sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
55807c7017081daae82df288720af6caa7e31f7b524c449ad8223dd4b2402038 | Python | 9,563 | 265 | """Machine type checkers for Proba scitype.
Exports checkers for Proba scitype:
check_dict: dict indexed by pairs of str
1st element = mtype - str
2nd element = scitype - str
elements are checker/validation functions for mtype
Function signature of all elements
check_dict[(mtype, scitype)]
Parameters
----------... |
a55ac3d2945d8326e5b489a281311dd097f3cabe74f00bcdb780b6c3ef647207 | Python | 9,564 | 259 | from __future__ import division
from __future__ import print_function
import warnings
warnings.filterwarnings("ignore")
import time
import argparse
import pdb
import pickle
import os
import shutil
import glob
import pandas as pd
import itertools
import numpy as np
import matplotlib.pyplot as plt
from tools import vide... |
12f731f050be6c19d0cc726d2b788ba3d4431235ceb5197dcbf83270940bd7a8 | Python | 9,566 | 286 | import torch
from lgn.g_lib import rotations as rot
import warnings
from lgn.g_lib import g_tau, g_tensor
from lgn.g_lib import g_vec, g_scalar, g_weight, g_wigner_d
from lgn.g_lib.cplx_lib import mul_zscalar_zirrep, mul_zscalar_zscalar
from lgn.g_lib.cplx_lib import mix_zweight_zvec, mix_zweight_zscalar
GTau = g_tau... |
cd7d1deeeccb3b5b2e26a66d5e12b0a11ba9396f21770e97f4f464d2270c0caf | Python | 9,568 | 233 | # Copyright (C) 2022-2025 Shijiazhuang Xianyu Digital Biotechnology Co., Ltd
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published
# by the Free Software Foundation, either version 3 of the License, or
# (at your option) any la... |
331786394f00da97df686f1ae745d637d47ffe8e741750b0bf35de484fcf60e9 | Python | 9,575 | 252 | # This is a BrainVISA process, to use it you have to install it as a “personal”
# BrainVISA process:
#
# mkdir -p ~/.brainvisa/processes
# cp SegmentationOfCorpusCallosum.py ~/.brainvisa/processes/SegmentationOfCorpusCallosum.py
#
# After this is done, it will become available in the brainvisa user interface
# ... |
188a4e7361d1fb36d6aea14944a03762d6b4b07832a2c23c223370319acc13c9 | Python | 9,576 | 261 | from typing import List
import numpy as np
import torch
from torch.autograd import Variable
from torch.nn import Linear as Lin
from torch.nn import ModuleList, ReLU
from torch.nn import Sequential as Seq
from torch_geometric.nn import (
BatchNorm,
GATConv,
GENConv,
GINEConv,
NNConv,
global_add_... |
e25a78d11c14074f26637ba75dd2d9aa2d6f69ef7122b5ed6990d96cfcb5fd44 | Python | 9,578 | 286 | from __future__ import annotations
from concurrent.futures import FIRST_COMPLETED
from concurrent.futures import ThreadPoolExecutor
from concurrent.futures import wait
import copy
import datetime
import gc
import itertools
import os
import sys
from typing import TYPE_CHECKING
import warnings
import optuna
from optuna... |
7ac8d3a14c5db6af2275a44d4a5348c3bcb34ce122ea16f201309d3e17b714bf | Python | 9,580 | 310 | import os
from shutil import copyfile
from pathlib import Path
import numpy as np
import pytest
from asreview.models.classifiers import list_classifiers
from asreview.state import open_state
from asreview.review.factory import get_reviewer
ADVANCED_DEPS = {"tensorflow": False}
try:
import tensorflow # noqa
... |
f3232b378fd2114e9587c95bd3fce534f18efe5a2ec5d60e682c61b3b60fa8df | Python | 9,585 | 271 | # 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... |
3daa4dc48ad363fdc8669b415958d68f006f5b04043a2dcb8d8d938292bd6b44 | Python | 9,587 | 326 | # Copyright (c) ONNX Project Contributors
#
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
from typing import Any
import numpy as np
import onnx
from onnx.backend.test.case.base import Base
from onnx.backend.test.case.node import expect
class RNNHelper:
def __init__(self, **params: An... |
69624cd4206a2c675e8983337d725c8de18862cff17b610c2034bf87b5f6ede1 | Python | 9,588 | 264 | # Copyright (c) OpenMMLab. All rights reserved.
import torch.nn as nn
import torch.utils.checkpoint as cp
from mmcv.cnn import ConvModule
from mmcv.runner import BaseModule
from torch.nn.modules.batchnorm import _BatchNorm
from mmcls.models.utils import make_divisible
from ..builder import BACKBONES
from .base_backbon... |
3c6becd635c82ec86835ab8ce921b56958a289bd7c63847382ae2eb0db7a48d2 | Python | 9,591 | 290 | #!/usr/bin/env python
import click
from click_option_group import optgroup, RequiredMutuallyExclusiveOptionGroup
import copy
import json
import numpy as np
import os
import pandas as pd
import pickle
import shutil
import sys
sys.path.insert(0, os.path.join(os.path.abspath(os.path.dir... |
81638f4ace0b754b3e1299c1863690f1074e10c9570154e2cafa96603a810bf9 | Python | 9,592 | 250 | import torch
from torch import nn
torch.cuda.empty_cache()
import datasets
import transformers
from transformers import activations
import pandas as pd
import numpy as np
from transformers import DistilBertTokenizer, \
DistilBertForSequenceClassification, DistilBertModel, DistilBertPreTrainedModel, Trainer, TrainingArg... |
e700ce5c149d96fd658510494c1c4f73b0f97e7348395aad3c74d1a8c419fefc | Python | 9,593 | 223 | # 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... |
e73c5735b381766c7a0ab8467a64730fe80496ad30a63bdfcea2c4d953151045 | Python | 9,598 | 282 | """Windowed local outlier factor."""
__author__ = ["Alex-JG3"]
import datetime
import numpy as np
import pandas as pd
from sklearn.neighbors import LocalOutlierFactor
from sktime.detection.base import BaseDetector
class SubLOF(BaseDetector):
"""Timeseries version of local outlier factor.
The LOF models a... |
3d7556ae2e5e8b80f790fc7c22c95c6638b105e838410f1d3270b16d96b679a2 | Python | 9,604 | 248 | # 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... |
f933b496515f3e29bfb0cd857c8c00ceaf4ee843c2ce2b53ee297a4085cf4429 | Python | 9,605 | 236 | """Functions to cluster structures.
functions:
get_rmsd: Computes the rmsd matrix of the conformers in a list of rdkit mol
objects.
get_labels_affty: Clusters data in affinity matrix form by assigning labels to
data points.
get_labels_vector: Clusters data in vectorial form by assigning labels to
data poin... |
15602859257280ffaa3b839dc8308ec2b0e3e37faeda451fe01c8f1ad6dce23b | Python | 9,610 | 173 | from socket import socket, AF_INET, SOCK_STREAM
import struct
import numpy as np
from datetime import datetime, timedelta
from collections import defaultdict
from functools import reduce
from fileManagement import selectClassifierID
from classifierClient import ClassifierClient
from sampler import up_or_down_sa... |
ca9031091b3196ca5f9989bb180f74ff037409863152f4c7d2564fb4817c8cf1 | Python | 9,611 | 307 | 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... |
d941912a07d39fbfa0008f77b16b8a493a16a490a46bd1d48de669e6a7aabf17 | Python | 9,611 | 293 | # 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 agreed to in writing, software
# distributed under t... |
3f6a20207fc3c57b7a5a29144da97c1106d9e9ab7a4dcf6e69d416fcde14fc37 | Python | 9,612 | 242 | """Time series kmeans."""
__author__ = ["chrisholder", "TonyBagnall"]
from collections.abc import Callable
import numpy as np
from numpy.random import RandomState
from sktime.clustering.metrics.averaging import _resolve_average_callable
from sktime.clustering.partitioning import BaseTimeSeriesLloyds
from sktime.dist... |
def3ff873109673d8c23eecc703337f91fa4812589a529a7d0c1d4c02541d582 | Python | 9,612 | 258 | """
precision.py
This routine generates the simulated precision data which is designed
to mimic our behavioural experiment (testing the precision of two
cues against one).
"""
import json
import numpy as np
import dict_key_definitions as keydefs
from extended_ring_model import *
from dict_key_definitions import rmke... |
d2e448d23596b6442217d58be427dbc3b71408c254b01056b498aae63ee40302 | Python | 9,614 | 295 | # -*- coding: utf-8 -*-
#
# seaborn documentation build configuration file, created by
# sphinx-quickstart on Mon Jul 29 23:25:46 2013.
#
# This file is execfile()d with the current directory set to its containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
# All... |
ec9600f2884d112257743c11bf388be2b09df197849ff05e2adfe737bb76e271 | Python | 9,617 | 352 | #%% [markdown]
# # Connectome data
#%%
import datetime
import time
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from pkg.data import load_split_connectome
from pkg.io import OUT_PATH
from pkg.io import glue as default_glue
from pkg.io import sav... |
a0d4b59fc58479f5e6988c42783a5185a73870d58207b3e50d52cf070ef195f0 | Python | 9,619 | 250 | __author__ = ["chrisholder", "TonyBagnall"]
from collections.abc import Callable
from typing import Any
import numpy as np
from sktime.dists_kernels._numba_distances.base import (
DistanceAlignmentPathCallable,
DistanceCallable,
NumbaDistance,
)
DerivativeCallable = Callable[[np.ndarray], np.ndarray]
... |
a5dcecf07222b61deacf51d74ceed013a92f62c0542d0f0ee298b7a78f17bb79 | Python | 9,622 | 290 | # 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... |
4ba01def50b4ea08df32b4293ed8f203e70092bc1f379f2b79f56a78140ea040 | Python | 9,623 | 215 | import itertools
import math
import numpy as np
import pandas as pd
import scipy.stats
from sklearn.linear_model import LinearRegression
from figures.figure1 import find_leaves
from figures.util import produce_figure, main_regions, get_subplots, plot_grid, \
plot_annotations, plot_scatter
CORRELATION_THRESHOLD =... |
0c5ef18872c30077befe651b8c1586a5fbbb671fcd917c0824d5f7abea9e6544 | Python | 9,624 | 279 | from copy import deepcopy
from itertools import compress
import colorednoise as cn
from mne.time_frequency import tfr_array_morlet
import numpy as np
import pytorch_lightning as pl
from sklearn.preprocessing import QuantileTransformer, StandardScaler
import torch
from torch.utils import data
from .feature_extraction ... |
310b579690f309235399f72d2ca5019571f7a3175ec2e08e3bd0675117173775 | Python | 9,636 | 278 | """Multi Channel Deep Convolutional Neural Classifier (MCDCNN)."""
from copy import deepcopy
import numpy as np
from sklearn.utils import check_random_state
from sktime.classification.deep_learning.base import BaseDeepClassifier
from sktime.networks.mcdcnn import MCDCNNNetwork
class MCDCNNClassifier(BaseDeepClassi... |
23d2c3e63d7bdeec6b3ea9d8cf128e46b366696ae41897a724f10eb606b58e4d | Python | 9,637 | 279 | # 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... |
aeca90ad39031f353bffbbb4bbaf39bb1cf4b0be8e265340788490708c4ce542 | Python | 9,638 | 330 | """Atlas loading: format detection and region weight extraction."""
import re
import xml.etree.ElementTree as ET
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional
import numpy as np
import nibabel as nib
from bcblib.imaging.io import is_nifti
@dataclass
class AtlasSpec:
... |
9e44082de7cbdedcd5871d4822f692a1472e4489ea8c530b332ce235b8040c8d | Python | 9,653 | 239 | # 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... |
94bb789f126fcd2efad946eb63128b32ad397782393d6d2ea9834efb29da21fe | Python | 9,658 | 251 | """Test suite for numba distances."""
__author__ = ["chrisholder"]
from collections.abc import Callable
import numpy as np
import pytest
from numpy.testing import assert_almost_equal
from skbase.utils.dependencies import _check_soft_dependencies
from sktime.dists_kernels._numba_distances._distance import (
_MET... |
e3aa30660d8602720f074c4634a4c69512fecdfcb56007331a42abf1be9fc76e | Python | 9,668 | 275 | # Pytorch Geometric class - Aggregation operator for GNNs
# SOURCE CODE FOR TORCH_GEOMETRIC.NN.AGGR.BASE
from typing import Optional, Tuple
import torch
from torch import Tensor
from torch_geometric.nn.inits import reset
from torch_geometric.utils import softmax, to_dense_batch
from torch_scatter import scatter, segm... |
85d6e516da3770a30d5950b05bb095b47115413fb7ede33323fdfce4e2d2f805 | Python | 9,669 | 282 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import dataclasses
import numpy as np
from onnx.reference.op_run import OpRun
@dataclasses.dataclass
class PrepareContext:
boxes_data_: np.ndarray | None = None
boxes_size_: int = 0
score... |
cf73fd04680d3e880985f3c8bf1d881d2bbca1e29623a8235f0f0e69e7d97d10 | Python | 9,672 | 274 | """Multi Layer Perceptron Network (MLP) for classification."""
__all__ = ["MLPClassifier"]
from copy import deepcopy
from sklearn.utils import check_random_state
from sktime.classification.deep_learning.base import BaseDeepClassifier
from sktime.networks.mlp import MLPNetwork
class MLPClassifier(BaseDeepClassifie... |
bec06c40016f48e51b21bb693b4bfca5c5487ce2cae96babce4506a34ba472c2 | Python | 9,678 | 321 | # 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... |
89d718208e007077cc76b2ea684165f0daabb46a3bccc1f4a7b0a7a6a68df16f | Python | 9,679 | 232 | import csv
import os
import math
import yaml
import logging
import datetime
from shutil import copyfile
import torch
import wandb
from src.utils.ensure_dir import ensure_dir
from src.utils.visualization import WriterTensorboardX
class BaseTrainer:
"""
Base class for all trainers
"""
def __init__(se... |
d8866c55cd934f8b625e45d9241ce5c4e67559e5f4f764f865b0bde78f26109c | Python | 9,681 | 251 | """
This plots figure 6h of the paper.
This is the psychometric fit of the behaviour output of the trained model after inactivating MOs neurons
Internal notes:
This is from notebook 21.21c-simulate-inactivation-MOs-hemisphere-unilateral-model
Note that it currently requires xarray == 0.16.2
TODO: there are some pickl... |
d652857a277af62ffca0876cde6a20fdb5cf53759f93849a54dfd21d8a125411 | Python | 9,698 | 217 | # Copyright 2019 Martin Haesemeyer. All rights reserved.
#
# Licensed under the MIT license
"""
Module to parse experimental file structure extracting relevant acquisition information
"""
from datetime import datetime
from os import path, listdir
from typing import Any, Dict, List, Tuple, Optional
class LineParse... |
de5e5624c063626544604f788ce11f784e1b7fc814cbfe196fbdbbf40595892d | Python | 9,699 | 233 | import os
import h5py
import nibabel as nb
import numpy as np
import torch
import torch.utils.data as data
from torchvision import transforms
import utils.preprocessor as preprocessor
# transform_train = transforms.Compose([
# transforms.RandomCrop(200, padding=56),
# transforms.ToTensor(),
# ])
class Imdb... |
5715bd5f61d2a89e090228f9122c40ddc6b354532ab7f80798f09fd81f6b97b7 | Python | 9,700 | 284 | #!/usr/bin/env python
#
# Copyright 2007 Neal Norwitz
# Portions Copyright 2007 Google Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0... |
369396bcc816ba044c7b633bbbcccb2d20b6ddb69e7d01f5685f61f433ba425a | Python | 9,701 | 230 | """
Module for all network models with tensorflow dependency
"""
import numpy as np
import tensorflow as tf
import tensorflow.keras as keras
from tensorflow.keras import layers, regularizers, initializers
from typing import Optional, Union, Tuple
from sklearn.linear_model import LinearRegression
class NotInitialized(... |
749b9f8e5c4cde5d4e8ab7b0718e6df113c31e863681537fb5c0580cd4c3e995 | Python | 9,704 | 227 | # -*- coding: utf-8 -*-
import unittest
from onmt.inputters.audio_dataset import AudioSeqField, AudioDataReader
import itertools
import os
import shutil
import torch
import torchaudio
from onmt.tests.utils_for_tests import product_dict
class TestAudioField(unittest.TestCase):
INIT_CASES = list(product_dict(
... |
41f814b559478c1094baadf80b577b782ef6614d84dbce01eb9ffd7b6294a0a8 | Python | 9,709 | 255 | import logging
import typing
from pathlib import Path
from typing import Any, Optional, Union
import torch
from torch import nn
from torch.utils.data.dataset import Dataset
from tqdm import tqdm
import flair
import flair.embeddings
from flair.data import Corpus, Dictionary, Sentence, _iter_dataset
from flair.datasets... |
7e7ca2224ee1c1b21e4b6487256da5d98805c1643ab98f8ed5ca4d0188e2e29d | Python | 9,713 | 283 | '''
Functions for visualising abnormalities and D_RS in continuous iEEG data.
Gabrielle M. Schroeder
CNNP Lab, Newcastle University
May 2023
'''
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib import cm
from mpl_toolkits.axes_grid1.inset_locator import inset_axes
import sklear... |
74a41eee2bb943fd5728cf790bcdc07baef9ae59ef777bde0ce7a8a7b548bb74 | Python | 9,729 | 244 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import logging
from types import FunctionType
from ray.rllib.utils.annotations import DeveloperAPI
from ray.rllib.evaluation.rollout_worker import _validate_multiagent_config
from mprl.rl.common.shared_pol_ro... |
a9ea90ffb25b5afebb3ce3a4c342b5d3697b59afe358359944f93145db10ef75 | Python | 9,732 | 251 | __author__ = ["chrisholder", "TonyBagnall"]
from typing import Any
import numpy as np
from sktime.dists_kernels._numba_distances.base import (
DistanceAlignmentPathCallable,
DistanceCallable,
NumbaDistance,
)
class _WddtwDistance(NumbaDistance):
"""Weighted derivative dynamic time warping (wddtw) d... |
39b96d6e2679d1561c43b58ee7e36341fd0888f0db5435cf54b69d4a1d4ef083 | Python | 9,738 | 307 | # -*- coding: utf-8 -*-
#
# wordsegment documentation build configuration file, created by
# sphinx-quickstart on Tue Aug 11 10:46:02 2015.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#... |
11c61cc4f598ffae6a1094cc82ec826ccb57eb37e17bcbcc6a653efe70bba6c8 | Python | 9,741 | 297 | """
resnet for 1-d signal data, pytorch version
Reference https://github.com/hsd1503/resnet1d/blob/master/resnet1d.py
"""
import numpy as np
from collections import Counter
from tqdm import tqdm
from matplotlib import pyplot as plt
from sklearn.metrics import classification_report
import torch
import torch.nn as n... |
30598f4cf3b1ffb039ffe4accae206f21b09307ade0b6e5e9166355e1e9f327f | Python | 9,742 | 308 | # SPDX-License-Identifier: LGPL-3.0-or-later
"""DeePMD training entrypoint script.
Can handle local training.
"""
import logging
import time
from typing import (
Any,
)
from deepmd.dpmodel.train import (
AbstractTrainEntrypoint,
TrainEntrypointOptions,
TrainingTaskConfig,
iter_training_task_confi... |
03505a42681268a8cca853f3fcae553bde6c0eecd459d070bfdd627b17b5bc8c | Python | 9,745 | 236 | from typing import Callable, List, Set, Union, Optional, Tuple
import numpy as np
import logging
from .dataset import JetDataset
from .utils import (
checkConvertElements,
checkDownloadZenodoDataset,
firstNotNoneElement,
getOrderedFeatures,
checkStrToList,
checkListNotEmpty,
getSplitting,... |
c58e873db4485194889a5f0bd6183fd7bdd4cd6f497aa0c320a3f044168beaa7 | Python | 9,745 | 274 | import argparse
import datetime
import json
import os
import time
import tqdm
import numpy as np
import pandas as pd
import sklearn.metrics as sm
import torch
import torch.nn as nn
from torch.utils.data import DataLoader
from atom3d.datasets import LMDBDataset
from scipy.stats import spearmanr
from model import CNN... |
7b6be98aba7369c208cafb34ee1e8117616c7ac738d22fab258553a8245f811f | Python | 9,747 | 229 | import os
import copy
import logging
import numpy as np
import scipy as sp
import scipy.spatial
import pandas as pd
import torch
from torch.utils.data import Dataset, DataLoader
from atom3d.datasets import LMDBDataset, extract_coordinates_as_numpy_arrays
from utils import batch_stack, drop_zeros
label_names = ['A','B... |
c0eeb63eb23bddfdec298aa8008c7bddb552010acb798ce139801efb1fdf5a87 | Python | 9,748 | 219 | # -*- coding: utf-8 -*-
"""
Created on Thu December 10 11:41:02 2022
@author: Pawan Panwar, Quanpeng Yang, Ashlie Martini
PyL3dMD: Python LAMMPS 3D Molecular Dynamics/Descriptors
Copyright (C) 2022 Pawan Panwar, Quanpeng Yang, Ashlie Martini
This file is part of PyL3dMD.
PyL3dMD is free software: you ... |
345ae146717053beb1f40779adf57b9d8abd31cd1ff44f120537c7428da67d68 | Python | 9,756 | 291 | import torch
import torch.nn as nn
from lgn.nn.generic_levels import BasicMLP
from lgn.nn.position_levels import RadPolyTrig
from lgn.nn.mask_levels import MaskLevel
from lgn.g_lib import GTau, GVec
class InputLinear(nn.Module):
"""
Input linear layer.
This module applies a simple linear mixing matrix t... |
f985c1e850281dffbad1d3973578995b1d7b97bab3f081e2157d80f5b84b52be | Python | 9,757 | 292 | import torch
import torch.nn as nn
from lgn.nn.generic_levels import BasicMLP
from lgn.nn.position_levels import RadPolyTrig
from lgn.nn.mask_levels import MaskLevel
from lgn.g_lib import GTau, GVec
class InputLinear(nn.Module):
"""
Input linear layer.
This module applies a simple linear mixing matrix t... |
ac7d632d6e58cca95099a79f49582e0859449be0667acd2ffcd8251ea27ac3a2 | Python | 9,759 | 271 | # SPDX-License-Identifier: LGPL-3.0-or-later
"""Vesin graph builders for differentiable and compact deployment inputs.
Generic graphs recompute displacements from local neighbor pairs and periodic
image shifts, preserving coordinate and cell derivatives. Compact canonical
graphs use Vesin's detached displacements for ... |
091d66acc1c597c0af1e56dc03e58ba03d465839c6f9503011d4a2ba5e511bad | Python | 9,764 | 279 | # Copyright 2018-2026
# Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich GmbH
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICE... |
53e73dcd7acb86dc7dbf296df17e7f40a25ac1740c3d77ebefb49639aefb948b | Python | 9,766 | 250 | # 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... |
8dfbf69fedab77aa490fb055de7c255bced9944dced72c3ee20131c0374a15f1 | Python | 9,766 | 280 | # 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... |
7c3abd50832373f23707d52dbcacdcf5e132724b56e867c13c91583d53af8836 | Python | 9,767 | 233 | # coding = utf-8
import os
import math
import random
import numpy as np
import pandas as pd
import torch
from .utils.data_utils import data_generator
from .base.model import SASA
class SASA_Classiffer(object):
"""
SASA Classiffer
References
----------
[1]: https://arxiv.org/abs/2205.03554
P... |
49f5dd1574b8a38d7b1ceb8c677baf11f6c33e79d6dbba0baeb3bcb0ea0bc969 | Python | 9,770 | 263 | """ vector_strength.py - calculate standard vector strength
Calculates vector strength and related parameters from a spike train, for the specified frequency
Also included are the rate modulation transfer function (rMTF) and the
entrainment index (using a standard 0.5/f to 1.5/f window on the ISI distribution)
This ... |
e61aca288fd2714c6970ed7c6394ab97cbd5bc33a51f20a4f8eb7a2d3f4a19d2 | Python | 9,770 | 302 | """Spike time tiling calculation
from:
Cutts, C.S. and Eglen, S.J., "Detecting Pairwise Correlations in Spike Trains:
An Objective Comparison of Methods and Application to the Study of
Retinal Waves", The Journal of Neuroscience, October 22, 2014,
34(43):14288-14303
Implementation by P.B. Manis, Ph.D., UNC Chapel Hill... |
55babcc619c0e94b8c48196007b2e05975039f1481d2a84b35e0a867e26be4b8 | Python | 9,779 | 231 | """PyTorch Lamb optimizer w/ behaviour similar to NVIDIA FusedLamb.
This optimizer code was adapted from the following (starting with latest)
* https://github.com/HabanaAI/Model-References/blob/
2b435114fe8e31f159b1d3063b8280ae37af7423/PyTorch/nlp/bert/pretraining/lamb.py
* https://github.com/NVIDIA/DeepLearningExampl... |
cba57529198ee1008c3e803e699b5f8a4b6b7730b65c2f905da1c9f689fe2b46 | Python | 9,782 | 238 | import torch.nn as nn
import torch, math
import torch.nn.functional as F
import matplotlib.pyplot as plt
import numpy as np
import pylab
from PIL import Image
def calc_mean_std(feat, eps=1e-5):
# eps is a small value added to the variance to avoid divide-by-zero.
size = feat.size()
assert ... |
c90344f599741a6ad353db138bde5628f45b04b88dd1ff4bfb94fc642c939ac3 | Python | 9,786 | 208 | from __future__ import print_function
import json
import multiprocessing
import os
import sys
import numpy as np
import pandas as pd
import rdkit.Chem as Chem
import rdkit.Chem.AllChem as AllChem
from joblib import Parallel, delayed
from rdkit import DataStructs, RDLogger
from tqdm import tqdm
from rdchiral.main imp... |
e232f1aa080e5832ee06dff997ec1376464602f19f088866e505dafa63ef974d | Python | 9,797 | 246 | """versatile shortcuts for quick typing in an (i)python shell,
or even using ``from cma.s import *`` in interactive sessions.
Provides various aliases from within the `cma` package, to be reached like
``cma.s....``
Do not use this module for stable code developments!
This may not be actively maintained.
"""
import... |
a9ca0fa2287e92e7f52b0bfa68fb98ac2dd138ff92e423662a16ef8a22409879 | Python | 9,800 | 239 | from __future__ import annotations
import warnings
import networkx as nx
import numpy as np
import pandas as pd
import pytest
from scipy.sparse import csr_matrix, csgraph, find
from sklearn.metrics import pairwise_distances
from sklearn.neighbors import NearestNeighbors
from numpy.random import BitGenerator, SeedSequ... |
6e09a21146c6b7974909ae7d650b02bf0a91ee675fa3944b03e787bdec8266c6 | Python | 9,803 | 233 | import numpy as np
from rdkit import Chem
from typing import Set, Any, List, Union
idxfunc = lambda a: a.GetAtomMapNum() - 1
bond_idx_fn = lambda a, b, mol: mol.GetBondBetweenAtoms(a.GetIdx(), b.GetIdx()).GetIdx()
# Symbols for different atoms
ATOM_LIST = ['C', 'N', 'O', 'S', 'F', 'Si', 'P', 'Cl', 'Br', 'Mg', 'Na', '... |
a74eb6e7f29fd4d98e663d69cc28a4a12cec1b9281774556f9076fcf59065029 | Python | 9,807 | 307 | import diversipy as dp
import matplotlib.gridspec as grsp
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from scipy.stats import iqr
from Historia.shared.design_utils import get_minmax
from Historia.shared.indices_utils import diff, whereq_whernot
from Historia.shared.jsonfiles_utils import loa... |
f0eee54ee2f0231a9cfa7f2a907cbd4d57fe664c450ad8838aacddf468fe1d1a | Python | 9,810 | 229 | """This module aims to provide the necessary tools to identify defects and
position candidates at bulks and slabs"""
from collections import namedtuple
import numpy as np
from shapely.geometry import Point
from shapely.geometry.polygon import Polygon
Position = namedtuple('Position', 'type dcoords coords')
Atom_A = na... |
ba0c071a0d8709b2234c6b8aa28dd2a290a0839bc5e6abb77a880e1a4cf98594 | Python | 9,816 | 280 | """Wrappers to convert distance to kernel or kernel to distance."""
__author__ = ["fkiraly"]
import numpy as np
from sktime.dists_kernels.base import BasePairwiseTransformerPanel
SUPPORTED_MTYPES = ["pd-multiindex", "nested_univ", "df-list", "numpy3D"]
def _trafo_diag(fun):
"""Obtain a function which returns ... |
f8199da2d3ec9abada45e4d6a43b7b88402f8462087b907634233e3b74e35803 | Python | 9,827 | 283 | from typing import List, Tuple
import os
import matplotlib as mpl
import matplotlib.pyplot as plt
mpl.rcParams['svg.fonttype'] = 'none' # Takes care that texts show up when
# importing pdf-plots into Inkcape
import numpy as np
import pandas as pd
import seaborn as sns
from src.definitions import RESULTS_DIR, okabe_it... |
beb33da53f8313e89b04055bc49b314772b13fce8a2bb81ed6c5ff920dd5ebe4 | Python | 9,838 | 147 | # create the training data for mention disambiguation from SemEHR
from sent_bert_emb_viz_util import load_df, retrieve_section_and_doc_structure
from rare_disease_id_util import umls2prefLabelwithDict
from collections import defaultdict
import pickle
import sys
import argparse
if __name__ == '__main__':
... |
54aa4002af10a78c67b8b45cd69e75004a79e282680c00fcf8c07be52a2b2195 | Python | 9,840 | 170 | from socket import socket, AF_INET, SOCK_STREAM
import struct
import numpy as np
from datetime import datetime, timedelta
from collections import defaultdict
from functools import reduce
from fileManagement import selectClassifierID
from classifierClient import ClassifierClient
from sampler import up_or_down_sa... |
d0463fde8cc209266b1e7a37a5fd9182580d2a93fd4205be6c932cc081d81735 | Python | 9,843 | 275 |
from rdkit import Chem
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.metrics import confusion_matrix, accuracy_score
from sklearn.metrics import roc_auc_score, roc_curve, precision_score, recall_score
from torch.optim.lr_scheduler import _LRScheduler
#from torch.optim import Adam,... |
5c9bcc6c78b48735cc27cffeb55a364ae9d58967f43dc0c3702a36f737a7b256 | Python | 9,844 | 328 | # 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... |
6e2666fcd184d4bf0eee923b85e5e4c9662f576156b180a90e3e1c34aeed1646 | Python | 9,845 | 225 | import sys
from pyontutils.core import Source, LabelsBase, Collector, build
from pyontutils.utils import Async, deferred
from pyontutils.namespaces import makePrefixes, NCBITaxon, UBERON, nsExact
from pyontutils.namespaces import NIFRID, ilx, ilxtr, TEMP, DKT, DKTr, DKTs, MNDBGL, FSCL
from pyontutils.combinators import... |
351602b477e0ad594c8239c6934760dd057e1f97150415c11f8d7e43201862c7 | Python | 9,864 | 225 | import sys
from pyontutils.core import Source, LabelsBase, Collector, build
from pyontutils.utils import Async, deferred
from pyontutils.namespaces import makePrefixes, NCBITaxon, UBERON, nsExact
from pyontutils.namespaces import NIFRID, ilx, ilxtr, TEMP, DKT, DKTr, DKTs, MNDBGL, FSCL
from pyontutils.combinators import... |
3e74052127f5878e195eeb51c496c2f6113186758c0415a14ae48090fb73ca92 | Python | 9,869 | 214 | import os
import warnings
from datetime import datetime
from joblib import Parallel, delayed
import numpy as np
import pandas as pd
import torch
from h5py import File
with warnings.catch_warnings():
warnings.simplefilter('ignore', category=UserWarning)
from joblib import Memory, delayed
from torch.utils.data i... |
6d53a18a5f597443e06f48f05b76d2aeff417cd406834a221a442563d388fcad | Python | 9,870 | 188 | #coding:utf-8
import os
import keras
os.environ['CUDA_VISIBLE_DEVICES'] = '1'
import numpy as np
from keras.models import *
from keras.layers import Input, concatenate, Conv2D, MaxPooling2D, UpSampling2D, Dropout, Cropping2D
from keras.optimizers import *
from keras.callbacks import ModelCheckpoint, LearningRateSchedu... |
9ef0eab03dbf78535e5080f0e1245d5c28455a1968885a5c282dcde00c8708ca | Python | 9,870 | 336 | # 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... |
6c9b3e731b77a985e5abf86b006ef1f72a070048b65986372fda05bafc96483c | Python | 9,872 | 269 | from __future__ import annotations
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, List, Optional, Sequence, Tuple
import anndata as ad
import numpy as np
import pandas as pd
import scipy.sparse as sp
import torch
from sklearn.model_selection import train_test_split
from sklearn.pr... |
f163c3a5ec79bf1ecc7650bc2c2af37bbf1e20ef2a5e7a1be0aa0eddb17893e7 | Python | 9,878 | 257 | import argparse
import sys
import time
from dataclasses import dataclass
import numpy as np
import pylsl
import pyxdf
def _create_info_from_xdf_stream_header(header):
new_info = pylsl.StreamInfo(
name=header["name"][0],
type=header["type"][0],
channel_count=int(header["channel_count"][0]... |
4b6fafe362f6f563ad64ac7acc454f15576aa918498133e993621ba272db37c1 | Python | 9,882 | 299 | import json
from pathlib import Path
def get_delim(c):
"""
Gets the right delimiter from the c node
:param c: the c node json object
:return: delimiter of the transcription
"""
if "delim" in c:
return c["delim"]
else:
return None
def parse_tran(c, chars, key, add_three_do... |
608efc22dac1c79016a4ac260f169638a5bbf38598875f30e639cff8c10ad78d | Python | 9,882 | 297 | # -*- encoding: utf-8 -*-
from __future__ import print_function
from collections import OrderedDict
import re
# Unified collection point for all empirically-determined biophysical
# values. Each value is a tuple (val, source).
DATA = OrderedDict()
def get(*args, **kwds):
""" Get a single value from the database... |
a959f9361e37306e4e56468ab9834456bd9a5b5aaf99d94f545700a3ee25e7d7 | Python | 9,891 | 246 | import ray
import numpy as np
from trueskill import Rating, quality_1vs1, rate_1vs1
import random
from mprl.utility_services.cloud_storage import connect_storage_client, upload_file, get_default_path_on_disk_for_minio_key, maybe_download_object
from mprl.rl.common.util import save_model_weights_to_disk_tmp_and_minio, l... |
74d4197cb0ee931269ca685876e130d5f2ed5d638464526348d36391cde07151 | Python | 9,895 | 287 | # This code is an implementation of the model presented in Halnes et al. 2013
# with minor adjustments.
import dolfin as df
default_init_parameters = {"Na_i": "15.474585472970270",
"K_i": "99.892102216365814",
"Cl_i": "5.363687689337043",
... |
a5ff6ba70273a3c0d188eb9d8e157bc0476c46df01395bb605cd6e8f60b90c16 | Python | 9,908 | 315 | # 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... |
eeb8b6c43ec907dc29bd87fd63b40bb85dfc58c816cdead08ca50438722e1efa | Python | 9,919 | 270 | """Checkpoint resolution and loading for the Tabby backbone.
Two on-disk layouts are supported, and every entry point in the repository goes
through :func:`load_backbone` so they accept the same things:
``config.json`` + ``model.safetensors``
A Hugging Face snapshot -- what ``save_pretrained`` writes, what
``... |
aac5080c4eff0620e8a68047b02bc9107ebcc3a3de8abf894e8253baba7839a9 | Python | 9,923 | 262 | import argparse
from tqdm import tqdm
from torch.utils.data import DataLoader
from torch.optim.lr_scheduler import MultiStepLR
from data import *
from model.gat import *
# from util.misc import CSVLogger
import random
import torch
import numpy as np
import os
from typing import Optional
parser = argparse.ArgumentPar... |
363dcd1b5fdfb49f9488a86890cb12259815a53658fca76d10a18abb4834dc7d | Python | 9,934 | 307 | # 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... |
6fc21883bf36ef3bc67e74dfc452d33ddb348a9535980783c06f4c1f7fc69ac5 | Python | 9,936 | 234 | """BaseEstimator interface to sktime dtw distances in distances module."""
__author__ = ["fkiraly"]
import numpy as np
from sktime.dists_kernels._numba_distances import pairwise_distance
from sktime.dists_kernels.base import BasePairwiseTransformerPanel
class DtwDist(BasePairwiseTransformerPanel):
r"""Interfa... |
816ed2e6190a0f85f902967234369482d9833a81610c4eecc5aa94305617b868 | Python | 9,939 | 257 | """Per-region overlap statistics and subject map descriptive stats."""
from typing import Dict
import nibabel as nib
import numpy as np
import pandas as pd
from bcblib.imaging.stats import _fraction_covered_array, _weighted_region_mean_array
_EMPTY_COLUMNS = [
"region_name", "n_voxels_region", "n_voxels_overla... |
052384ac32991b191be0dfe0a6c5e3d907bd8cc96e1793c95c4ed6cbf87665d0 | Python | 9,943 | 232 | import pandas as pd
import numpy as np
import tensorflow as tf
from tqdm import tqdm
import matplotlib.pyplot as plt
import seaborn as sns
from sklearn.preprocessing import LabelEncoder
import os
import runner
def save_runner_result(runner, result, output_dir):
model_and_log_path_filepath = os.path.join(output_... |
88460bcd1577de397a997b3f732d18650487f0268c5e9bed0778dc58e9e2dc29 | Python | 9,946 | 268 | # 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... |
faf91f200c023c0b8665047d2018f6740b889c78ea14fa0a8883b005ff42729f | Python | 9,952 | 259 | """Arithmetic with distances/kernels, e.g., addition, multiplication."""
__author__ = ["fkiraly"]
import numpy as np
from sktime.base import _HeterogenousMetaEstimator
from sktime.dists_kernels.base import BasePairwiseTransformerPanel
SUPPORTED_MTYPES = ["pd-multiindex", "nested_univ", "df-list", "numpy3D"]
class... |
73afc1f019e8c3c2dc6d4235450fa89bbd907731104cae90f373d2d06e6418c6 | Python | 9,955 | 253 | """
@file: shuffle_netv2.py
Created on 02.05.19
@project: CrazyAra
@author: queensgambit
Incorporation of shuffling as in ShuffleNetV2 into the RISE architecture.
ShuffleNet V2: Practical Guidelines for EfficientCNN Architecture Design - https://arxiv.org/pdf/1807.11164.pdf
"""
from mxnet.gluon.nn import HybridSeque... |
d756e856f18b4bd0b6eabe91f7314cd1e2b4d62a74242816c6bbe86092ba7d29 | Python | 9,960 | 372 | """NIfTI statistical utilities: summary stats, centre of gravity, histograms."""
from typing import Any, Dict, Optional, Tuple, Union
import numpy as np
import nibabel as nib
from scipy.spatial.distance import euclidean
from scipy.ndimage import center_of_mass
from bcblib.imaging._types import NiftiLike
from bcblib.... |
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