f47a6ab8e96243293eea7f | 69,972 |
def action(method):
""" Marks an agent instance method to be registered as an action
:param method:
:return:
"""
method._register_action = True
return method | 15f32f6acd7e31e50ef3b61d0de04e029e65249a | 69,973 |
import pandas
import urllib
def get_sensor_data(
aranet_conf, sensor_id, from_time, to_time, timezone="0000",
metrics=list(DEFAULT_METRICS_DICT.keys()),
**kwargs) -> pandas.DataFrame:
"""Get the data for a given sensor from the Aranet Cloud.
Args:
aranet_conf: Object of the Ar... | a5254e3936a2d47c3bd40807cda7547e29dab4db | 69,974 |
import subprocess
import argparse
def is_valid_dokku(dokku_command=None):
"""
Checks whether dokku_command is a well defined path to an executable.
args:
- dokku_command (optional): str Path to dokku command location
returns:
- bool Whether dokku_command is a valid dokku command
... | 6bb5cafeee22034012c1a7e4eb8271064b104701 | 69,975 |
def OutputVector(r, name, mode="python", initial_tabs=3, max_index=30, replace_indices=True, assignment_op="="):
""" This method converts into text the RHS vector
Keyword arguments:
rhs -- The RHS vector
name -- The name of the variables
mode -- The mode of output
initial_tabs -- The number of ... | 4043f2d1166a1ebc65ae3120156eb3ebe4402eba | 69,976 |
def create_connection(url, timeout=None, **options):
"""
connect to url and return websocket object.
Connect to url and return the WebSocket object.
Passing optional timeout parameter will set the timeout on the socket.
If no timeout is supplied, the global default timeout setting returned
by g... | 2faaa073de7231d3446bcce505c46df9bfcb58db | 69,977 |
def _has_basal(morph_path):
"""Check if neuron has basal dendrites."""
_morph = Morphology(morph_path)
for root in _morph.root_sections:
if root.type == SectionType.basal_dendrite:
return True
return False | 799230bd4f16be92e559cb1d199f9626cae25a97 | 69,978 |
import re
def filter_illegal_chars(dirty, repl=''):
"""Remove character which allow to inject code which would be run by
displaying on the page
"""
illegal_chars_re = re.compile('[<>="]')
return illegal_chars_re.sub(repl, dirty) | d389df644959850ccd4de6dd7ab22f0276b47435 | 69,979 |
def get_congress_search(
congress=None, chamber=None, versions=None, text=None, page=None, page_size=None
) -> BillSearchList: # noqa: E501
"""Your GET endpoint
Search for the different bills # noqa: E501
:param congress: Comma separated list of sessions to filter by
:type congress: str
:para... | 5420907bfbf5c02691f0328be0cdbd2cec2c99f0 | 69,980 |
def ParseXMLString(raw_xml):
"""Parses raw_xml and returns an ElementTree node that includes comments."""
return ET.fromstring(raw_xml, _CommentedXMLParser()) | 84f76b8ef5d1ed57a83c4e1bdf27571db3ea7890 | 69,981 |
from typing import OrderedDict
def _flatten_obs(obs, space):
"""
Flatten observations, depending on the observation space.
:param obs: (list<X> or tuple<X> where X is dict<ndarray>, tuple<ndarray>
or ndarray) observations.
A list or tuple of observations, one per environment.
... | 1eb81c79f284226887a82a4b7cd7b7a748c4fa00 | 69,982 |
from typing import Optional
def generate_captcha(seed: Optional[int] = None,
length: int = 4,
format: str = "png"):
"""生成验证码（先生成字符，再生成图片）"""
code = generate_captcha_code(seed, length)
capthca_key = uuid4() # 理论上有碰撞的可能，但验证码嘛，换一个就是了。
key = current_config.CAPTC... | e005603263a5f81cbc901c55c3e1c12065cd80ca | 69,983 |
import re
import logging
import functools
def match(func=None, regex=None, thread=False):
"""
this decorator is used to create a command the bot will respond to.
"""
def decorator(func):
func.__brutal_event = True
func.__brutal_event_type = 'message'
func.__brutal_trigger = Non... | 8fb06014196ffb1b499ebf172cf4c88f247c100b | 69,984 |
import os
def read_firmware_file_tree(glue_database: str, fw_sha256: str) -> DataFrame:
"""
Reads a firmware file tree from the jsonl files backing the file_tree table defined in the Glue Data Catalog.
:param glue_database: The name of the Glue database from which to read the files, e.g. fimrware_prod.
... | 47e99256e55ed489d11a14a01957877f2effc5a0 | 69,985 |
def gen_task2() -> np.ndarray:
"""Task 2: head of random sequence."""
seq = rand_syms()
return np.concatenate(([2], seq, [seq[0]])) | fe98dbf30be0933f58c06f8914dc8835bcaf12ed | 69,986 |
def download_page(cluster_id):
"""Handle download of the SSH private key
"""
cluster = Cluster.query.filter_by(id=cluster_id).first()
if cluster and cluster.ssh_private_key:
return Response(
cluster.ssh_private_key,
mimetype="text/json",
headers={"Content-disp... | 65636f137234c633e9a23d63c667f3bd4365e1b7 | 69,987 |
from establishment.errors.errors import BaseError
def login_required_ajax(function=None):
"""
Just make sure the user is authenticated to access a certain ajax view
"""
def _decorator(view_func):
def _wrapped_view(request, *args, **kwargs):
if not request.is_ajax():
... | 238e764b855c8766165d105f9094be10ffee75ff | 69,988 |
def analyze_SENTINEL_temperature(sen_directory, sen_shape_path, daytime_S3):
"""
returns the temperature value for each pixel of each station for each SENTINEL scene
prints an array for the scenes according to the stations
:return:
returns three arrays (1st array displayed for each station is the te... | c270a6176170a73c1cbda728096a010af76e919f | 69,989 |
def exp_np_array_list(lst, power):
"""
Raise elements of a list (of np.arrays - elementwise) to power
@param lst: list of np.arrays
@param power: scalar, to which power the elements should be raised
@rtype list of np.arrays
"""
result = []
for nparr in lst:
result.append(nparr **... | 8c8b80c217f4a381e8514c7fff06dc98114087d9 | 69,990 |
def max_layout_dimensions(dimensions):
"""
Take the maximum of a list of :class:`.LayoutDimension` instances.
"""
min_ = max([d.min for d in dimensions if d.min is not None])
max_ = max([d.max for d in dimensions if d.max is not None])
preferred = max([d.preferred for d in dimensions])
retu... | 67e309465f400334dcd68ff8c8197b5cd641b205 | 69,991 |
import os
import re
def get_ch_names(path, dir):
"""获取文件中文名称，如无则返回文件名"""
file_ch_names = []
reg = r"new Env\(\"[\S]+?\"\)"
ch_name = False
for file in dir:
try:
if os.path.isdir(f"{path}/{file}"):
file_ch_names.append(file)
elif file.endswith(".js") ... | bae20e2a03b188aeb1f6dae33f6c3a66d26ca48e | 69,992 |
def split_dataset(dataset: Dataset, val_split: float = 0.1, seed: int = 17):
"""Splits dataset into train and validation ones and transform them into
dataloaders.
Parameters
----------
dataset : Dataset
Dataset to split.
val_split : float
Ratio used in spliting.
seed : int
... | 5b69ae352c96511546045ecba18a09ced6b1e15a | 69,993 |
def check_if_significant(data, thresh=1e-5):
"""
trim data based on threshold.
Args:
pandas DataFrame: data needs to be trimmed.
threshold (float): a constant. Default = 1e-5.
Returns:
pandas DataFrame: data after trimming.
pandas DataFrame: corrsponding index of data.... | 62494c97559632f2d8d3e542320cb72f3da90eab | 69,994 |
import math
def _cosine_anneal(x: float, min_y: float = 0.0, max_y: float = 1.0) -> float:
"""Implements a cosine decay curve.
Curve is cos(x) on domain [0, pi], stretched to the domain [0, 1] and range [min_y, max_y]. Additionally, param x is
clipped to the interval [0, 1]
"""
x = min(max(x, 0.0... | ea3b6dfb8158c12d447d1a23cb472f0be5ef46d9 | 69,995 |
def log_rebin_pix(lamRange, n, oversample=None, velscale=None, log10=False, newRange=None):
"""
Determine the number of new pixels and their coordinate step when
rebinning a spectrum in geometrically stepped bins. The input
spectrum must be sampled linearly in wavelength. This is primarily
a support routine for ... | 09d46e09cfba6e0fe00c2645ab55446e4cfe6e03 | 69,996 |
def is_image_file(filename):
"""Checks if a file is an image.
Args:
filename (string): path to a file
Returns:
bool: True if the filename ends with a known image extension
"""
filename_lower = filename.lower()
return any(filename_lower.endswith(ext) for ext in IMG_EXTENSI... | d87f4d48737292d619f7641f320b32f0ce760581 | 69,997 |
import csv
def from_line_file(filename, filter_negative=True):
"""
Loads file from directory ** needs input to be a fully qualified file
path.
Returns a new list of tuples (x,y) containing points, where
x = wavenums and y = intensities.
"""
spectra = []
# Read in files row by row
w... | 8ada4018ef0ce4ff874c548f6d12b611dd2ec59d | 69,998 |
from typing import Any
def _convert_v_0_1_imported_options(config: dict[str, Any]) -> Any:
"""Convert a key from the imported configuration."""
code: str | int | None = config.get("code")
force_bypass: LegacyArmingOptions | None = config.get("force_bypass")
no_entry_delay: LegacyArmingOptions | None ... | 8811cee6b9366b9f690f0727ca7a36dae6483859 | 69,999 |
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