sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
def83a781048ff3a0c948bf0dbf3f4151f18f2bffc88139a78aec6e7cd97e477 | Python | 3,525 | 107 | import numpy as np
import SimpleITK as sitk
def dice_coefficient(output, target, threshold=0.5, smooth=1e-5):
"""
Calculates the Dice coefficient between two binary masks.
Args:
output (numpy.ndarray): Predicted binary mask
target (numpy.ndarray): Ground truth/Label binary mask
threshold (floa... |
79c92375288cee91519cc3dad315918ecbf8129a94a169efb11d68b597d754dc | Python | 3,528 | 104 | import argparse
import logging
import os
import sys
from datetime import datetime
from gln.common.cmd_args import cmd_args as gln_args
from models.gln_model.gln_trainer import GLNTrainer
try:
from models.transformer_model.transformer_trainer import TransformerTrainer
from onmt.bin.train import _get_parser
excep... |
a706bc9f651dfc7319da9ab4b07b57139eff2695fbc882a12b3ffb96a46ca17f | Python | 3,528 | 120 | from __future__ import print_function
"""
Manage the vector strength summary files as .p files
Creates a dict with rows (cells) and columns (experimental manipulations)
Adds data to file, or prints results from the file
Usage:
import vspfile
routines:
vspfile.init_vsp()
vspfile.add_data()
vspfile.print_vsp()
This m... |
239c7babfba2ec4478fd0ebd4d35a871280f6eb8df3a94ca8ca0df2f2f0830d2 | Python | 3,529 | 103 | # 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
#
import tensorflow as tf
import numpy as np
from ampligraph.datasets import loa... |
b8f103a0c181bd9a6a8c1d7daefc9d17c83d848f914e12695774d2c7d59ddfbf | Python | 3,531 | 106 | # 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... |
53d8ad2409bcfb746ca89858980e104c3f25c6b7ef0e5b179f993315bbd089f8 | Python | 3,535 | 98 | # 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... |
04f227af394375110ff0a0e1b8a79137372f50299e74dedf8f833e111fcf204a | Python | 3,537 | 70 | import json
import numpy as np
import pandas as pd
import pytest
import torch
from isoprism import IsoPrism
from isoprism.benchmark import METHODS, build_queue, main, verify_prepared
from isoprism.report import export_tables
from short2long.competitive_model import CompetitiveAllocationNet
from short2long.published_be... |
a6b5da5956b32e99cb9741669f46e5204203996ec0dd572fd36e61a74ed45aea | Python | 3,537 | 55 | import unittest
import os
from marker_tools import get_nsforest_confidences
from dendrogram_tools import dend_json_2_nodes_n_edges
from nomenclature_tools import nomenclature_2_nodes_n_edges
current_dir = os.path.dirname(os.path.realpath(__file__))
PATH_MOUSE_NOMENCLATURE = os.path.join(current_dir, "../dendrograms/no... |
63d84622555dd570ac33087f951ab975b815463cf25593b6cc30762c42160fde | Python | 3,538 | 93 | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Thu Oct 11 17:46:18 2018
@author: tpisano
"""
import numpy as np, sys, os
from skimage.external import tifffile
from skimage import filters
from skimage.morphology import binary_dilation, ball
from tools.registration.register import similarity_transform, t... |
65699aa07aad9b72716917facbe47cdfe5aee7c763ca7545b2a5bb7f62e86fc0 | Python | 3,539 | 114 | # 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... |
9a14f39be373c2e6d178a3b64d406470c145cfffa0e60e66042e78293b2d76d6 | Python | 3,544 | 99 | # coding=utf-8
# Copyright (C) 2021. 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
#
# ... |
c7c9d7b534e03f1e4384e52eb3ce8219aea2056c92e900fac746e6e2d511cd2b | Python | 3,544 | 91 | # data preparation for zebra fish. data reading, scaling, croping, adjusting data format and split into train/val/test
# data loading
# all the 69 stacks of data
import os
import numpy as np
from scipy import ndimage
import random
import argparse
from skimage.transform import resize
import matplotlib.pyplot as plt
... |
1e1834aa57c2acd4e3b44260c967107af1293d1ba8a38859f1d6e9b16df26d6c | Python | 3,546 | 113 | """ Test shuffled autorrelation. (for pytest)
Shuffled autocorrelatioon routine testing We confirm that the status of the
results for all 6 patterns is the same as defined in the audit. The test data
are computed in the sac.py module
This module is part of *vcnmodel*.
Support::
NIH grants:
DC R01 DC015901 (... |
c9325531dbfea480a6fe05182d0d3d94329291905f8148a133a2cdbf4edeff29 | Python | 3,546 | 100 | # 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... |
4f100233a931d175093cf671629dbbe6937bf34fc258e2d04a87650064ff461e | Python | 3,547 | 115 | """
Test using sound stimulation to generate SGC spike trains.
This script uses an_model.get_spiketrain(), which internally calls MATLAB to
generate spike trains and caches the output. A higher-level approach is to use
DummySGC, which will automatically feed the spike train into a synapse for
input to downstream neu... |
a1b6006d5bc270b9f2a951448d8ca8b6ffcef3622b7556b338303dacf8cea3dc | Python | 3,548 | 98 | #-------------------------------------------------------------------------------
# Test handling for compressed debug sections
#
# Pierre-Marie de Rodat (pmderodat@kawie.fr)
# This code is in the public domain
#-------------------------------------------------------------------------------
import os
import unittest
fr... |
a3bf36fb3dae06c7f5a0f3d8ad8b2fc16c16c05f82378dd1896036db8f23e39e | Python | 3,549 | 62 | from __future__ import print_function
import numpy as np
from itertools import groupby
from functools import reduce
from operator import add
from scipy import signal
from featureExtractor import FeatureExtractor
from globalTimeManagement import getTimeDiffInSeconds
class FeatureExtractorRawDataWithSTFTWithTime(Feature... |
ad55365b85ccf1ba043f1467364b6818483f3f613b530a1bc882b52ec6c2778c | Python | 3,549 | 115 | import sys
import re
import matplotlib
matplotlib.use("Agg")
from matplotlib import pyplot as plt
import seaborn as sns
sns.set_style("white")
import pandas as pd
from matplotlib.ticker import FormatStrFormatter
colors = sns.color_palette("RdYlBu", 13)
colors = sns.cubehelix_palette(7, start=2, rot=0, dark=0.05, li... |
cec53d9e56106d9a9b1f0106a1a3eef6af0b82368a220549c6ab534b6d386fea | Python | 3,552 | 96 | # 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... |
7993202ef0778d38337ac5deee5d25296ab30d212afe7c2ff04984413f552c2e | Python | 3,553 | 113 | """Solar dataset for time series forecasting."""
import pandas as pd
from sktime.datasets._single_problem_loaders import load_solar
from sktime.datasets.forecasting._base import _ForecastingDatasetFromLoader
__all__ = ["Solar"]
class Solar(_ForecastingDatasetFromLoader):
"""Load the GB National Solar Estimates... |
c51343cfed7af32f2f83ec6bcca7b6028259a9332947931ec151f6c7df1da968 | Python | 3,553 | 109 | # 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... |
60a50f1759beca88ba178bfce15d86313374a27eac513fffa51f44b7e03de808 | Python | 3,557 | 126 | from lgn.models.autotest.lgn_tests import lgn_tests
from lgn.models.autotest.utils import plot_all_dev
from utils.argparse_utils import (
get_device,
get_dtype,
parse_model_settings,
parse_data_settings,
)
from utils.initialize import initialize_autoencoder, initialize_test_data
from utils.utils import... |
ca691c28084aeed76a5e40dc0b789b71a18d15804cf3566b0e86cf359d58499b | Python | 3,559 | 107 | import os
import numpy as np
# Read in all files and split them according to the specification.
with open("dataset/abstracts.csv") as f:
abstracts = f.read().strip("\n").split("\n")
with open("dataset/content.csv") as f:
content = f.read().strip("\n").split("\n")
with open("dataset/features.csv") as f:
f... |
4e02d5643d77b88d0141a6d10fcba7a4cf682242a581b3566e3978fd782102dc | Python | 3,560 | 82 | # Copyright 2007 Zachary Pincus
# This file is part of CellTool.
#
# CellTool is free software; you can redistribute it and/or modify
# it under the terms of version 2 of the GNU General Public License as
# published by the Free Software Foundation.
import re
import freeimage
from celltool.contour import contour_class... |
584370fab610e51bbafe925ab690fd6911591469f2f289b58a2066270cb822e7 | Python | 3,560 | 84 | #-------------------------------------------------------------------------------
# elftools tests
#
# Yann Rouillard (yann@pleiades.fr.eu.org)
# This code is in the public domain
#-------------------------------------------------------------------------------
import copy
import os
import unittest
from typing import Cla... |
adf781edc19639199e6db0e61447eb0bff40bb79614a0456aeef325125b2fd25 | Python | 3,561 | 111 | # 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... |
876e0573952d6a8b8971bde1d05694fec9a48028ab72e6f023bf2ce9f7c9b166 | Python | 3,565 | 103 | # 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... |
7328d6c3e86ed25dd4330a1ff169e12623b2f575d233f11b7240737cc67fcf4f | Python | 3,566 | 101 | # 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... |
9b3609d95268a1a58429bc7e61894779c4f2890a92c35baa71e70e0a9d2ee7af | Python | 3,570 | 88 | # 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... |
dbba0745da0694e87c9417c5adde9df66e1def9bab6f10b6bbbe55b8a90f9500 | Python | 3,570 | 98 | # 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 DepthToSpace(Base):
@staticmethod
def export_default_mode_exam... |
034475cd47164cf8328303e4e4641138cc67ed8fcec1000119f74d005da08a8f | Python | 3,573 | 100 | """Tests for HMM annotation estimator."""
__author__ = ["miraep8"]
import numpy as np
import pytest
from numpy import array_equal, asarray
from scipy.stats import norm
from sktime.detection.hmm import HMM
from sktime.tests.test_switch import run_test_for_class
@pytest.mark.skipif(
not run_test_for_class(HMM),
... |
e558c343a2cc280d7037987a37bc9139c8105473d5fe18fbba1b52ed00e63f72 | Python | 3,577 | 107 | """
Make a master file list for a group of runs
This list is created after the runs are done, and in a subdirectory.
"""
from pathlib import Path
import pickle
import toml
import datetime
from dataclasses import dataclass, field
from typing import Union, Dict, List
import dataclasses
# @dataclass
# class Rundata:
#
... |
f00ee7b014ab913d484d1d7fe1accb7a2b542a34028bf71553887819ac2e55b0 | Python | 3,578 | 100 | # Copyright (c) Open-MMLab. All rights reserved.
import os
import os.path as osp
import tempfile
from unittest.mock import MagicMock
import matplotlib.pyplot as plt
import mmcv
import numpy as np
import pytest
from mmcls.core import visualization as vis
def test_color():
assert vis.color_val_matplotlib(mmcv.Col... |
140acbc785c5998dab2aabe5bf8ddcf919d042c4bd1ba1b076d7edc0e0012ede | Python | 3,581 | 100 | """Testing panel converters - internal functions and more extensive fixtures."""
import numpy as np
import pandas as pd
import pytest
from sktime.datatypes import check_is_mtype
from sktime.datatypes._series_as_panel import (
convert_Panel_to_Series,
convert_Series_to_Panel,
convert_to_scitype,
)
from skt... |
7962fb61ee851e94882f4b2002b60f941e143b105dcff1cae4826d10fa686649 | Python | 3,581 | 103 | # coding=utf-8
# Copyright (C) 2021. 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
#
# ... |
85e5c17a7e52ab775511c1d26f85b8aecee7f67397cb736aa7e78ed15ce3cf80 | Python | 3,583 | 113 | # 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... |
e64e492cc1b984ff44b84e6c4fa3574454b49ff4c25a5f33b0bb27fedc0a93f0 | Python | 3,583 | 80 | # SAFE TEAM
#
#
# distributed under license: CC BY-NC-SA 4.0 (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.txt) #
#
import argparse
from dataset_creation import DatabaseFactory, DataSplitter
def debug_msg():
msg = " DATABASE UTILITY"
msg += "-------------------------------------------------\n"
... |
fc546b3815d07a5a7b5d93382fd5d1a312932a50561b6ea7359243a2107f5869 | Python | 3,584 | 118 | from __future__ import division
import re
import numpy as np
import pandas as pd
class Node(object):
"""
Class for extracting the structure of vrml files
"""
def __init__(self, dict):
"""
Initialize an instance of the "Node" class from a file name.
Parameters
... |
567d366aefcb2b29cee5221fa8bca3ab3c427fb243f569b88bbc8415c4d7d165 | Python | 3,585 | 108 | # 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... |
3835aefc124250b35710a754d32084935aa7c6aa57140619ae9f13e1d66dd896 | Python | 3,587 | 93 | # Copyright (c) OpenMMLab. All rights reserved.
from functools import partial
import pytest
import torch
from mmcls.core import average_performance, mAP
from mmcls.models.losses.accuracy import Accuracy, accuracy_numpy
def test_mAP():
target = torch.Tensor([[1, 1, 0, -1], [1, 1, 0, -1], [0, -1, 1, -1],
... |
0931b3ad1ca07035981174d60d6d97d598e745515a5a560bd604fd5750e88688 | Python | 3,589 | 120 | # 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... |
418d98b41024c39597c19d532e20f1c7640996aa28b20ff96502a4a8ad71084c | Python | 3,589 | 98 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
from onnx.reference.ops.aionnxml._common_classifier import (
compute_probit,
compute_softmax_zero,
expit,
)
from onnx.reference.ops.aionnxml._op_run_aionnxml import OpRunA... |
ff33a7d8efb74d7a9d6b2f7f59c183394bf639bf0be66937b6e2f7287da2f2a6 | Python | 3,590 | 125 | """Tests for bycycle.utils.dataframe."""
import pytest
from copy import deepcopy
import numpy as np
import pandas as pd
from bycycle.utils.dataframes import *
###################################################################################################
########################################################... |
ac5067ece95d99bb377b6bf7ea74772be7ddd6c19608bc1eec17fd89eeae0115 | Python | 3,591 | 113 | #!/usr/bin/env python3
# CBDA validation and training set creation.
# This script defines the set of ordinal line numbers to use for the validation
# set of a CBDA project.
#
# Inputs:
# File name of original data file.
# The following assumptions are made about the contents of the file:
# It ... |
feee50e93820f12f949175d3b878a63ce54bdf9e9a9744fe94cac5ad70f5f619 | Python | 3,591 | 103 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
class TreeEnsembleAttributes:
def __init__(self):
self._names = []
def add(self, name, value):
if not name.endswith("_as_tensor"):
self._names.ap... |
f429d14b314527c175bf3ef04f0836773df6d4da4359d003f24ac77e31c9afd7 | Python | 3,592 | 74 | # Setup
import warnings
warnings.filterwarnings("ignore")
import numpy as np
import pandas as pd
import pickle as pkl
import matplotlib.pyplot as plt
import matplotlib as mpl
from sccoda.util import comp_ana as mod
from sccoda.util import cell_composition_data as dat
from sccoda.util import data_visualization as viz
... |
4eeb742367958f4c0d6fd53621b0398926ecc04eb944e2d36ed306d7aa482bc7 | Python | 3,593 | 125 | import pandas as pd
import os
import Levenshtein
BASE_PATH = 'data/tl_train/U6T7/'
PRE_TRAIN_PATH = 'data/pre_train/DeepHF_old/'
def get_folders(path):
folders = []
names = []
for folder in os.listdir(path):
if os.path.isdir(os.path.join(path, folder)):
folders.append(folder)
... |
f3cb1493aa1402db0df9275971d51e3af5d76cf075140bd7cbbf203afb4c89d6 | Python | 3,596 | 106 | import os
import h5py
import numpy as np
from sklearn.metrics import roc_curve, auc, precision_recall_curve, accuracy_score, roc_auc_score
def make_directory(path, foldername, verbose=1):
"""make a directory"""
if not os.path.isdir(path):
os.mkdir(path)
print("making directory: " +... |
85e502d84643f6fd56304cad3b8bffac46143c35b410cfd0c61716edf85b93ce | Python | 3,597 | 111 | # copyright: sktime developers, BSD-3-Clause License (see LICENSE file)
# Ported from skchange (BSD-3-Clause), original authors: johannvk
"""Multivariate Gaussian change score."""
__author__ = ["johannvk"]
import numpy as np
from sktime.detection.base._base_interval_scorer import BaseIntervalScorer
from sktime.detec... |
d4861e90de343d52e2cefe501122e1d37f7e2452a4252abde319c38d2ff48207 | Python | 3,597 | 84 | import numpy as np
import joblib
import torch
from torch_geometric.data import Data
class FileLoader(torch.utils.data.Dataset):
"""Data loader for graph data. The loader will use features defined in features.yml."""
def __init__(self, file_list, feat_names, feat_stats, norm, data_clean):
self.file_l... |
d512cdbcdd978339b431294d97faf319ce023eef724189d24a00e216119bb174 | Python | 3,604 | 107 | # Copyright 2019 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://aws.amazon.com/apache2.0/
#
# or in the 'license' file acc... |
b222eab8447085645821d45e6522332757b344d94fc9ec29203207affd593cd2 | Python | 3,606 | 111 | '''
@author: Nicholas Browning
'''
from __future__ import print_function
from builtins import str
import os
import sys
import argparse
import openbabel
from src import outprocesses as op
import subprocess
def sander_minimize(mol, out_mol, num_procs):
delete_files = ["mol.pdb", "mol.prmtop", "mol.inpcrd", "mol.rs... |
08263ef4954b7e54eea1117663fe1c1e5a0fde8218a672fecdca1466532befe6 | Python | 3,608 | 116 | # 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... |
7e84ef732a78d01c7444e9bb218f667e34424dce2d0b0b050f455802aea788e5 | Python | 3,612 | 81 | # Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT!
import grpc
from google.protobuf import empty_pb2 as google_dot_protobuf_dot_empty__pb2
import real_time_payoff_tracker_pb2 as real__time__payoff__tracker__pb2
class RealTimePayoffTrackerStub(object):
# missing associated documentation comment i... |
459db2a0094d6485a076edc5853cc70343d95da1da4e880840261c97154e9226 | Python | 3,613 | 109 | """Tests for bcblib.imaging.info."""
import numpy as np
import nibabel as nib
import pytest
from bcblib.imaging.info import (
header_summary, header_dump, header_field,
format_summary, format_summary_short, format_dump,
)
def _make_nii(shape=(4, 5, 6)):
data = np.zeros(shape, dtype=np.float32)
retur... |
837c9bee88aa8001c2fab005ee5140e206efdf5faf117ec57d8aa5ae94eb85bf | Python | 3,613 | 103 | import argparse
import math
import os
import matplotlib.pyplot as plt
import numpy as np
import torch
import wandb
from torch.utils.data import DataLoader
from tqdm import tqdm
import src.model.metrics as module_metric
from src.trainer.trainer import Trainer
from src.utils.config import process_config
from src.utils.... |
c005d2fdd13e4d9ed9f04cd10e26f82d20df593ab11844f023d90b9b219228d0 | Python | 3,613 | 175 | from __future__ import division
import numpy as np
def cart_to_spherical(x, y, z):
"""
Convert coordinates from Cartesian to spherical.
Parameters
----------
x : float
x coordinate.
y : float
y coordinate.
z : float
z coordiante.
Returns
-------
r... |
30170c8c14fbf2f9b4ff9aa9ad6ced5284f36d1e5b7cdffc9f04ced56abaa158 | Python | 3,615 | 108 | """Testing mtype/scitypes lookup."""
__author__ = ["fkiraly"]
from skbase.utils.dependencies import _check_soft_dependencies
from sktime.datatypes._registry import (
generate_mtype_register,
generate_mtype_soft_deps,
mtype_to_scitype,
scitype_to_mtype,
)
def pytest_generate_tests(metafunc):
reg... |
4716d6d63b9c5b4869f48bc489c9c4ba744a96f4b79edf9ed0be4473c30d2741 | Python | 3,615 | 95 | import matplotlib.pyplot as plt
import numpy as np
from Historia.cellcontr import solver as solcontr
from Historia.ep import solver as solep
from Historia.shared.plot_utils import get_col
def fun(axes, rat, color):
# ---------------------------------------------------------------
# Electrophysiology
hz =... |
a43839f4e93020b75f4290da86c7b68c0705b02c26ebe1653107d7e3ad8369e7 | Python | 3,615 | 104 | import numpy as np
from keras.models import *
from keras.optimizers import *
from sklearn.metrics import mean_squared_error, r2_score
import scipy as sp
from scripts import models_util
from scripts import data_handler as dh
from keras.callbacks import Callback
def scheduler(epoch, lr):
learning_rate = 0.... |
23e11eee7db6a886ca981b98c1ecf8bd38746611c5dc80723b4b290dbd6daef5 | Python | 3,616 | 86 | # 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... |
8f6e3a7ee164da0eb865758576e4eb40f40a761bb90f76508cf86610afc78d08 | Python | 3,618 | 116 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Creates example patient plot in Figure 4 from Wang et al. (2023) Temporal
stability of intracranial EEG abnormality maps for localizing epileptogenic
tissue.
Calculates time-varying D_RS from abnormalities before plotting.
Choose example patient at beginning of scr... |
fe22fcbe901ed5c767da2d7938282652426c4ea8a4876251ad00dada08adddee | Python | 3,618 | 92 | '''
Pure-python implementation of UCSC "liftover" genome coordinate conversion.
Liftover coordinate conversion correctness test.
Copyright 2013, Konstantin Tretyakov.
http://kt.era.ee/
Licensed under MIT license.
'''
import os.path
import gzip
import sys
from pyliftover.liftover import LiftOver
THIS_DIR = os.path.d... |
7feedbbd4375aeab5ebf2bca48fe2c3b2b17f9831af616d22e29b9ebf0d7a7f0 | Python | 3,620 | 88 | # Copyright (c) ONNX Project Contributors
#
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
import pytest
from onnx import TensorProto, checker, helper, numpy_helper, version_converter
from onnx.reference import ReferenceEvaluator
from onnx.reference.op_run import OpRun
c... |
10429ca473ab152f5cd3a521f289506055b7e6c526b94866b0044c30ad072cb2 | Python | 3,621 | 112 | from __future__ import print_function
import numpy as np
from scipy.ndimage.filters import gaussian_filter
class Perturb(object):
"""
Callable class for in-place image perturbation.
"""
def __init__(self):
raise NotImplementedError
def __call__(self, img):
raise NotImplementedErro... |
7e62c831885c0e9f4070e244da94b63089fc46e786dadae78fa6152a7afbef65 | Python | 3,621 | 112 | # 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... |
0d7fcc3488ee5e31023d554bbd6e2d01b654d0101d13077cd6fed9aa8e2dc07d | Python | 3,622 | 115 | #!/usr/bin/env python
import click
from functools import partial
from multiprocessing import Pool
import os
import pandas as pd
import re
import subprocess as sp
import sys
sys.path.insert(0, os.path.join(os.path.abspath(os.path.dirname(sys.argv[0])),
os.pardir,
... |
9384cbd582e8ad8b7db4d9bc6ae0ed54d69950e6d9bbe6c3ef304c2dd6fcc20d | Python | 3,623 | 96 | # 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... |
95982f3c217c703c3ce1e093ddbb75b9c1aabe39f91c462a4fdb17d4288cffee | Python | 3,623 | 114 | import logging
from pathlib import PosixPath
from typing import Optional, Tuple
import ants
from omegaconf import DictConfig
from rich.logging import RichHandler
from roiloc._cache import handle_cache
from roiloc.locator import RoiLocator
from hsf.roiloc_wrapper import save_hippocampi
FORMAT = "%(message)s"
logging.... |
5c9ca3effe0a0feeb6d9f936c3a77aa53c34957c24e347d0791363ca9ecb6a15 | Python | 3,624 | 132 | import click
from itertools import product
from pathlib import Path
from typing import Iterable
import warnings
import pandas as pd
classifiers = (
'xgboost_cce',
'logistic_regression_cce',
'logistic_regression_ovr',
)
segmentations = (
'freesurfer',
'sri',
)
def load_results(filename: Path) -> ... |
77ca316029b1c409933f5ac3d110d32b4947f216a2b0a8f8ad5afe6065df831f | Python | 3,625 | 117 | # -*- coding: utf-8 -*-
#
# Copyright © 2013 Charles E. Vejnar
#
# This Source Code Form is subject to the terms of the Mozilla Public
# License, v. 2.0. If a copy of the MPL was not distributed with this
# file, You can obtain one at https://www.mozilla.org/MPL/2.0/.
#
import logging
import os
import subprocess
fro... |
70f926be29e2cf5eb63d2649405b281e71f2f3f65435a1a58ed5a4bb1e32689f | Python | 3,626 | 95 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
import onnx
from onnx import TensorProto, helper, numpy_helper, shape_inference
class TestTrainingTool:
def test_training_info_proto(self) -> None:
# Inference graph.
... |
697ff3dc9107e0dadebda40110257bc83b6821876e1e99d478a1f7630a365527 | Python | 3,627 | 104 | #!/usr/bin/env python3
#!/usr/bin/env pypy3
"""Set qnames based on the curies defined for a given ontology.
Usage:
qnamefix [options]
qnamefix [options] (-x <prefix>)...
qnamefix [options] <file>...
qnamefix [options] (-x <prefix>)... <file>...
Options:
-h --help print this
-k --keep ... |
c051843b9abbb2660c132267726b83864da049269b2accebd440361bca8f5ee9 | Python | 3,627 | 110 | import gzip
import shutil # for removing and creating folders
import urllib
import warnings
from pathlib import Path
import requests
import yaml
from Bio import SeqIO
from Bio.Seq import Seq
from tqdm.autonotebook import tqdm
from yarl import URL
from .paths import DATASET_DIR_PATH, DATASET_URL_PATH
def _guess_loc... |
fc956f53c540112e28a76552ea44b4bc874a5ccdd43b78c4d0ac28386369e470 | Python | 3,627 | 106 | # 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... |
c5451c4cf78d0905c9e3121e405cd0dc20b11e2a2c65b234c5dda0d34fd42896 | Python | 3,628 | 77 | # Copyright 2020 Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
#
# 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://w... |
e74adfe05d9b2b243a383016bdd64765e70c8a0e3be7c589c01bbad85ce0fd87 | Python | 3,628 | 136 | """Example generation for testing.
Exports examples of in-memory data containers, useful for testing as fixtures.
Examples come in clusters, tagged by scitype: str, index: int, and metadata: dict.
All examples with the same index are considered "content-wise the same", i.e.,
representing the same abstract data objec... |
f1dc31ad82328ed89753265c25dc329b7a9ae7dfbf03246b652aa6f8bfd76d02 | Python | 3,628 | 99 | import os
import numpy as np
import pickle
import keras
from scripts_tool import models_util
from scripts_tool import training_util
gl_init_lr = 0.0008
def create_data(config, DataHandler):
# Create main dir
data_dir = f'tool data/datasets/{config.new_data_path}/6_fold/'
if not os.path.exists(data_dir):
... |
0fb9d24a1b8fca0d580a4345b706b99475cdb1f16d0064203b7560cf332317a4 | Python | 3,631 | 95 | # 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 LpNormalization(Base):
@staticmethod
def export_l2normalizatio... |
afe5706b626bd43f371a73b3728193f7ea5b92850e85c017bbb6019ef790f9a8 | Python | 3,633 | 117 | # copyright: sktime developers, BSD-3-Clause License (see LICENSE file)
# Ported from skchange (BSD-3-Clause), original authors: Tveten, johannvk
"""Base cost function for interval-based scoring."""
__author__ = ["Tveten", "johannvk"]
from sktime.detection.base._base_interval_scorer import BaseIntervalScorer
class... |
32d66f7a77154847d54161b29755bf35de759ef62bbf13da4c7e9a11a8384dbb | Python | 3,635 | 97 | from copy import deepcopy
import sys, os
import torch
import numpy as np
from vp_suite.models import PhyDNet as OurModel
from vp_suite.utils.models import state_dicts_equal
REFERENCE_GIT_URL = OurModel.CODE_REFERENCE
REPO_DIR = "PhyDNet"
# noinspection PyUnresolvedReferences
def test_impl():
from models.model... |
6c3ccc140196bc664b1b294470ee0c58f68ce7d2c7a7459941419a1e5a8a1b72 | Python | 3,637 | 99 | """
Model component of the MVC pattern for pciSeq diagnostics.
"""
import redis
import pandas as pd
import numpy as np
import logging
from typing import Optional, Dict, Any
from pciSeq.src.diagnostics.constants import DiagnosticKeys
model_logger = logging.getLogger(__name__)
class DiagnosticModel:
def __init__(... |
090550bd1b371ebf9b3d9e5aeae2a59a1f390532d394baec7828bff4dfe27a4e | Python | 3,638 | 60 | import argparse
from trainer import Trainer
from utils import init_logger, load_tokenizer
from data_loader import load_and_cache_examples
def main(args):
init_logger()
tokenizer = load_tokenizer(args)
train_dataset = load_and_cache_examples(args, tokenizer, mode="train")
test_dataset = load_and_cache... |
e047488c1597dceea8fadb81cff4c301d9de7a7a52a960df90e99233d9a29309 | Python | 3,639 | 80 | from types import SimpleNamespace
import numpy as np
from scipy import sparse
import torch
from short2long.unified_data import select_catalogue
from short2long.unified_benchmark import PlainMLP, classical_fit, classical_predict
from short2long.unified_metrics import moran, spatial_metrics
from short2long.coverage_retr... |
4c89dbe2d89c7779c7994cf00b44f48e99449f13dc55246b08a003b2a4ca53a4 | Python | 3,641 | 92 | import unittest
from onmt.inputters.image_dataset import ImageDataReader
import os
import shutil
import cv2
import numpy as np
import torch
class TestImageDataReader(unittest.TestCase):
# this test touches the file system, so it could be considered an
# integration test
_THIS_DIR = os.path.dirname(os.pa... |
ed425b38182b5611765519b16eb2b3485c187e9f40a88a8581684b549f8a9aab | Python | 3,642 | 113 | # 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 and
commun... |
05061e49c71041f12440475e02e96f3a3bf7619451ac5b4a17d1a04e2eca0761 | Python | 3,643 | 98 | import numpy as np
np.random.seed(1234567)
import random
random.seed(1234567)
from collections import Counter
import re, os, csv, math, operator
import pandas as pd
#Contains 86 elements (Without Noble elements as it does not forms compounds in normal condition)
elements = ['H','Li','Be', 'B', 'C', 'N', 'O', 'F', 'Na... |
2449a6fde71acb1067bc67190fbad8d148e39165ab13c260db2615472985705c | Python | 3,644 | 100 | import torch
import torch.nn as nn
class RevIN(nn.Module):
def __init__(self, dim=-1, std_min=1e-5, max_val=100, use_sinh=False):
super().__init__()
self.dim = dim
self.std_min = std_min
self.max_val = max_val
self.use_sinh = use_sinh
def fit_transform(self, x, mask=No... |
51137902d4df89351a90821eefc78b0d1fb4dc484cbfb9f248e4d6b491efdce9 | Python | 3,646 | 120 | # roifile/setup.py
"""Roifile package setuptools script."""
import re
import sys
from setuptools import setup
def search(pattern: str, string: str, flags: int = 0) -> str:
"""Return first match of pattern in string."""
match = re.search(pattern, string, flags)
if match is None:
msg = f'{pattern... |
daf58f06a87d5dd4dcd35fc1cfd44f5c16bac466a1dcd0348d8bfeb6f816194b | Python | 3,647 | 108 | # copyright: sktime developers, BSD-3-Clause License (see LICENSE file)
"""Implements compositor for ignoring exogenous data."""
__author__ = ["fkiraly"]
from sktime.forecasting.base._delegate import _DelegatedForecaster
class IgnoreX(_DelegatedForecaster):
"""Compositor for ignoring exogenous variables.
C... |
8ff02002d260e05b92f07b7513436e467c0f72462646506a557cc609198caf03 | Python | 3,648 | 116 | import logging
import random
from collections import defaultdict
import torch
from torch.utils.data.sampler import Sampler
log = logging.getLogger("flair")
class FlairSampler(Sampler):
def set_dataset(self, data_source):
"""Initialize the data source for the FlairSampler.
Args:
data... |
e296c5b30a74ed7f404c2f074d98d8f89109cfb61c421c7e77ab783db8108b7b | Python | 3,649 | 97 | # In Nomine Functions Team
# distributed under license: GPL 3 License http://www.gnu.org/licenses/
import argparse
import numpy as np
"""
Precision = #correctly_predicted_tokens / #predicted_tokens
Recall = #correctly_predicted_tokens / #original_tokens
"""
def calculate_precision_recall(original_names, predicted... |
9c4025d6e12b2f5bfd06a7446dd682fbbf4ce5a5dc1a3d3c240450bba0d33124 | Python | 3,651 | 118 | import io
import lmfit
import numpy as np
import pandas as pd
import seaborn as sns
from lmfit import Model
from matplotlib import pyplot as mpl
from pylibrary.plotting import plothelpers as PH
from pylibrary.plotting import styler as ST
# all runs 20 dB SPL 8/28, 8/29 2020 pbm 100ms pip
# Plot the FSL and SSl for ea... |
4be791945aa8c559f3188cfb42caad5a01a0bf5fc50ea63c1cf3c86119d2141b | Python | 3,652 | 98 | # copyright: sktime developers, BSD-3-Clause License (see LICENSE file)
"""Unit tests for (dunder) composition functionality attached to the base class."""
__author__ = ["fkiraly"]
__all__ = []
import pytest
from sklearn.preprocessing import StandardScaler
from sktime.clustering.compose import ClustererPipeline
from... |
03bf7372a7cbb87641c7ed83daf7ccdeb4402ac2b05ac5fb21d9a5384161c4e2 | Python | 3,653 | 84 | import numpy as np
import pickle
from parameterSetup import ParameterSetup
from fileManagement import getFileIDs
from evaluationCriteria import y2sensitivity, y2confusionMat, printConfusionMat
from sequentialPrediction import classifySequentially
from featureExtractor import featureExtraction
from classifierTrainer imp... |
a0022ae2abcb1ce14b347333a0a11a942d11b208cef365f7daa009ac3c8e34c7 | Python | 3,655 | 122 | # 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... |
036f97b2c301139953786e0a4e4635aa5cb0823bedbc62045db14e03ba8135f5 | Python | 3,656 | 101 | import argparse
import logging
import os
import sys
from datetime import datetime
from gln.common.cmd_args import cmd_args as gln_args
from models.gln_model.gln_tester import GLNTester
try:
from models.transformer_model.transformer_tester import TransformerTester
from onmt.bin.translate import _get_parser
excep... |
69f71e389eb5ce061a515ad42d4656d07de71fb61f844fda7ee43b77afd6fee6 | Python | 3,659 | 121 | # SPDX-License-Identifier: LGPL-3.0-or-later
"""Model wrapper for Uni-Mol v1 self-supervised pretraining."""
from typing import (
Any,
)
import array_api_compat
from deepmd.dpmodel.array_api import (
Array,
)
from deepmd.dpmodel.atomic_model import (
DPUniMolAtomicModel,
)
from deepmd.dpmodel.common impo... |
69892b8e00463748ecd6a07027ec3916a1b26276425718eb70ca91932608d7f0 | Python | 3,661 | 108 | # 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... |
8d3e46a0c24c4310b5f69a143fee6bec6543d117251fe2c3af8882122a6c3d87 | Python | 3,661 | 102 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Apr 14 14:45:34 2022
@author: nagehan
"""
import matplotlib.pyplot as plt
import numpy as np
# Sulcal depth with respect to shape
# Surface area small - senegal galago, night monkey, white faced saki
s1 = [[1.23,2.32,2.73],
[0.93,1.74,1.98],... |
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