sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
d1cb73df61dafee48d655e1b12745b50da95215064f9edc4b67dfc2b20a76dec | Python | 6,256 | 148 | # Copyright (c) OpenMMLab. All rights reserved.
from mmcv.cnn import build_conv_layer, build_norm_layer
from ..builder import BACKBONES
from .resnet import Bottleneck as _Bottleneck
from .resnet import ResLayer, ResNet
class Bottleneck(_Bottleneck):
"""Bottleneck block for ResNeXt.
Args:
in_channels... |
d4576e4d8d9679abe79eccae5f64d7a767a3cc1f7045f6fdd685c8e4bdee89dd | Python | 6,256 | 185 | import argparse
import re
import os
import pickle
import numpy as np
from tqdm import tqdm
from rdkit import Chem
from collections import Counter
import torch
import random
from typing import Optional
def seed_everything(seed: Optional[int] = 0) -> None:
torch.manual_seed(seed)
random.seed(seed... |
cca0c65fbf6702192d566c74b3ca62ee875a1537611e6e3c2191862f18bea601 | Python | 6,257 | 169 | """
plot_conflict_weight.py
Produce circular scatter plots showing the change in bearing
between rolls three and four of the data generated by
conflict_weight.py.
"""
import json
import numpy as np
import itertools
import matplotlib.pyplot as plt
from test_utilities import circ_scatter, k, circmean
import dict_key_de... |
f73d6f183754346a60007498ba192e06663d198e84da6dc7b610f42c73185a41 | Python | 6,257 | 154 | # 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... |
c94ffe03360cd9c318f8dc942fe855d4ed3d3ab90d4f2830f95fbac4ef1bd208 | Python | 6,258 | 170 | """
plot_conflict_weight.py
Produce circular scatter plots showing the change in bearing
between rolls three and four of the data generated by
conflict_weight.py.
"""
import json
import numpy as np
import itertools
import matplotlib.pyplot as plt
from test_utilities import circ_scatter, k, circmean
import dict_key_de... |
1c8225a9d07dcdfb514e4d85dfbac443465f7ac8922358d72d6704a0b49e09f3 | Python | 6,259 | 161 | # Copyright (c) OpenMMLab. All rights reserved.
import functools
from inspect import getfullargspec
import torch
from .utils import cast_tensor_type
def auto_fp16(apply_to=None, out_fp32=False):
"""Decorator to enable fp16 training automatically.
This decorator is useful when you write custom modules and w... |
f2289157a973a44dbd4a3179a981203b9a4eda037b1a61406d877308b79f342c | Python | 6,259 | 154 | # -*- coding: utf-8 -*-
"""Package `cma` implements the CMA-ES (Covariance Matrix Adaptation
Evolution Strategy).
CMA-ES is a stochastic optimizer for robust non-linear non-convex
derivative- and function-value-free numerical optimization.
This release was tested with Python versions 3.8 to 3.13. The
implementation i... |
ef535c85c0f6de6d3f6d9be40c282173d813a21b922cc4cb93457d9610a4af26 | Python | 6,266 | 202 | # 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
def pad_impl(data, raw_pads, mode, constant_values=0.0, axes=None):
inpu... |
f86aba37eb186db0af7abc718ef6fee794c499a3992d8b75c310c8a456343f97 | Python | 6,268 | 158 | # -*- encoding: utf-8 -*-
from __future__ import print_function
import sys
import numpy as np
import pyqtgraph as pg
import neuron
import cnmodel
import cnmodel.cells as cells
from cnmodel.protocols import SynapseTest
from cnmodel.util import random_seed, reset
from cnmodel import data
"""
Check that sgc PSDs have co... |
53ab09035f03f8e33fe8592f587dbd26c1a2d1c909d58a509b70dccc1a019ed6 | Python | 6,270 | 133 | # ----------------------------------------------------------------------------
# Copyright (c) 2017-2026, QIIME 2 development team.
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file LICENSE, distributed with this software.
# ------------------------------------------------... |
742863e8485607c7d0de0e5063b7cdf1ed61368c108b7ace391e0ef6bb6f56b9 | Python | 6,279 | 219 | import os
import random
import time
from datetime import datetime
import numpy as np
import pandas as pd
import torch
def seed_everything(seed: int = 42):
random.seed(seed)
np.random.seed(seed)
torch.manual_seed(seed)
torch.cuda.manual_seed(seed)
torch.backends.cudnn.deterministic = True
torc... |
3663cef2559d2cb3e2543cc33061be6e3f6954ae1d31d403fee7bc6f184c0b15 | Python | 6,280 | 175 | import os
import random
import shutil
from collections import OrderedDict
import numpy as np
import torch
import torch.nn as nn
from imgaug import imgaug as ia
from termcolor import colored
from torch.autograd import Variable
####
def check_manual_seed(seed):
"""
If manual seed is not specified, choose a
... |
8843fcc85e8c942af53750b5297e9098c0e8b90e994c170f55461e1ca2ab580e | Python | 6,283 | 191 | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... |
810048f50505e09424879041d5fbfd857a210052d4de62f175f0acaad962ceda | Python | 6,284 | 181 | """Classifier Experiments: code to run experiments as an alternative to orchestration.
This file is configured for runs of the main method with command line arguments, or for
single debugging runs. Results are written in a standard format.
"""
__author__ = ["TonyBagnall"]
import os
import sys
import numpy as np
os... |
337fa291b23342ba7d0737e1cd69329ee10a6a00dc00e31abe3fa4dccd506af1 | Python | 6,285 | 156 | import numpy as np
import matplotlib.pyplot as plt
from matplotlib import gridspec
import os
from scipy.stats import norm
import sys
from numpy import nan
import numpy.ma as ma
import seaborn as sns
import panel as pn
sys.path.insert(1, "/Users/hyung/Research23_Network_Analysis/mBIN/Python/NetworkAnalysisGeneral/Code/... |
64112512aa125a02b0f5342613a61065f1b8e2593bab91274cf545b334479d07 | Python | 6,294 | 181 | # 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
from onnx.reference.ops import op_grid_sample
def _deform_conv_implementation(
X, W, offset, B, mask, dilations, group, kernel_shape, of... |
4b4f99c768c70ae2322c73ada2591b805a36f6ce891d459b2c6fca903fef3d97 | Python | 6,295 | 184 | import sys
import numpy as np
import torch
from torch_scatter import scatter
from torch_geometric.nn import radius_graph
import dgl
from dgl.nn.pytorch import GraphConv, NNConv
from torch import nn
from torch.nn import functional as F
from typing import Dict, Tuple, List
from models.se3transformer_layers.modules imp... |
f0a69ad19c879b5b5a79f785661ff0dc052b642503365f48475a611921989d34 | Python | 6,296 | 138 | #Copyright (C) 2021. Huawei Technologies Co., Ltd. All rights reserved.
#This program is free software;
#you can redistribute it and/or modify
#it under the terms of the MIT License.
#This program is distributed in the hope that it will be useful,
#but WITHOUT ANY WARRANTY; without even the implied warranty of
#MERCHA... |
5c42fe250f72d7f4569cd496754b3d2d990a90906e13ae5504f4ffa0543d5aae | Python | 6,297 | 154 | #!/usr/bin/env python
import pandas as pd
import numpy as np
import torch
import torch.utils.data
import pickle
import h5py as h5
import os
import argparse
import pyBigWig
'''
Script for preprocessing input epigenomic tracks (from .bigWig file)
and target Hi-C data (from diagonal.txt file).
Usage example:
python /t... |
6c5dcc9173fa03cb5ac0c922cb19a8bbe3da7963f02121d832575d12f6df18c3 | Python | 6,302 | 140 | # 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... |
7ec6c4aeca0daff8fc8912deb360381f301a086c9449f593919382de1af99c7b | Python | 6,302 | 177 | #!/usr/bin/env python3
import csv
from posixpath import split
import sys
import pandas as pd
from sys import argv
import argparse
from pickle import TRUE
import re
csv.field_size_limit(sys.maxsize)
parser = argparse.ArgumentParser(add_help=TRUE)
parser.add_argument("--blastout", help="output from submit_mito_blast2... |
4e0c5103ad0f0cb29392698cc57b6bc79fe3b3a455ab961d593e53b558612dff | Python | 6,305 | 154 | import numpy as np
import gym
from collections import OrderedDict
import logging
from mprl.rl.envs.stratego.stratego_multiagent_env import STRATEGO_ENV
from mprl.utility_services.cloud_storage import upload_file, maybe_download_object, get_default_path_on_disk_for_minio_key
from mprl.utils import datetime_str
import os... |
d932c5f7286bfb3899f4e3095155c49356172bf7893f56b63d3c008d576c146e | Python | 6,306 | 191 | #!/usr/bin/env python
# coding: utf-8
import os
import scipy.spatial
import atom3d.util.file as fi
import atom3d.util.formats as ft
import get_labels as lab
from rdkit import Chem
import Bio.PDB
from Bio.PDB.PDBIO import Select
from tqdm import tqdm
import argparse
def get_ligand(ligfile):
"""
Read liga... |
53bbb1e99b3a9336ca3cd85ec1f7c3a51d4d36210abad5006437241e2c9cf79e | Python | 6,307 | 191 | """
codes for generating synthetic datasets
"""
import numpy as np
from copy import deepcopy
from sklearn.preprocessing import PolynomialFeatures
def generate_W(d=6, prob=0.5, low=0.5, high=2.0):
"""
generate a random weighted adjaceecy matrix
:param d: number of nodes
:param prob: prob of existing an... |
cf60c3f016569c9343e622f321ece6549af428774bcf447dffa54998a0118b2a | Python | 6,307 | 146 | import os.path as osp
import os
import tqdm
import json
import numpy as np
import torch
import torch.nn.functional as F
from PIL import Image
from models.Network import FeatureNet
import torchvision.models as models
import pdb
import random
import cv2
src = './'
class ZoneClassifier(object):
def __init__(self, ar... |
d591654294c124de7fce809e60e2313ce34eb59315d2f02ecd4e17a20e8aaeaf | Python | 6,308 | 160 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import division
import six
import argparse
import torch
from onmt.utils.logging import init_logger, logger
from onmt.inputters.inputter import _old_style_vocab
def get_vocabs(dict_path):
fields = torch.load(dict_path)
vocs = []
for side in ['s... |
08c9c7b5a7beb75235df86129624110ea87f466f5b738214db46ec3d37535268 | Python | 6,310 | 234 | # 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
#
# ... |
230d22ae9cbef9763a473d96ec596f3cf33cf58348fb22930c1f92727a32f3d9 | Python | 6,311 | 140 | """
Evaluate models on synthetic data: classification and interpretability performance.
"""
import os, h5py
import numpy as np
from six.moves import cPickle
from tensorflow import keras
from gradient_correction import helper, explain, model_zoo, geomath
import tfomics
#------------------------------------------------... |
4142ab1df9cfeb638c16807b6afb222014bbddceb0b83ec8be178dd99068c2be | Python | 6,311 | 137 |
import logging
logger = logging.getLogger(__name__)
def create_reference_policy_update_callback_for_self_play_eval(trainable_policy_key: str, reference_policy_key: str,
new_policy_accept_score=None,
... |
9eb639e10e48292401e68c0cf2d182b0f574fe32ea58cc17124e766e6aeda3ea | Python | 6,313 | 193 | #Copyright (C) 2021. Huawei Technologies Co., Ltd. All rights reserved.
#This program is free software;
#you can redistribute it and/or modify
#it under the terms of the MIT License.
#This program is distributed in the hope that it will be useful,
#but WITHOUT ANY WARRANTY; without even the implied warranty of
#MERCHA... |
6343f58442fb2844b1020b7380baf89deec9719881c2b1cfba58f0f5425409fa | Python | 6,317 | 149 | # 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... |
d37eaae35ab83f35d4250ed0b91b59b5debc63aa8959d176aab78a5eb63516bd | Python | 6,317 | 178 | # 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
# Layer normalization's reference implementation
def _layer_normalization(X,... |
f338f1219eef944f5f05d6c2f93487ebc0b88fa166ad1ce7fbb14f5508e0ae5d | Python | 6,320 | 118 |
"""
This module parses the arguments given through the torch-model-archiver command-line.
"""
import argparse
import os
from .manifest_components.manifest import RuntimeType
# noinspection PyTypeChecker
class ArgParser(object):
"""
Argument parser for torch-model-archiver commands
"""
@staticmeth... |
69311e1d305740d98c01b2a36e471364ca080ac8d764ad4bb21c4e1e0c4c0289 | Python | 6,324 | 125 | import pytest
from e2e.util import check_duplicate
import siibra
from siibra.locations import Location, PointCloud
from siibra.livequeries.bigbrain import WagstylProfileLoader
from siibra.features.feature import CompoundFeature
import numpy as np
# We get all registered subclasses of Feature
@pytest.mark.parametriz... |
2c3f0ff47b4bbbb2e16092822e78b58afb63e2116f62ded896c078fae6373723 | Python | 6,326 | 206 | # 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... |
5bcd85c1063f1f8c57a03ee03669eb742eee53719876955cb4731f78038a53ea | Python | 6,330 | 184 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import pytest
from onnx import checker, inliner, parser
class TestInliner:
def test_basic(self):
model = parser.parse_model(
"""
<ir_version: 8, opset_import: [ "" ... |
a1ce498728b99b6b2fb519f3ee7836b5d422db1f83bab8dee4218c882b96c914 | Python | 6,330 | 171 | """CLI: bcb-lf-preprocess — normalise lesions and compute disconnectomes."""
import argparse
import sys
from pathlib import Path
_BIDS_SUFFIX = "*_label-lesion_mask.nii.gz"
_FLAT_SUFFIX = "*_lesion_mask.nii.gz"
def _build_parser():
p = argparse.ArgumentParser(
prog="bcb-lf-preprocess",
descripti... |
65baeb0ad020eb4f5cfca9ac159243511183e419916932237aadae3e42321099 | Python | 6,331 | 152 | import re
import pandas as pd
from config import Config
class Dataset(Config):
"""
Attributes
----------
ukbb_vars: list
Variable names based on user selections as coded in the Biobank.
recoded_vars: list
Variable names based on user selections as will be recoded.
... |
232391fc36a27e6791c6d97a1a0324a36d0e2c6d0b140e3d02e6d5d10e509a54 | Python | 6,333 | 209 | # 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... |
f6c3c6d2dd927eb651772c30dbc46d91b44d9a0e7ad5f3d8cfae5e1df73bf47d | Python | 6,333 | 174 | #!/usr/bin/env python3
from pathlib import Path
import rdflib
from pyontutils.core import Ont, OntGraph
from pyontutils.config import auth
from pyontutils.sheets import Sheet
from pyontutils.namespaces import owl, rdf, rdfs, ilxtr, NIFRID, OntCuries, skos, makeNamespaces
from neurondm import OntTerm, OntId
from neuron... |
621ff2a37253789ec8e4da4deabb82e4648a1e05087b9df4b2b189f2036b6c50 | Python | 6,335 | 190 | """
Build the list of matched transcript pairs to align.
Pairs come either from an explicit two-column table supplied by the user, or
are derived from reciprocal best BLAST hits between the two transcriptomes.
"""
from collections import Counter
import logging
import os
from typing import Optional
from ..exceptions ... |
43a2767121820433452bcb7878f8e69c53d82ccdc1ca77e67a822178a838171c | Python | 6,337 | 161 | from itertools import product
from scipy.spatial import Voronoi
import networkx as nx
import ase
import numpy as np
import json as js
# Atomic radii from Cordero
CORDERO = {'Ac': 2.15, 'Al': 1.21, 'Am': 1.80, 'Sb': 1.39, 'Ar': 1.06,
'As': 1.19, 'At': 1.50, 'Ba': 2.15, 'Be': 0.96, 'Bi': 1.48,
'B' ... |
8c83f418b35af0bcaf79cf80fd2a39323f40c659d6225d67ddd4b54eff9eb5e9 | Python | 6,341 | 209 | # Copyright (c) ONNX Project Contributors
#
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
import onnx
from onnx import helper
from onnx.backend.test.case.base import Base
from onnx.backend.test.case.node import expect
def dropout(X, drop_probability=0.5, seed=0, trainin... |
4bf317c7fb06fa973fcf1770a7f8c9e468abf46e0ef4d4d48b507a1886ac01f0 | Python | 6,346 | 159 | import os
import numpy as np
import torch
from torch.utils.data import Dataset
from torch_geometric.data import Data
from torch_geometric.loader import DataLoader as PyGDataLoader
from dataset.utils import anidataloader
ATOM_DICT = {('Br', -1): 0, ('Br', 0): 1, ('C', -1): 2, ('C', 0): 3, ('C', 1): 4, ('Ca', 2): 5, ('... |
b8396ded6925a06493cb88302920cbe5e5058ee3c6000b449b83557cf01d0d00 | Python | 6,348 | 182 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Nov 19 13:53:51 2018
@author: wanglab
"""
import os, numpy as np, sys, time, shutil
import collections
import tifffile
import torch
from torch import sigmoid
import dataprovider3 as dp
import forward
import utils
def main(noeval, **args):
#args... |
eb48cf4c03a29b39f1020cb92632057bdeeeb4d1d28631d9b0602529aa6ae9a4 | Python | 6,353 | 172 | # SAFE TEAM
#
#
# distributed under license: CC BY-NC-SA 4.0 (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.txt) #
#
from FunctionAnalyzerRadare import RadareFunctionAnalyzer
import json
import multiprocessing
from multiprocessing import Pool
from multiprocessing.dummy import Pool as ThreadPool
import os
... |
89a63c82d8927f03da37060ff189070b91330b8af2a9c6b1993edfbe5d2d121d | Python | 6,355 | 164 | # -*- coding: utf-8 -*-
#import os
#os.environ["CUDA_VISIBLE_DEVICES"]= "3"
#
# Description :
# Patching training data for DIAM-CNN
#
# Input :
# RDF : the tissue field
# QSM : the COSMOS susceptibility
# x : Serial number of subjects
# y : the orientation of each subject
# z : the number for dat... |
c20473d1bf41b3364c375bef354f0b19df3a5ce93e1f9f40725fbcab0de83c13 | Python | 6,355 | 151 | from __future__ import annotations
from typing import TYPE_CHECKING, Any
from .enums import Units
from .formatting import CONVERSION_FACTORS, FormattingOptions
if TYPE_CHECKING:
from .layer_info import LayerInfo
class ModelStatistics:
"""Class for storing results of the summary."""
def __init__(
... |
e7b95e98de1c66c046f15bed43bf7359ff174228372b2c9ccc9b6680150d9141 | Python | 6,355 | 201 | # Copyright 2024 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... |
7add9a36033dd83a3da85ec6bea6dd9fd4e3a0ed78b47f801559067bfa8d56e4 | Python | 6,356 | 175 | """
@file: sf_cz_game_generator.py
Created on 31.12.18
@project: CrazyAra
@author: queensgambit
Script to generate self played games by stockfish.
The script is basic wrapper for the cutechess-cli executable.
For transferability a fixed node count is used for every game for BLACK and WHITE.
The fixed node count is de... |
ee39b0da952436ce64508d36794fe85ca3c34754915f0cf84c3af53d779bc84c | Python | 6,356 | 190 | import os
from collections import defaultdict
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from allensdk.core.mouse_connectivity_cache import MouseConnectivityCache
from matplotlib import cm
from matplotlib.colors import Normalize
from matplotlib.ticker import FormatStrForma... |
8fd58402afd6efd251f9b78f7a20746bf1e9e2e43e405cfecff4a5f9663d3968 | Python | 6,357 | 131 | #=======================================================================================================================
#Copyright
#=======================================================================================================================
# Copyright (C) 2021 Matvey Safroshkin, Grigory Arutyunov, Patrick ... |
13658d9ecb2e30a2b41968534a41f6387597ed67492778979329684ee7caa71c | Python | 6,361 | 182 | import argparse
import re
import os
import pickle
import numpy as np
from tqdm import tqdm
from rdkit import Chem
from collections import Counter
import torch
import random
from typing import Optional
def seed_everything(seed: Optional[int] = 0) -> None:
torch.manual_seed(seed)
random.seed(seed)
os.enviro... |
3bd87de1ba6598628a74efa89f8e3de137c6ad776197aa64a95b09ee64a07272 | Python | 6,361 | 259 | #!/usr/bin/env python
__doc__ = """
Symmetric 3d U-Net implemented in PyTorch
(Optional)
Factorized 3D convolution
Extra residual connections
Nicholas Turner <nturner@cs.princeton.edu>, 2017
Based on an architecture by
Kisuk Lee <kisuklee@mit.edu>, 2017
"""
import torch
from torch import nn
from torch.nn import functi... |
7edc0306d5ea8f18fd04b96a2c299d2907baf9264f53fa31b33fc9ec0982dcb3 | Python | 6,361 | 174 | import os, time
import multiprocessing
import subprocess
from dataclasses import dataclass, field
from typing import List
@dataclass
class ANTSStage:
transform: str
transform_args: str
metrics: str
metrics_args: str
convergence: str
shrink_factors: str
smoothing_sigmas: str
@dataclass
clas... |
b748b1efda580a984c936c63a1efdaf1e69740315adbf7d8800c886553028b74 | Python | 6,361 | 212 | # 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... |
79a8dbf79e2ca7d773ba74446dcbcfcc7012f9975f45af97fd3c1a68886da731 | Python | 6,367 | 176 | """Catch22 Classifier.
Pipeline classifier using the Catch22 transformer and an estimator.
"""
__author__ = ["MatthewMiddlehurst", "RavenRudi", "fkiraly"]
__all__ = ["Catch22Classifier"]
from sklearn.ensemble import RandomForestClassifier
from sktime.base._base import _clone_estimator
from sktime.classification._de... |
b9173d76dec230cacabbea02e15ca0e51480d1c9ad784ca87d919d4b4e84f9df | Python | 6,367 | 220 | """Utility functions for unit vectors."""
import math
import numpy as np
import pyrr as pr
def fibonacci(num_points):
"""
Create an approximately uniform grid on the unit sphere.
Adapted from
http://matplotlib.1069221.n5.nabble.com/
Generating-N-regularly-spaced-points-on-a-sphere-td20763.html
... |
f2f4720919ca960b4a75d6ad1afcadcb938aefbe470fd4f2adbe9e0b0835e3a9 | Python | 6,368 | 159 | """ To quick test Elastic to make sure it's behaving normally
Usage:
elastic_search.py [-h | --help]
elastic_search.py [-v | --version]
elastic_search.py [--username=<path>] [--password=<path>]
Options:
-h, --help Display this help message
-v, --version Current version o... |
5955adfa1d66d8fbe3cf3cfbd329d501e8eaf680dc6f28dc2686b9008577ac97 | Python | 6,369 | 208 | # SPDX-License-Identifier: LGPL-3.0-or-later
import copy
import unittest
import numpy as np
import paddle
from deepmd.pd.model.model import (
get_model,
)
from deepmd.pd.utils import (
env,
)
from deepmd.pd.utils.utils import (
to_numpy_array,
)
from ...seed import (
GLOBAL_SEED,
)
dtype = paddle.fl... |
c8d180457e32fc8939065e2275dec669a74150a457f5e866ecfa14af402d81b2 | Python | 6,369 | 170 | import sciunit
import seaborn as sns
from uuid import uuid4
from networkunit.plots.sample_histogram import sample_histogram
from networkunit.utils import use_cache
from elephant.parallel import SingleProcess
sns.set_palette('colorblind')
class two_sample_test(sciunit.Test):
"""
Parent class for specific two s... |
8f9d425eb6dbf7fee95a5eb8147a20d3045a490273a5667afac9957bbc2805e2 | Python | 6,370 | 205 | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from torch.nn.modules import GroupNorm
from torch.nn.modules.batchnorm import _BatchNorm
from mmcls.models.backbones import ShuffleNetV2
from mmcls.models.backbones.shufflenet_v2 import InvertedResidual
def is_block(modules):
"""Check if ... |
1e393709f4f3e630e2d7ff48bb414c6d117818f05a1506678910d35a24fe01a6 | Python | 6,372 | 155 | import tensorflow as tf
import numpy as np
import keras
from keras.optimizers import *
# my scripts
# General scripts
from scripts import models_util
import os
# Transfer learning scripts
from scripts_tl import configurations_tl as cfg_tl
from scripts_tl import preprocess_tl
from scripts_tl import data... |
93ea0b06b54a497f52cfe76d9ab9712a5e6d1fc19ee0fec3a5e9520133446559 | Python | 6,373 | 236 | # 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
#
# ... |
a2a29cb47569e6dcd5ce46bba3efa98c114823e9f52d8b6fed625b8b4f71c917 | Python | 6,374 | 135 | # SAFE TEAM
#
#
# distributed under license: CC BY-NC-SA 4.0 (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.txt) #
#
import argparse
import time
import os
import logging
def getLogger(logfile):
logger = logging.getLogger(__name__)
hdlr = logging.FileHandler(logfile)
formatter = logging.Forma... |
62e1dd937b748f02990fc3f1943682012666198cd3b29b5784266f66787743bb | Python | 6,375 | 136 | import pandas as pd
import os
import re
import numpy as np
from livingTree import SuperTree
from functools import reduce
class Proportions:
def __init__(self, read_from: str):
path = read_from
path_dir = os.listdir(read_from)
path_dir = [i for i in path_dir if re.match('.*csv', i)]
... |
3fc49d69c0b44fa0e5ce7b43cc519933705ee45334d8189456ccf54f2c616e12 | Python | 6,378 | 184 | #%% [markdown]
# # Simulation
#%%
import datetime
import time
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from graspologic.simulations import er_corr
from pkg.io import FIG_PATH, OUT_PATH
from pkg.io import glue as default_glue
from pkg.io import savefig
from pkg.match... |
7e3a66fb0cc21ae89927198acb9485e2a95bb9560cb94a4a8e81eed411334d4b | Python | 6,378 | 161 | import os
import numpy as np
import torch
from torch.utils.data import Dataset
from torch_geometric.data import Data
from torch_geometric.loader import DataLoader as PyGDataLoader
from rdkit import Chem
ATOM_DICT = {1: 'H', 6: 'C', 7: 'N', 8: 'O'}
PAIR_DICT = {('Br', -1): 0, ('Br', 0): 1, ('C', -1): 2, ('C', 0): 3, ('... |
f8e22c69323b8fadea4a18c3150645cbb125c17040937bc44dc18f37ff28a622 | Python | 6,378 | 197 | import os
import os.path as osp
import time
import dill
import numpy as np
import pandas as pd
import torch
from sklearn.model_selection import train_test_split
from torch.optim.lr_scheduler import ReduceLROnPlateau
from torch_geometric.data import DataLoader
from molucn.dataset.pair import get_num_features
from molu... |
617cb37fc8c13c0cb8f317f8e638b602ee4dc2a4bae596c14d4f72cefaaa55ce | Python | 6,381 | 142 | # 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... |
ab7e8ddd0412e40ee78eed711a36b0320d47184c2cdfa8aede387c728bfc311a | Python | 6,381 | 135 | """ Tests the validity of scicrunch_client and not the data outputed itselfself.
Output tests not needed bc data is collected and replaced instead of built.
Only known bug is tid->superclass_tid change & is corrected in dictlib.
Crawl option is tested in test_addTerms function.
Usage: scicrunch_client_tes... |
8e8f21564b8c27e8f7fadd1d3fa71f8180bf96306fdda658b9045d408edf4bae | Python | 6,388 | 208 | from typing import Any
import numpy as np
import pytorch_lightning as pl
import torch
from sklearn.metrics import balanced_accuracy_score
from torch import nn
from .arch import create_model, ARModel
def step(model, loss_module, batch, use_mixup: bool):
"""Forward pass for non-recursive model"""
x, y = batch... |
b7f1e9ba888abe96c148a89e494b855609bc79eed444ecc0824fe174b3ddedfd | Python | 6,389 | 208 | import pandas as pd
import numpy as np
from functools import reduce
from livingTree import SuperTree
import os
from tqdm import tqdm
from collections import OrderedDict
from pandas.io.json._normalize import nested_to_record
def get_dmax(path):
with pd.HDFStore(path) as hdf:
dmax = len(hdf.keys())
#h... |
2edd1f307eb219d64e728f7e5c97808c03c97a3db226cfdfddd80d6ad60ddecb | Python | 6,396 | 156 | # SPDX-License-Identifier: LGPL-3.0-or-later
"""Sampling probabilities shared by data formats and training backends."""
from collections.abc import (
Sequence,
)
import numpy as np
from deepmd.utils import random as dp_random
def process_sys_probs(
sys_probs: Sequence[float], nbatch: Sequence[int] | np.nda... |
3b92c9dcf38f46d058ade309568b3cd7b1f170441829f7861219cc2042e17bea | Python | 6,397 | 151 | # 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... |
fac69d04e21590f6a00028aa1fc481ba6ca4080b30e90f1c1b6432f199729abb | Python | 6,398 | 171 | # 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... |
80a206eb8bce19ab415fd68f4171d5059cd960d6305d2f9d9f92561f798810eb | Python | 6,401 | 171 | import numpy as np
from sklearn.linear_model import LinearRegression
from scipy.linalg import expm as matrix_exponential
from scipy.spatial.distance import pdist, squareform
from sklearn.gaussian_process import GaussianProcessRegressor as GPR
from sklearn.preprocessing import PolynomialFeatures
import logging
class g... |
c3b564d92e01472697df6b44b76432976995d887c8cd2e5b49b1531bc8cfbb7e | Python | 6,402 | 200 | # @requirements:
# pip3 install --upgrade pip
# pip3 install pyedflib
# pip3 install -U wxPython
# @description
# Tool for (1) identifying all unique .edf channel names in a specified directory and
# (2) creating categories to group like channels for processing in a pipeline.
# Creates json file for with fields named b... |
f8143456417a83df9ceca2c994c43efd555583615abaf2bc1681e70c2c2fe292 | Python | 6,402 | 278 | # -*- coding: utf-8 -*-
"""
Created on Wed Oct 26 13:51:51 2022
@author: M. Agustina Frechou
"""
'''
Bootstrapping code and preprocessing to analyze tuning data
'''
import os
import glob
import scipy.io
import numpy as np
import random
from random import choices
import csv
#%%
'''
Functions
'''
def get_fi(fil... |
85120f2c63ded2761f28ae6344cbfe8838ac2e686e6636c97a097677d0499f26 | Python | 6,404 | 200 | import os
import os.path
from neuron import h
import numpy as np
import scipy
import scipy.integrate
import scipy.stats
from .protocol import Protocol
try:
import pyqtgraph as pg
HAVE_PG = True
except ImportError:
HAVE_PG = False
from ..util import custom_init
from ..util.stim import make_pulse
#import ... |
b00115943a8b381c2650d40833854527ebf9f2e12a20cc1114e117bb30a2ca3d | Python | 6,405 | 178 | #!/usr/bin/env python3
from pathlib import Path
import rdflib
from pyontutils.core import Ont, OntGraph
from pyontutils.config import auth
from pyontutils.sheets import Sheet
from pyontutils.namespaces import owl, rdf, rdfs, ilxtr, NIFRID, OntCuries, skos, makeNamespaces
from neurondm import OntTerm, OntId
from neuron... |
5964b64818f2f4a7a8635f5ba1759a8cb7375e4d1c99914f16c9f3a3c34e40c3 | Python | 6,406 | 152 | # Definition of
# 3D UNet
# Author: Zhe Liu (zl376@cornell.edu)
# Modified by: Jinwei Zhang (jz853@cornell.edu)
# Date: 2018-08-27
from keras import backend as K
from keras.layers import Activation
from keras.layers import Input
from keras.layers import BatchNormalization
from keras.layers import MaxPooling3D
from k... |
23ac917e2ecbd5fcd9fe0d6dca2dfacfbe4f051ff9c31c036910ecd574232b0f | Python | 6,408 | 190 | # This is meant to be run in Jupyter or IPython in combination with whole.py
# It assumes an X and y and various models
import shap
#background = shap.maskers.Independent(test_features,max_samples=100)
#explainer = shap.Explainer(rf,background)
language_map = {'LowpH': 'Lowest pH',
'HighpH': 'Highest pH',
'H... |
bc585ca0fa251e9b73c63b66d7742d8d98d0c2775c1369b3264014eb3b3b7381 | Python | 6,412 | 187 | """
========
numpydoc
========
Sphinx extension that handles docstrings in the Numpy standard format. [1]
It will:
- Convert Parameters etc. sections to field lists.
- Convert See Also section to a See also entry.
- Renumber references.
- Extract the signature from the docstring, if it can't be determined otherwise.... |
49d6859647c4ec9cf6dd6104c4d4a2c8460fc78c388566a3df76a919259654af | Python | 6,413 | 196 | # SPDX-License-Identifier: LGPL-3.0-or-later
"""Shared training-data helpers for backend entrypoints."""
from __future__ import (
annotations,
)
import inspect
from dataclasses import (
dataclass,
)
from typing import (
TYPE_CHECKING,
Any,
)
from deepmd.utils.data import (
DataRequirementItem,
... |
c04722fe048ed6606fdf196c252417cda7c64e9cb2a73d2703c60b0ddb76006b | Python | 6,415 | 190 | # 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... |
409fd6090c72cd52f649395f5376eedccccde52d8bc3fca2b083039c182e6c16 | Python | 6,416 | 185 | # Copyright (c) OpenMMLab. All rights reserved.
import codecs
import os
import os.path as osp
import numpy as np
import torch
import torch.distributed as dist
from mmcv.runner import get_dist_info, master_only
from .base_dataset import BaseDataset
from .builder import DATASETS
from .utils import download_and_extract_... |
d34ec10d74d57e4d652fe985ea2a737e399a652b26df5c1f3f9fdc137ec99574 | Python | 6,416 | 184 | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
sns.set()
import json
from cplAE_TE.utils.load_helpers import get_paths
def get_spc_names_v2():
"""Parse sparse pc names from .json generated by Nathan, for revised dataset in Gouwens et al. 2020.
Returns:
... |
5875bfdaabdeb257c4120c90b2b4093281ccf7093df64a3ba6ddda949490bd61 | Python | 6,419 | 170 | """Tests for feature importances in time series forests."""
import numpy as np
import pytest
from sklearn.base import clone
from sklearn.pipeline import FeatureUnion, Pipeline
from sklearn.preprocessing import FunctionTransformer
from sklearn.tree import DecisionTreeClassifier
from sktime.classification.ensemble._cts... |
a537e48952aa7c1583819163342b8c224a1ca9f57817e2b5215c8fca941d9952 | Python | 6,423 | 173 | #!/usr/bin/env python3
"""Find dead ids in an ontology and raise them to be owl:Classes again.
Also build a list of classes that may be banished to the shadow realm
of oboInOwl:hasAlternativeId in the near future.
Usage:
necromancy [options] <file-or-url>...
Options:
-h --help print this
-v --verbos... |
eb3641636afd05fba0b4b732cdebccbc037155bb6fca329704f47bbae4372154 | Python | 6,424 | 203 | # -*-coding:utf-8-*-
# from __future__ import absolute_import
import torch.nn as nn
import torch.nn.functional as F
import math
def conv1x1 (in_planes, out_planes, stride=1):
return nn.Conv1d(in_planes, out_planes, kernel_size=1, stride=stride, bias=False)
def conv1x3 (in_planes, out_planes, stride=1):
re... |
73911839d9190cb7da2e3f54802f101f64a398e92d82fc7f0028b30316358a28 | Python | 6,425 | 154 | """ Processing Tools for all datasets. """
import os,json,pdb,argparse
import os.path as osp
import numpy as np
from PIL import Image
import torch
def CommonLoad(args, dataset, label_id_dict):
data,label = [],[]
THE_PATH = osp.join(args.dataset_dir, dataset)
this_folder = osp.join(THE_PATH, 'membranes')
... |
87032407bfce04efa689d1a1b707bd5c5b1ea478b7c8ad372b94d49706e1a3e0 | Python | 6,426 | 274 | # SPDX-License-Identifier: LGPL-3.0-or-later
import glob
import json
import os
import platform
import shutil
import warnings
from hashlib import (
sha1,
)
from pathlib import (
Path,
)
from typing import (
TYPE_CHECKING,
Any,
TypeVar,
get_args,
)
try:
from typing import Literal # python >=... |
77a6e43a8a5ffbf57d2c2f41399b8b2fcfd8616c53bb281a597982b23953f2b7 | Python | 6,427 | 160 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Jun 28 14:39:11 2020
@author: user
"""
from functional.plot_functions_CLEANED import *
import matplotlib.pyplot as plt
""" Tracker class """
class tracker():
def __init__(self, batch_size, test_size, mean_arr, std_arr, idx_train, idx_valid, d... |
9c79fa254eb251751ec66130eb1c75b43e6a1490c22369820e51c1c140dee1e1 | Python | 6,428 | 186 | # 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... |
6488cbf454018e43c302bdb89a387209f2af7d5efaa5751ab05cf893476bb213 | Python | 6,436 | 195 | # 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... |
7524e420142a71d0bf4a32486f067ccb27a12542c4ac2aa7093c6418e84052a1 | Python | 6,437 | 175 | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from torch.nn.modules import GroupNorm
from torch.nn.modules.batchnorm import _BatchNorm
from mmcls.models.backbones import MobileNetV3
from mmcls.models.utils import InvertedResidual
def is_norm(modules):
"""Check if is one of the norms.... |
c8f3b910193195a2a9a19ac21c6056dbcf9857ea54d9d5ac4d29d37d0052fd06 | Python | 6,437 | 268 | #!/usr/bin/env python
__doc__ = """
Symmetric 3d U-Net implemented in PyTorch
(Optional)
Factorized 3D convolution
Extra residual connections
Nicholas Turner <nturner@cs.princeton.edu>, 2017
Based on an architecture by
Kisuk Lee <kisuklee@mit.edu>, 2017
"""
import torch
from torch import nn
from torch.nn import fun... |
f8a978f6039f4eccde2ce10589d6100f7decebeddbd8650ea720a4870aed12cf | Python | 6,439 | 210 | import torch
from torch import nn
from lgn.cg_lib import CGDict
class CGModule(nn.Module):
"""
Clebsch-Gordan module. This functions identically to a normal PyTorch
nn.Module, except for it adds the ability to specify a
Clebsch-Gordan dictionary, and has additional tracking behavior set up
to all... |
13f205789f82921740463f3f9bfc2413d458864e319ccb88160b1605c6b7fae5 | Python | 6,440 | 211 | import torch
from torch import nn
from lgn.cg_lib import CGDict
class CGModule(nn.Module):
"""
Clebsch-Gordan module. This functions identically to a normal PyTorch
nn.Module, except for it adds the ability to specify a
Clebsch-Gordan dictionary, and has additional tracking behavior set up
to all... |
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