sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
4bbf77dfba73e2db1c41900c3d88c4cad9075b40a2cda3f7d37757259b981439 | Python | 1,448 | 50 | import re
from setuptools import setup
def find_version(filename):
_version_re = re.compile(r"__version__ = '(.*)'")
for line in open(filename):
version_match = _version_re.match(line)
if version_match:
return version_match.group(1)
__version__ = find_version('librdflib/__init__.... |
15e3647457c7c32a1e11085d28c2d382e85b2c58c003d17af6f6d3e54dda9bbc | Python | 1,449 | 61 | # 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
def scatter_elements(data, indices, updates, axis=0, reduction=None):
"""Scatter elements.
::
for 3-dim and axis=0
... |
321cc44ba2bfbd0451b641e36c181c2b586924c4d78566a3d9152d45c6c16e1a | Python | 1,450 | 33 | from expert.src.utils import samples_to_countmatrix, merge_countmatrices, scale_abundance
from expert.src.preprocessing import Transformer
from expert.CLI.CLI_utils import find_pkg_resource
import pandas as pd
from tqdm import tqdm
import numpy as np
def convert(cfg, args):
print('running...')
print('Read... |
521ae46ca293ceda33f82fa54d7fa9406cda4095c06276f35b6e9d5a35003b5c | Python | 1,450 | 45 | def convert_gluonts_result_to_multiindex(gluonts_result):
"""Back Convert from Gluonts to sktime.
Convert the output of Gluonts's prediction to a multiindex
dataframe compatible with sktime.
Parameters
----------
gluonts_result: The first element of the tuple resulting
from running `make_e... |
6a5de0cd0a3f8c4ec0bbd292e059799a4e545a7b57d9b30b99813bdf291e6dc0 | Python | 1,450 | 44 | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmcls.models.backbones import ResNeSt
from mmcls.models.backbones.resnest import Bottleneck as BottleneckS
def test_bottleneck():
with pytest.raises(AssertionError):
# Style must be in ['pytorch', 'caffe']
BottleneckS... |
914172475ab7341e31b108bfbb7f94736029afca7b1d229e9b9153bae27e29c0 | Python | 1,452 | 43 | # 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 Selu(Base):
@staticmethod
def export() -> None:
node =... |
604e80eebde5a3770e0ab5cdabecf6a1fc7295fc83ae010dfdb7d7075c888476 | Python | 1,453 | 46 | # Copyright (c) OpenMMLab. All rights reserved.
import json
import logging
from collections import defaultdict
from mmcv.utils import get_logger
def get_root_logger(log_file=None, log_level=logging.INFO):
return get_logger('mmcls', log_file, log_level)
def load_json_log(json_log):
"""load and convert json_... |
64f4bbc5a721c5baf51160ef51783d976d9e632d3b732f4e399e39f3f4d2a147 | Python | 1,453 | 47 | """Wilcoxon rank-sum test evaluator for benchmark results."""
__all__ = ["RankSumTest"]
import itertools
import pandas as pd
from sktime.benchmarking.analysis._base import BaseBenchmarkAnalyzer
class RankSumTest(BaseBenchmarkAnalyzer):
"""Wilcoxon rank-sum test on each ordered pair of estimators.
Non-par... |
66aea61d101eafe54a87bc155da9b50d85ecf8d279400727ea7f4d4a21a57619 | Python | 1,454 | 52 | import os
import random
import logging
import torch
import numpy as np
from sklearn.metrics import f1_score
from transformers.tokenization_bert import BertTokenizer
ADDITIONAL_SPECIAL_TOKENS = ["<e1>", "</e1>", "<e2>", "</e2>"]
def get_label(args):
return [label.strip() for label in open(os.path.join(args.data_... |
2043821b5c1b9bfeb2712f2a54732da6ca1f543a95244300b918e28ab8a33cd8 | Python | 1,456 | 33 | import matplotlib.pyplot as plt
from baseline_utils import load_annotations, sanity_plot, combine_and_split, compute_baseline, mean_test_error
# Python file replicating notebook that generates baseline plots
# Configure annotations and root paths before running
# file path for annotations
left_annotations_file = '../... |
e05da956c4232303deb5b956eea0c8f5fe3920c6e5d9a6a10b1862390aaefaf3 | Python | 1,457 | 52 | """
Utility functions specific to cnn_sta_test and mine_edf to avoid circular imports
"""
import numpy as np
import utilities
def sta_nonlin(x: np.ndarray) -> np.ndarray:
return x / (1+np.exp(-5*x))
def stc_nonlin(x: np.ndarray) -> np.ndarray:
# constant multiplier puts output of nonlinear filter in
# ... |
332089171a29151ecf132dffcd9488a48478b11224db78bcdab18fe8f7d3143c | Python | 1,458 | 50 |
import MDAnalysis as mda
import numpy as np
from MDAnalysis.lib.mdamath import make_whole
from MDAnalysis.analysis.distances import self_distance_array
import sys
def calc_fragment_dimensions(listFragments):
x=None
for frag in listFragments:
if x is None:
x = make_whole(frag)
else:... |
e034c6f41f2d3b77427866c098da87c02c0aa99e4ee7d878ba221e365a5f082c | Python | 1,460 | 50 | """
Functions for preprocessing of single cell RNA-seq counts
"""
import numpy as np
import anndata
from scipy.sparse import issparse
def filter_counts_data(data, cell_min_molecules=1000, genes_min_cells=10):
"""Remove low molecule count cells and low detection genes
:param data: Counts matrix: Cells x Gene... |
942afb33b7e0b80f309da0951c9b1282acce7ac72a7efc66a1a802a6b3040b46 | Python | 1,462 | 54 | import io
from unittest.mock import patch
import uuid
import pytest
from optuna.artifacts import Backoff
from optuna.artifacts.exceptions import ArtifactNotFound
from .stubs import FailArtifactStore
from .stubs import InMemoryArtifactStore
def test_backoff_time() -> None:
backend = Backoff(
backend=Fai... |
a87cb9de243ffbf45dd2832b0901299ef2be75bf9e21d456e74dd9554ecb7ab9 | Python | 1,462 | 32 | # 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... |
37f73c4f75e5889b8d4be99a98d50fa0b1024318f106a513824fb16114f88609 | Python | 1,463 | 48 | # 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... |
76de5afa5a3de01bcd8baa059e0f53cca55bbc93fb1d9a36ade0cf951d859906 | Python | 1,464 | 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... |
c92af0dd5077994897e8c297f81862712b0791feb408837090e751df52d33936 | Python | 1,465 | 44 | #-------------------------------------------------------------------------------
# elftools tests
#
# Test 'R_ARM_CALL' relocation type support.
# Compare the '.text' section data of ELF file that was relocated by elftools
# with an ELF file that was relocated by linker.
#
# Dmitry Koltunov (koltunov@ispras.ru)
# This ... |
cb44be304cd8737f3768d46edf9c759fff1512ff0bbd7fbb95e23fd8b066b791 | Python | 1,465 | 41 | # Copyright 2019-2021 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... |
ef37bba007bbe487505bbb0b39ec31689952d29233254e0775dcab7fcad9d1cf | Python | 1,466 | 45 | """Rotation Forest test code."""
import numpy as np
import pytest
from sklearn.utils.estimator_checks import parametrize_with_checks
from sktime.classification.sklearn import RotationForest
from sktime.datasets import load_unit_test
from sktime.tests.test_switch import run_test_for_class
@pytest.mark.skipif(
no... |
10b12d398de9a2eab5734754c15835bcf04e4d52221403b78237914c80032878 | Python | 1,467 | 36 | import os
import unittest
from elftools.elf.elffile import ELFFile
address_a = 0x112f
address_b = 0x1154
class TestRangeLists(unittest.TestCase):
def test_arange_absent(self):
with open(os.path.join('test', 'testfiles_for_unittests', 'aranges_absent.so.elf'), 'rb') as f:
elffile = ELFFile(f)
... |
6ea4a8d55d8819b5f2b701ebe6629c5865a8b1e7df79ffcca2b01e08ebf63ef5 | Python | 1,467 | 38 | from networkunit.tests.correlation_test import correlation_test
from networkunit.capabilities.ProducesSpikeTrains import ProducesSpikeTrains
from scipy.linalg import eigh
from networkunit.utils import use_cache
from quantities import ms
class eigenvalue_test(correlation_test):
"""
Test to compare the eigenvalu... |
a1b89e79edc7911294b073a323a2800c4eca19369d8feaf93dedbb58a027112e | Python | 1,467 | 41 | # 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... |
c9c030d2b6b365694953d66d4511929f0e847e7033099f381dc4af4b9840fef0 | Python | 1,468 | 45 | """BasicMotions dataset."""
from sktime.datasets._single_problem_loaders import load_basic_motions
from sktime.datasets.classification._base import _ClassificationDatasetFromLoader
class BasicMotions(_ClassificationDatasetFromLoader):
"""BasicMotions time series classification problem.
Example of a multivar... |
7e6f66684f4cb4977f8576088b6181dde5be39d30c49b61763ddeef0d2dc6ade | Python | 1,470 | 46 | """
This scripts generates figure S7a of the paper
This is the full model error (AV + interaction term) + movement vs. additive model error + movement interaction, during active conditions
"""
import pandas as pd
import matplotlib.pyplot as plt
import sciplotlib.style as splstyle
import numpy as np
import os
data_fo... |
8c4dded682f1e3216727d92bf7fb3690f49091cc286e632458c3fc4406a6e1ba | Python | 1,470 | 55 | import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
def matched_stripplot(
data,
x=None,
y=None,
jitter=0.2,
hue=None,
match=None,
ax=None,
matchline_kws=None,
order=None,
**kwargs,
):
data = data.copy()
if ax is None:
ax = plt.gca()
if... |
ff0c99c116b6f5ee65a26e1572f275d9447babbfde763f184175156075ecee42 | Python | 1,472 | 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... |
523c1e5b4dbba1870822aa9a209e5ed223d91d49283e4ee63c2f7d84da9a58cb | Python | 1,473 | 63 | """Distance computation."""
__author__ = ["chrisholder", "TonyBagnall"]
__all__ = [
"DISTANCES_SUPPORTED",
"distance",
"distance_factory",
"pairwise_distance",
"euclidean_distance",
"squared_distance",
"dtw_distance",
"ddtw_distance",
"wdtw_distance",
"wddtw_distance",
"edr_... |
7357f59fa6b5e3b961ae3d2ff22638b3186b2a9304eae19b3fcbe8b5f8f4ab2f | Python | 1,473 | 49 | """
Example of the SMOTE for compositional data, applied on synthetic data generated with
the function smote_cd.dataset_generation.generate_dataset, having 2 features and 2 classes.
"""
import numpy as np
import matplotlib.pyplot as plt
import smote_cd
def create_imbalanced_dataset():
n_features=2
n_cl... |
6c90cb0881858992a4364d6027de703a60c3dbec3e3fd27bfb91aaf20980710a | Python | 1,475 | 55 | """Airline dataset."""
from sktime.datasets._single_problem_loaders import load_airline
from sktime.datasets.forecasting._base import _ForecastingDatasetFromLoader
__all__ = ["Airline"]
class Airline(_ForecastingDatasetFromLoader):
"""Load the airline univariate time series dataset [1].
Examples
------... |
ee9dbb7af17ef4945cd03db3cabc39b66289e5cad1f482868839cc3bd758398a | Python | 1,476 | 49 | from setuptools import find_packages, setup
from glob import glob
classes = """
Development Status :: 3 - Alpha
License :: OSI Approved :: BSD License
Topic :: Software Development :: Libraries
Topic :: Scientific/Engineering
Topic :: Scientific/Engineering :: Bio-Informatics
Programming Langua... |
1cddcfb40488d7dcd7d2adcd601c5195438539000d5770a442eb2d75fa6b85f4 | Python | 1,478 | 39 | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Wed Oct 3 13:11:59 2018
@author: wanglab
"""
import subprocess as sp
def transfer(src, dest, label, pull = True, other_endpoint = False):
'''Tranfers files from tigress to local/jukebox locations.
Inputs:
src = tigress source path
... |
63d4022268a48dc0f478e103e1a38bbcd0f348a668bd6a197007a02391650829 | Python | 1,478 | 40 | """Tests for bycycle.plts.features."""
import numpy as np
from bycycle.burst import detect_bursts_cycles
from bycycle.tests.tutils import plot_test
from bycycle.tests.tsettings import TEST_PLOTS_PATH
from bycycle.plts.features import *
###############################################################################... |
dbac224d035bb3e69abb5b197fc7f2eafee834715a260ad04ed63578807c2038 | Python | 1,480 | 51 | ###############################################################################
# DoC Stage 3
###############################################################################
from camstim.change import DoCTask, DoCImageStimulus, DoCTrialGenerator
from camstim import Window, Experiment
from psychopy import visual
import... |
070bff560540b2591dbc26399e83a9c74c535cf64bc3680dddb8c2526b2cb079 | Python | 1,482 | 40 | import functools
from typing import Callable, Optional, Iterable, Iterator
import numpy as np
from rdkit import Chem, DataStructs
import rdkit.Chem.rdMolDescriptors
# rdkit's DataStructs.ExplicitBitVect is more efficient for rdkit-internal use.
get_morgan_fp: Callable[[Chem.Mol], DataStructs.ExplicitBitVect] = functo... |
f58588e2b144b2253d2e0f77ee612a8180f3a4c6f53dde9f222bc30d0e59acbb | Python | 1,482 | 42 | import torch
import atom3d.datasets.datasets as da
import click
import logging
import os
logger = logging.getLogger(__name__)
def read_split_file(txt):
split_indices = []
with open(txt) as f:
for line in f:
split_indices.append(int(line.strip()))
return split_indices
@click.comman... |
2709a7f8c0c1ecdb0d0639abf5df9ffd967538efc650ceffd477975cc122ef4e | Python | 1,483 | 44 | import rdflib
from pyontutils.core import OntResIri, OntResPath, OntGraph
from pyontutils.namespaces import rdf, rdfs, owl
from pyontutils.config import auth
def main():
olr = auth.get_path('ontology-local-repo')
ori = OntResIri('http://purl.obolibrary.org/obo/doid.owl')
orp = OntResPath(olr / 'ttl/extern... |
2a43affafe4cff9544d870aeda0bf898eacbb3199bf2851084bb17f9a5ef875f | Python | 1,483 | 48 | import pytest
import torch
from torch_geometric.data import DataLoader
from molgnn.pygdata import RedDB
from molgat.models import MolGAT
import os.path as osp
from molgnn.molfeatures import GenMolFeatures
@pytest.fixture
def dataloader():
## Load the RedDB dataset in PyG graph format
path = osp.join(osp.dirna... |
8e02cbc8ab638e0e35d450d657f0d5eed2b5477a60d1236e057846e80b8f4b85 | Python | 1,484 | 44 | import argparse
from models.gln_model.gln_proposer import GLNProposer
def parse_args():
parser = argparse.ArgumentParser("gln_proposer_sample.py")
parser.add_argument("--model_name", help="model name", type=str, default="gln")
parser.add_argument("--processed_data_path", help="output path for processed da... |
2994131bd731393507b0180fd446c22764ab062266e15f22d0ca67bcafcfb7a4 | Python | 1,486 | 41 | from netplotbrain import plot as npbplot
import pytest
import pandas as pd
import numpy as np
# Create 100 random edges. Setting negative ones to 0 for simplicity
np.random.seed(2022)
xtriu, ytriu = np.triu_indices(100, k=1)
weights = np.random.normal(-.5, 0.5, len(xtriu))
graph = np.zeros([100, 100])
graph[xtriu, ytr... |
05ab64cbda4d147eb67980475b5c286d7cf2d03ed126ccaa22320c6e8021b2d5 | Python | 1,487 | 52 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Nov 15 15:01:52 2018
@author: wanglab
"""
import tifffile as tif
import numpy as np
import time
def pad(src, start):
img = tif.imread(src).astype("float32")
print(img.shape, img.dtype)
imgshp = img.shape
ptchsz = (20,192,192)... |
5e96d19f4096d1f9852a991ca22f88fad5054d7985e26d347621290205f557b7 | Python | 1,487 | 44 | # Copyright 2019-2021 The AmpliGraph Authors. All Rights Reserved.
#
# This file is Licensed under the Apache License, Version 2.0.
# A copy of the Licence is available in LICENCE, or at:
#
# http://www.apache.org/licenses/LICENSE-2.0
#
import numpy as np
import tensorflow as tf
from ampligraph.latent_features impo... |
2f01520703035c30b5890da9ba3c298432eee9783c558c0a765f0a1bc8d4c6e8 | Python | 1,489 | 52 | """PBS dataset."""
from sktime.datasets._single_problem_loaders import load_PBS_dataset
from sktime.datasets.forecasting._base import _ForecastingDatasetFromLoader
__all__ = ["PBS"]
class PBS(_ForecastingDatasetFromLoader):
"""Load the Pharmaceutical Benefit Scheme (PBS) univariate time series dataset [1]_.
... |
471109297f648ae39bada1858657c35cfaa2b97812f83d0e76557415ec2bba9e | Python | 1,489 | 50 | # Copyright 2019-2021 The AmpliGraph Authors. All Rights Reserved.
#
# This file is Licensed under the Apache License, Version 2.0.
# A copy of the Licence is available in LICENCE, or at:
#
# http://www.apache.org/licenses/LICENSE-2.0
#
import numpy as np
import logging
SUBJECT = 0
PREDICATE = 1
OBJECT = 2
DEBUG =... |
6d91228697ee3a7d9923c681426668cb789135d889feb9e825aae019817135bb | Python | 1,489 | 43 | # Copyright 2019-2021 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... |
cc71b68fcc3faab0f2e0514c16431584e5d009727478b156082dbd316222d28f | Python | 1,490 | 38 | """
Utilities for plotting neural activity.
"""
from matplotlib import pyplot as plt
def spike_raster_plot(t,data,colors=None,offset=0) -> None:
"""
Plot spike rasters of spiking data.
:param t: vector of timesteps.
:type t: List, np.ndarray, or torch.tensor
:param data: 2D vector of spikin... |
57b3f0549a01253dbc3b6a119b6fc8c072764c76529aa79169d1365841a42c06 | Python | 1,492 | 44 | """Sign test evaluator for benchmark results."""
__all__ = ["SignTest"]
import itertools
import numpy as np
import pandas as pd
from sktime.benchmarking.analysis._base import BaseBenchmarkAnalyzer
class SignTest(BaseBenchmarkAnalyzer):
"""Sign test for consistent differences between estimator pairs.
Non-... |
5dfd9dab71513a71c988408021b3770c312bd19d2aa8e53021093a78863f14be | Python | 1,492 | 36 | import shutil
from pathlib import Path
import urllib.request
import shutil
# files are cached on Zenodo: https://zenodo.org/records/16605299
CLOUD_CACHE = {
("human_nontata_promoters", 0): "https://zenodo.org/records/16605299",
("demo_coding_vs_intergenomic_seqs", 0): "https://zenodo.org/records/16605299",
... |
959d069d1a960e48df2fcc2d6f8787151848b976313823bd61f94fc0dc82be89 | Python | 1,492 | 45 | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
from ..builder import NECKS
@NECKS.register_module()
class GlobalAveragePooling(nn.Module):
"""Global Average Pooling neck.
Note that we use `view` to remove extra channel after pooling. We do not
use `squeeze` as it will... |
e8ec0bee1bf413b1d49c54e0aec5fb975ce6deb8e115a880f067b84fa5d4015d | Python | 1,492 | 41 | #-------------------------------------------------------------------------------
# elftools example: elf_relocations.py
#
# An example of obtaining a relocation section from an ELF file and examining
# the relocation entries it contains.
#
# Eli Bendersky (eliben@gmail.com)
# This code is in the public domain
#--------... |
4833b0c26df6945e1369c211ddd652e53c97b506da0e3ac4693e3a545abc64da | Python | 1,493 | 42 | from __future__ import print_function
from __future__ import division
import numpy as np
from sklearn.utils.validation import check_array
from sklearn.model_selection import StratifiedShuffleSplit
class GroupShuffleSplitStratified(StratifiedShuffleSplit):
def __init__(self, n_splits=5, test_size=2, train_size=... |
935ae3da7c552dccc2bef65b67605dc634d75daa425966787e1e401d3fab4b22 | Python | 1,493 | 38 | import torch
import torch.nn as nn
import torch.nn.functional as F
class TPerceptualLoss(nn.Module):
def __init__(self, use_S=True, type='l2'):
super(TPerceptualLoss, self).__init__()
self.use_S = use_S
self.type = type
def gram_matrix(self, x):
b, ch, h, w = x.size(... |
cd7919c6802ee6b9a3b6f9f4e44d6c2f1de6e1b2f06ed02b804deb1d743f2e19 | Python | 1,493 | 37 | import subprocess
from pathlib import Path
from translation_tokenize import tokenize
from translate_common import source, translation, detokenize_cuneiform, detokenize_translation
def translate_cuneiform_base(file, capture_output=False):
tokenize("signs_char", file, False, Path("NMT_input/tokenization"), Path("")... |
6beb1a22806d2d867fd8f6d5773f7c254853a005d117bc387dde00ba75ab40ce | Python | 1,494 | 45 | """
plot_terminator_improvement
===========================
.. autofunction:: optuna.visualization.plot_terminator_improvement
:no-index:
The following code snippet shows how to plot improvement potentials,
together with cross-validation errors.
.. _visualization-plot-terminator-improvement-plotly-content:
"""... |
c8b1a7d81f885510d7f6d48d825e8830d4c6e66796b2568e89c2c985cbc03053 | Python | 1,495 | 56 | import torch
import torch.nn as nn
import torch.optim as optim
import torch.backends.cudnn as cudnn
import torchvision.transforms as transforms
import torchvision.datasets as datasets
import argparse
import numpy as np
import JH_utile
# import JH_DataAug
import JH_net_param_setting as NetSet
import sys
import math
imp... |
d3db9748260f686e331b47f705887cb00a5a0a2b18c32fd5850b50fff8a5c725 | Python | 1,496 | 47 | """ACSF1 dataset."""
from sktime.datasets._single_problem_loaders import load_acsf1
from sktime.datasets.classification._base import _ClassificationDatasetFromLoader
class ACSF1(_ClassificationDatasetFromLoader):
"""ACSF1 time series classification problem.
Example of a univariate classification dataset wit... |
02207fc81be6fb6c5fc6333caff489ceeb445f2bef10c3f68ea90079f13faa3d | Python | 1,497 | 59 | """Utilities to handle checks and conversions between output formats of detectors."""
import pandas as pd
def _is_valid_detection(obj, type="points"):
"""Check if the input is valid common output format.
Parameters
----------
obj : pd.DataFrame
Output of a detector to check for validity
... |
16a48d3ff7f458cb523f3f10de27173e36b4d67dffef846bdc9cf89437d9d1c3 | Python | 1,498 | 57 | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Tue Nov 20 15:13:29 2018
@author: wanglab
"""
import os
import h5py
from augmentor import Augment
from dataprovider3 import DataProvider, Dataset
class Sampler(object):
def __init__(self, datadir, spec, vols=[], mode="train", aug=None):
as... |
29008a1ce97ef11592081e5739f9180a76f5b08cbba0a41f56decaa904961f19 | Python | 1,498 | 51 | # 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... |
2ec59ec1c814d85f69abeb6e2af65f02d8318ca4aae4f9ea078af7c6cd104a57 | Python | 1,498 | 46 | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from torch.utils.data import DistributedSampler as _DistributedSampler
from mmcls.datasets import SAMPLERS
@SAMPLERS.register_module()
class DistributedSampler(_DistributedSampler):
def __init__(self,
dataset,
num_rep... |
c5551b2efbeeecd9d89ac480dcee8386b207b5f0bf69f52c071365bfc285be06 | Python | 1,498 | 41 | from setuptools import setup, find_packages
def readme_file_contents():
with open('README.rst') as f:
data = f.read()
return data
setup(
name='sns_toolbox',
version='1.5.2',
packages=find_packages(),
url='https://github.com/wnourse05/SNS-Toolbox',
license='Apache v2.0',
author... |
47f456a070cd6fe1395f7fb1eb3161ef700a33aabc759ed414d8fe75609ff7f0 | Python | 1,504 | 78 | configs = dict()
configs["beta_gamma"] = {
"betas": [0.55, 0.5],
"gammas": [0.5, 0.55],
"beta_sharpness": None,
"phase": None,
"pac": None,
"cross_pac": None,
"phase_shift": None,
"burst_length": None,
}
configs["beta_sharpness"] = {
"betas": None,
"gammas": None,
"beta_sha... |
738d7f1d61763e215fbc50864f411e80b6900069ede78f20d4ce13eeb3f44d3e | Python | 1,504 | 40 | # Copyright 2019 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... |
d5062d100e9de9e573f0fa7c73087c5bd70c46805fa7e77abfdb116f11b2471b | Python | 1,504 | 47 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import inspect
from collections import defaultdict
from textwrap import dedent
from typing import Any, ClassVar
import numpy as np
def process_snippet(op_name: str, name: str, export: Any) -> tuple[st... |
f2da7cd6dfebf353bdce1ff2dae2287e79e76d47ce1c8f07ab16704028d14ed7 | Python | 1,504 | 52 | ###############################################################################
# DoC Stage 3
###############################################################################
from camstim.change import DoCTask, DoCImageStimulus, DoCTrialGenerator
from camstim import Window, Experiment
from psychopy import visual
import... |
b7456f2c15fc9f3750f5dbe0713c3fc71e1176b9af7d22647218d46f3bdcf859 | Python | 1,508 | 47 | """Wilcoxon signed-rank test evaluator for benchmark results."""
__all__ = ["WilcoxonSignedRankTest"]
import itertools
import pandas as pd
from sktime.benchmarking.analysis._base import BaseBenchmarkAnalyzer
class WilcoxonSignedRankTest(BaseBenchmarkAnalyzer):
"""Wilcoxon signed-rank test on each unique pair ... |
e049454e9216c50b22150417d257c7361c39e9ba589f11f263bec21af921bc4a | Python | 1,508 | 39 | import unittest
import numpy as np
from ddt import ddt
from sklearn import svm
from sklearn.model_selection import cross_val_score
from scipy import ndimage
from SPHARM.classes.stratified_group_shuffle_split import GroupShuffleSplitStratified
@ddt
class TestCrossval(unittest.TestCase):
def test_crossval(self):... |
a05d534ddcae13834bff1ce67658aa9d2814a50ff8ffd5726a08df7361de91f1 | Python | 1,510 | 32 | # 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... |
f611310ef1f82f567f8c31e2f41c3195d7524bcf72db8bf3b0ffacc751770bc0 | Python | 1,510 | 44 | """
plot_terminator_improvement
===========================
.. autofunction:: optuna.visualization.matplotlib.plot_terminator_improvement
:no-index:
The following code snippet shows how to plot improvement potentials,
together with cross-validation errors.
.. _visualization-plot-terminator-improvement-matplotli... |
74147a78fece8d78f26a5a3580ee20cede38f175387ee7d69d838060388c1b37 | Python | 1,511 | 41 | import numpy as np
import pandas as pd
class CachedValues():
"""Class for mapping keys to pre-computed values.
Keys are hashable objects in numpy arrays, for example, SMILES strings.
"""
def __init__(self, keys: np.ndarray, values: np.ndarray):
if len(set(keys)) != len(keys):
raise ValueError('All... |
8793027fd2cd0dd09363930ceccf4d6e4c28502abebc49eaf5762113230eff3f | Python | 1,512 | 66 | from pygel3d import hmesh
from utils import *
from center_points import CenterPoints
import numpy as np
if __name__ == '__main__':
input_path = 'artery_mesh.obj'
output_path = 'artery_centerline_raw'
original_file = 'artery_seg.nii.gz'
saved_vtk = 'artery_centerline_filtered.vtk'
m = hmesh.lo... |
ddf6952d6b7bc773f4dc83bf72259de47bd3c61ddcf4aeadad45c2e828448b4d | Python | 1,512 | 48 | # 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... |
f0e3cbbbb7189a60b7240a074abfc56d57016ec997bcf9cf1727076287e30f64 | Python | 1,512 | 44 | # Copyright 2019 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... |
eef16b50f02ae2094b7f2bdb705be44630a2d7ff70c2d683e3b672f05392203c | Python | 1,513 | 44 | import logging
from typing import Any
from flair.trainers.plugins.base import TrainerPlugin
log = logging.getLogger("flair")
class CheckpointPlugin(TrainerPlugin):
def __init__(
self,
save_model_each_k_epochs,
save_optimizer_state,
base_path,
) -> None:
super().__init... |
53bdb76f34c84859b19959eb1da2b75e158867db6fab79d0de715ff3d6d90840 | Python | 1,514 | 44 | # 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... |
95d4283872f41d460a69c55e568f162824881ea92b5fbce269ef4b6506efee48 | Python | 1,515 | 45 | # Copyright 2019 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... |
9df13eaeeabbfcc4243342753ea4ead4341688f1be413a9aabb70476418ad014 | Python | 1,515 | 42 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
from onnx.reference.ops._op import OpRunBinaryNum
class BitShift(OpRunBinaryNum):
def __init__(self, onnx_node, run_params):
OpRunBinaryNum.__init__(self, onnx_node, run... |
fb97cc075a35a99839bf18e5ea0a31ca2390230811a979473d81d2a02cf5767a | Python | 1,516 | 48 | from setuptools import find_packages, setup
from glob import glob
classes = """
Development Status :: 3 - Alpha
License :: OSI Approved :: BSD License
Topic :: Software Development :: Libraries
Topic :: Scientific/Engineering
Topic :: Scientific/Engineering :: Bio-Informatics
Programming Langua... |
08cc6f2d12b8873efa93d38ed343ab12620ed32149c0e9f27160fd2b62347fa6 | Python | 1,517 | 45 | # Copyright 2019 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... |
d3d8fb06c466928ec40d34053e58284e0c1bd50a333ac5e3bfaa167d15d34b98 | Python | 1,517 | 46 | # 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... |
118c7d027db752d9df64b6b9df49ccbffbf5c4cda8d3c4a2b6847a16748c08b0 | Python | 1,519 | 38 | # Copyright 2019-2026 The AmpliGraph Authors. All Rights Reserved.
#
# This file is Licensed under the Apache License, Version 2.0.
# A copy of the Licence is available in LICENCE, or at:
#
# http://www.apache.org/licenses/LICENSE-2.0
#
from ampligraph.datasets import load_fb15k_237
from ampligraph.latent_features... |
2cf2e9bd893f83a780411cd26ede7ddb36188509c41869d8adfecc569736a7b9 | Python | 1,519 | 46 | #
# # Visualizing a single network
#
# [Open interactive notebook in Binder](https://mybinder.org/v2/gh/wiheto/netplotbrain/main?filepath=docs/gallery/plot_dmn.ipynb)
#
# ## Goal
# Here we are going to take a atlas from templateflow and only visualize the default mode network
#
# Import packages
import templateflow.... |
611f98c5724f70bcf6fd1243153b6106524f15f3df1731dbcce4757e4e74f858 | Python | 1,521 | 59 | """
"""
import pickle
import yaml
def dict2types(input_dict):
""" Converts a dictionary into a matching dictionary
of just its types.
"""
output_dict = {}
for k, v in input_dict.items():
if isinstance(v, dict):
output_dict[k] = dict2types(v)
elif isinstance(v, ... |
6bbb3031310977e0ef4feee72b66a663c9570e186641e15fdcafc5de7507289e | Python | 1,521 | 57 | """File-related utilities."""
import os
from pathlib import Path
import subprocess
def find_files(path, suffix, relative=None):
"""
Find all files in path with given suffix. =
:param path: Directory in which to find files.
:type path: Union[str, Path]
:param suffix: Suffix determining file type t... |
602c4b06e2701b20a2ea5ce2a1005f37b15025b78054356c5da4ac53fa080a0e | Python | 1,522 | 59 | from utils import *
import pandas as pd
import numpy as np
import torch.utils.data
import torch
import pickle
import h5py as h5
import os
from model import *
def make_chip():
chroms = ["chr" + str(i) for i in range(1,23)][::-1]
for cell in ['GM12878']:
chipseq_path = os.path.join('./GM12878/')
... |
3015349705bce53ed2f83dcc9f311636a967322a01f14d108b32170fd48dee5d | Python | 1,523 | 69 | # SPDX-License-Identifier: LGPL-3.0-or-later
"""The model that takes the coordinates, cell and atom types as input
and predicts some property. The models are automatically generated from
atomic models by the `deepmd.dpmodel.make_model` method.
The `make_model` method does the reduction, auto-differentiation
(dummy for... |
6b252885a406fae3492d3590cf9b9a2312bcb1c06a18793de916714dbd1220e5 | Python | 1,523 | 53 | # from src.cajal.sample_swc import compute_icdm_all_euclidean, compute_icdm_all_geodesic
from src.cajal.swc import get_filenames, default_name_validate
from src.cajal.sample_swc import (
read_preprocess_compute_geodesic,
read_preprocess_compute_euclidean,
compute_icdm_all_euclidean,
compute_icdm_a... |
af3bab351981b5e67e4294185cae844f1a7c02543d5830a8454f3ff5354e0fcd | Python | 1,525 | 46 | """ArrowHead dataset."""
from sktime.datasets._single_problem_loaders import load_arrow_head
from sktime.datasets.classification._base import _ClassificationDatasetFromLoader
class ArrowHead(_ClassificationDatasetFromLoader):
"""ArrowHead time series classification problem.
Example of a univariate problem w... |
cc88f23ea204e9b5272d2f774cc8397db9a7cad1341f5aa6eefc6bab5e065aa7 | Python | 1,526 | 46 | """Util function for reading tsv files."""
__author__ = ["TonyBagnall"]
__all__ = ["load_from_ucr_tsv_to_dataframe"]
import pandas as pd
from sktime.datasets._readers_writers.utils import get_path
# TODO: original author didn't add test for this function
def load_from_ucr_tsv_to_dataframe(
full_file_path_and_n... |
9fe3da0339816dac64af5db0edf29b0ab07bce426f4b03efa0e5f57466f36fb1 | Python | 1,527 | 44 | __author__ = ["chrisholder"]
import numpy as np
from sktime.utils.numba.njit import njit
@njit(fastmath=True)
def _dba_update(
center: np.ndarray, X: np.ndarray, path_callable
) -> tuple[np.ndarray, float]:
"""Perform an update iteration for dba.
Parameters
----------
center: np.ndarray (2d arr... |
e05a3ab0fafa33e0ef5dd404c54a722266fb1aeb91b48db7625a04452ae5c971 | Python | 1,527 | 40 | from sklearn.ensemble import RandomForestClassifier
from sklearn.model_selection import GridSearchCV
import sklearn.metrics as metrics
def gridSearchRF(XA_train, yA_train, seed, n_jobs):
# Build classificer model
rf = RandomForestClassifier(random_state=seed)
# Create the parameter grid based on the resu... |
c04ef196d72203efcff48bd50d2cc7ee2b05f19dbbadd1ebf93b069b65a0a5ce | Python | 1,528 | 54 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
from typing import TYPE_CHECKING
from onnx.reference.op_run import OpRun
if TYPE_CHECKING:
import numpy as np
class SplitToSequence(OpRun):
def common_run(
self, mat: np.ndarray, spli... |
ed5c32559e97aae16e8be550f2e8f48b011066233668776f00ffd92916f0327a | Python | 1,528 | 44 | """Util function for reading long format files."""
__author__ = ["TonyBagnall", "AidenRushbrooke", "Markus Löning"]
__all__ = ["load_from_long_to_dataframe"]
import pandas as pd
from sktime.datasets._readers_writers.utils import get_path
from sktime.datatypes._panel._convert import from_long_to_nested
# TODO: orig... |
12876d92161b49cdc4f59244c48dcc5117a65bbbb56d97ceed0a8ad39981a75a | Python | 1,531 | 34 | #!/usr/bin/python
from __future__ import print_function
import os
import subprocess
import logging
logging.basicConfig(filename='george_run.log',level=logging.DEBUG, format='%(asctime)s %(message)s', filemode='w')
cells = [9, 14, 16, 17, 18, 19, 20, 21, 22]
missingcells =[11]
runid = ''
for cellno in cells:
cmdin... |
b957d8c2b1a6eec564bef279e238f3f2e1e674d7c69e31b59f89fc7b31c2c172 | Python | 1,532 | 50 | import importlib
import inspect
from collections.abc import Iterable
from types import ModuleType
from typing import Any, Optional, Protocol, TypeVar, Union, overload
T = TypeVar("T")
class StringLike(Protocol):
def __str__(self) -> str: ...
def get_non_abstract_subclasses(cls: type[T]) -> Iterable[type[T]]:
... |
8cca1d5f5490334058fd23add21b935e0f4a2c52095099298b9f502c044ac939 | Python | 1,533 | 46 | import torch
from torch import nn
class DiceLoss(nn.Module):
"""
Code borrowed from kaggle segmentation dataset
"""
def __init__(self, sigmoid_required=False):
super(DiceLoss, self).__init__()
self.smooth = 1.0
self.normalization = None
if sigmoid_required:
... |
fb95f92d4e724eca9ded68d788b55311da7f8de39ab03bae9a918df26d40f811 | Python | 1,533 | 68 | # Copyright 2019-2026 The AmpliGraph Authors. All Rights Reserved.
#
# This file is Licensed under the Apache License, Version 2.0.
# A copy of the Licence is available in LICENCE, or at:
#
# http://www.apache.org/licenses/LICENSE-2.0
#
"""Support for loading and managing datasets."""
from .datasets import (
_l... |
9ddd028b39f5564d354aec5d7137481f67b163a0ab47b946922db33d8bc86b0c | Python | 1,535 | 51 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
from onnx.reference.op_run import OpRun
class CommonSplit(OpRun):
def __init__(self, onnx_node, run_params):
OpRun.__init__(self, onnx_node, run_params)
self.n_outputs = len(onnx_no... |
15ef7d9f9e8777d00da020f5ca6903e1ca071303205bb57e99e8bcda021566d4 | Python | 1,539 | 56 | # 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 BlackmanWindow(Base):
@staticmethod
def export() -> None:
... |
52f0270fe9e3b62dd9590034088da4bc72bec88caf9c24bf089d22034d9db714 | Python | 1,539 | 54 | #!/usr/bin/env python3
"""Report on overlaping triples between all pairs of ontology files.
Usage:
overlaps [options] <file>...
Options:
-h --help print this
-v --verbose do something fun!
"""
import os
import rdflib
from docopt import docopt
from pyontutils.core import makeGraph
try:
break... |
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