sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
f7162e7415836837200fa96d8f310751c84da33fea8b48573bf18dec96087756 | Python | 934 | 29 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import math
import numpy as np
from onnx.reference.op_run import OpRun
class LRN(OpRun):
def _run(self, x, alpha=None, beta=None, bias=None, size=None):
minimum_rank = 2
if len(x.... |
cb02f235ba41141716d265fb09c5f6018e9ef8bb54141cc2b7c497d0a2f960b5 | Python | 935 | 29 | """Distance based time series classifiers."""
__all__ = [
"ElasticEnsemble",
"ProximityTree",
"ProximityForest",
"ProximityStump",
"KNeighborsTimeSeriesClassifier",
"KNeighborsTimeSeriesClassifierPyts",
"KNeighborsTimeSeriesClassifierTslearn",
"ShapeDTW",
]
from sktime.classification.d... |
877ba1f6a7049801e338ef5f5e0a1abfe3d6ac6623754c6907a39470e89cb3b5 | Python | 936 | 31 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
from onnx.reference.ops.aionnxml._op_run_aionnxml import OpRunAiOnnxMl
class FeatureVectorizer(OpRunAiOnnxMl):
def _preprocess(self, a, cut):
if len(a.shape) == 1:
... |
f5e8958e0193aaaf4188525a2d52c006d4eb848704da4dc29f9d720b810aa658 | Python | 936 | 24 | # Copyright 2018-2025
# Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich GmbH
# 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/LICE... |
1e67054fa11b246eed67ab819006d7e7ce3cba5767193ca3bdfa489c44dc2f44 | Python | 937 | 35 | """
Plotting a diagonal correlation matrix
======================================
_thumb: .3, .6
"""
from string import ascii_letters
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
sns.set(style="white")
# Generate a large random dataset
rs = np.random.RandomState(33)
d ... |
207372ef1745bf5921b126199b2f53896d7474263322ff5dd35460dccb3efb97 | Python | 940 | 24 | # Copyright 2026 DeepMind Technologies Limited
#
# 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 agr... |
701cf2cd15913ea0b164233b9c6d39fe6b703f188408e191856bce6db5294bd7 | Python | 941 | 27 | import numpy as np
from networkunit.tests.two_sample_test import two_sample_test
from networkunit.capabilities.ProducesSpikeTrains import ProducesSpikeTrains
from elephant.statistics import mean_firing_rate
from networkunit.utils import use_cache, parallelize
class firing_rate_test(two_sample_test):
"""
Test ... |
90ed3a300094dd44e545fe4cee900da9ec58f1bf0ffdf4fc219e054f648b6b1a | Python | 941 | 29 | """Forecasting datasets."""
from sktime.datasets.forecasting.airline import Airline
from sktime.datasets.forecasting.hierarchical_sales_toydata import (
HierarchicalSalesToydata,
)
from sktime.datasets.forecasting.longley import Longley
from sktime.datasets.forecasting.lynx import Lynx
from sktime.datasets.forecas... |
acf080bde4592b279f2260edf4c585367e7b9d944f79c085bcef15f948b96001 | Python | 942 | 24 | # SPDX-License-Identifier: Apache-2.0
# Copyright (c) ONNX Project Contributors
from __future__ import annotations
import pytest
import onnx.helper
import onnx.shape_inference
class TestNodeInference:
@pytest.mark.parametrize("op_type", ["GreaterOrEqual", "LessOrEqual"])
def test_comparison_op(self, op_typ... |
64d81aa639168bf6d7b70a6a05e2109fff5fc97819ac057296d5f16a0a4ab0fb | Python | 945 | 30 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
from onnx.reference.ops._op_common_window import _CommonWindow
class BlackmanWindow(_CommonWindow):
r"""Blankman windowing function.
Returns :math:`\\omega_n = 0.42 - 0.5 \... |
df637eaa49158f0d4ce31d781d7a952a0735063025088ceeb736668eccb1ea92 | Python | 945 | 33 | import torch.nn.functional as F
from torch.nn import CrossEntropyLoss
def nll_loss(output, target):
return F.nll_loss(output, target.long())
def temporal_crossentropy_loss(output, target):
return F.cross_entropy(output, target, reduction='mean')
if __name__ == '__main__':
import numpy as np
impor... |
6324649a269552695a632d2d72ab5be23f047efb67c60b63cbf88ebd0b003c46 | Python | 946 | 30 | import numpy as np
import constants
es = constants.ExperimentSettings()
fname = constants.csv_filename(
constants.chosen_prefix,es)
chosen = np.genfromtxt(fname, dtype=int, delimiter=',')
msize = 4
for fold in range(constants.n_folds):
label = chosen[fold,0]
idx = chosen[fold,1]
# Uncomment for regul... |
01e671deb7dd0451fdaaa5431cbaa8f88c68eef45fbc386aa438f3a4dc5635f7 | Python | 947 | 36 | import io
import pytest
import pyxdf
import pyxdf.pyxdf
# %% test
def test_load_xdf_present():
"""Check that pyxdf has the all important load_xdf."""
assert hasattr(pyxdf, "load_xdf")
def test_read_varlen_int():
"""Check that _read_varlen_int decodes 1-, 4-, and 8-byte integers."""
def vla(data: ... |
9217ad00f325511ffd65f0a095850444ccbd6c42e793dd0d409b97ccc8a2d607 | Python | 948 | 26 | # Copyright 2023 The TensorFlow Authors. All Rights Reserved.
#
# 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 applica... |
b5074eb03eabe6d9348d32f250236f72469e6b12804e8ec0560c85d0fa33e9df | Python | 949 | 25 | import torch
import torch.nn.functional as F
def get_local_weights(residual, ksize):
pad = (ksize - 1) // 2
residual_pad = F.pad(residual, pad=[pad, pad, pad, pad], mode='reflect')
unfolded_residual = residual_pad.unfold(2, ksize, 1).unfold(3, ksize, 1)
pixel_level_weight = torch.var(unfolded_residua... |
e22261bfda8bb7b88307ad62ac53ea1e8779fbaeabd18f3af2bbd98bdb66297e | Python | 950 | 29 | # Copyright (c) OpenMMLab. All rights reserved.
def nlc_to_nchw(x, hw_shape):
"""Convert [N, L, C] shape tensor to [N, C, H, W] shape tensor.
Args:
x (Tensor): The input tensor of shape [N, L, C] before convertion.
hw_shape (Sequence[int]): The height and width of output feature map.
Retur... |
05d99f6eb995bf8c6483fe3e71c765da806872a3de6316bc86c281e570e53c7d | Python | 951 | 29 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
from onnx.reference.op_run import OpRun
class ConstantOfShape(OpRun):
def _run(self, data, value: np.array | None = None):
if self.value is None:
value = np.... |
2c86b8ef879ca5dcdb6b155cb3544d71232716a67a33f02d9d56c9bd06349fa9 | Python | 954 | 33 | # Copyright (c) OpenMMLab. All rights reserved.
from abc import ABCMeta, abstractmethod
from mmcv.runner import BaseModule
class BaseBackbone(BaseModule, metaclass=ABCMeta):
"""Base backbone.
This class defines the basic functions of a backbone. Any backbone that
inherits this class should at least defi... |
0703c055c9d2b984c2ea61af1b8f5ac8397d85a221949ff39dcace182f21bdc8 | Python | 956 | 25 | """Tests for bycycle.features.cyclepoints."""
from bycycle.cyclepoints import find_extrema, find_zerox
from bycycle.features.cyclepoints import *
###################################################################################################
#######################################################################... |
dce78e3614614f47a1f4644bfe989a6feb6c9a62fa0b767cb8613bd5323fd5f9 | Python | 959 | 28 | # Copyright 2019 DeepMind Technologies Ltd. All rights reserved.
#
# 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 appl... |
c932e606379957fcdd44b5fe9317ffd287e72a04e747344390d946c6f8addf03 | Python | 960 | 27 | """Tests for bycycle.burst.cycle."""
import itertools
import numpy as np
from bycycle.features import compute_burst_features
from bycycle.burst.cycle import *
###################################################################################################
########################################################... |
7b6198f7bd3135d24f1a304f2e8eed8fa11b41fec49d74e583f4ae8cf4cc0d8a | Python | 961 | 35 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
"""Thin wrapper around run-clang-tidy that filters noisy output."""
from __future__ import annotations
import re
import subprocess
import sys
NOISE = re.compile(
r"^\[|^\d+ warnings? generated\.|^Suppressed \d|^Use -header-filter"
... |
63220a317fd54fb13f41980a3f691ba9157fd3ed003aea04845fae9274e6faae | Python | 962 | 36 | # Copyright (c) ONNX Project Contributors
#
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
import onnx
from onnx.backend.test.case.base import Base
from onnx.backend.test.case.node import expect
class IsNaN(Base):
@staticmethod
def export() -> None:
node ... |
0318373c068bcca320f9ca9472bed0a386ffa937cd05b8db2e19e8ccd9a73c41 | Python | 963 | 25 | """web URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/4.1/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: path('', views.home, name='home')
Class-based vie... |
ce0e623110d4008908dfab8a7006915d012bd2b7a8c0c45427a1b69cd50d3320 | Python | 963 | 35 | import nose.tools as nt
import matplotlib.pyplot as plt
from .. import miscplot as misc
from ..palettes import color_palette
from ..utils import _network
class TestPalPlot(object):
"""Test the function that visualizes a color palette."""
def test_palplot_size(self):
pal4 = color_palette("husl", 4)
... |
9049be1a30f248be85b58fb256b55bda4f309d4b7292a4df8998c79b4102d654 | Python | 965 | 38 | """
Transcriptome distance calculator.
Aligns matched transcript pairs drawn from two transcriptomes, converts the
observed gaps and mismatches into an expected per-read Bowtie2 alignment
penalty, and reports whether reads would cross-map under a given
``--score-min`` setting.
"""
from .align import AlignedPair, alig... |
ca4815e13f69c97151c1dfc8d666da48d7ee2bb959b2ad931e9940a6d4fa84e3 | Python | 965 | 58 | #!/usr/bin/env python
# coding: utf-8
# In[15]:
import os
import sys
import joblib
import glob
import numpy as np
from scipy import signal
import pandas as pd
import keras
thr = 0.139
print ('Models are loading..!')
#models = glob.glob('Model_CNN\*.h5') #CNN models
model = 'Model_CNN/Settled_3_yearX_pd_visit_count... |
59afafe872aa7b0a0acdce6b1fc9e9cba2d8220ab2539eb5acd2519363cf4b17 | Python | 967 | 28 | from src.cajal.utilities import (
read_gw_dists,
dist_mat_of_dict,
read_gw_couplings,
avg_shape_spt,
leiden_clustering,
louvain_clustering,
)
import numpy as np
def test():
cell_names, gw_dist_dictionary = read_gw_dists("tests/gw.csv", True)
assert isinstance(cell_names, l... |
91207469e3b410e94b9ffcf923e00fe811cf6ad8316e1ea9067702c453f3ec25 | Python | 967 | 31 | #------------------------------------------------------------------------------
# elftools tests
#
# Seva Alekseyev (sevaa@sprynet.com)
# This code is in the public domain
#------------------------------------------------------------------------------
import random
import unittest
from io import BytesIO
from elftools.... |
c2c03c9b259d729cad24dfa66efeed521e22273765e4efcfd73bf8ea461d22c5 | Python | 969 | 29 | __author__ = ["chrisholder", "TonyBagnall"]
__all__ = [
"DistanceCallable",
"DistanceAlignmentPathCallable",
"DistanceFactoryCallable",
"DistancePairwiseCallable",
"ValidCallableTypes",
"AlignmentPathReturn",
]
from collections.abc import Callable
import numpy as np
# Callable types
DistanceCa... |
9fd98d68f3e2974301510de201ba1fd20396f7f504ef2d06b784d86bc3112b1d | Python | 970 | 40 | import pytest
from unittest.mock import patch
import tempfile
import numpy as np
import os
import seas.filemanager
# create a temporary folder for test files
TEMP_FOLDER_HANDLE = tempfile.TemporaryDirectory()
TEMP_FOLDER = TEMP_FOLDER_HANDLE.name
MOCK_FOLDER_CONTENTS = ['170721_02_RoiSet.zip', '170721_02.tif']
EXPN... |
91868b486c80e2617b1c7a6a216275ae0564534d3500b97caf3fbd6e4f69dbcd | Python | 971 | 38 | """Tests for bycycle.utils.download."""
import os
import shutil
import numpy as np
from bycycle.utils.download import *
###################################################################################################
################################################################################################... |
e0518ac69c6fa1a95a81ca397de0153040b574ebd5a144c6bc4b8d2e5cc8904c | Python | 971 | 20 | # Copyright 2018-2026
# Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich GmbH
# 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/LICE... |
a455815d949831bd7a75f9916bea2aa4c0838ba4f44118bc71043078e0c574a7 | Python | 973 | 32 | #!/usr/bin/env python
#-------------------------------------------------------------------------------
# test/run_all_unittests.py
#
# Run all unit tests (alternative to running 'python -m unittest discover ...')
#
# Eli Bendersky (eliben@gmail.com)
# This code is in the public domain
#---------------------------------... |
a8fa2c2e3378d496fb75b4a82348cab0d414fa5cba70bec81384ca9638a9410d | Python | 973 | 27 | from PIL import Image, ImageDraw
import face_recognition
# Load the jpg file into a numpy array
image = face_recognition.load_image_file("two_people.jpg")
# Find all facial features in all the faces in the image
face_landmarks_list = face_recognition.face_landmarks(image)
print("I found {} face(s) in this photograph... |
f81bd0774dc2eeafbdbfcb918b11657b413195e954f8267893f679c9999bdef6 | Python | 973 | 28 | # SPDX-License-Identifier: LGPL-3.0-or-later
"""The reference result channel is independent of native initialization logs."""
import pytest
from python_reference import (
run_python_reference,
)
@pytest.mark.parametrize("result", [{"energy": [1.0, -2.0]}, [1.0, {"force": 0.0}]])
def test_reference_ignores_diagno... |
875a837df44e372466d386fa6c3a99f5d10c60e11d0df7bd49d05802cf4f8e90 | Python | 974 | 28 | import onnx
def change_input_dim(model):
# Use some symbolic name not used for any other dimension
sym_batch_dim = "N"
# or an actal value
actual_batch_dim = 1
# The following code changes the first dimension of every input to be batch-dim
# Modify as appropriate ... note that this requires al... |
03a8e5a7863589855f3ec0286ec63e063520872d62a20d6d7ee117831824a184 | Python | 976 | 30 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
from onnx.helper import tensor_dtype_to_np_dtype
from onnx.reference.op_run import OpRun
class _CommonWindow(OpRun):
@staticmethod
def _begin(size, periodic, output_datatype... |
8e1b6cbb692f49b77a1129677808e619d1dfb98453ae3eaf8dd45c0124949acd | Python | 978 | 31 | from setuptools import setup
setup(
name='dynamic_spharm', # This is the name of your PyPI-package.
version='1.0', # python versioneer
url="https://github.com/applied-systems-biology/Dynamic_SPHARM/",
author="Anna Medyukhina",
author_email='anna.medyukhina@gmail.com',
... |
85c774c56457b990ebb378304916bff88e1199fd0ded3d5afcd0fad0469cc625 | Python | 980 | 22 | # Copyright 2019-2020 The ASReview Authors. All Rights Reserved.
#
# 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 appl... |
547a21496558483e2fca0a511d606173890263789e738f0ddfbe2d784e3cd975 | Python | 983 | 27 | # Copyright 2019 DeepMind Technologies Ltd. All rights reserved.
#
# 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 appl... |
c2076109a1994359298b4fae5448d968b3d29d83db46eec9463884d57aa872e1 | Python | 983 | 26 | from __future__ import print_function
import pickle
import numpy as np
class FeatureConnector():
def __init__(self):
self.outputTensorExists = 0
def featureConnecting(self, inputFeaturePath):
print('inputFeaturePath = ' + inputFeaturePath)
inputFileHandler = open(inputFeaturePath, 'rb... |
40591c27ed1d42aeecf8a338338512549c8309687e96d19071640f9f7c1c1b28 | Python | 984 | 44 |
fi=open('/home/disk/database/data/ICS_scHIC/f01_frontalCortex/tracks/scATAC_RefLoop.txt')
header=fi.readline().rstrip().split('\t')
import os
os.chdir('/home/disk/database/data/ICS_scHIC/f01_frontalCortex/tracks')
fo_list=[]
for one in header:
fo_list.append(open(one+'.bedpe','w'))
for line in fi:
seq=... |
e554510b5e9c31912b8703b7acd6b44c31f22666e1f4e4f4ecc15380eaf6145e | Python | 984 | 26 | """Prepare fixed source-only catalogues and held-out benchmark partitions."""
import argparse
import json
from pathlib import Path
from short2long import unified_data
def main():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--config", type=Path, required=True)
parser.add_arg... |
4edfea8e67100ab42e23341eccc859a59bf4d5890fc45c3ae1252eb6eb0f1866 | Python | 985 | 34 | # Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
# Licensed under the Apache License, Version 2.0 (the "License").
# You may not use this file except in compliance with the License.
# A copy of the License is located at
# http://www.apache.org/licenses/LICENSE-2.0
# or in the "license" file... |
5245686864fdab4bd057d9c5a5be6710e203df636f7cf7d5b278df82e9bb1d46 | Python | 985 | 35 | """Import commonly used libraries"""
import numpy as np
import pandas as pd
import collections
# matplotlib
import matplotlib as mpl
import matplotlib.pyplot as plt
mpl.rcParams['pdf.fonttype'] = 42 # editable text in matplotlib
mpl.rcParams['svg.fonttype'] = 'none'
# mpl.rcParams['font.family'] = 'sans-serif'
# mpl.... |
07e2e72534d9fe51b0f0301ca8492b41c0b904cc94c64e6d9a9e6af6ae395ce5 | Python | 986 | 37 | """
Color palette choices
=====================
"""
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
sns.set(style="white", context="talk")
rs = np.random.RandomState(8)
# Set up the matplotlib figure
f, (ax1, ax2, ax3) = plt.subplots(3, 1, figsize=(7, 5), sharex=True)
# Generate some sequent... |
a560991acf195b1b65136815db1292f0b6f198e505f31cc8e40d16a4fec94132 | Python | 986 | 34 | import torch
import torch.nn as nn
import torch.nn.functional as F
class AcrNET(nn.Module):
def __init__(self):
super(AcrNET, self).__init__()
self.conv = nn.Conv2d(in_channels=1, out_channels=20, kernel_size=(5, 34),
stride=(1, 1))
self.dnn_fc1 = nn.Linear(... |
bbedab524c65a8381e7ff2b5e40efa4299810784b9b6f216d5abea39916a47fe | Python | 986 | 27 | #------------------------------------------------------------------------------
# elftools tests
#
# Seva Alekseyev (sevaa@sprynet.com)
# This code is in the public domain
#------------------------------------------------------------------------------
import os
import unittest
from elftools.elf.elffile import ELFFile... |
57b5739c978e43a6e071273b913aa963578d255b9e7eb3a81e5816cbba2e215c | Python | 987 | 25 | #-------------------------------------------------------------------------------
# elftools tests
#
# Eli Bendersky (eliben@gmail.com), Santhosh Kumar Mani (santhoshmani@gmail.com)
# This code is in the public domain
#-------------------------------------------------------------------------------
import os
import unitt... |
db508e7cfe0975556bdd3624ba6f2e508622076dcc7989a3ea49c7473265e3cc | Python | 987 | 30 | import nbformat as nbf
import numpy as np
import sys
ipath = sys.argv[1]
# Collect a list of all notebooks in the content folder
# notebooks = glob(loc)
# Text to look for in adding tags
# text_search_dict = {
# "# HIDDEN": "remove-cell", # Remove the whole cell
# "# NO CODE": "remove-input", # Remove only ... |
f054f336b236e8929dc0c0434f9a3a77356fc16734d8cb26af573eb6220762f9 | Python | 988 | 27 | import setuptools
with open(file="README.md", mode="r", encoding="utf8") as fh:
long_description = fh.read()
setuptools.setup(
name="akkadian",
version="1.0.12",
author="Gai Gutherz, Ariel Elazary",
author_email="gaigutherz@gmail.com, am.elazary@gmail.com",
description="Translating Akkadian si... |
da7b2be96f1f7f0b89bb6ae328e0088e47ddab6c20eaec6f64666d61f6bd6107 | Python | 989 | 46 | import os
import yaml
#################################################################
# Config loading and handling
class ConfigMeta(type):
def __getitem__( cls, key ):
return cls.data[key]
def __contains__( cls, key ):
return key in cls.data
class Config(metaclass=ConfigMeta):
data = []
@staticmethod
def ... |
18990a041790da58094210228d6c0808c3ba3ff34bf662fff03dad345d918326 | Python | 990 | 35 | import unittest
from pyontutils.core import ilxtr
from pyontutils.combinators import annotation
annotation_ev = """ Axioms
[] a owl:Axiom ;
owl:annotatedSource ns1:a ;
owl:annotatedProperty ns1:b ;
owl:annotatedTarget ns1:c ;
ns1:e ns1:f ;
ns1:g ns1:h .
"""
class TestAnnotation(unittest.TestCas... |
b5215a8d579a7a4bbbb88b06d261d57094ce39aae293e22e419136601d7eea45 | Python | 990 | 31 | import numpy as np
import py3Dmol
from pyRDTP import geomio
from pyRDTP.molecule import Molecule
def show_molecule(molecule, center=True, index=False):
uni_obj = geomio.MolObj(molecule)
xyz_obj = geomio.XYZ(uni_obj)
if center:
center = molecule.find_centroid('cartesian')
vector = np.zeros(... |
1a0ec78df8a08a09ee13e2a1a34aa80705d5333ab81448e3a9c04e67cca27d1b | Python | 991 | 31 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
from onnx.helper import tensor_dtype_to_np_dtype
from onnx.onnx_pb import TensorProto
from onnx.reference.op_run import OpRun
class EyeLike(OpRun):
def _run(self, data, *args, d... |
79aa6b2511da0a4c110e8c3266bc5e46401607d5f93e66343064933d6d8ae8ec | Python | 991 | 31 | import numpy as np
import constants
import random
es = constants.ExperimentSettings()
# We can do this because in fashion there are the same
# number of labels as folds.
chosen = np.zeros((constants.n_folds, 2), dtype=int)
classes = [*range(constants.n_labels)]
random.shuffle(classes)
print(classes)
for fold in range... |
5d59997c5db3672b6e9b8a445cf1876af298a24bbfed5c308625a290cab26c1f | Python | 992 | 31 | import functools
import pytest
def skip_on(pytest_expected_exception):
r"""
A decorator annotator that can be used to skip tests if specific exceptions occur.
Source for this code: https://stackoverflow.com/a/63522579
Source for the arrangement: https://stackoverflow.com/a/33515264
Args:
... |
6140f31bd4734a7911ed02f21504fbf04d1a546786ee8fbec8292b98c763d77e | Python | 992 | 28 | import os
import glob
from os.path import join as pjoin
from setuptools import setup, find_packages
with open('README.md', 'r') as rf:
long_description = rf.read()
# the 'install_requires' parameter can't deal with non-PYPI packages!
setup(
name='dnnbrain',
version='1.0a',
author='Xiayu Chen, Ming Zh... |
f4b9c9e1878482d6c85c7f4c5ebc3ada6c72549ad008f586996051c10f20766a | Python | 992 | 18 | """ Attention and normalization modules """
from onmt.modules.util_class import Elementwise
from onmt.modules.gate import context_gate_factory, ContextGate
from onmt.modules.global_attention import GlobalAttention
from onmt.modules.conv_multi_step_attention import ConvMultiStepAttention
from onmt.modules.copy_generat... |
d3535f5bf99428e5609df5c379a226798ed01d830cbc2104ce545f17933fe18f | Python | 993 | 33 | # Copyright 2019-2020 The ASReview Authors. All Rights Reserved.
#
# 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 appl... |
f5c40ebb5e8eb5d9d3a43df52de52b1bdaa0cd57b53cf2691109e847b134f709 | Python | 993 | 18 | import argparse
from abc import ABC
from task_manager import TaskManager
class ExperimentProcessTaskManager(TaskManager, ABC):
def add_args(self, parser: argparse.ArgumentParser):
parser.add_argument('--input-dir', '-i', action='store', required=True, help='Input directory')
parser.add_argument('... |
10a3870825fca30e199da7c279a4ddb15fa15a4865c85b370436eb7526b06e40 | Python | 994 | 33 | """
Copyright (c) 2019 XyChen
The original source code for kl_divergence is released under the MIT License
https://github.com/chxy95/Deep-Mutual-Learning/blob/master/LICENSE
"""
import torch
import torch.nn as nn
import torch.nn.functional as F
import matplotlib.pyplot as plt
from torch.autograd import Variable
... |
aa62f7e1091ab352cc78448fc4175e332ae036ed7e81758b3de2d2d9d14e8e61 | Python | 994 | 38 | from collections import OrderedDict
import numpy as np
def to_volume(data):
"""Ensure that data is a numpy 3D array."""
assert isinstance(data, np.ndarray)
if data.ndim == 2:
data = data[np.newaxis,...]
elif data.ndim == 3:
pass
elif data.ndim == 4:
assert data.shape[0]==1
... |
2559b6843436455770788ef238aba86edc5e9b19d14edeb66a0794bb1d5934db | Python | 996 | 32 | #!/usr/bin/env python
from __future__ import print_function
import sys,os
import argparse
import gzip
desc = 'Determine if file is empty'
epi = """DESCRIPTION:
Returns '1' if empty; else returns '0'.
Can handle gzip'ed and uncompressed files.
"""
parser = argparse.ArgumentParser(description=desc,
... |
3ad016c7410a9bc561878e3ad95daa97694bde90b67738ccbd38c804fc3c817b | Python | 996 | 22 | # Copyright (c) OpenMMLab. All rights reserved.
from .base_dataset import BaseDataset
from .builder import (DATASETS, PIPELINES, SAMPLERS, build_dataloader,
build_dataset, build_sampler)
from .cifar import CIFAR10, CIFAR100
from .dataset_wrappers import (ClassBalancedDataset, ConcatDataset,
... |
fdfc01bd633f6d35aeac63f2255e905c59bb91c671dbb76f184450739b1feea8 | Python | 996 | 33 | """
List the active morphology files in our data set
Useful for checking which files are available and their current status.
This module is part of *vcnmodel*.
Support::
NIH grants:
DC R01 DC015901 (Spirou, Manis, Ellisman),
DC R01 DC004551 (Manis, 2013-2019, Early development)
DC R01 DC019053 (Mani... |
9fbb882b2b8817b23ea17e7e0d5513247edf1fc696213c5980c8ca4b8d3bd962 | Python | 999 | 24 | from __future__ import print_function
import numpy as np
from scipy import signal
import matplotlib.pyplot as plt
from parameterSetup import ParameterSetup
from featureExtractorWavelet import FeatureExtractorWavelet
params = ParameterSetup()
waveletWidths = params.waveletWidths
samplingFreq = params.samplingFreq
### s... |
43ce3efd4eb2539570f279fb4aa07c111811582eaeaf1f6f179fb4147775cad9 | Python | 1,000 | 30 | import netplotbrain
import pytest
import pandas as pd
import networkx as nx
# Example node and edges dataframes included with package
nodes = pd.read_csv('./examples/example_nodes.tsv', sep='\t', index_col=0)
edges = pd.read_csv('./examples/example_edges.tsv', sep='\t', index_col=0)
g = nx.Graph()
# Create network x ... |
605f3795cd657a9a1fb506db05ed025f7e427490729df58555e1017f0bad164a | Python | 1,000 | 36 | import sys
import unittest
from ttlser.ttlfmt import main
f1 = 'test/good.ttl', 'test/f1.ttl'
f2 = 'test/nasty.ttl', 'test/f2.ttl'
class TestTtlfmt(unittest.TestCase):
argv = ['ttlfmt', f1[1], f2[1], '--slow']
def setUp(self):
for source, dest in (f1, f2):
with open(source, 'rt') as s, ope... |
a3765ef7053b7e37c86722df25cb650d80b9703df946782942d7f72082167e0e | Python | 1,002 | 36 | #!/usr/bin/env python3
import rdflib
import yaml
from pyontutils.config import auth
try:
breakpoint
except NameError:
from IPython import embed as breakpoint
def main():
with open(auth.get_path('curies'), 'rt') as f:
curie_map = yaml.safe_load(f)
curie_map['nlx_only'] = curie_map[''] # map n... |
d6ab554c2013d1907072d26cb509f4a4209620fa54b391e040c060f3fbea8e0b | Python | 1,002 | 28 | """Tests for TSFreshClassifier."""
import numpy as np
import pytest
from sklearn.ensemble import RandomForestClassifier
from sktime.classification.feature_based import TSFreshClassifier
from sktime.datasets import load_unit_test
from sktime.tests.test_switch import run_test_for_class
@pytest.mark.skipif(
not ru... |
637fba5ca9553a2fd9e1d948f8e37d2ca094c286350f7bc552e7f3b81d208b9c | Python | 1,003 | 36 | """Random seeding for ParaDime.
The :mod:`paradime.utils.seed` subpackage implements a function to seed all
random number generators potentially involved in a ParaDime routine.
"""
import os
import random
import numpy as np
from packaging import version
import torch
def seed_all(seed: int) -> torch.Generator:
... |
5aedcc140f455751bc00735bf5311f6e5e21f2ac29e5db18db03c9f18c1ce750 | Python | 1,005 | 30 | # Copyright 2026 DeepMind Technologies Limited
#
# 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 agr... |
7899f1b7dd3baf581767888ff198b4e2c812f13dfa3ce7b846f2684449e40035 | Python | 1,005 | 36 | # Copyright (c) ONNX Project Contributors
#
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
import onnx
from onnx.backend.test.case.base import Base
from onnx.backend.test.case.node import expect
from onnx.numpy_helper import create_random_int
class BitwiseNot(Base):
... |
07cb21d13cd5c40fc8582bd37f364e12f23fd75d30ca3adf28409f4279074b9e | Python | 1,006 | 37 | import numpy as np
import os
import pandas as pd
def predict(all_models, DataHandler):
predictions = []
test_input = [DataHandler['X_test'], DataHandler['dg_test']]
for ind, model in enumerate(all_models):
print(f'Genating predictions for model_{ind}')
test_prediction = model.predict(test_... |
0dcc0ec1bec2165003a89aef3f663342f4ac4d656439b4c65f1cff824305569e | Python | 1,006 | 31 | #!/usr/bin/env python3 -u
# copyright: sktime developers, BSD-3-Clause License (see LICENSE file)
"""Custom exceptions and warnings."""
__author__ = ["mloning"]
__all__ = ["NotEvaluatedError", "NotFittedError", "FitFailedWarning"]
from skbase._exceptions import NotFittedError
class NotEvaluatedError(ValueError, Att... |
a1e440c204851617c33f5fee0dafb95d345b37664affa3cce026eff62e917485 | Python | 1,006 | 26 | r"""
This package contains the all datasets available for use. See docs section "Available Datasets" for an overview.
"""
from vp_suite.datasets.bair import BAIRPushingDataset
from vp_suite.datasets.kth import KTHActionsDataset
from vp_suite.datasets.mmnist import MovingMNISTDataset
from vp_suite.datasets.mmnist_on_th... |
aec0b2cbfd4a90513a2bd2f0cdb849beb9393157fb1e44c47da57b8a91554fe8 | Python | 1,009 | 41 | from neuron import h
import numpy as np
from ..util import random_seed, custom_init
class Protocol(object):
"""
Base class providing common tools for running, analyzing, and displaying
simulations.
"""
def __init__(self):
self.reset()
def reset(self):
self._vectors = {}
... |
67951921caaf15cf0615c98facf4a5c42d3cb0a779106ae634f1935e5214e087 | Python | 1,010 | 29 | # coding=utf-8
# Copyright (C) 2022. Huawei Technologies Co., Ltd. All rights reserved.
#
# 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
#
# ... |
fd42db897b2739c25e9d7fa5c70060898e014e1238a4e23f64df70b6572cb86d | Python | 1,010 | 38 | # Copyright (c) ONNX Project Contributors
#
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
import onnx
from onnx.backend.test.case.base import Base
from onnx.backend.test.case.node import expect
class Det(Base):
@staticmethod
def export_2d() -> None:
node... |
22b1e7a3d245b90eebb88aa4613219cd66110a0a8c9994cd230e49d233baf7f9 | Python | 1,012 | 29 | import os
import shutil
from tqdm import tqdm
train = set()
with open('/oak/stanford/groups/rbaltman/aderry/atom3d/data/residue_deletion/train.txt') as f:
for line in f:
train.add(line.strip())
val = set()
with open('/oak/stanford/groups/rbaltman/aderry/atom3d/data/residue_deletion/val.txt') as f:
fo... |
445b3b57e09297bdf5b8597d5e43b43c3c7126ab1acf944654582cb00b5002de | Python | 1,012 | 45 | from setuptools import setup, find_packages
import re
install_requires = [
"numpy >= 1.21.0",
"torch >= 1.8.0",
"energyflow >= 1.3.0",
"scipy >= 1.6.2",
"awkward >= 1.4.0",
"coffea >= 0.7.0",
"h5py >= 3.0.0",
"pandas",
"tables",
"requests",
"tqdm",
]
extras_require = {"emdl... |
841c99e5164d51eea3c0323474c82fa156a417f1a44d47ee53f96f7c1c806477 | Python | 1,012 | 32 | from typing import Any
from flair.trainers.plugins.base import TrainerPlugin
from flair.training_utils import WeightExtractor
class WeightExtractorPlugin(TrainerPlugin):
"""Simple Plugin for weight extraction."""
def __init__(self, base_path) -> None:
super().__init__()
self.base_path = base... |
f05b47b1870b31e29fa1bff1a607889ad156af59db4d54e9ba4b5314a6daa685 | Python | 1,012 | 30 | """Dummy change point detector which detects change points after steps."""
from sktime.detection.dummy._dummy_regular_an import DummyRegularAnomalies
class DummyRegularChangePoints(DummyRegularAnomalies):
"""Dummy change point detector which detects a change point every x steps.
Naive method that can serve ... |
098de28a8cd0a997b9de10fb42aa309e71fc2f796b2dd94508e26fd462dfeaf0 | Python | 1,013 | 34 | import pandas as pd
import sys
from rich import print
from rich.console import Console
console = Console()
query_csv = sys.argv[1]
fp_search_out_csv = sys.argv[2]
# Read the CSV files
csv1 = pd.read_csv(query_csv)
csv2 = pd.read_csv(fp_search_out_csv)
# Get the names from the first CSV
names_csv1 = set(csv1['names']... |
4aa7b5c9552943be8c2acd9199d37fd32c4ad2551e534f22460fe16f16ec1818 | Python | 1,013 | 37 | """
Color palette choices
=====================
"""
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
sns.set_theme(style="white", context="talk")
rs = np.random.RandomState(8)
# Set up the matplotlib figure
f, (ax1, ax2, ax3) = plt.subplots(3, 1, figsize=(7, 5), sharex=True)
# Generate some s... |
b2a46c1708d12ebd3724a238eefe68a2f08ec0146636369cc69621c4ea06c8b0 | Python | 1,014 | 42 | import os
import torch
from torch.utils.data import Dataset
import numpy as np
from .indexes import *
class MVSECDataset(Dataset):
def __init__(self, root:str, sequence: int, transform=None):
assert sequence in [1, 2]
self.sequence = sequence
self.root = root
... |
d1a7df8f01ec468ca0ee9cc3779079578eb0ffc7351d199d350f526bb6a6b52d | Python | 1,014 | 29 | from __future__ import print_function
from cnmodel.util import ExpFitting
import numpy as np
def test_fit1():
fit = ExpFitting(nexp=1)
x = np.linspace(0., 50, 500)
p = [-50., 4., 5.]
y = p[0] + p[1]*np.exp(-x/p[2])
res = fit.fit(x, y, fit.fitpars)
pr = [float(res[k].value) for k in res.keys()]... |
93b0d106e019ad9c246762c2a61961a9aad30c138fd4ed2223d7b3e58813aff4 | Python | 1,015 | 39 | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmcls.models.necks import GlobalAveragePooling
def test_gap_neck():
# test 1d gap_neck
neck = GlobalAveragePooling(dim=1)
# batch_size, num_features, feature_size
fake_input = torch.rand(1, 16, 24)
output = neck(fak... |
73df7bcb49e9e5ca341353f3209d7a835e158f888e4b3f255de58967397dfba9 | Python | 1,016 | 30 | import pytest
import flair
from flair.embeddings import DocumentRNNEmbeddings, WordEmbeddings
from flair.models.text_regression_model import TextRegressor
from tests.model_test_utils import BaseModelTest
class TestTextRegressor(BaseModelTest):
model_cls = TextRegressor
train_label_type = "regression"
tra... |
f7b268ab1479b8772d0a0029784f737a7f971cdb6963b20b7853e51bae4181e2 | Python | 1,017 | 38 | import pytest
import tempfile
import numpy as np
import os
import seas.video
import seas.colormaps
def test_tiff_loading_and_saving():
test_video = np.random.random((3, 10, 10))
test_video = (test_video * 255).astype('uint8')
with tempfile.TemporaryDirectory() as tempdir:
tempdir = tempdir
... |
fdc32cbca8ba65570f83ffec98b8c152dbe522bfe43e42ad4fedcefc006b1940 | Python | 1,017 | 28 | # The code contained in this file is licensed under the MIT license,
# and is borrowed from the ivadomed repository:
# https://raw.githubusercontent.com/ivadomed/ivadomed/ac29c7cbe299e6478854823ed6bd818c0e5f9642/ivadomed/uncertainty.py
# Copyright (c) 2019 Polytechnique Montreal, Université de Montréal
import torch
d... |
4886da5e40884738e26512b67929cb35d2ce1b44e5de20720f511951de6c704b | Python | 1,019 | 31 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import ml_dtypes
import numpy as np
from onnx.reference.op_run import OpRun
# np.einsum cannot accumulate with bfloat16 output.
_ACCUMULATE_IN_FLOAT32 = (np.dtype(ml_dtypes.bfloat16),)
class Einsum(O... |
c9e1721726dad7c438d23e6ffd98c63ae710117dfb9058fc4b0fbd414b9e894d | Python | 1,019 | 26 | # Copyright 2022 DeepMind Technologies Limited
#
# 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 agr... |
5084cd06bbdf643e560f17b15aa5821ac84825cf2d6355ac1f8e58a5a8647710 | Python | 1,021 | 34 | """
Conditional means with observations
===================================
"""
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
sns.set(style="whitegrid")
iris = sns.load_dataset("iris")
# "Melt" the dataset to "long-form" or "tidy" representation
iris = pd.melt(iris, "species", var_name="m... |
94c9ed456b3ddf5fe3c7545ceb634f278b587b09a82d95e49bc621eb1f2d1fa0 | Python | 1,021 | 28 | """Time series anomaly, changepoint detection, segmentation."""
import sys
import warnings
from importlib import import_module
# alias dictionary to map old module names to new module names
# if an old module name is queried, imports work, but
# a deprecation warning is issued to update the import statement
# .deprec... |
62befe62cc02dde988814505e628c51943cd2a5ddfe58beb86c68d951cad0c54 | Python | 1,022 | 31 | from typing import Optional
from torch import nn
import torch
from .distance_sq import cdist
class ChamferLoss(nn.Module):
def __init__(self, device: Optional[torch.device] = None):
super(ChamferLoss, self).__init__()
self.device = (
device
if (device is not None)
... |
9b77896ffebe637f162db5c9bcfdc8ce752bbe7f928c6cb03796ed00e12cc1b5 | Python | 1,022 | 30 | # Copyright 2019-2020 The ASReview Authors. All Rights Reserved.
#
# 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 appl... |
0b4b5b6199a2325550dc2c449d4b0740fe645ccaf5afc1969e9e849b44bf2c14 | Python | 1,023 | 39 | """
Small multiple time series
--------------------------
_thumb: .42, .58
"""
import seaborn as sns
sns.set_theme(style="dark")
flights = sns.load_dataset("flights")
# Plot each year's time series in its own facet
g = sns.relplot(
data=flights,
x="month", y="passengers", col="year", hue="year",
kind="l... |
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