sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
4e27ab1e01c1a791b55be707b6865719b2638dd021b676ff426a91ce23516665 | Python | 2,151 | 63 | # MIT License
#
# Copyright (c) 2020 Gabriel Nogueira (Talendar)
# Copyright (c) 2023 Martin Kubovcik
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without ... |
e0fbecd5b1786f7ee436dfb024822e2f816c4f13c2b93d18bbcec8e77dc4eed4 | Python | 2,152 | 58 | """Exercise release commands in a disposable project without network writes."""
import os
import shutil
import subprocess
import sys
from pathlib import Path
import pytest
ROOT = Path(__file__).resolve().parents[1]
@pytest.fixture
def release_project(tmp_path):
shutil.copy2(ROOT / "Makefile", tmp_path / "Makef... |
f6a41225fb8487d401a9c85d59de2c31aba695beef71bcd8da6945c075dd9b93 | Python | 2,152 | 69 | from cmath import sqrt
from numpy import random
import numpy as np
import math
import time
class viewContainer():
# container 应该包含所有刺激所需的要素
def __init__(self, config) -> None:
# w 代表window,所有的刺激都要在win上显示
self.w = None
# displayFrame是呈现最终结果的刺激帧
self.displayFrame = N... |
26bd4d17dbde286d8e6fa2776eb9c054469deb090e766e040501b5044b807eeb | Python | 2,157 | 88 | """Create a pdb list hdf5 file for base of coordinate processing pipeline"""
from argparse import ArgumentParser
import logging
import os
import urllib.request
import pandas as pd
import h5py
import numpy as np
def csv_to_hdf5(
csv_filename: str,
hdf5_filename: str,
ds_name: str,
download: bool=Fals... |
bcf594621d21e5f5f3fbdbb7d9d7daf8f8ccab8b2c7b9550aefda42f0a5c124c | Python | 2,157 | 65 | # Copyright 2018-2023 Xanadu Quantum Technologies Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or... |
4acb6faaf494f174349a33a382ed8cfde0dadd1296121180e054ce10a3f36638 | Python | 2,158 | 49 | from .activation_functions import matrix_3D, matrix_2D
import pandas as pd, numpy as np, psutil, os
def matrix_G(param, inputs):
if len(inputs) == 3:
input_1, input_2, Iapp = inputs
return matrix_2D(param, input_1, input_2, Iapp, hidden_layer(param, 2))
if len(inputs) == 4:
input_1, inp... |
f73559ec86015159ba0f64149315d755e898eda170219ec56589bf9e59563dab | Python | 2,158 | 75 | import numpy as np
from PyQt6 import QtWidgets, QtGui
class DoubleSpinBoxNan(QtWidgets.QDoubleSpinBox):
"""A doubleSpinBox that uses minimum() and maximum() as np.nan"""
def __init__(self, *args, **kwargs):
super(DoubleSpinBoxNan, self).__init__(*args, **kwargs)
self._suffix = self.suffix() ... |
3e94e3acb929c4132745d5e050c1e192629d78f58d40584f1e231cee6f20b687 | Python | 2,159 | 72 | import os
import numpy as np
np.seterr(all="raise")
from deepglyco.speclib.common.combine import NonRedundantSpectraConsensus
from deepglyco.speclib.pep.filter import PeptideSpectrumFilter
from deepglyco.speclib.pep.hdf import PeptideSpectralLibraryHdf
from deepglyco.speclib.pep.spec import PeptideMS2Spectrum
from d... |
9e64cf3c6469e05e200fc1d77f1dc7cfe7738472ae3e6e3a8fa58806fcff1cf9 | Python | 2,160 | 91 | __all__ = [
"BaseOffset",
"Day",
"IncompatibleFrequency",
"NaT",
"NaTType",
"OutOfBoundsDatetime",
"OutOfBoundsTimedelta",
"Period",
"Resolution",
"Tick",
"Timedelta",
"Timestamp",
"add_overflowsafe",
"astype_overflowsafe",
"delta_to_nanoseconds",
"dt64arr... |
eba93bebbb9f526ccc4e3c7ffbbc58dd3a261bdcc62c29db4fd2c9ed96fa09b0 | Python | 2,161 | 59 | import os
import argparse
import json
import pandas as pd
def geometric_descriptor_to_dataframe(di, df, gsa, vsa, vf, output='output.csv'):
result = {}
for path, label in zip([di, df, gsa, vsa, vf], ['di', 'df', 'gsa', 'vsa', 'vf']):
assert os.path.exists(path), f"{path} does not exists"
with ... |
40ce727b495cf4632b74dc1d7c5fbc100c1ba629623693da815d400b5466a18a | Python | 2,162 | 72 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
@pytest.mark.parametrize(
"key_strs,groupers",
[
("inner", pd.Grouper(level="inner")), # Index name
(["inner"], [pd.Grouper(level="inner")]), # List of index name
(["B", "inner"], ["B", pd.Grouper(leve... |
d7db34a29b10befc92a9b5c916a416939b0d5538dfe3a4693515c2805d8ea688 | Python | 2,163 | 55 | import numpy as np
from tensorflow.keras.datasets import mnist
from tensorflow.keras.utils import to_categorical
def probabilistic_proofreading(parent_genotype, offspring_genotypes, ec_factor):
offspring_genotypes = offspring_genotypes.copy()
rows, cols = np.where(offspring_genotypes != parent_genotype)
... |
08e17177c9ebe5b6f69ba75cba923e43e578c86abc06ad722aec5d2c407ca381 | Python | 2,164 | 70 | import numpy as np, sys, shutil, os
import pumpprobe as pp, wormdatamodel as wormdm, wormbrain as wormb
#wormdatamodel is not necessary but its import will serve as a check that all
#the libraries are installed
print("\n\n\nPlease be patient, this script might take some time because it has to rewrite files.\n\n\n")
y... |
64d116c8d6bc549303ba94ccf8fe0b9af8613c849a7836a1f2b23a004c79b7ce | Python | 2,167 | 67 | """PC clocks evaluated with algebraically composed PCA/regression weights.
The builders preserve the original authors' double-precision coefficients.
Composing rotation and regression once avoids storing the large PCA rotation
again for each standalone PCGrimAge proxy. This does not retrain the models.
"""
import tor... |
58f3e6bdfc4a77bf1392a5f23e551f94b1ee4443a33a8e032bceafdb1ccd0cc3 | Python | 2,169 | 56 | #####################################################################################################################
# Date created : 10/21/2022
# Date modified: 10/21/2022
# Purpose : To extract more feature from DSSP file
#######################################################################################... |
c0a4de2dcf072723deb3b21de081cd215902a4e068f1bb36de8ac155cea46e81 | Python | 2,169 | 66 | import numpy as np
import pytest
import pandas as pd
from pandas.core.arrays import IntervalArray
def test_repr():
# GH#25022
arr = IntervalArray.from_tuples([(0, 1), (1, 2)])
result = repr(arr)
expected = (
"<IntervalArray>\n[(0, 1], (1, 2]]\nLength: 2, dtype: interval[int64, right]"
)
... |
7d4ce6b63a419cb0773c474a987f8792f5b195b9718c4661a0f2a6b24b760984 | Python | 2,170 | 61 | import requests
import json
import networkx as nx
import mygene
import os, io
import numpy as np
import pandas as pd
def get_snap(genes, remove_components):
print(len(genes))
G = nx.read_edgelist('data/networks/PPT-Ohmnet_tissues-combined.edgelist', nodetype=int, data=(('tissue', str),))
tissues_edgelis... |
da1a3700ce89c1d86ff76428576370eae2155d1474fbdc9cb11d28f4904f78c3 | Python | 2,170 | 65 | '''
Created on Feb 1, 2013
Implements standard scripts for
anatomical and functional network realizations.
@author: regger
'''
import os, time
from . import reader
from . import writer
from . import cell_parser
from .synapse_mapper import SynapseMapper
from .network import NetworkMapper
from sumatra.parameters impor... |
fa63a5dc1c0ae6da1e2ad8d7f4acba978b677485a3360ba5aebd99395b26dba6 | Python | 2,171 | 76 | from datetime import (
date,
datetime,
)
import numpy as np
import pytest
from pandas._libs.tslibs import ccalendar
import pandas as pd
@pytest.mark.parametrize(
"date_tuple,expected",
[
((2001, 3, 1), 60),
((2004, 3, 1), 61),
((1907, 12, 31), 365), # End-of-year, non-leap ... |
25e2b355fd3327d7cf0d94a8684c7779bfd54d3813ffbd6c6cae0353e658bb7f | Python | 2,172 | 64 | import sys
import re
import tree
def change( t ):
## Fix adjectives combining with nouns to get noun phrases...
if len(t.ch)==2 and re.search( '^.*-lM(-[lmnstuwxy].*)? N-aD(-[lmnstuwxy].*)? N(-[lmnstuwxy].*)?$', t.ch[0].c + ' ' + t.ch[1].c + ' ' + t.c ) != None:
sys.stderr.write( 'Fixing ' + t.ch[0].c + ' ' +... |
38c36444d4bce07440af446a1bf1fec4de1516661bfcd65c399c4364f944c3c9 | Python | 2,175 | 55 | """
Reads one or more fasta MSA files, writes the column-wise letter counts.
That is:
for every column in every input MSA, the number of each amino acid is counted and written to a line in the output file.
Thus the number of lines in the output file is equal to the total number of columns over ... |
782db7576ce05cb46143969e6e09055347d4e750da4e78f736974694c41c28bb | Python | 2,175 | 40 | ##############################################################################
## ##
## This file is part of ModelBlocks. Copyright 2009, ModelBlocks developers. ##
## ##
#... |
d610d40d22bb4ddb74308510edb244dd64f487335f12bce2451f73cd9ff58f27 | Python | 2,175 | 71 | import numpy as np
import pandas as pd
import pandas._testing as tm
class TestDataFramePop:
def test_pop(self, float_frame):
float_frame.columns.name = "baz"
float_frame.pop("A")
assert "A" not in float_frame
float_frame["foo"] = "bar"
float_frame.pop("foo")
asse... |
52f8b9b85bd5d12bbc482519af089b3f334748ce7910683718e5e4057945e137 | Python | 2,176 | 62 | import os
import json
import concurrent.futures
import time
# 多进程 每次处理20个 开16进程 7.231800556182861
# 多进程 新函数 16.66970205307007
apkfilename = []
permission_frequency={}
path = r'E:\pythonProject\Experiment\out_benign_samples'
apk_list=os.listdir(path)
for apk in apk_list:
apk = os.path.join(path,apk)
... |
a7e4eeb5b19b1fe495df420007838e6ab0199eefa06c16760ab9dd48491efee2 | Python | 2,176 | 72 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
def test_take(idx):
indexer = [4, 3, 0, 2]
result = idx.take(indexer)
expected = idx[indexer]
assert result.equals(expected)
# GH 10791
msg = "'MultiIndex' object has no attribute 'freq'"
with pytest.raises... |
da237846b239e24e3b11b41af4f36e3f27b5535e9d7111b2a5eb6fd71fd3d697 | Python | 2,177 | 79 | # -*- coding: utf-8 -*-
"""
Created on Mon Mar 7 19:01:53 2022
@author: System 6
"""
import delta
import deepcellcontrol as dcc
import pycromanager_tessie as pmt
# Start platform:
platform = pmt.microscope.platform.Platform(load_synchronizer=True)
#%% Experimental parameters:
controller = dcc.control.MLPMPC(
m... |
e93cc6c437359df37cb3deaf02ef134d6342c371bc1da4f69b9e0dea8e50233a | Python | 2,177 | 64 | """Tests for Varimax rotation."""
import pytest
import torch
from mrpro.algorithms.varimax import varimax
from mrpro.utils import RandomGenerator
@pytest.mark.parametrize('shape', [(3, 8), (2, 3, 8)])
def test_varimax_shape_dtype(shape: tuple[int, ...]) -> None:
"""Varimax keeps the input shape, dtype, and devic... |
ed252cf8dcd8f1af0e0b8f65cf48a612db5c344843913e5021a16eef677899a7 | Python | 2,179 | 69 | from typing import Any, Optional
import torch
import numpy as np
from scipy import sparse
from torch_geometric.data import Data
from torch_geometric.data.datapipes import functional_transform
from torch_geometric.transforms import BaseTransform
from torch_geometric.utils import to_scipy_sparse_matrix
@functional_tra... |
2568fa926e0bcb4846cc2e42340e0a3d7b5cf0cc06bf93fc8fb96aa96b41531e | Python | 2,181 | 70 | # -*- coding: utf-8 -*-
import numpy as np
import torch
from sdna.net.core import *
def encode(args, net, in_arr=None):
"""
Helper function for encoding.
:param args: Arguments as dictionary.
:param net: Instance of the class net.
:param in_arr: Array of bits to be encoded, if the input is a fi... |
60df8eef74bccc43f78d3e4ce885e2e62fcc488427c7e991e9f1bad44237e900 | Python | 2,182 | 66 | from keras.engine.topology import Layer
import keras.backend as K
class PyramidPooling(Layer):
def __init__(self, pool_list, **kwargs):
self.dim_ordering = K.image_dim_ordering()
self.pool_list = pool_list
self.num_outputs_per_channel = sum([i for i in pool_list])
super(PyramidPoo... |
f3dc87c7acc97ebf0df6173525b6ea883aa242f6bd9917d0b34ca37800ea43ed | Python | 2,182 | 79 | # -*- coding: utf-8 -*-
"""
Created on Sun Oct 8 13:27:53 2023
Convolutional Spiking Neural Networks for Intent Detection Based on Anticipatory
Brain Potentials Using Electroencephalogram
Authors: Nathan Lutes, V. S. S. Nadendla, K. Krishnamurthy
"""
# Ablation study: reduce number of channels in loop to determine ... |
72db2fcae0da61e2640be5308d43f2ed0977c42e0007446ad21e9bac19835eb5 | Python | 2,185 | 66 | # -*- coding: utf-8 -*-
"""
Created on Wed Aug 11 11:15:43 2021
@author: Emmanuel Calvet
"""
from random import gauss
import matplotlib.pyplot as plt
from scipy.signal import butter, lfilter, freqz
import numpy as np
import pandas as pd
from pandas import Series
def butter_lowpass(cutoff, fs, order=1):
nyq = 0.5 ... |
a74f09295b88cfcbce3aecc7689d89f0213d465f76f18323696c9044beaea726 | Python | 2,185 | 68 | import numpy as np
from pathlib import Path
from sklearn.preprocessing import StandardScaler
from sklearn.decomposition import PCA
def loadwl(filename, mode='au'):
""" Returns angles and time from wormlab output
Args:
filename : string
relative path of .txt wormlab output
mode : {'... |
6d4142bfea78d46e0c7a01dffd9bcbbdacc5426ba70a9dd866dc44eb5a038de1 | Python | 2,186 | 62 | import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm
from mpl_toolkits.axes_grid1 import make_axes_locatable
from matplotlib import rc
from pylab import rcParams
from matplotlib.ticker import FormatStrFormatter
import sys
from helper_make_data import make_data
from helper_make import make
# the... |
bc1cc391eb1c007dafec31fb2b6768182820c7f165f4ae090190b6329c303178 | Python | 2,186 | 68 | import torch
import torch.nn as nn
class Conv3x3x3(nn.Module):
def __init__(self, in_channels, out_channels, kernel_size, stride, padding, bias) -> None:
super(Conv3x3x3, self).__init__()
self.conv = nn.Conv3d(in_channels=in_channels, out_channels=out_channels, kernel_size=kernel_size,
... |
d472363d2425809e87d1e55a241b9e0f85a06b95ebd17fa2c26ce3bf2aa125a1 | Python | 2,194 | 59 | """End-to-end smoke test: build -> train -> evaluate -> save/reload -> Grad-CAM.
No OASIS-3 or pretrained weights needed: everything runs on tiny synthetic
arrays, on CPU, to keep this fast enough for CI (`model-smoke` job in
`.github/workflows/ci.yml`).
"""
from pathlib import Path
import numpy as np
import pytest
... |
1860e07e68cb959fcfe3ff6d38b87d3d8d57e37cc598bbc788a3fc3502b95d05 | Python | 2,195 | 75 | import torch
from torch import nn as nn
from torch.autograd import Function
class DiceLoss(nn.Module):
"""
Computes dice loss
"""
def __init__(self, normalization='sigmoid'):
assert normalization in ['sigmoid', 'softmax']
if normalization == 'sigmoid':
self.normalization =... |
4742bee89c7f3fbabbc37d6c0cb768072bf4bcdd6ddadbda4622489982e64904 | Python | 2,195 | 80 | # Configuration file for the Sphinx documentation builder.
#
# For the full list of built-in configuration values, see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Project information -----------------------------------------------------
# https://www.sphinx-doc.org/en/master... |
b082d6c446e4b8489f57aea04a2cf5c3eb0c37175fb29e84450380a0cc889f73 | Python | 2,196 | 57 | from datetime import timedelta
import numpy as np
import pandas as pd
import pandas._testing as tm
class TestDatetimeIndexReindex:
def test_reindex_preserves_tz_if_target_is_empty_list_or_array(self):
# GH#7774
index = pd.date_range("2013-01-01", periods=3, tz="US/Eastern", unit="ns")
as... |
3d78da13c15f4170fae8c81a2b7e2aec197f2e822b3cf80a627a5fa54f154f79 | Python | 2,199 | 65 | import numpy as np
import os
import sys
from hdf5storage import loadmat
from hdf5storage import savemat
sys.path.append('data')
from data.DataProcess import process
def computing_predictive_measures(res_path="results", rank=2, model='oslmm', domains=["equity"], verbose=False):
for domain in domain... |
5f7fc7f498bff04c12e3f48a95223f127795d67ca5e91b8f017e5027730f9561 | Python | 2,199 | 57 | import numpy as np, matplotlib.pyplot as plt
import pumpprobe as pp
fname = "external_data/GenesExpressing-unc-7-unc-9-inx-_-eat-5-thrs2.csv"
funa = pp.Funatlas(merge_bilateral=True)
funa.load_aconnectome_from_file(gap_th=0)
f = open(fname,"r")
lines = f.readlines()
f.close()
ids = lines[0].split(",")[4:]
exp_levels ... |
8ecf9fb3527d92ce76ada452230696fb4f5125c426c7d0be073910cc1a596831 | Python | 2,199 | 59 | # _*_ encoding: utf-8 _*_
__author__ = 'wjk'
__date__ = '2019/12/18 16:07'
'''https://github.com/Bjarten/early-stopping-pytorch/blob/master/pytorchtools.py'''
import numpy as np
import torch
class EarlyStopping:
"""Early stops the training if validation loss doesn't improve after a given patience."""
def __... |
befc536a1ca041840d495107136b2d7a78bfe8aaee8ac7974d4b33bf19c6270c | Python | 2,199 | 69 | """Assignment gate: flag PRs whose author doesn't hold the linked issue.
A PR against an unclaimed issue is labeled and left open; one against an
issue someone else already holds is labeled, commented on, and closed.
Triggered by ``pull_request_target`` on ``opened`` / ``reopened``.
"""
from __future__ import annota... |
aa7d21ddcfda7a98fbadfa593f27326017156cc8fbcf003f8b857237597c6e4c | Python | 2,201 | 78 | # Copyright 2024 Xanadu Quantum Technologies Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agre... |
65a1b9e0a17d06e2437b0d3e0036cb155435bc706f2a733c1eaac747325fa251 | Python | 2,202 | 68 | """Test nimare.decode.continuous.
Tests for nimare.decode.continuous.gclda_decode_map are in test_annotate_gclda.
"""
import pandas as pd
import pytest
from nimare.decode import continuous
from nimare.meta import kernel, mkda
def test_CorrelationDecoder_smoke(testdata_laird, tmp_path_factory):
"""Smoke test for... |
04349dc9f0b466095bde7167dc0d82b4e3c20ad5af467da477bf310b163ca6fc | Python | 2,203 | 67 | #!/usr/bin/env python
import pandas as pd
import scanpy as sc
import numpy as np
import os
import pegasusio as io
import argparse
parser = argparse.ArgumentParser(description='Parser for Downsampling - Demultiplexing')
parser.add_argument('--hto_data', help='path to HTO data')
parser.add_argument('--downsampling_seed'... |
0f4874fecc61ec16487369478be479a28136de1505314ca3d75712352fdd5bd7 | Python | 2,203 | 64 | # Copyright 2018-2023 Xanadu Quantum Technologies Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or... |
5b73b401b343a6a2e539c00abed163c187fb35c1d5cc80a2f9b4a3145638696e | Python | 2,203 | 59 | # Copyright 2018-2023 Xanadu Quantum Technologies Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or... |
d9b24bad613eba018c4b6fc1e580b816d7a139fe85c6e4c8a8e92d1414d8b6e9 | Python | 2,203 | 71 | import numpy as np
import pandas as pd
import pandas._testing as tm
class TestUnique:
def test_unique_uint64(self):
ser = pd.Series([1, 2, 2**63, 2**63], dtype=np.uint64)
res = ser.unique()
exp = np.array([1, 2, 2**63], dtype=np.uint64)
tm.assert_numpy_array_equal(res, exp)
d... |
8283180f97b731e7d0335516c5b2c784ab4bee74d19fea44ca06a01f3f433072 | Python | 2,204 | 67 | import os.path
import shutil
import tarfile
import zlib
import zipfile
from time import gmtime, strftime
refuseddirs = ['CVS','Debug','Release','moc','obj','tmp','data','hannes','doc','lib','bin']
refusedfiles = ['Makefile','.cvsignore','gl2psTest.c','gl2ps.bat','gl2ps.pro']
requiredfiles = ['qwtplot3d.dsw','... |
0e303d4e1cff8a0fd7b322154236deb23887b8ddd994438471d1a66a803f0ee6 | Python | 2,205 | 78 | """
detection.py
Created May 23, 2021
Converts a color image to binary mask of the grid.
"""
import cv2
import numpy as np
from ..image import BinaryImage, ColorImage
from .. import vision
from ..signal.detection import adaptive
def kernelApproach(colorImage: ColorImage) -> BinaryImage:
binaryImage = colorImage... |
7f5e90ba3d229321649c3398f0c7df21bd41d2870aac42e56637add311557183 | Python | 2,205 | 74 | # -*- coding: utf-8 -*-
"""
Created on Mon Jul 25 16:04:54 2022
@author: fm02
"""
### Author: federica.magnabosco@mrc-cbu.cam.ac.uk
### Plot results from LDvsSD individual ROIs accuracy
import numpy as np
import pandas as pd
import pickle
import seaborn as sns
import matplotlib.pyplot as plt
from scipy.stats import ... |
8f5118fd2fee2af76da244026833f3d1cd93982ae0762e1d3ac53bf7ac5308da | Python | 2,209 | 69 | import argparse
import pandas as pd
from aggregate_surp_lstm import load_surp_lstm
from utils import filter_bccwj_eyetrack, normal_bracket2ptb_bracket, zen2han
parser = argparse.ArgumentParser()
parser.add_argument(
"--bccwj_eyetrack_path", type=str, default="data/BCCWJ-EyeTrack/fpt.csv"
)
parser.add_argument("--... |
c0da02bad5b022b79478a0a0e2271e06ebbe516b185bc6697cd6b86b05c9d46a | Python | 2,209 | 53 | #!/usr/bin/env python
__author__ = 'etseng@pacb.com'
"""
Sequence headers must have:
@i0_LQ_sample32f89e|c31/f12p0/433 isoform=c31;full_length_coverage=12;non_full_length_coverage=0;isoform_length=433;expected_accuracy=0.300
"""
import os, sys
from Bio import SeqIO
def func(r):
fl_count = None
exp_acc = No... |
fc6454fb30668c8bc34e95305c26ec350c2a04d29126951dd7eaff22f044929c | Python | 2,209 | 69 | # Source - https://stackoverflow.com/a
# Posted by TomNorway
# Retrieved 2025-12-04, License - CC BY-SA 4.0
import numpy as np
def autoscale(ax=None, axis="y", margin=0.1):
"""Autoscales the x or y axis of a given matplotlib ax object
to fit the margins set by manually limits of the other axis,
with margi... |
0b1a5bfa48cb8e553d413c890166f951c1839a703051678c102684c9e03c2f30 | Python | 2,210 | 66 | # %%
import numpy
import spycon
from spycon import coninf, load_test
from spycon.coninf import setup_ensemble
model_path = "../data/nn_models/"
# Name of tests that are used for training
train_test_names = [
"ren_simulation_2602_cell3VC_340_20",
"ren_simulation_2602_cell3VC_340_16",
"ren_simulation_2602_c... |
b9a71f3f6205ef983193cdea69736f740485c4b4961bbda29e06d0ba0b08f568 | Python | 2,210 | 49 | import torch
from mrpro.operators import ConstraintsOp, FunctionalType, OptimizerOp
from mrpro.operators.functionals import L2NormSquared
from mrpro.operators.models import InversionRecovery
from mrpro.utils import RandomGenerator
def test_optimizer_op_gradcheck() -> None:
"""Test the optimizer op with gradcheck.... |
c77a4a2d038983abb6e35e7492bb4e1124cc724a196cc434b4f3f70081615d5b | Python | 2,210 | 73 | import torch.nn as nn
import torch
class SparseConv(nn.Module):
"""
A very simple but inefficient way of implementing sparse convolution according to
3D Semantic Segmentation with Submanifold Sparse Convolutional Networks, CVPR 2018
"""
def __init__(self, conv_type, mask_exclude_first_dim=False, ... |
080e93bfcaecd09f6aa149c4f6cd3541e911603aade384d682acc1a89a2e7e0b | Python | 2,212 | 66 | """Screenshots for quick guide emodulus"""
import os
import sys
import tempfile
import dclab
import h5py
import numpy as np
from PyQt6 import QtCore
from PyQt6.QtWidgets import QApplication
from shapeout2.gui.main import ShapeOut2
app = QApplication(sys.argv)
QtCore.QLocale.setDefault(QtCore.QLocale(QtCore.QLocale.L... |
828c7994998f04be1125fdaf5ba6069b02a1206e9f72497111f824ed20fdb502 | Python | 2,213 | 90 | from functools import reduce
import numpy as np
from pybedtools import BedTool
# numpy log10 float max
FLOAT_MAX = np.finfo(np.float64).max
LOG10_FLOAT_MAX = np.log10(FLOAT_MAX)
# Fast method for getting number of lines in a file
# For BED files, much faster than calling len() on file
# From https://stackoverflow.c... |
4f664dfb3b0b5184051d36f0048ad76f7a2a010ccc111912efb99d8f8160e0bf | Python | 2,215 | 57 | # -*- coding: utf-8 -*-
# Copyright (C) 2019 Andrea Vázquez Varela
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#... |
7738c3a249bfdb995f32c0ed640d8444aa5e13f72b29b44919914dbd218b4946 | Python | 2,216 | 66 | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... |
0770bf9b82203077e01848a11918bcd77cf822b0db177e6e3be8b2662dd6b16b | Python | 2,217 | 58 | import os
import pandas as pd
import numpy as np
from copy import deepcopy
def tuning_analysis(r_dir, r_f, tuning_table):
df = pd.read_csv(r_f, index_col="Run Name")
df = df[df['Table'] == tuning_table]
if tuning_table in ["lf_tuning", "bert_lf_tuning"]:
df = df[df['Class Imbalance Fix'] == 'unde... |
fa4986f1a111538e8a40732410db17e84bb702b94fadb2d2b3fd126a66c62081 | Python | 2,217 | 40 | import os
import models.args
def get_args():
parser = models.args.get_args()
parser.add_argument('--bidirectional', type=bool, default=True)
parser.add_argument('--num-layers', type=int, default=1)
parser.add_argument('--hidden-dim', type=int, default=512)
parser.add_argument('--mode', type=str,... |
731b276485d59c784038c0db207c15c3d99c38a681edfd33240d4cbd2bff457a | Python | 2,218 | 63 | """
Python implementation of kernel Current Source Density method
"""
from setuptools import setup, find_packages
import sys
def readme():
"""
Used for README
"""
if sys.version_info.major < 3:
print('No support for python versions < 3.8')
with open('README.rst') as f:
retu... |
992a2c00c506191e7c0ef55398ef044f787b14f316ed7385d3d256344a07ab87 | Python | 2,218 | 64 | import argparse
import pysam
import os
def get_args():
"""
Get arguments from command line with argparse.
"""
parser = argparse.ArgumentParser(
prog='bam2paf.py',
description="""Convert an aligned bam from minimap2 into paf.""")
parser.add_argument("-i", "--input_bam",
... |
1375d0654f85fa65deb8b78523fffc8790c4800ee42f288859be11b8483eb78f | Python | 2,219 | 59 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Jan 24 20:50:46 2022
@author: rt2372
"""
import numpy as np
import torch
class EarlyStopping:
"""Early stops the training if validation loss doesn't improve after a given patience."""
def __init__(self, patience=7, verbose=False, delta=0, path... |
ffe0256a5d69dbdc8c9abe3fed0e1a3dd825d018dc9f16988cf502f0bb82a189 | Python | 2,219 | 60 | # Copyright 2018-2023 Xanadu Quantum Technologies Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or... |
243eacc0ae82447f6ae594382452922de36e085da8b821253da19f1c5a0b728d | Python | 2,220 | 82 | # JN 2015-04-24
"""
read out the structure of a sorting folder
"""
from __future__ import division, print_function, absolute_import
import logging
logger = logging.getLogger(__name__)
import os
import glob
from .. import options
def check_folder(dirname, data_only=False):
"""
check whether there is a file dat... |
eea1020c6e8cea0db8f3efb5665a59e4dc6b0e23b04435bfae6d95e0b644f439 | Python | 2,222 | 51 | import pandas as pd
from sklearn.utils import shuffle
from sklearn.model_selection import train_test_split
import os
pwd = os.path.abspath(os.path.dirname(__file__))
print(pwd)
files = ["Bitter", "Sweet", "Sour", "Salt", "Umami", "Kokumi", "Astringent", "Tasteless"]
for i,file in enumerate(files):
path = pwd... |
0604197ec0694a77ab9b47277e68f5c6b318dc592e5da57b2f64f2d4a46a7a31 | Python | 2,224 | 69 | from datetime import time
import locale
import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
from pandas.core.tools.times import to_time
class TestToTime:
@pytest.mark.parametrize(
"time_string",
[
"14:15",
"1415",
"2:15pm",
... |
bc36970d3a00616fdfe95c22638a858053a392fa4728ab13758675d1950c8215 | Python | 2,225 | 98 | """Auto-generate the private API page."""
from pathlib import Path
from rich import print
code_src = Path(__file__).parent.parent / "+bids"
doc_src = Path(__file__).parent / "source"
bidspm_file = doc_src / "developper_doc" / "private_api.rst"
dir_ignore_list = ("+util", "+transformers_list")
file_ignore_list = ... |
0ffd874ee7ea642b73547f0fb573a55df5c5161e3c582e6cee8c29d696c7a86e | Python | 2,226 | 48 | # -*- coding: utf-8 -*-
import matplotlib.pyplot as plt
import numpy as np
import json
import time
import openmc
from utils.mcsimulation_tetris import *
from env_config import *
#=========================set values below==========================
num_sources = 1 # the number of radiation sources to place.
shape_na... |
5685eedc24a88826dfab5a1f3937717eb9681447c28cc8431a23e0f7be6b3b1a | Python | 2,226 | 84 | import os
import sys
from recommonmark.parser import CommonMarkParser
from xml.sax.handler import feature_external_ges
sys.path.insert(0, os.path.abspath("../"))
mathjax_path = (
"https://cdn.mathjax.org/mathjax/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML"
)
# Configuration file for the Sphinx documentation bui... |
2bced037bdc977797d5a05498ee237bcb40269c34466abc327e8eb8a096d9bbb | Python | 2,227 | 61 | """Tests for MultiEchoSpinEcho signal model."""
from collections.abc import Sequence
import pytest
from mrpro.operators.models.NeuroMRF import DELICS_FLIP_ANGLES, NeuroMRF
from mrpro.utils import RandomGenerator
from tests import autodiff_test
def test_neuro_mrf_basic(parameter_shape: Sequence[int] = (2, 1, 3, 4, 2... |
81bf75f96db1591cf9b0ed98dbfd628d7003c71094d76fa0c310a72a62f939d5 | Python | 2,227 | 41 | """Shared type aliases for inference-time configuration: precision, execution
runtime, export target, and video reader.
Kept in a standalone module with no heavy dependencies (no torch/cv2/pandas) so
`lightning_pose.cli` can import these values eagerly, at argument-parser
construction time, without paying the cost of ... |
84273a01eb5375fc401adbe537d5ea0681add3f36be8f541360c63d746de2142 | Python | 2,227 | 68 | __all__ = ["PeptideMS2Output", "PeptideMS2BiLSTM", "PeptideMS2CNNLSTM"]
import torch
from torch import nn
from ....util.collections.dict import chain_get_typed, chain_item_typed
from ...util.timedistributed import TimeDistributed
from ..common.data import PeptideDataBatch
from ..common.model import PeptideBiLSTM, Pep... |
0d30c5ddf464c03fda9d8c64b3179be878c0553d5b14e72e4c750eafc5a54f30 | Python | 2,228 | 64 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
class TestDataFrameSetItem:
def test_isetitem_ea_df(self):
# GH#49922
df = pd.DataFrame([[1, 2, 3], [4, 5, 6]])
rhs = pd.DataFrame([[11, 12], [13, 14]], dtype="Int64")
df.isetitem([0, 1], rhs)
... |
39e5a4eb83361140eafa61ac71a406293a16fae633d56f53a3675abb7db0a8c0 | Python | 2,229 | 68 | #%%
import torch
import torch.nn as nn
import torch.nn.functional as F
class DoubleConv(nn.Module):
"""(convolution => [BN] => ReLU) * 2"""
def __init__(self, in_channels, out_channels, mid_channels=None):
super(DoubleConv, self).__init__()
if not mid_channels:
mid_channels = out_c... |
0b5b65640e9af8e007b3a6e87c3189d4c0f6f1a93fb2186e236a617f4185b480 | Python | 2,230 | 66 | """Analysis result envelope + base error type."""
from __future__ import annotations
from dataclasses import dataclass, field
from typing import Any
class AnalysisProcedureError(RuntimeError):
"""Raised when a procedure can't compute (missing column, empty
group, singular matrix, …). The API layer converts ... |
dca6fa5f652b04e7b5bb794ba8752f9a3475234cc08fce70588c56c39f2aa60b | Python | 2,230 | 81 | """Test ISMRMRD acquisitions based on their flags."""
import ismrmrd
from mrpro.data.enums import AcqFlags
# Same criteria as https://github.com/wtclarke/pymapvbvd/blob/master/mapvbvd/mapVBVD.py uses
DEFAULT_IGNORE_FLAGS = (
AcqFlags.ACQ_IS_NOISE_MEASUREMENT
| AcqFlags.ACQ_IS_DUMMYSCAN_DATA
| AcqFlags.AC... |
883181419f71fc9dda5f021642a7c937a240acadd3e24a4885e876a39672714e | Python | 2,231 | 71 | # -*- coding: utf-8 -*-
"""
WM segmentation
"""
import os
import numpy as np
import nrrd
from app.processing.preprocess import hist_perc
from app.processing.morphops import fill_holes_2D, labelsize
from skimage import morphology
import logging
logger = logging.getLogger(__name__)
def segment(im_t1_path, im_brain_ma... |
bac66f0b63e404fe9c95e0a4e12f672c1a020f9c248e165ff9337de9d3406f85 | Python | 2,231 | 70 | #!/usr/bin/env python
"""
Given a FAA file, group identical ORFs.
INPUT: a single FAA file
OUTPUT: a de-duped FAA file with a companion "group" file
The de-duped FAA format:
>ORFgroup_<PB.X>_<index> if it is in PB.X.Y format
>ORFgroup_<index> if not PB.X.Y format
The group file format:
ORFgroup_<index> \t comma... |
ac8f6d884024159f87c8a2aa5ef21fccd7d0f387d586ae582dbafc1219bf3558 | Python | 2,232 | 71 | import numpy as np
import pytest
import pandas as pd
@pytest.fixture
def data():
"""Fixture returning boolean array, with valid and missing values."""
return pd.array(
[True, False] * 2 + [np.nan] + [True, False] + [np.nan] + [True, False],
dtype="boolean",
)
@pytest.mark.parametrize(
... |
b3843c883a54c3b10b1b67faebaa578efcd604a3e3eff1789ed2e3a1fb19907f | Python | 2,232 | 63 | import pytest
from cardiomyocyte_emulator import APEmulator, load_default_emulator_model
import torch
import numpy as np
all_devices = ["cpu", "cuda"]
available_devices = (all_devices if torch.cuda.is_available() else ["cpu"])
def test_import():
pass
@pytest.fixture(scope="module", params=all_devices)
def defaul... |
451456c6d556c9589aaf067c1bb80b188a1803dd33726c8e44698b119ddb6f0e | Python | 2,233 | 61 | """Inversion recovery signal model for T1 mapping."""
from collections.abc import Sequence
import torch
from mrpro.operators.SignalModel import SignalModel
from mrpro.utils.reshape import unsqueeze_right
class InversionRecovery(SignalModel[torch.Tensor, torch.Tensor]):
"""Inversion recovery signal model."""
... |
2cd26d602943ab28a6feb35536a2a5b9c511c6a65e4e71f12abbc0daeb6b5317 | Python | 2,238 | 68 | #%%
from src import fs_roi_lut
import json
import os
import pytest
import pandas as pd
TEST_FILE_ROIS= 'rois.json'
TEST_FILE_LUT= 'ROI_LUT_FS_2_PVE_test.xlsx'
def _create_json(mode):
""" create a json file for testing
args:
mode (int): 0: working, 1: wrong label, 2 not matching index/label length"""
... |
3bf044798e4e7041a72877f3c0a986fb3bd54e09c70bb26af809206f033e45ff | Python | 2,238 | 63 | from umap.spectral import spectral_layout, tswspectral_layout
import numpy as np
import scipy.sparse
import pytest
import re
from scipy.version import full_version as scipy_full_version_
from warnings import catch_warnings
scipy_full_version = tuple(
int(n)
for n in re.findall(r"[0-9]+\.[0-9]+\.?[0-9]*", scip... |
0f187984957371369a15078f3b567b71968431a58fd675154b04e590e54d27fe | Python | 2,239 | 61 | import pytest
import pandas as pd
import pandas._testing as tm
class TestAppend:
@pytest.fixture
def ci(self):
categories = list("cab")
return pd.CategoricalIndex(list("aabbca"), categories=categories, ordered=False)
def test_append(self, ci):
# append cats with the same categori... |
f5d94bffcfbc9f03d6aaf6661c2bfdbfb13ea5759afe9e9741bb3a9efb488456 | Python | 2,240 | 67 | """`LLMProvider` Protocol — the one interface every LLM backend implements.
The router dispatches on `provider` name; every backend normalises its native
response into a plain ``dict`` that matches `LLMAdvice.model_validate(...)`.
Prompt + output-schema shape come from `consultations/*.py`; the provider
is only respon... |
27e062abe10ba7c7b2aaaee44f77d596c128f3c760e41ade57fb546e105919e2 | Python | 2,241 | 83 | import argparse
import pandas as pd
from utils import filter_bccwj_eyetrack, normal_bracket2ptb_bracket, zen2han
parser = argparse.ArgumentParser()
parser.add_argument(
"--bccwj_eyetrack_path", type=str, default="data/BCCWJ-EyeTrack/fpt.csv"
)
parser.add_argument("--unit", type=str)
parser.add_argument("--rnng_s... |
4b86cf13a0bac4db090e44c523530c2d9dda52f5d408f76829f465c66750b4cd | Python | 2,241 | 75 | import zoneinfo
import pytest
from pandas.compat import (
pa_version_under23p0,
)
import pandas as pd
import pandas._testing as tm
from pandas.io._util import arrow_table_to_pandas
pa = pytest.importorskip("pyarrow")
pytz = pytest.importorskip("pytz")
pytestmark = [
pytest.mark.filterwarnings(
"i... |
a9bc7b33d5acc77b836e418e9c4cf519ed6584ab58c4a7ef598726b9bff7707d | Python | 2,241 | 54 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
class TestDateTimeIndexToJulianDate:
def test_1700(self):
dr = pd.date_range(start=pd.Timestamp("1710-10-01"), periods=5, freq="D")
r1 = pd.Index([x.to_julian_date() for x in dr])
r2 = dr.to_julian_date()
... |
8b52921cdd175d9e7b05a1592ae2ec32ad0c031d2e70d16c6ece9da36d228262 | Python | 2,243 | 60 | """Regression tests for persistent Merge View resource cleanup."""
from phylib.utils.event import _EVENT
from phy.gui.tests.conftest import gui # noqa: F401
from .test_supervisor import _select, supervisor # noqa: F401
def test_supervisor_merge_mode_reuses_callbacks_until_shutdown(supervisor): # noqa: F811
... |
9b4b1aa6173f6d4cabdbcb98f8e29435b50a657544233e10db544218d53494bd | Python | 2,243 | 67 | """
Three Gaussians spread along the diagonal of a six-dimensional hypercube.
This coding style for the integrand is almost as simple as slow.py
but much faster because the integrand is coded in Cython and compiled.
Run times are 20x shorter than slow.py.
Runtime is about the same for faster.py and fastest.py. This... |
df01a80511c174505fb2f1d934bf07ec1575650e556118652b1fdc4dad1f6b7f | Python | 2,245 | 68 | import os
import sys
import numpy as np
# Get the absolute path to the root directory of your project
project_root = os.path.dirname(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))))
# Append the project root to sys.path
sys.path.append(project_root)
from src.nexi.models.functions.rician_m... |
74b2f73c3962fbb8cd3317874d1097364044c79051b62c9548d49f7f0a0b4fd2 | Python | 2,247 | 77 | import sys
import re
import pdb
class Counter(object): #ummm, why not just use an integer here?
def __init__(self,start=1):
self.count = start
def __call__(self):
val = self.count
self.count += 1
return val
def invertChains(chains):
inverted = {}
for item in chains.item... |
d9ca454db17a4fd3203d3d4ccc0ea5898e6b8418b91b836f35a854ac3d78db6d | Python | 2,248 | 68 | # Created by G. Peter Lepage (Cornell University) in 12/2013.
# Copyright (c) 2013-14 G. Peter Lepage.
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# an... |
987c18d4cea3e30e1bbd58710563620fab88f4573422f255700a65e690cc74a8 | Python | 2,249 | 66 | import argparse
import logging
import re
from Bio import SeqIO
def get_args():
"""
Get arguments from command line with argparse.
"""
parser = argparse.ArgumentParser(
prog='Parse-SAM.py',
description="""Get ordered unique read names in SAM file.""")
parser.add_argument("-s", "--sa... |
0e2ce0d0538ac7ea3ae2ad8c475566463a4e04dbe293f2f695201baa75ffd4cd | Python | 2,250 | 56 | """Explicit, bounded reuse of prepared models across prediction calls."""
from collections import OrderedDict
from numbers import Integral
import torch
from ..utils._hf import get_data_revision
class ClockCache:
"""Keep a bounded number of prepared clocks for repeated datasets.
Pass the same instance to `... |
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