content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def system(cmd):
"""Win32 version of os.system() that works with network shares.
Note that this implementation returns None, as meant for use in IPython.
Parameters
----------
cmd : str
A command to be executed in the system shell.
Returns
-------
None : we explicitly do NOT ret... | 591c03e6555a271ae3152890888963928bb66d2e | 3,619,800 |
def make_dataset(name, args):
""" Creates the dataset with the given name.
Parameters
----------
name: the name of the dataset to create.
args: hyper-paremeters for the dataset.
Returns
-------
dataset_fn: a function which creates the specified dataset.
"""
if name not in _data... | 13a06cba585f673a83fcfdbdf1ab32874ac51d65 | 3,619,801 |
def create_df(client, candles):
"""
Создаеv датафрейм для списка свечей
:param dict candles: List of candles from API
:return: DataFrame with candles
"""
df = DataFrame([{
'time': c.time,
'volume': c.volume,
'open': cast_money(client, c.open),
'cl... | 4d84cd1c5368586926fcbfd4104aac74c6f807ef | 3,619,802 |
import select
def current_user(request, user_id=None):
"""Return the list of all the users with their ids.
"""
print("TODO Take time and refact this s...")
session = request.dbsession
if user_id is not None:
userid = user_id
else:
userid = int(request.authenticated_userid... | 8cea15008da2aaa8897a6f88582d4b4154e600f7 | 3,619,803 |
def istext(obj):
"""
Deprecated. Use::
>>> isinstance(obj, str)
after this import:
>>> from future.builtins import str
"""
return isinstance(obj, type(u'')) | 60f3d751f22ad4d120ce7624dd9a07d2c841e206 | 3,619,804 |
def track_to_p_matrix(track, char_map=CHAR_MAP, x_vel_limits=None, y_vel_limits=None,
x_accel_limits=None, y_accel_limits=None, max_total_accel=np.inf):
"""
Converts a map described by a list of strings to P-matrix format for an OpenAI Gym Discrete environment.
Maps are specified usin... | 68cddbbd0b8bd9bd1b0a0cf33c0d5eb4b9a22a31 | 3,619,805 |
def crc16(string, value=0):
"""CRC-16 poly: p(x) = x**16 + x**15 + x**2 + 1
@param string: Data over which to calculate crc.
@param value: Initial CRC value.
"""
crc16_table = []
for byte in range(256):
crc = 0
for _ in range(8):
if (byte ^ crc) & 1:
... | e31ddafc6216b682d9cd0ac24a9fb634f1be1fb8 | 3,619,806 |
def get_fpn_featureMaps(features,num_filt=256):
"""
features: list of different maps produced by a backbone
**Resnet50** : for resnet50 it contains all the 5 feature maps from each block
Return: list of pyramid features
"""
C1,C2,C3,C4,C5 = features
C5d1 = keras.layers.Conv2D(num_filt,(... | 3b265bb62163cc075e8aa608bbbf21b654df4b98 | 3,619,807 |
import time
def calculate_frechet_distance(mu1, sigma1, mu2, sigma2, eps=1e-6):
"""Numpy implementation of the Frechet Distance.
The Frechet distance between two multivariate Gaussians X_1 ~ N(mu_1, C_1)
and X_2 ~ N(mu_2, C_2) is
d^2 = ||mu_1 - mu_2||^2 + Tr(C_1 + C_2 - 2*sqrt(C_1*C_2)).
S... | bd225cd4ecd5af4a9ee9f29137e46807bf534ee9 | 3,619,808 |
def Interface_Static_Standards(*args):
"""
* Initializes all standard static parameters, which can be used by every function. statics specific of a norm or a function must be defined around it
:rtype: void
"""
return _Interface.Interface_Static_Standards(*args) | 85dfea02a10d62203eaf7afe814b7ee25b925cfe | 3,619,809 |
from typing import Sequence
from typing import Dict
from typing import List
def batch_inputs(input_records: Sequence[Dict[K, V]]) -> Dict[K, List[V]]:
"""Batch inputs from list-of-dicts to dict-of-lists."""
assert input_records, 'Must have non-empty batch!'
ret = {}
for k in input_records[0]:
ret[k] = [r[... | c7e5a13258b131f93d11886f114d49b8804c3bd1 | 3,619,810 |
def chunks(seq, size):
"""Breaks a sequence of bytes into chunks of provided size
:param seq: sequence of bytes
:param size: chunk size
:return: generator that yields tuples of sequence chunk and boolean that indicates if chunk is
the last one
"""
length = len(seq)
return ((seq... | 25abe8afdb032af0e2b10dbd3c03b369d862813f | 3,619,811 |
def compare(
left, right, left_label="left", right_label="right", drop_close=True, **kwargs
):
"""Compare the data in two IamDataFrames and return a pandas.DataFrame
Parameters
----------
left, right : IamDataFrames
two :class:`IamDataFrame` instances to be compared
left_label, right_la... | 0820c606a93d3e12c333d43018f55f53407ff530 | 3,619,812 |
from sys import path
def locate_package_directory():
"""Identify a directory of the package and its associated files."""
try:
return path.abspath(path.dirname(__file__))
except Exception as path_error:
message = ('The directory in which the package and its '
'associated ... | 690b309e3348d9c606a9fc8a023fd240c5855b77 | 3,619,813 |
def combine_shuffle(parcellation, scale, spatnull, alpha):
"""
Combines outputs of all simulations into single files for provided inputs
Parameters
----------
parcellation : str
Name of parcellation to be used
scale : str
Scale of `parcellation` to be used
spatnull : str
... | 6e56b3d57e0c14b7a624f406e66c3a902590a2db | 3,619,814 |
def tcycle(iterable, n):
"""
>>> tcycle([1, 2, 3], 2)
(1, 2)
>>> tcycle([1, 2, 3], 4)
(1, 2, 3, 1)
"""
return tuple(islice(cycle(iterable), n)) | d836316de1dd91770d662aca9fb024c702499317 | 3,619,815 |
from typing import List
from typing import Callable
from typing import Any
from typing import Union
from typing import Tuple
def compute_best_permutation(x: List,
y: List,
sim: Callable[[Any, Any], Union[bool, int, float]],
agg: Ca... | 4d0c9a4d1a719c6b67f585e13fb803f8ff81bb6e | 3,619,816 |
import torch
def change_box_order(boxes, order):
"""Change box order between (xmin,ymin,xmax,ymax) and (xcenter,ycenter,width,height).
Args:
boxes: (tensor) bounding boxes, sized [N,4].
order: (str) either 'xyxy2xywh' or 'xywh2xyxy'.
Returns:
(tensor) converted bounding boxes, sized [N... | 6dd1ef6d2370c79de7ec321ab16592316b7b75da | 3,619,817 |
def GetLidarSimulation(environment,position,orientation):
"""
This function simulates the operation of the LIDAR by returning a list with the polar coordinates of
the location of the obstacles
environment -> List with all objects that are in the circuit as well as the edges of the circuit
posi... | 18b82528945a541411f21f36015c6518cd0e81fd | 3,619,818 |
import ast
def For_range(t, x):
"""Special conversion for ``for name in range(n)``, which detects
``range()`` calls and converts the statement to:
.. code:: javascript
for (var name = 0, bound = bound; name < bound; name++) {
// ...
}
"""
if (isinstance(x.target, ast.Name)... | e1d71e1c76798e7282c67de01dd7ff281ef28f9e | 3,619,819 |
def calculate_G3(
n_numbers,
neighborsymbols,
neighborpositions,
G_elements,
gamma,
zeta,
eta,
cutoff,
cutofffxn,
Ri,
normalized=True,
image_molecule=None,
n_indices=None,
weighted=False,
):
"""Calculate G3 symmetry function.
These are 3 body or angular i... | 41b8e163da879ca9e0339f8ac79f3f3d1abfb6fe | 3,619,820 |
import fractions
def decimals():
"""Generates instances of decimals.Decimal."""
return (
floats().map(float_to_decimal) |
fractions().map(
lambda f: Decimal(f.numerator) / f.denominator
)
) | b8e376543fc6182e5a9b6434865410f0950d622b | 3,619,821 |
def is_index(obj):
"""Verifies whether an object is a table index."""
return isinstance(obj, _supported_types().index_types) | e658951433b63e67ddbc4a98439569b1fb5b98fc | 3,619,822 |
def stack_controls(controls: list[dict], key: str = "tau"):
"""
Stack the controls in one vector
Parameters
----------
controls : list[dict]
List of dictionaries containing the controls
key : str
Key of the controls to stack such as "tau" or "qddot"
"""
the_tuple = (c[ke... | 8936bfbb1e4074cc79157fbdffaeb9e75de93f3a | 3,619,823 |
def secondYAxis(requestContext, seriesList):
"""
Graph the series on the secondary Y axis.
"""
for series in seriesList:
series.options['secondYAxis'] = True
series.name= 'secondYAxis(%s)' % series.name
return seriesList | d1c34f16da1f2142021c845afffb63b595e2ce69 | 3,619,824 |
def _next_incompatible_version(version):
"""
Find the next non-compatible version.
This is for use with the ~= compatible syntax. It will provide
the first version that this version must be less than in order
to be compatible.
:param str version: PEP 440 compliant version number
:return: T... | 7a9bdddf27cdd06e975236b0e7a64ae38d08bc98 | 3,619,825 |
def SNR_tot(G, BP, RP, J, H, K, lum, mass, teff, rad, numax, s=1., deltaT=1550, Amax_sun=2.5, obs='kepler-sc', D=1):
"""
predicted S/N for a given set of parameters
INPUT:
mag - relevant magnitude e.g. V or Kp for kepler...
lum - luminosity in Lsun
mass - stellar mass in Msun
... | 14c1f2d1b612fa5a4c1a3b820b14d7d49cab563e | 3,619,826 |
def checkFormat(DATAFIL):
"""
check the file format
"""
# Open file, read first 4 bytes as string
f = open(DATAFIL, 'rb')
dataBytes = np.fromfile(f, dtype=np.uint8, count=4)
data = "".join(map(chr, dataBytes))
f.close()
# If string matches a particular format, return format
if d... | 8e82a9f3a62092dbe75d7d948756eecc026b4b45 | 3,619,827 |
from datetime import datetime
import csv
def parse_csv(csv_path, ftype='csv', dt_col="date_time",
dt_format="%Y%m%d %H:%M:%S", dni_col='DNI',
dhi_col='DHI', stime=None, etime=None):
"""Parse a csv file containing direct normal
and diffuse horizontal data, ignoring NULL
and zero... | e29c7dbbb71b0353ceec0522ecab382f429d3c6a | 3,619,828 |
import re
def has_surr_char(string):
""" Returns True if the given string contains any 'surround' characters,
False otherwise.
These characters many cause bugs in programs if used.
"""
re1 = re.compile(INVALID_CHARACTERS)
if re1.search(string):
return True
else:
ret... | 4da7ee3c2041e2dc113b65e55233d6aad9e978ad | 3,619,829 |
import logging
def CreateChrootSnapshot(snapshot_name, chroot_vg, chroot_lv):
"""Create a snapshot for the specified chroot VG/LV.
Args:
snapshot_name: The name of the new snapshot.
chroot_vg: The name of the VG containing the origin LV.
chroot_lv: The name of the origin LV.
Returns:
True if t... | ef804e01da6143b2ff4393a27a6db16c66fc5ff4 | 3,619,830 |
import typing
def decode_u256(as_bytes: typing.List[int]) -> int:
"""Decodes an unsigned 256 bit integer.
"""
size = as_bytes[0]
if size <= NUMERIC_CONSTRAINTS[CLTypeKey.U8].LENGTH:
return decode_u8(as_bytes[1:])
elif size <= NUMERIC_CONSTRAINTS[CLTypeKey.U32].LENGTH:
return d... | 0fd8e9a47a805d9d56c6d019c470e22a06e0c606 | 3,619,831 |
def import_image(
dbsession,
account: str,
operation_id: str,
import_manifest: ImportManifest,
force: bool = False,
annotations: dict = None,
) -> dict:
"""
Process the image import finalization, creating the new 'image' record and setting the proper state for queueing
:param dbsess... | e385bfd6032cd7919dae325d2021f4cf15ea27a5 | 3,619,832 |
def image_code():
"""
图片验证码的实现逻辑
1. 获取参数 图片验证码的随机值
！ 切记！ 一定要判断
2. 生成图片验证码
3. 将图片文字和随机值保存到redis中
4. 将图片验证码 返回
:return:
"""
image_code_id = request.args.get("imageCodeId", None)
# 判断参数是否有值
if not image_code_id:
abort(403)
# 生成图片验证码
name, text, image = capt... | cb154182071efd367d1229e058cf90166b7bea44 | 3,619,833 |
from typing import Union
from pathlib import Path
from typing import Optional
def clone_renku_repository(
url: str,
path: Union[Path, str],
gitlab_token=None,
deployment_hostname=None,
depth: Optional[int] = None,
install_githooks=False,
install_lfs=True,
skip_smudge=True,
recursiv... | 1fbc1941b670caab64619705c666d636f0f6bcf1 | 3,619,834 |
import os
def traintest_split(data_dir='.', in_extension='.obfs',
save_dir=None,
save=True, trainfile='train', testfile='target', recurse=0,
testsize=0.1):
"""
Implements the sklearn train_test_split function in a recursive fashion
"""
w... | e0c987c80d0d04dcd7012fa109623c360809af83 | 3,619,835 |
def display_content(value):
"""This callback is used on the User Guide page and returns the selected User Guide when a user selects
a certain tab. User Guides can be added to HIVE in the userguide.py page.
"""
return userguide.user_guide(value) | f47dd22f395b8b249d2d2bfc1d14a09f6004325b | 3,619,836 |
def adjust_anomaly_scores(scores, dataset, is_train, lookback):
"""
Method for MSL and SMAP where channels have been concatenated as part of the preprocessing
:param scores: anomaly_scores
:param dataset: name of dataset
:param is_train: if scores is from train set
:param lookback: lookback (win... | 2f6adcdcae841573b362f1629138fdc70a568a24 | 3,619,837 |
import mpmath
def sf(k, nc, ntotal, ngood, nsample):
"""
Survival function of Fisher's noncentral hypergeometric distribution.
"""
_hg._validate(ntotal, ngood, nsample)
sup, p = support(nc, ntotal, ngood, nsample)
if k < sup[0]:
return mpmath.mp.one
elif k >= sup[-1]:
retur... | 4b4915b3bc2a9201bb66fca3e630cf59cd9afc8e | 3,619,838 |
def part_2_solution(graph, search_key):
"""
keeps a persistant counter that is recursively passed into a helper function
for ever depth of the helper function, the branch product gets updated, when a recursive function
exits it updates the counter with the product of counts for each sub-bag
the co... | 16ac48370de6d94397747b6b16791e0615f390aa | 3,619,839 |
def example3():
"""Demonstrates exception handling, peek, reduce.
"""
def square_and_raise_on_3(x):
if x == 3:
raise ValueError('unaccepted value')
return x ** 2
result = (Pipes(_EXAMPLE_COLLECTION)
.lz_map(lambda x: x['size'])
.lz_peek(lambda x:... | 962ebdbabe1fd0e2fe0c9cf09964b996b0385a02 | 3,619,840 |
def get_func_qty(*args):
"""get_func_qty() -> size_t"""
return _idaapi.get_func_qty(*args) | affa7952d604fd20674cadbe76cd9f55db669c14 | 3,619,841 |
def is_model_quantized(sym_model):
"""Checks whether the model is quantized.
Args:
sym_model (tuple): symbol model (symnet, args, auxs).
Returns:
boolean: True if model is quantized, else False.
"""
assert isinstance(sym_model, tuple) and isinstance(sym_model[0], mx.... | 32e8fd62bbc3280c0edd158194e8e7b2ffee53bf | 3,619,842 |
def evaluate(bounds, func):
"""
Evaluates simpsons rules on an array of values and a function pointer.
.. math::
\int_{a}^{b} = \sum_i ...
Parameters
----------
bounds: array_like
An array with a dimension of two that contains the starting and
ending points for the int... | af5102d37c1943420a0ff3fff980342ee8c9dad9 | 3,619,843 |
def process_image(image, target_shape): # downsampling to desired shape
"""Given an image, process it (downsample if needed) and return a numpy array."""
h, w, c = target_shape
image = load_img(image, target_size=(h, w)) # Load the image. Downsampling included! e.g. to (32,32,3)
img_arr = img_to_array(... | 968daaf8da198fc4ce129ea07c57c84942dc86ab | 3,619,844 |
import hashlib
def get_dataset_id(settings):
""" Creates and returns an unique ID (for practical purposes), given the data parameters.
The main use of this ID is to make sure we are using the correct data source,
and that the data parameters weren't changed halfway through the simulation sequence.
"""... | a696f0f85c8ee9c3cab975838db520cc061dfaf4 | 3,619,845 |
def get_sampler_diags(fit):
"""Returns useful sampler diagnostics for a particular MCMC fit with pystan"""
rhat=fit.summary()['summary'][:,-1]
rhat_worst=rhat[np.abs(1-rhat)==max(np.abs(1-rhat))][0]
n_eff_int_site=int(fit.summary()['summary'][0,-2])
return rhat_worst,n_eff_int_site | acee6147024ae32116e8b905eae18d8e47125148 | 3,619,846 |
def get_category(url=None, category='nieruchomosci', transaction_type='wszystkie', voivodeship=None, city=None,
street=None, filters=None):
""" Parses available offer urls from given category search page
:param url: Url to search web page
:param category: Type of property of interest (Mies... | 60aa51056bb209de8b777a7977504ab04847b6a2 | 3,619,847 |
def wmt_preprocess(dataset, training, max_length=-1, max_eval_length=-1):
"""Preprocessing for LM1B: filter out targets exceeding maximum length."""
def train_right_length(example, target):
l = tf.maximum(tf.shape(example["inputs"])[0], tf.shape(target)[0])
return tf.less(l, max_length + 1)
def eval_rig... | 870d1c1a7b6ee8e2a9c424884558355d4164a6d6 | 3,619,848 |
import torch
def instance_masks_to_semseg_mask(instance_masks, category_labels):
"""
Converts a tensor containing instance masks to a semantic segmentation mask.
:param instance_masks: tensor(N, T, H, W) (N = number of instances)
:param category_labels: tensor(N) containing semantic category label fo... | 127c9b9ff3d1044b1c5e1e8650ed493f8a4bc6de | 3,619,849 |
def URem(a, b):
"""Create the SMT expression (unsigned) remainder `self % other`.
Use the operator % for signed modulus, and SRem() for signed remainder.
>>> x = BitVec('x', 32)
>>> y = BitVec('y', 32)
>>> URem(x, y)
URem(x, y)
>>> URem(x, y).sort()
BitVec(32)
>>> (x % y).sexpr()
... | e37ed84f308e0936880f134344c9563428110059 | 3,619,850 |
import requests
def _make_request(endpoint: str) -> dict:
"""Helper method handles terra fcd api requests. [Source: https://fcd.terra.dev/v1]
Parameters
----------
endpoint: str
endpoint url
Returns
-------
dict:
dictionary with response data
"""
url = f"https://f... | 85617c3fbba2b8bd3624e50837f3f9fecd97555d | 3,619,851 |
import time
def fix_end_now(json):
"""Set end time to the time now if no end time is give"""
if 'end' not in json or json['end'] is None:
json['end'] = int(time.time())
return json | 2c126e00ac293c6a511cb86457d60536f1d690ef | 3,619,852 |
import os
def load_and_concate(rfiles):
"""
Loads and concatenates radiomic features from different MR contrasts
Args:
rfiles (list): list of radiomic files (one for each scan)
Returns:
pandas dataframe: radiomic features
"""
animal_id = []
for i, file in enumerate(rfiles... | bc6813097f00d0c7f23b4c362cdaca1a2323659c | 3,619,853 |
def file_to_bounding_boxes(file_path, output_folder=None, save_images=False, **kwargs):
"""
file_path: path to image file.
"""
# read image using PIL:
image = Image.open(file_path)
# convert to numpy array:
image_numpy = np.asarray(image)
# Predict bounding boxes and store to dictionar... | 60efc4bfb7c5fbe6d97658f4b54888bcb8415091 | 3,619,854 |
def count_parameters(net, trainable=False):
"""Counts the parameters of a given PyTorch model."""
params = trainable_parameters(net) if trainable else net.parameters()
return sum(p.numel() for p in params) | 4fc2b7fe1c40bb60db48270da4b03dcdd8499728 | 3,619,855 |
def prepare_computational_basis(nqubits, number):
"""Encode number as binary and create the circuit"""
# Create empty circuit of requested size
qc = QuantumCircuit(nqubits)
# encode number into a byte array
ba = int2ba(number, nqubits);
# Populate the circuit
for q in range(nqubi... | ca2d1d3ca6b153aa02cedf45a7f80647ef7dbbc0 | 3,619,856 |
def dropout(x, rate, is_training):
"""drop out layer"""
return tf.layers.dropout(x, rate, name='dropout', training = is_training) | 1965781d9b16708e5c0dc8c8b153bd2d24c13395 | 3,619,857 |
def get_cell_inj_span(test_line):
"""
Return the location of %cell in the given line as (start_index,
end_index), or None if %cell does not occur.
"""
if not test_line.strip().startswith(CELL_INJ_TOKEN):
return None
else:
cell_start = test_line.index(CELL_INJ_TOKEN)
cell_... | bd844a139cbd28b697b877c07f094d56094f7460 | 3,619,858 |
def in1u_w(name, shape, seed=None, regu=None):
"""
Convolutional Architecture for Fast Feature Embedding.
FAN_IN, factor=1.0, uniform=True.
"""
init = tf.contrib.layers.variance_scaling_initializer(
factor=1.0, mode="FAN_IN", uniform=True, seed=seed)
return w(name, shape, tf.float32,... | 992d3e19eaa869d3da67d480382f73728918e773 | 3,619,859 |
def topics_to_calldata(topics, bytes_per_topic=3):
"""Converts a list of topics to calldata.
Args:
topics (bytes[]): List of topics.
bytes_per_topic (int): Byte length of each topic.
Returns:
bytes: Topics combined into a single string.
"""
return b''.join(topic.to_bytes(b... | 2d500016963934fdbc60b388632b817624d5ad8d | 3,619,860 |
def read_size(calibxml):
"""
This function extracts the size of an image from the xml file.
.. note::
Usually, it is similar to "AutoCal_[Focal]_[CameraName].xml"
Parameters
----------
calibxml : str
Name of the camera calibration file
Returns
-------
np.ndarra... | 5fb106c54ed63a13c6f8ae312fb2e5b6055a0a20 | 3,619,861 |
import re
def get_packages_names(latex_file):
"""Find all the package name in a file
Args:
latex_file: A pathlib file
Returns:
A list of all the package name found in the latex_file
"""
with latex_file.open('r', encoding='utf-8') as f:
data = f.read()
packages_info ... | 6eb1b1c02ef254fa6e112ecbae960060af3b7405 | 3,619,862 |
def remove_basic_block_assembly(pydot_cfg):
"""
Remove assembly text from the CFG's basic blocks
"""
# Avoid graph and edge nodes, which are the 1st and 2nd nodes
nodes = pydot_cfg.get_nodes()[2:]
for n in nodes:
n.set_label("")
return pydot_cfg | 3ca5d7fcd46dc96bff92aea67b47afbe53accc40 | 3,619,863 |
import sys
def python(*args, **kwargs):
"""Run a python script with the current interpreter."""
return exec_getout(sys.executable, *args, **kwargs) | 4f7622f5d5cf2427ffb79661bc70258ee7caa03d | 3,619,864 |
def CheckNaN(data):
"""
Raise exception if data contains NaN.
Useful to stop training if network doesn't converge and loss function
returns NaN. Example:
samples >> network.train() >> CheckNan() >> log >> Consume()
>>> from nutsflow import Collect
>>> [1, 2, 3] >> CheckNaN() >> Collect()
... | c6d10a034a787e53ef493c755e326bd374131427 | 3,619,865 |
from typing import Any
def build_patch302_request(*, json: Any = None, content: Any = None, **kwargs: Any) -> HttpRequest:
"""Patch true Boolean value in request returns 302. This request should not be automatically
redirected, but should return the received 302 to the caller for evaluation.
See https:/... | 300330aea3a177307e52d77f55df9844f367e39b | 3,619,866 |
def construct_array(nums):
"""
:param nums: array
:return: mul array
"""
l = len(nums)
ans = [1 for _ in range(l)]
p = q = 1
for i in range(l):
ans[i] *= q
ans[-i - 1] *= p
q *= nums[i]
p *= nums[-i - 1]
return ans | 5327945cbb83290af94efcce07e4ae391fb3da45 | 3,619,867 |
def create_col(card: dbc.Card) -> dbc.Col:
"""Pass each card to create a Col element"""
return dbc.Col(
className="mb-2",
children=[card],
width=12,
sm=12,
lg=6,
xl=4
) | 8624d68e7a80cefe6587a614150aed0023412428 | 3,619,868 |
import argparse
import os
import json
import shutil
def main():
""" Use pw_module_tests.testinfo.json files to find and copy fuzzers. """
parser = argparse.ArgumentParser()
parser.add_argument('--buildroot')
parser.add_argument('--out')
args = parser.parse_args()
print(' buildroot: ' + args.buildroot)
... | bcbbda75629e9186d37387ccad02b5560ad4342c | 3,619,869 |
def make_report(subreads, output_dir, dpi=DEFAULT_DPI):
"""
Create a basic subread metrics report. Since this may be run either as an
independent tool or as part of the barcoding report, it handles the .pbi
file reading flexibly.
"""
pbi_stream = get_pb_index_streamed(subreads)
dists, uniqu... | 469f22291ff591aeaf6219a97eb09aa4d4ad966c | 3,619,870 |
def return_point(m, n, p):
"""
m is the index number of the Hammersley point to calculate
n is the maximun number of points
p is the order of the Hammersley point, 1,2,3,4,... etc
l is the power of x to go out to and is hard coded to 10 in this example
:return type double
"""
if p == 1:... | 73b1c75d6b4ebdc6a0616d9a7b2d6207a4728316 | 3,619,871 |
def select2_css_url():
"""
Return the full url to the Select2 CSS file.
"""
return get_select2_setting('css_url') or \
select2_url('css/select2.min.css') | ea9cac6f9e687620ed3cc8d4c45d33e551df3dbe | 3,619,872 |
def GetQuasiSequenceOrder(ProteinSequence, maxlag=30, weight=0.1):
"""
###############################################################################
Computing quasi-sequence-order descriptors for a given protein.
[1]:Kuo-Chen Chou. Prediction of Protein Subcellar Locations by
Incorporating Quasi... | 99b0d6129f2693893382493a3de241cd00f75b68 | 3,619,873 |
def OverscanTrim(d,ds):
"""
Overscan correct and Trim a refurbished HIRES image
"""
ds = ds.split(',')
dsy = ds[0][1:]
dsx = ds[1][:-1]
dsy = dsy.split(':')
dsx = dsx.split(':')
x0 = int(dsx[0])-1
x1 = int(dsx[1])
y0 = int(dsy[0])-1
y1 = int(dsy[1])
newdata = d[x0:x1]... | ceb434ca75f458c43137b73b89c0f0242bfe7e93 | 3,619,874 |
import requests
def requests_put(url, expected_sc=200, **kwargs):
"""
Calls our above requests wrapper for a PUT request, and sets the default expected status code to 200.
"""
return do_request_with_auth_retry(url=url, method=requests.put, expected_sc=expected_sc, **kwargs) | 3c5aa69d8b21e67960cfff76820ccf2b64a6f879 | 3,619,875 |
def calculate_decomposition(data, model=MODEL_ADDITIVE, frequency=2):
"""
Calculate time series decomposition
Args:
data (list[float]): Input time series values
model (str): Seasonal component type
frequency (int): Seasonal component frequency
Returns:
dict: Calculation... | 444e05c5f36479f7c1ddbd8c7fbb3d6785d6bf2f | 3,619,876 |
from typing import List
from typing import Dict
def add_funders_relationships(funders: List, funders_by_key: Dict) -> List:
""" Adds any children/parent relationships to funder instances in the funders list.
:param funders: List of funders
:param funders_by_key: Dictionary of funders with their id as key... | 4411094812ae3932453f4cbb33f8c845fca6f800 | 3,619,877 |
import re
def __tokenize(syntax) -> list:
"""
Validate and tokenize the syntax.
Valid syntax: snake_case_words, integers, plus, minus.
"""
if not re.match(r"^[\w\d\s\+-]+$", syntax):
raise SyntaxError("Invalid syntax.")
syntax = re.sub(r"\s*([+-])\s*", r" \g<1> ", syntax)
return ... | 68e79222987771d964ac0d39e38c425d710d3765 | 3,619,878 |
import copy
def reducer(state, action):
"""Screen specific reducer
Given :func:`screen.set_position` action adds "position" data
to state
:param state: data structure representing current state
:type state: dict
:param action: data structure representing action
:type action: dict
"""... | 2c918ee2b9ae40689f1df4de6b48a1da951716de | 3,619,879 |
def see_model_list():
"""
Get's the data about all models in the DB to put on a table:
- name
- organism
- strain
Returns:
render_template to see_data with tab_status set to models.
"""
tab_status = {"enzymes": "#", "metabolites": "#", "models": "active", "organisms": "#", "... | 1edcdc1382d3a6d26f22e8e5ffcb9a5f1c294742 | 3,619,880 |
def localsys_get_login():
"""Retrieves the login credentials from the computer you are on.
Good for command line tools"""
try:
sid = local_credentials.get_password('minervaclient_sid','minerva')
pin = local_credentials.get_password('minervalcient_pin','minerva')
if sid is None or pin... | d3c6a5870680f8688816e158015260d598c001fe | 3,619,881 |
def GetOrigFn( module, fnName ):
"""Return the original function."""
return DictGet( orig_fns, ( module, fnName ), getattr( module, fnName ) ) | cb36ff0baa63abd08ac9651a251cd6feb2e7913b | 3,619,882 |
import platform
def host_toolchain(xcrun_toolchain='default', tools=None, suffixes=None):
"""
Return a Toolchain with the first available versions of all
specified tools, plus clang and clang++, searching in the order of the
given suffixes.
If no matching executables are found, return None.
"... | d385dc97ea2051282b5d096fb1243783d067c46a | 3,619,883 |
def transcribe_audio(audio_stream, model: str, language_code: str):
"""
Transcribe the given audio chunks
"""
global client
encoding = RecognitionConfig.AudioEncoding.LINEAR16
try:
audio = RecognitionAudio(content=audio_stream)
config = RecognitionConfig(
s... | 0c2c0c7c5455cdb79965bd38108a6e71ddde41a9 | 3,619,884 |
def indent(yaml: str):
"""Add indents to yaml"""
lines = yaml.split("\n")
def prefix(line):
return " " if line.strip() else ""
lines = [prefix(line) + line for line in lines]
return "\n".join(lines) | 815babb29378f1cfac6ada8258322df92235fc9e | 3,619,885 |
def smooth_pr(prec, rec):
"""
Smooths precision recall curve according to TREC standards. Evaluates max precision at each 0.1 recall. Makes the curves look nice and not noisy
"""
n = len(prec)
m = 11
p_smooth = np.zeros((m), dtype=np.float)
r_smooth = np.linspace(0.0, 1.0, m)
for i in range(m):
j = np.argmi... | 6129cb1348446df2f56eb5601cac585c498d5311 | 3,619,886 |
def get_rbac_role_assigned(self) -> dict:
"""Get list of accessible menus based on the current session
permissions
.. list-table::
:header-rows: 1
* - Swagger Section
- Method
- Endpoint
* - rbacRole
- GET
- /rbac/role/menuAssigned
.. no... | 91d0dcbded36b857a0dc0ddfeaa2815516d162f6 | 3,619,887 |
def close_session(module_session):
"""Closes the Shell Interactive Session
Args:
module_session (object): The module session object that should be closed
Returns:
A dict holding the result message
"""
module_session.close()
return Response.ok("The Shell Interactive session has be... | 45bc4a094e8d33320efb1b5738ee59fddc344f46 | 3,619,888 |
def Xfact(m):
"""Xfact(m)
Computes (2m-1)!!/sqrt((2m)!)
"""
res = 1.
for i in xrange(1,2*m+1):
if i % 2: res *= i # (2m-1)!!
res /= np.sqrt(i) # sqrt((2m)!)
return res | 23653360ef3f8f5d4e5b9cdb16e8ab58835960cf | 3,619,889 |
import os
def process_csv(csv_file=None):
"""
Function to read the content(s) of CSV file(s).
The function reads the contents of CSV file(s) available in a
certain directory and populate a dictionary with e-mail id as key
in order to have unique e-mails.
:param csv_file: Name of the csv_file... | 00368fff96e0c254b57f395e1b4ba769a01f995d | 3,619,890 |
import requests
def stacks_list(credentials):
"""
List the stacks accessible to the currently logged in user.
"""
url = _urljoin(credentials["host"], "api/a0.1/stacks/")
headers = {"Authorization": "Token {}".format(credentials["token"])}
resp = requests.get(_ensure_protocol(url), headers=head... | 9a63b7a402104f41f6a7c1f9c023b979428b088f | 3,619,891 |
def remove_0x_head(s):
"""
Better use from django_eth_events.utils import remove_0x_head,
because in pyEthereum version <= 1.6.1 is bugged for Python3
"""
return s[2:] if s[:2] in (b'0x', '0x') else s | b903e6eb97e8cb5fc2d7b216cdabcdc2f3b157a0 | 3,619,892 |
def build_doc(cls, **kwargs):
"""Decorator to build docstrings for datalad commands
It's intended to decorate the class, the __call__-method of which is the
actual command. It expects that __call__-method to be decorated by
eval_results.
Note that values for any `eval_params` keys in `cls._params_... | 570d149ca0c56c5d85ed3eaff366d4843fa3fa2d | 3,619,893 |
from typing import List
def get_dev_requirements() -> List[str]:
"""Fetch requirements for library development."""
with open(_DEV_REQUIREMENTS, mode="r") as f:
return f.readlines() | b0f9a4a958d64ff3da0c7622fb6dcea69dd95de5 | 3,619,894 |
def wait_result(ref):
"""
Waits for the referenced agent to finish, whereupon its latest result will
be returned.
Args:
ref (uuid.UUID): The UUID of the agent. Usually received when a window
is created.
Raises:
KeyError: When an agent with the given UUID could not be fo... | afa95f1378813da5bedeea3d2e9aa2c3a5b7108b | 3,619,895 |
import torch
from typing import Tuple
def mask_tokens(inputs: torch.Tensor, tokenizer: PreTrainedTokenizer, args) -> Tuple[torch.Tensor, torch.Tensor]:
""" Prepare masked tokens inputs/labels for masked language modeling: 80% MASK, 10% random, 10% original. """
if tokenizer.mask_token is None:
raise ... | 7f633b0c08de12655b406c852dd038aca3dd64d4 | 3,619,896 |
def _has_sectors(tax_name: str, ignore_sectors: bool) -> bool:
"""Determine whether we are doing a sector-based forecast."""
return tax_name in ["birt", "sales", "wage", "rtt"] and not ignore_sectors | 5725693c514937988b4e668c699606cb3ab46d10 | 3,619,897 |
import tqdm
def merge_modules(pose_graph, module_corners, observations,
image_width, image_height, merge_threshold, max_module_depth, max_num_modules,
max_combinations, reproj_thres, min_ray_angle_degrees):
"""Merge duplicate modules by projecting each module into each keyframe
and finding overlapp... | d228530251074b39abf5234be0418818f224c867 | 3,619,898 |
def KK_RC23_fit(params, w, t_values):
"""
Kramers-Kronig Function: -RC-
Kristian B. Knudsen (kknu@berkeley.edu / kristianbknudsen@gmail.com)
"""
Rs = params["Rs"]
R1 = params["R1"]
R2 = params["R2"]
R3 = params["R3"]
R4 = params["R4"]
R5 = params["R5"]
R6 = params["R6"]
... | fab416c023a215c62e51c6cc2e5857be8e85a063 | 3,619,899 |
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