content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
from rst2pdf.createpdf import PageCounter as pc
import shlex
def parseRaw(data, node):
"""Parse and process a simple DSL to handle creation of flowables.
Supported (can add others on request):
* PageBreak
* EvenPageBreak
* OddPageBreak
* FrameBreak
* Spacer width, height
* Transition... | 5b24c6a47dc56ee4a3ee77ff46391704b940465f | 3,610,900 |
def yolo_loss(args,
anchors,
num_classes,
rescore_confidence=False,
print_loss=False):
"""YOLO localization loss function.
Parameters
----------
yolo_output : tensor
Final convolutional layer features.
true_boxes : tensor
Grou... | 0c18252cbce632f6997e499bfbae73a625e03ee5 | 3,610,901 |
import re
def extract_authorization_token(request):
"""
Get the access token using Authorization Request Header Field method.
Or try getting via GET.
See: http://tools.ietf.org/html/rfc6750#section-2.1
Return a string.
"""
auth_header = request.META.get('HTTP_AUTHORIZATION', '')
if r... | 9776df3ecd59ba3db15664259a6e65114ec61a07 | 3,610,902 |
def resnet101(pretrained=False, **kwargs):
"""Constructs a ResNet-101 model.
"""
model_args = dict(block=Bottleneck, layers=[3, 4, 23, 3], **kwargs)
return _create_resnet('resnet101', pretrained, **model_args) | 42da2c20d6b66bc31b5c3a8c0232f19d5726fd4f | 3,610,903 |
def filter_problematic(features, vcf_file="data/problematic_sites_sarsCov2.vcf", callback=None):
"""
Apply problematic sites annotation from de Maio et al.,
https://virological.org/t/issues-with-sars-cov-2-sequencing-data/473
which are published and maintained as a VCF-formatted file.
:param featur... | e1edd82c6223fc88b1db5e929c6147464fc7051d | 3,610,904 |
import jinja2
def gen_model_header(env: jinja2.environment.Environment, model: onnx.ModelProto) -> str:
"""
Generates the header of the script for the given `model`
:param env: Jinja environment to load the template files
:param model: the onnx model for which the header shall be generated
:retur... | e12b7ac02d382fcb541d6df94ac2bea722f7ea2c | 3,610,905 |
def abmag(flux):
""" takes flux as nanomaggies, gives AB mag """
# don't take the log of 0!
if flux <= 0:
return 0
return -2.5 * np.log10(flux) + 22.5 | e09380c76dbaaba0c37dd5eb42e9d010960b6d68 | 3,610,906 |
import os
def add_map(new_prot, new_target, map_path, map_type):
"""Add a Django map obect
:param new_prot: the Django protein object
:param new_target: the Django target object
:param map_path: the path to the map file
:param map_type: the two letter code signifyign the type of the map
:retu... | 1e1a5b9bb26ad62f29dc0a78000adb534762e485 | 3,610,907 |
import os
def _make_requirements(foldername, virtual_env_obj):
"""
Function that build the 'requirements.txt' file used to create a
virtual environment by the PIPENV, based on :virtual_env_obj: object.
"""
requirements_filename = os.path.join(foldername, 'requirements.txt')
with open(r... | daa8bb3af7c0a953cf7ce64e13e21259128c2127 | 3,610,908 |
def block2(x, filters, kernel_size=3, stride=1, conv_shortcut=False, name=None):
"""
residual 블록.
Parameters
----------
x : [type]
입력 텐서
filters : int
bottleneck 레이어의 필터 수.
kernel_size : int, optional, default=3
bottleneck 레이어의 커널 크기.
stride : int, optional, defa... | 1739e6cd9f774bed7c608900c77b1bc983120ac2 | 3,610,909 |
import logging
def _get_port_v1(port_name, depth=0, selector=None, **kwargs):
"""
Perform a GET call to retrieve data for a Port table entry
:param port_name: Alphanumeric name of the port
:param kwargs:
keyword s: requests.session object with loaded cookie jar
keyword url: URL in mai... | e6db99eda520016dd4b67f620a99a6970633eadc | 3,610,910 |
import random
def sample_with_replacement(population,len,choose=random.choice):
"""Sample from a population with replacement
Taken from Python Cookbook, 2nd ed, recipe 18.3
"""
s = []
for i in xrange(len):
s.append(choose(population))
return s | 3fe59998c19c501a5eeb26f0cc65e15ff3c1af7e | 3,610,911 |
def power_mod(val, power, m_value):
"""
Calculate power mod the efficent way
"""
if power <= 100:
return (val ** power) % m_value
if power % 2 == 0:
return (power_mod(val, power // 2, m_value) ** 2) % m_value
return (power_mod(val, power // 2, m_value) * power_mod(val, power ... | 59bb407db88e344b33571d74eef75ae0f7baa54e | 3,610,912 |
def stokes_right_circular():
"""Stokes vector for right circular polarized light."""
return np.array([1, 0, 0, 1]) | 65f1b90e9b3799026a8ec4b79543efc1ea6a472c | 3,610,913 |
def hello_http(request):
"""HTTP Cloud Function.
Args:
request (flask.Request): The request object.
<http://flask.pocoo.org/docs/0.12/api/#flask.Request>
Returns:
The response text, or any set of values that can be turned into a
Response object using `make_response`
<... | 60353b0d7d54a3f95bb0b8ad1b641aabbc64f03b | 3,610,914 |
def search_objects(params: dict, results: dict, meta: dict):
"""
Convert Elasticsearch results into the RPC results conforming to the
"search_objects" method
"""
post_processing = _get_post_processing(params)
objects = _get_object_data_from_search_results(results, post_processing)
ret = {
... | 9e0a7eafcd9442fc88994cbf48ce088cb249cb69 | 3,610,915 |
def encode_raw(objs):
"""
Encode a list of raw data and types to binary wire format
Useful for analyzing Protobuf messages with unknown schema
"""
return RawWire().encode(objs) | 91680c2a5fbfab11292b58d976602a56d1934d70 | 3,610,916 |
def inv_income_weighted_utility(coin_endowments, utilities):
"""Social welfare, as weighted average utility (weighted by inverse endowment).
Args:
coin_endowments (ndarray): The array of coin endowments for each of the
agents in the simulated economy.
utilities (ndarray): The array ... | 0cca315fc52b5a90867300d595a0d1c7bf6cf11c | 3,610,917 |
import os
def get_full_path(pset, photo):
"""
Assemble a full path from the photoset and photo titles
@param pset: str, photo set name
@param photo: str, photo name
@return: str, full sanitized path
"""
return os.path.join(sanitize_filepath(pset), sanitize_filepath(photo)) | 16fb05dea97315804de5c8763238d447c8ab2c4e | 3,610,918 |
from datetime import datetime
def new_post():
"""
Display and handle form for creating a new blog post.
"""
form = PostForm()
if form.validate_on_submit():
post = Post(pub_date=datetime.date.today())
post.title = form.title.data
post.content = form.content.data
post... | d9f54039cce68fc850d0225c43c9593da7d4735d | 3,610,919 |
from typing import List
def _inv_shift_rows(s: List[List[bytes]]) -> List[List[bytes]]:
"""
Performs the inverted shift rows transformation as described in the standard
:param s: the state matrix
:return: the new state matrix with shifted rows
"""
s[0][1], s[1][1], s[2][1], s[3][1] = s[3][1], ... | bdb593e912275bfdf387334916123830e081ed50 | 3,610,920 |
def create(dtype, key_len=None, val_len=None):
"""
Input : Example input dtype=i32:i32 will create an i32_i32 instance.
"""
k_ty, v_type = None, None
try:
splitted_words = dtype.split(':')
except AttributeError as e:
raise TypeError("dtype must be a string")
if len(splitted_words) != 2:
raise ValueErr... | a44b78f797030625252da5f48b0ebe0a31b48809 | 3,610,921 |
import io
def read(*filenames, **kwargs):
""" Read specified filenames and return contents """
enc = kwargs.get('enc', 'utf-8')
sep = kwargs.get('sep', '\n')
buf = []
for filename in filenames:
with io.open(filename, encoding=enc) as f:
buf.append(f.read())
return sep.join... | 9261a976cfdc1775888220001cba52aefb45efb3 | 3,610,922 |
def tile_context_feature(feat, max_sequence_size):
"""
Tile context features to max_sequence_size. Do nothing if sequence feature
Parameters
----------
feat: Tensor
Feature tensor to be tiled
Shape: [batch_size, max_len] or [batch_size, sequence_size, max_len]
max_sequence_size:... | c0eb6e12770116773e073f6d6a9f42ba0a67569c | 3,610,923 |
import uuid
import os
def thread_image_file_path(instance, filename):
"""Generating a file path for avatar image"""
ext = filename.split('.')[-1]
filename = f'{uuid.uuid4()}.{ext}'
return os.path.join('uploads/thread/', filename) | 5cb2f7afecd3e54b8ab0f3bcb47a0c7cf69cc94f | 3,610,924 |
def conv_transpose(num_filters, kernel_size=3, activation='relu', conv_order='conv_first', use_batch_norm=True,
name=None, **conv_kwargs):
"""A composite layer for deconvolution with BatchNormalization."""
assert conv_order in ['conv_first', 'conv_last']
def inner(x):
conv_first... | 0c08edb87107b7246d3938458b96487f51045cf4 | 3,610,925 |
def get_id_character_mapping(data, columns):
"""Creating a mapping between characters and ids given dataframe.
Args:
data: dataframe that contains characters that need to be converted to ids
column: a column of the dataframe that contains characters that need to be converted to ids
columns:
... | 904a9dde05c26d2d669d16e466317379acbdeec5 | 3,610,926 |
import os
import subprocess
def ensure_local_services_are_running() -> int:
"""Ensure all required services (mysql, redis) are running."""
# NOTE: if you have any problems with this, please contact me
# @cmyui#0425/cmyuiosu@gmail.com. i'm interested in knowing
# how people are using the software so th... | d6e42e46cb219bafc635fdfaadd7cffd30eb26df | 3,610,927 |
def estimate_dimension(X, n_neighbors='auto', neighbors_estimator=None):
"""Estimate intrinsic dimensionality.
Based on "Manifold-Adaptive Dimension Estimation"
Farahmand, Szepavari, Audibert ICML 2007.
Parameters
----------
X : nd-array, shape (n_samples, n_features)
Input data.
... | bdeb2631b22f443378746f0728a8e0062e55b962 | 3,610,928 |
def start(subj, body):
"""
parse Twitter message
"""
lines = body.splitlines()
for index, line in enumerate(lines):
if line in SUBJECTS:
text = '\n'.join(lines[index + 1:])
return TITLE + line + '\n' + cut_text(text)
if DELIMETER in body:
return convert_p... | f36cfc5a6b6c1e01abc2d4077a7f6eece94cd04e | 3,610,929 |
import re
import os
def load_json_files(dirpath):
"""
Collects process definitions (JSON files) from a local process directory.
Parameters
----------
dirpath : str
Directory path of the process files (.json) folder.
Returns
-------
list
List of processes decoded as di... | e7cc37a8085373af55f2a7d51e927b52445d1264 | 3,610,930 |
import torch
def img_collate(imgs):
"""
Args:
imgs:
Returns:
torch.tensor, (B, 3, H, W)
"""
w = imgs[0].width
h = imgs[0].height
tensor = torch.zeros(
(len(imgs), 3, h, w), dtype=torch.uint8).contiguous()
for i, img in enumerate(imgs):
nump_array = np.a... | c6d8cc0434f4db6d70f388b99037448587b2784f | 3,610,931 |
def __args_to_weka_options(args):
"""
Function that creates list with options (args) in format
approperiate for weka.
:param args: dictionery with command line input
:return: list of command line arguments
"""
result = []
for k,v in args.items():
if v:
result.append(... | 1d480ffaf840ae67d805d7845684eef24d3da583 | 3,610,932 |
import json
def execute(
context: cli.CommandContext,
verbose: bool = False,
as_json: bool = False
) -> Response:
"""
:return:
"""
response = context.response
settings = environ.package_settings
if verbose:
data = environ.systems.get_system_data()
dat... | fee4e55b52902ccc62339687d298db2d2c635c70 | 3,610,933 |
import os
def batch_input_file_validator(value):
"""
All input files should be valid image files. Supported extensions: ['.jpg','.jpeg','.png','.bmp','.webp']
"""
for i in value:
if not os.path.isfile(value):
raise TypeError("Select a valid input file.")
return value | 2e326ee3022bfe1def13a775c9585669a27eb3cd | 3,610,934 |
import torch
def generate_response(tokenizer, model, chat_round, chat_history_ids, question):
"""
Generate a response to some user input.
"""
# Encode user input and End-of-String (EOS) token
new_input_ids = tokenizer.encode(">> You: "+ question + tokenizer.eos_token, return_tensors='pt')
... | 138299247b6b5b46b8999489e44676a6819e3e10 | 3,610,935 |
def gamma_closures(expressions, could_not_close=None):
"""
Try to compute gamma closure for each of expressions.
:param expressions: list of moment expressions, where each expression is a product of
powers of moments
:param could_not_close: a list that will be filled with expressions that c... | f84351a4fd0361b2f7de02707c9e3c13877d0974 | 3,610,936 |
def find_by_history(view: kvstore.View, storage: bool, key: bytes, block_number: int) -> (bytes, bytes):
"""find_by_history"""
if storage:
bucket = tables.STORAGE_HISTORY_LABEL
else:
bucket = tables.ACCOUNTS_HISTORY_LABEL
index_chunck_key = history_index.index_chunck_key(key, block_numb... | 973fe9d02ffaac30d19fbc8df83b2d98f3013dad | 3,610,937 |
def linear_coeff(x, y):
"""
This function returns the inclination coeffecient and
y axis interception coeffecient m and b.
----------
Parameters
----------
x : Output of the split vector function.
y : Output of the split vector function.
-------
Returns
-------
float numb... | d38669165af0752837a32ee0df11a4e56e57abdf | 3,610,938 |
import struct
def _package_contents_metadata(origin_label, grouping_label):
"""Named construct for helping to identify conflicting packaged contents"""
return struct(
origin = origin_label if origin_label else "<UNKNOWN>",
group = grouping_label,
) | 505776bf36740e91e1eb25470b22527af89309e2 | 3,610,939 |
import math
def str_to_feet(value="0'-0"):
"""
Returns string converted into decimal feet.
Acceptible formats include:
1. 5'-7"
5'-7 1/2"
5'-7 1/2''
5'-7
5'-7 1/2
2. 7 3/4
-8
The trailing quotation mark can b... | 3d9e17f3a900d4962ab65e5fdac3dcd44fa49399 | 3,610,940 |
from typing import Tuple
from typing import List
def deconstruct_answer(
answer_sentence: T5_SENTENCE = ''
) -> Tuple[List[T5_SENTENCE], List[str]]:
"""Gets individual answer subsentences from the compound answer sentence.
Args:
answer sentence: a T5 output sentence.
Examples:
>>> se... | c6aa7402382e71828d2146166b20ab50430416a6 | 3,610,941 |
def distance_modulus(distance):
"""Given a distance in parsecs, returns the value :math:`m - M`, a characteristic value used to convert
from apparent magnitude :math:`m` to absolute magnitude, :math:`M`.
Uses the formula from Carroll and Ostlie, where :math:`d` is in parsecs
.. math:: m - M = 5 \log_{... | 4d09231ea999a8ddaabf587cfba219b264da6442 | 3,610,942 |
def _serialize_data_asset(asset: DataAsset) -> JSON:
"""Serialize a DataAsset to JSON."""
return _serialize_asset(asset) | d1ed7dd410e9de0f70ef84ebc2da0f5afe492dea | 3,610,943 |
def behroozi10_model_dictionary(redshift=sim_defaults.default_redshift, **kwargs):
"""
Dictionary that can be passed to the `~halotools.empirical_models.SubhaloModelFactory`
to build a subhalo-based composite model using the stellar-to-halo-mass relation
published in Behroozi et al. (2010),
`arXiv:1... | c45219b650ca9e69c9a157c6b84023da92f81479 | 3,610,944 |
def detects(label=None, frac=None):
"""list of outlier detection algorithms to select from"""
algo = {'isoForest': IsolationForest(contamination=frac, random_state=42),
'MCD': EllipticEnvelope(contamination=frac),
'LOF': LocalOutlierFactor(n_neighbors=20, contamination=frac)}
return ... | aa1cad7376b25ede814df9d3f1522666a6364865 | 3,610,945 |
def zpadlist(values: list, inputtype: str, minval: int, maxval: int) -> list:
"""Return a list of zero padded strings and perform input checks.
Returns a list of zero padded strings of day numbers from a list of
input days. Invalid month numbers (e.g. outside of 1-31) will raise
an exception.
Para... | bcc06dfb36b93af69d031b44f64dfd3ee7d082c3 | 3,610,946 |
def find_backend(txt):
"""
Determine the needed background based on a text string
Parameters
----------
txt : str
name to find in the list
Returns
-------
b : :class:`~beast.physicsmodel.helpers.gridbackends.GridBackend` subclass
corresponding backend class
"""
... | 34de08e646aa1ed78eeaa666fd0926eb5cff9dcc | 3,610,947 |
def _make_gmm(ft_data: pd.DataFrame, n_feature: int, cluster_name: str):
"""
fit a gaussian model and set subcluster names for each feature. Auxiliary
function to process cluster.
Parameters
----------
ft_data : DataFrame
The mz and rt columns of the cluster DataFrame
n_feature : in... | fc2fb4ac47e158bc5c476ced11d3349321e1af3e | 3,610,948 |
def _set_health_check_defaults(health_check):
"""Sets default values for any missing attributes in HealthCheck.
These defaults need to be kept up to date with the production values in
health_check.cc
Args:
health_check: An instance of appinfo.HealthCheck or None.
Returns:
An instance of appinfo.Hea... | cb6cfb86722912cb10b316c5750a4b09601aec2e | 3,610,949 |
import math
def singular_values_plot(syslist, omega=None,
plot=True, omega_limits=None, omega_num=None,
*args, **kwargs):
"""Singular value plot for a system
Plots a Singular Value plot for the system over a (optional) frequency range.
Parameters
---... | 26db379b0f7b598d05d345edb6110f4e35485747 | 3,610,950 |
from dmriprep.interfaces.bids import BIDSDataGrabber
from niworkflows.engine.workflows import LiterateWorkflow as Workflow
from niworkflows.interfaces.bids import BIDSInfo
from smriprep.workflows.anatomical import init_anat_preproc_wf
from ..interfaces import DerivativesDataSink
from ..utils.misc import sub_prefix as _... | 4188f07bb03a6b4806f0197d5c4ba0020d3d9440 | 3,610,951 |
import os
def _get_scxdir(scxdir=None):
"""Retrieve the base secondary directory with error checking.
Parameters
----------
scxdir : :class:`str`, optional, defaults to :envvar:`SCND_DIR`
Directory containing secondary target files to which to match.
If not specified, the directory is... | a2affd580a078582de3af8bf9936e50a61f0f10e | 3,610,952 |
def find_spike_from_templates(recording, waveform_extractor, method='simple',
method_kwargs={}, **job_kwargs):
"""Find spike from a recording from given templates.
Parameters
----------
recording: RecordingExtractor
The recording extractor object.
waveform_extr... | a02e61d9c7ff668e0264cd50d1fe4294394cb58e | 3,610,953 |
import os
import json
def get_metadata(path):
"""
Find the json metadata file associated with content at `path` (dir or file).
"""
metadata_filename = get_metadata_file_path(path)
if not os.path.exists(metadata_filename):
return {}
with open(metadata_filename, 'r') as json_file:
... | ab8f84624dd0e6090fcfa3d98d380a312f886671 | 3,610,954 |
def model_outputs() -> str:
"""
Parses the model outputs in a human readable format. It also gets the
boathouses by reach, so the user knows what boathouses are associated with
each reach.
Returns:
Rendering of the model outputs via the `model_outputs.html` template.
"""
df = latest... | 848dba8f8b29c4176bce827c2e5c831c3f534b73 | 3,610,955 |
import itertools
import copy
import logging
def check_process(process, evaluator, quick, options):
"""Check the helas calls for a process by generating the process
using all different permutations of the process legs (or, if
quick, use a subset of permutations), and check that the matrix
element is in... | a4cb209596353ebc873aab0fecc7bbc4de42fa3e | 3,610,956 |
def getFileState(fileName, workDir, jobId, ftype="output"):
""" Return the current state of a given file """
# create a temporary file state object
FS = FileState(workDir=workDir, jobId=jobId, ftype=ftype)
# update this file
state = FS.getFileState(fileName)
# cleanup
del FS
return s... | b19f193deb0a2a0268589d1f87f1f0906a778c07 | 3,610,957 |
def to_minimal_subject_jobject(subdomain, minimal_subject):
"""Converts the given MinimalSubject of Subject into an object that
can be passed to to_json()."""
subject_types = cache.SUBJECT_TYPES[subdomain]
attributes = get_attributes_to_render(subject_types)
attribute_jobjects, attribute_is = make_j... | 8d229cebf859ec26b1f4c879e20bcb7f4d841e96 | 3,610,958 |
def left_ascending_super_operator(hamiltonian, isometry, unitary):
"""
binary mera left ascending super operator
Args:
hamiltonian (tf.Tensor): hamiltonian
isometry (tf.Tensor): isometry of the binary mera
unitary (tf.Tensor): disentanlger of the mera
Returns:
tf.Tensor... | 2833b9cad67f3889c1d04a47af33544fca10170d | 3,610,959 |
def TASK_JUMP_FWD(step=1):
"""Jumps to the next task - eng.jumpCallForward()
example: A, B, TASK_JUMP_FWD(2), C, D, ...
will produce: A, B, D
@var step: int
"""
def _x(obj, eng):
eng.jumpCallForward(step)
_x.__name__ = 'TASK_JUMP_FWD'
return _x | de2bb5e71d54ea8cfcef61fa3ba687695b00315c | 3,610,960 |
from pathlib import Path
import jinja2
from functools import reduce
def __save__(
script_name: str, benchbuild: BoundCommand, experiment: 'Experiment',
projects: tp.Iterable[str]
) -> str:
"""
Dump a bash script that can be given to SLURM.
Args:
script_name (str): name of the bash script.... | c7f0628fbf293626e42a7c6b1ce288a6b1b0e577 | 3,610,961 |
def fib_iterative(n):
"""Calcualte n-th element of Fibonacci sequence. Assumes n >= 2
Returns: Fibonacci sequence up to element n, and n-th element of the seq.
"""
fibSeq = [0, 1] # base case
for ii in range(2,n): # note: list(range(2,2)) is an empty list []
fibSeq.append(fibSeq[ii-2... | f28c44bc277c8f5e97e507461f3321bc0aa0510e | 3,610,962 |
from typing import Union
from pathlib import Path
from typing import Iterable
from typing import Type
from typing import Callable
from typing import List
from typing import Any
def discover_functions(
source: Union[Path, str, Module, Iterable[Module], type],
signature: Type[Callable] = Callable, # ty... | 3169e7979cf6e138e4116e9512f5fd4583acbeee | 3,610,963 |
from sys import path
def is_single_file(source_ref_path):
"""return bool"""
return path.isfile(source_ref_path) or uri_validator(source_ref_path) | 9dfae30ab5e72c8de87d1adcd213db6a3719c8b3 | 3,610,964 |
import re
def translate_connstring(connstring):
"""
Acepta un parámetro "connstring" que tenga la forma user@host/dbname
y devuelve todos los parámetros por separado. Tiene en cuenta los
valores por defecto y las diferentes formas de abreviar que existen.
"""
user = "postgres"
... | d74d5a1f22179d8906c8a2e8b568b68b97cc4ba9 | 3,610,965 |
def bytescale(im):
"""
The input should be between [0,1]
output is [0,255] in a unsigned byte array
"""
imout = (im*255).astype('u1')
return imout | d3de7ebeb7601235c91d2ea345925ae0e11351ad | 3,610,966 |
import hashlib
def gen_md5(src_byte):
""" gen md5
:param src_byte:
:return:
"""
m2 = hashlib.md5()
m2.update(src_byte.encode("utf-8"))
return m2.hexdigest() | 3243606076735065c87c28eed473d47c6166b0b0 | 3,610,967 |
import json
def workout_map_shot(context, request):
"""
Ask for the screenshot of a map, creating one if it does not exist.
A json object is returned, containing the info for the needed screenshot
"""
if context.map_screenshot is None:
save_map_screenshot(context, request)
info = {'ur... | efd560ce96545262aa01f774a62a3352caa91f2e | 3,610,968 |
import os
def config_read_only(host):
""" Determine how read_only should be set in the cnf file
Args:
host - a hostaddr object
Returns:
The string value of READ_ONLY_OFF or READ_ONLY_ON.
"""
zk = MysqlZookeeper()
try:
(_, replica_type) = zk.get_replica_set_from_instance(host)... | 163141531ccefd29166e033094ae236721251f8b | 3,610,969 |
def to_string(opt):
"""Encodes the option into a string"""
entry = opt.entry
if not tosave(entry):
return False
line = ''
for key, val in entry.items():
if key in ['kid']:
continue
val = '{!r}'.format(val)
val = val.replace(assign_sym,
... | dffa69ffb4468da9704db04728fcf144fab25c21 | 3,610,970 |
from typing import List
from typing import Union
from typing import Optional
from typing import Match
import re
def search_in_comments(
comments: List[Union[str, Comment]], filter_regex: str
) -> Optional[Match[str]]:
"""
Find match in pull request description or comments.
Args:
comments: Lis... | 488723975d8d91a2796c25bd6bed12e562194c38 | 3,610,971 |
import os
import logging
import time
def train():
"""Train fasterrcnn dataset."""
config_train = DatasetConfig().to_dict()
config_train = config_train['_class_data'].train
prefix = "FasterRcnn.mindrecord"
mindrecord_dir = config_train.mindrecord_dir
mindrecord_file = os.path.join(mindrecord_di... | e8ecbe34249c4b420b2745c3f5074003c3d1c63c | 3,610,972 |
def create_local_adapter_access(mmu_access, adapter_description, adapter):
"""
Creates a local adapter access.
Parameters
------------
mmu_access : MMUAccess
The mmu access the adapters are connected to
adapter_descriptions : AdapterDescription
The adapter description
ad... | 4151336f814daad1c0357eafd6426357f0638285 | 3,610,973 |
def avro_artifacts(version = "1.8.2"):
"""
version: str = "1.8.2" - the version of avro to fetch
"""
return [
maven.artifact(
group = group_id,
artifact = artifact_id,
version = version,
)
for [group_id, artifact_id] in [AVRO, AVRO_TOOLS]
] | 0f5120fc73fa060bd3ea0291e99222fd714a3a32 | 3,610,974 |
import keras.backend as K
from keras.layers import Input
from keras.layers import Conv2D
from keras.layers import MaxPooling2D
from keras.layers import BatchNormalization
from keras.layers import Activation
from keras.layers import GlobalAveragePooling2D
from keras.layers import ZeroPadding2D
from keras.layers import D... | 720a61c92d1e873e789e9e73b3b5c8669e4e86a4 | 3,610,975 |
import subprocess
import re
def bed_generate_random_negatives(in_bed, chr_sizes_file, out_bed,
incl_bed=False,
excl_bed=False,
allow_overlaps=False):
"""
Shuffle given in_bed, generating random negative regio... | bebd8983a7c91289a9b4430fb9b4f97861ed65b0 | 3,610,976 |
import re
def parse(docs):
"""Parse __docs__ text into markdown. Will parse directives like `:param name:` etc"""
# strip leading tabs
if not docs:
return ""
docs = strip_leading_tabs(docs)
if ":param" in docs:
out, title_set = [], False
for line in docs.splitlines():
if ":param" in line:
if not t... | d78f2e1cac80134f65c492b7a48109c745b1ea81 | 3,610,977 |
def mergersort(arr):
"""Sort function."""
def split(arr):
if len(arr) <= 1:
return lst
mid = len(arr) // 2
left = arr[:middle]
right = arr[middle:]
left = split(left)
right = split(right)
return merge(left, right)
def merge(left, right):... | a592c75d6903c0d82feff4eda21d9136e13fe452 | 3,610,978 |
def default_interface():
"""
Return just the default interface device dictionary.
"""
parser = get_parser()
return parser.default_interface | b0e8c296e43b00d224db4e243b033957e8b380b2 | 3,610,979 |
def ape(y, p):
"""Absolute Percentage Error (APE).
Args:
y (float): target
p (float): prediction
Returns:
e (float): APE
"""
assert np.abs(y) > EPS
return np.abs(1 - p / y) | 0093cb2474b42a2dddc00577afbcc5b920bf1964 | 3,610,980 |
def new_record(score):
"""Verifie si le score peu entrer dans le top ten"""
topten = load_json('topten.json')
for index, player in enumerate(topten):
if score > player["score"]:
return index
return None | 2ea1ca763d2f60ccc668377f0c694815eb9a1e84 | 3,610,981 |
def _mean_of_cycle(data, setup_time=30, data_dict={}):
"""
Calculates mean of raw and reference signal during a zero cycle
setup_time in seconds
"""
row_selection = (data.zerocycle_runtime >= setup_time) & (data.State_Zero == 1)
cycle = data.loc[row_selection].agg(
{
"times... | 789cce42efebfa4b46b19e7be991cb1fa433ddae | 3,610,982 |
def proteinnet_tf_dataset(pn_map, batch_size, prefetch=0,
shuffle_buffer=0, repeat=True):
"""
Initiate a TensorFlow Dataset from a ProteinNetMap.
Create a TensorFlow Dataset from a ProteinNetMap, taking the output of the map and adding batching, shuffling and repeating in additio... | c277a591793e9618d3bd8ffc29b21533250ec3a1 | 3,610,983 |
import json
import requests
def post_gist(content, description="", filename="file", auth=False):
"""Post some text to a Gist, and return the URL."""
post_data = json.dumps(
{
"description": description,
"public": True,
"files": {filename: {"content": content}},
... | eddeada0d9bf04f10bc94e290a0f57912573f95b | 3,610,984 |
import functools
def lru_cache(protected: bool = False, maxsize: int = 128, typed: bool = False):
"""
Wrapped version of the functools.lru_cache decorator which
keeps track of all decorated functions to allow clearing all caches.
:param protected: if set to True, the cache for this function will only... | 2ba9ddc450d78f74d509718d6493c6aa8a5a42a5 | 3,610,985 |
def mask2rle(mask):
"""
Efficient implementation of mask2rle, from @paulorzp
img: numpy array, 1 - mask, 0 - background
Returns run length as string formated
Source: https://www.kaggle.com/xhlulu/efficient-mask2rle
"""
pixels = mask.T.flatten()
pixels = np.pad(pixels, ((1, 1), ))
ru... | 8b5feabbb73d88e7055be3cc973f6d4f517aa673 | 3,610,986 |
def CreateUniformBuffer(program, uniform_type, uniform_name, default_data=None):
""" create uniform buffer from .mat(shader) file """
uniform_classes = [
UniformBool, UniformInt, UniformUint, UniformFloat,
UniformVector2, UniformVector3, UniformVector4,
UniformBoolVector2, UniformBoolVec... | 83f5b54ec44a6a8f9100ecb1d4f390d65dea7302 | 3,610,987 |
def root():
"""Base view."""
over10 = Record.query.filter(Record.value >= 10).all()
return str(over10) | 040f7d39311c525b8356065e7cad0a4c65deb920 | 3,610,988 |
def quadratic_2d(data):
"""
Compute the quadratic estimate of the centroid in a 2d-array.
Args:
data (2darray): two dimensional data array
Returns
center (tuple): centroid estimate on the row and column directions,
respectively
"""
arg_data_max = np.argm... | b064d0f6fe4dd5eef51ffe3514731ee3bb588767 | 3,610,989 |
def tr_to_final_ph(stage, tr_to_ph, wind_final_perf, final_ph):
""" Computes the number of trials required to reach the final phase.
"""
time = np.where(stage == final_ph)[0] # find those trials in phase 4
reached = False
if len(time) != 0:
first_tr = np.min(time) # min trial is first tria... | 985ef980475450b62815d5daf200250bcf944798 | 3,610,990 |
def get_shannon_entropy(sequence):
"""Given a sequence, compute the Shannon Entropy, defined in
https://ijssst.info/Vol-16/No-4/data/8258a127.pdf
Args:
sequence (np.array, [t, ]): sequence over which to compute.
Returns:
float: shannon entropy.
"""
# Remove zero entries in sequ... | 9b7a66ef8c0b0d3a05c58e36f1a038471af60f59 | 3,610,991 |
def interpolate_df(x, name, fp):
"""Interpolate a dataframe
:param x: the x-coordinates at which to evaluate the interpolated values
:type x: array
:param name: the name of the column to use in the dataframe for the x-coordinate
:type name: str
:param fp: the dataframe containing the y-coordina... | a48231f4557053082658fe67c479bf31ad5b249d | 3,610,992 |
def geocoder_to_place(result):
"""Convert a result object from geocoder to a Place object"""
return Place(
name=result.address,
country=result.country,
country_code=result.country_code,
state=result.state,
description=result.description + " - " + result.class_description,... | bf0a3d5772dbbdb85c25fdd206b0b8e5c4483bfa | 3,610,993 |
def query_session_job_status(session, status, user=None):
"""
:type session: Session
:type user: User
"""
session = Session.objects.with_id(session)
if not session:
return None, HTTPStatus.NOT_FOUND
if status not in ['success', 'started', 'dispatched', 'ready', 'failure', 'created']... | 3ccc3de65dc834e837c46bea3c6465b8df45c4b6 | 3,610,994 |
def replace_string_newline(str_start: str, str_end: str, text: str) -> str:
"""
re.sub function stops at newline characters, but this function moves past these
params: str_start, the start character of the string to be delted
str_end, the end character of the string to be deleted
te... | c2f4888ed285dc6a48b6a839ff62dbe50865472c | 3,610,995 |
def convert_cell(ase_cell):
"""
Convert a parallelepiped (forming right hand basis)
to lower triangular matrix LAMMPS can accept. This
function transposes cell matrix so the bases are column vectors
"""
cell = ase_cell.T
if not is_upper_triangular(cell):
tri_mat = np.zeros((3, 3))
... | e3272d91517979cfb0be1be0a158f359c88c278e | 3,610,996 |
def header_required(response, name, callback=do_nothing):
"""Checks that a specific header is in a headers dictionary.
Args:
response (object): An HTTP response object, expected to have a
``headers`` attribute that is a ``Mapping[str, str]``.
name (str): The name of a required heade... | 6454b2e201114051a85da5e3142030d46ec88130 | 3,610,997 |
def test_node_catchup_when_3_not_primary_node_restarted(
looper, txnPoolNodeSet, tdir, tconf,
allPluginsPath, steward1, stewardWallet):
"""
Test case:
1. Create pool of 4 nodes
2. Stop not primary node
3. Send some txns
4. Start stopped node
5. Ensure, that restarted node go... | ea3eb0a7ce7ec9dd81c753193a12d572fe03aeb6 | 3,610,998 |
def get_model(point_cloud, is_training, num_class, bn_decay=None):
""" Semantic segmentation PointNet, input is BxNx3, output Bxnum_class """
if isinstance(num_class, int):
num_class = [num_class]
batch_size = point_cloud.get_shape()[0].value
num_point = point_cloud.get_shape()[1].value
end_... | 751d27dddab1948a0cba2bf9bcf89ad7a13f4b2e | 3,610,999 |
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