sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
a7825754092faef20171a63e1c44e2c5a576504193cab0fa622e47e6b555ec30 | Python | 8,101 | 242 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Feb 10 12:08:20 2022
Last update: 3/11/2023
@author: sudhanshu
Usage: python evaluate_on_testset.py
Returns: Dice, DVO, and DCC for each file in ../dataset/test/pdb_npz/
"""
import torch
import os
import numpy as np
from prediction_utils import load_m... |
c84bd6e4940ae88e67d1c0ef507eb3dcf26a30bc5d95519e758b0202ce898c09 | Python | 8,101 | 294 | """Test the move from (m,d) to (d,m)."""
import numpy as np
from sklearn import metrics
from sktime.clustering.k_means import TimeSeriesKMeans
from sktime.datasets import load_arrow_head, load_basic_motions, load_unit_test
from sktime.dists_kernels._numba_distances import (
dtw_distance,
erp_distance,
lcs... |
eb48ebef980ef34220ad173534d63672f296b527febfb11647a4c7bc84b8744b | Python | 8,101 | 270 | """
timeseries.py
This script generates the timeseries plots which demonstrate the basic
network characteristics (namely bump retention in 'darkness' and
R dominance over E-PG neurons).
Both the sm_peturbation and double_bump options are considered legacy
features. They are not used in the final paper. Double bumps c... |
0392c56db659eaf80f0449bb5726d461397c968b3428586de735215e1fb9c194 | Python | 8,102 | 219 | import os
import warnings
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
warnings.filterwarnings('ignore', category=FutureWarning)
warnings.filterwarnings('ignore', category=DeprecationWarning)
import numpy as np
import pandas as pd
from scripts_tool import configurations as cfg
from scripts_tool import data_handler as dh
... |
87c6299411fcd91e129b7005a27496bcb287c0e8ccfddcc847c700f794da6e24 | Python | 8,113 | 232 | # 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... |
76f3caceb4b45b6e55826b3a4d1936b3e89b9ed0dcf21ba8c92b93a9e09b5b03 | Python | 8,114 | 230 | # 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... |
5764ba23a6aee58f8303f104f08cf438825f22379af0a022cd2fb478fb940155 | Python | 8,118 | 210 | # 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... |
e08d7bda8aa0dcc2625968178765f986dc1d546db5ed816f24cb68e61bcd8a47 | Python | 8,118 | 232 | # coding=utf-8
# Copyright (C) 2022. Huawei Technologies Co., Ltd. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# ... |
2216b3b23ed12b3d92c1adafb60cd09db2b25c32df04e09a19ed89e6ff0cd157 | Python | 8,121 | 238 | from __future__ import print_function
import re
import os
import sys
import tempfile
import subprocess
import multiprocessing
import multiprocessing.pool
import dxpy
def normalize_timedelta(timedelta):
"""
Given a string like "1w" or "5d", convert it to an integer in seconds.
Integers without a suffix are... |
d7d2ca1715e20e36fbe45c478a94a09038be9b0b7408596d19da1011b8620820 | Python | 8,123 | 196 | # Compatibility adapter used by the release pretraining recipe and the
# HF-style model files.
#
# The pretraining entry point uses this module to expose:
#
# * ``PatchTSTFMConfig`` -- a **dataclass** (the trainer calls
# ``dataclasses.asdict(cfg)`` when checkpointing) with fields
# ``context_length, patch_si... |
3fa25c2974c7c3411caf0ee4ebc961067a32d6681cf9377b7edf2fab5d4394ee | Python | 8,131 | 262 |
import numpy as np
import pandas as pd
import pytest
from numpy.testing import assert_array_equal
from seaborn._core.groupby import GroupBy
from seaborn._stats.counting import Hist, Count
class TestCount:
@pytest.fixture
def df(self, rng):
n = 30
return pd.DataFrame(dict(
x=rn... |
90c2f321ecb5d67d34740092c6b0a1a1134b73e6b64826db6116759944d6f350 | Python | 8,131 | 207 | # 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... |
54f0c156acbc7f52a0113a82fe5f1be675f88fde54dca66edf172c5110ba908b | Python | 8,134 | 232 | # 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... |
119ca8bd3454d7d7dbb0f5d4f2d12db9c5f2899a374dd7acac7225077937a724 | Python | 8,139 | 193 | import math
import os
import torch
import dotenv as de
import numpy as np
import pandas as pd
from atom3d.datasets import LMDBDataset
from atom3d.util.voxelize import dotdict, get_center, gen_rot_matrix, get_grid, intersperse
from torch.utils.data import DataLoader, IterableDataset
import atom3d.datasets.ppi.neighbo... |
37d37ab7c6292bd04ba423cbb2ec7ae3586d861d524e186774cf9a8a6986ebff | Python | 8,142 | 217 | """Time series SVC, from tslearn."""
from sktime.base.adapters._tslearn import _TslearnAdapter
from sktime.classification.base import BaseClassifier
class TimeSeriesSVCTslearn(_TslearnAdapter, BaseClassifier):
"""Time Series Suppoer Vector Classifier, from tslearn.
Direct interface to ``tslearn.svm.svm.Time... |
6c8fd570367c6d4d300afee199cc9428be800d6a41e1ea2eaac508d0bd80e2f4 | Python | 8,144 | 218 | """Time series kmedoids."""
__author__ = ["chrisholder", "TonyBagnall"]
from collections.abc import Callable
import numpy as np
from numpy.random import RandomState
from sktime.clustering.metrics.medoids import medoids
from sktime.clustering.partitioning import BaseTimeSeriesLloyds
from sktime.dists_kernels._numba_d... |
badc5760cdc699d4dc92378d0fc6bc53e5f0e2a8477558a1f91cde9c00aeb19e | Python | 8,145 | 249 | # Copyright 2019-2021 The ASReview Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... |
2eda1ccf88c60427abc754cc48459cc34b05124e572dcc6c51477302300afc8f | Python | 8,153 | 238 | # 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... |
3fec113995853199f1d54ff906b53321d3d7fce809fb5811aecd66fdc4c85635 | Python | 8,155 | 208 | # 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... |
01e1982127de97498edf873e1bb1bdcdcfe4f5ecd735eb670fa54ac41e47547d | Python | 8,156 | 183 | import warnings
import pytest
import pandas as pd
import numpy as np
from palantir.presults import PResults
from palantir.core import _compute_pseudotime, identify_terminal_states, run_palantir
# Test with basic DataFrame input
@pytest.mark.filterwarnings("ignore:np.find_common_type is deprecated.")
@pytest.mark.fi... |
140e5818ed03cd32c2e2bee248b23f7ac28b48893c911adcbbe5aff8ec641de8 | Python | 8,156 | 200 | from __future__ import print_function
from freqAnalysisTools import band
from os import listdir
from os.path import isfile, join, splitext
import pickle
import math
import numpy as np
from itertools import groupby
#---------------
# set up parameters
# for data handling
metaDataLineNum4eeg = 18
metaDataLineNum4stage ... |
63312d4e02d7a6207f7c616323e546ec00084daf314b763b29d1113ac723f578 | Python | 8,157 | 214 | # 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... |
a6666cf493e796012ff3822c2506db3e440fa15b2bb4a0d43343bbf4987fea67 | Python | 8,158 | 230 | """Space handling: template detection, resampling, and cross-template warps."""
import warnings
import numpy as np
import nibabel as nib
import templateflow.api as tflow
from nilearn.image import resample_to_img as _resample_to_img
from nitransforms.io.itk import ITKCompositeH5
from nitransforms.nonlinear import Dens... |
37d24983ba5265d38c6c86f608a33e048fb44b88e9d73e6c57a9f212e9ea3e57 | Python | 8,159 | 186 | import numpy as np
from itertools import groupby
from parameterSetup import ParameterSetup
def up_or_down_sampling(signal_rawarray, model_samplePointNum, observed_samplePointNum):
# downsampling
# print('-------')
# print('model_samplePointNum =', model_samplePointNum)
# print('observed_samplePointNum ... |
fc9f24b04c103c1de6f5ff5ea0c6f0d38285230deb7583c38a7aa3ca1d0ecbe2 | Python | 8,160 | 210 | import collections as col
import logging
import os
import sys
import click
import pandas as pd
from rdkit import Chem
from torch.utils.data import Dataset
import atom3d.datasets.datasets as da
import atom3d.protein.sequence as seq
import atom3d.splits.splits as spl
import atom3d.util.file as fi
import atom3d.util.fo... |
11488b03ac9f1616cff2eee2b0ab1f0bedbbf25013422e5f97f7f6e441534863 | Python | 8,161 | 233 | from __future__ import annotations
import math
from typing import Literal
import pytest
import optuna
from optuna.pruners import _percentile
from optuna.study import Study
from optuna.study import StudyDirection
from optuna.trial import TrialState
def test_percentile_pruner_percentile() -> None:
optuna.pruners... |
1ff884d8082c674632aae05fa58e93ceaa988755df24cf3aea9638d1dd8fd442 | Python | 8,161 | 257 | # coding=utf-8
# 2021.03 added (1) logging;
# (2) BaseLearner;
# (3) NotearsMLP, NotearsSob;
# 2021.03 deleted (1) __main__
# Huawei Technologies Co., Ltd.
#
# Copyright (C) 2021. Huawei Technologies Co., Ltd. All rights reserved.
#
# Copyright (c) Xun Zheng (https://github.com... |
60cfc7f2b9215158e89b7436713f327d61000ff0b571e9b38267e001db7113bf | Python | 8,165 | 215 | from __future__ import print_function
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torchvision import datasets, transforms
import numpy
import matplotlib.pyplot as plt
import pickle
from scipy import stats
import copy
from scipy.stats import entropy
from sklearn im... |
cf5e54a3f2d68fb57914c0d222301faed37c1905845216d31fb21d21f6adac46 | Python | 8,168 | 231 | # 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... |
6aa9c728f4b6fdd68a73e3fc165a51afe9917bcee685b5a39b5a82818f703d7a | Python | 8,169 | 221 | import argparse
import logging
import os
import time
import datetime
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import torch
import torch.nn.functional as F
from torch_geometric.data import DataLoader
from model import GNN_RSR
from data import GNNTransformRSR
from atom3d.datasets import LMD... |
7b7cbdbd584e0593bec2c90cd8315150aa8890f71d7170f611afa8f5997418cb | Python | 8,171 | 174 | import os, sys
import numpy as np
import torch
import pytorch_lightning as pl
from six.moves import cPickle
from evoaug import evoaug, augment
sys.path.append('../../evoaug_analysis')
import utils
from model_zoo import CNN
device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
output_dir = '../resul... |
d9923eb5786f0811b0310f7a4c733ef1e6f55466abcdfe88761c249d9a0d5a30 | Python | 8,173 | 257 | # 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 Conv(Base):
@staticmethod
def export() -> None:
x = np... |
2bd4ba5bb1a004098db6647d02e4d40eb1d9c0edc58804e122655cd95fbc8f0e | Python | 8,174 | 196 | #!/usr/bin/env python
import os
import sys
import stat
from os.path import join as pjoin, exists as pexists, realpath
import numpy as np
"""#---------------------------------#---------------------------------#---------------------------------
The following script helps you generating job files for processing the lar... |
bf11555f3bca862b952531ebec2e6bce28e377475407118c0020dbe14e55c522 | Python | 8,175 | 258 | # SPDX-License-Identifier: LGPL-3.0-or-later
from typing import (
Any,
Literal,
overload,
)
import numpy as np
from deepmd.dpmodel.output_def import (
FittingOutputDef,
ModelOutputDef,
OutputVariableDef,
)
from .deep_eval import (
DeepEval,
)
class DeepPot(DeepEval):
"""Potential en... |
6d932317f63058d507e0f558e67e51fde7891ebb6a193f853c08a6d86d7431c0 | Python | 8,181 | 182 | """Functions to generate the conformers to be adsorbed and the most stable one.
functions:
remove_C_linked_Hs: Removes hydrogens bonded to a carbon atom from a molecule.
gen_confs: Generate a number of conformers in random orientations.
get_moments_of_inertia: Computes moments of inertia of the given conformers.
get_m... |
a647381f33ce16e739ec21f80d3d4ff30e5d2be7e55a0a31b858d04c262db2c6 | Python | 8,184 | 191 | # Copyright (c) ONNX Project Contributors
#
# SPDX-License-Identifier: Apache-2.0
"""Optional runtime validation of static shape annotations.
This module implements the runtime semantics described in
``docs/ShapeAnnotationSemantics.md``: each symbolic dimension name
(``dim_param``) occurring in a model is treated as e... |
b3da96ea220a0c1a83ef8cd9c28f4ad83dc0d3c073b040ddbb1b948e761102d3 | Python | 8,184 | 208 | # -*- coding: utf-8 -*-
import os
os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
os.environ["CUDA_VISIBLE_DEVICES"] = "1"
#
# Description:
# Training code of QSMnet
#
# Copyright @ Yanqiu Feng
# Laboratory for Medical Imaging and Diagnostic Technology
# Southern Medical University
# email: foree@163.com
#
# sess ... |
aa85f692a9bbddbe507e81b518d299ffbc52efdc2c8385a1697dcaa3b083363b | Python | 8,191 | 263 | # SPDX-License-Identifier: LGPL-3.0-or-later
"""Training entrypoint for the TensorFlow 2 eager backend."""
from __future__ import (
annotations,
)
import logging
import time
from typing import (
TYPE_CHECKING,
Any,
)
from deepmd.dpmodel.model.base_model import (
BaseModel,
)
from deepmd.dpmodel.train... |
62b835c171bcdc99e67e58a3b20447499d88845046424ea5047ccbff6154739d | Python | 8,196 | 237 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
'''
Unittests for the openbabel based modules
Tests
- MoleculeCreator
- MoleculeInfo
'''
import unittest
import openbabel
#from openbabel import openbabel
from src import MoleculeInfo as mi
from src import MoleculeCreator as mc
import filecmp
import os
import subpro... |
f5f5d43e9b20f188a58bc4945f813f7d1f5659ebf622490a97dbbc1e10062ffc | Python | 8,196 | 129 | import os
import scipy.io
import sys
sys.path.insert(1, "/Users/hyung/Research23_Network_Analysis/mBIN/Python/LBD/")
from LoadDataLBD import loaddataLBD
from PathCovLBD_noAmy import pathCovLBD_noAmy
from ThicknessCovLBD import ThicknessCovLBD
sys.path.insert(1, "/Users/hyung/Research23_Network_Analysis/mBIN/Python/Ne... |
45357070252cada16415410a8948eaf502e4087d4cdff0c557bb34f7d2d58cec | Python | 8,198 | 230 | from mprl.rl.envs.stratego.stratego_spatial_multiagent_env import SpatialStrategoMultiAgentEnv
from progress.bar import Bar
import numpy as np
import dill
from multiprocessing.pool import Pool
from multiprocessing import cpu_count
def run_dill_encoded(payload):
fun, args = dill.loads(payload)
return fun(*args)... |
506fe51629ceb9bbfb39294aa2dbcdd13fcd51a29ec98c89f9c03ec47f6e1d0d | Python | 8,198 | 232 | # 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... |
d9754d596e30142784dfc6f244643e469cbc83873ddbf3b42557612988be5813 | Python | 8,200 | 238 | """Summary Classifier.
Pipeline classifier using the basic summary statistics and an estimator.
"""
__author__ = ["MatthewMiddlehurst"]
__all__ = ["SummaryClassifier"]
import numpy as np
from sklearn.ensemble import RandomForestClassifier
from sklearn.tree import DecisionTreeClassifier
from sktime.base._base import... |
5ed4cac91478e7f57948b04e1def98c52f998944948e0b9b2a97a23ce9cfb8b8 | Python | 8,201 | 210 | #!/usr/bin/env python3
"""
NCBIgff2chrom.py
================
Parse an NCBI GFF annotation and produce a `.chrom` file (ODP format).
This script supports two invocation styles:
1. **Legacy / odp:** one positional argument (the GFF, possibly gzipped).
Emits the chrom table to stdout. CDS extents are unioned per p... |
d85157bb4a3cc060a4d7e93809936d5f08fe2d1fbe2a1b794504b7e3bbb0dcd9 | Python | 8,206 | 239 | from collections import defaultdict
import csv
from pathlib import Path
import os
from rdflib import Graph, URIRef, Literal, BNode, RDF, RDFS, OWL
from sqlalchemy import create_engine, inspect, Table, Column
from sqlalchemy.orm.session import sessionmaker
from pyontutils import utils
from pyontutils.config import auth
... |
f95a85dbc6b2161904fe971d53a3fbc5777c590036bd7e1978b09d016b0d8352 | Python | 8,209 | 196 | import argparse
import logging
import os
import time
import datetime
import matplotlib.pyplot as plt
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.utils.data import DataLoader
from model import GNN_MSP, MLP_MSP
from data import GNNTransformMSP, CollaterMSP
from atom3d... |
5665aabffc6ac3fa7f3f65aaf26648be8bbfbb99b4a3e773af6462d689e26fc8 | Python | 8,229 | 238 | # -*- coding: utf-8 -*-
"""
Created on Fri July 09 14:54:37 2023
@author: Mesfin Diro
"""
import warnings
warnings.filterwarnings("ignore")
import os
import os.path as osp
import argparse
import torch
import torch.nn.functional as F
import torch_geometric.transforms as T
from torch.optim.lr_scheduler import _LRSchedul... |
52db28b84d9dd7a74390fd6a7d91e0e98715873a68ca204b7fe386905e97546d | Python | 8,230 | 228 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
from ray.rllib.models.tf.tf_modelv2 import TFModelV2
from ray.rllib.utils import try_import_tf, try_import_tfp
tf = try_import_tf()
tfp = try_import_tfp()
SCALE_DIAG_MIN_MAX = (-20, 2)
d... |
c81bfdf6f3d2816647aa74392b55547fddc8ac52c0a49a9bdd4aa889352c2bc6 | Python | 8,233 | 232 | import unittest
from onmt.translate.translation_server import ServerModel, TranslationServer
import os
from six import string_types
from textwrap import dedent
import torch
from onmt.translate.translator import Translator
TEST_DIR = os.path.dirname(os.path.abspath(__file__))
class TestServerModel(unittest.TestCa... |
7f82a6de93581b473c994dc00e8f4ff74c4453930fbb779a832aa6aa519ba0c2 | Python | 8,246 | 195 | ##+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
## Created by: Yaoyao Liu
## Tianjin University
## liuyaoyao@tju.edu.cn
## Copyright (c) 2019
##
## This source code is licensed under the MIT-style license found in the
## LICENSE file in the root directory of this source tree
##++++++++++++++... |
eef5f9d6313fe540b7af31e92e8d523862155faccd597789744647744c959212 | Python | 8,246 | 208 | """Functions for splitting data into test, validation, and training sets."""
from functools import partial
import numpy as np
import torch
import atom3d.util.log as log
logger = log.get_logger('splits')
def split(dataset, indices_train, indices_val, indices_test):
"""Split a dataset into train, validation, and... |
31e2dd73d61b02a860ab74a320caae860a616682a6efd1f63f5b9288f57abd31 | Python | 8,256 | 169 | import numpy as np
import SimpleITK as sitk
import config as cfg
def get_data_info(sitk_image):
"""
Extracts information about a given SimpleITK image and stores it in a dictionary.
Args:
sitk_image (SimpleITK.Image): SimpleITK image to extract information from.
Returns:
d... |
ef1f592cd0076565fe845c2abad9f84ccb4c6e63876bbd8d5c87833988b2aa1b | Python | 8,260 | 188 | # SPDX-License-Identifier: LGPL-3.0-or-later
"""This module ensures input in the examples directory
could pass the argument checking.
"""
import unittest
from pathlib import (
Path,
)
from deepmd.common import (
j_loader,
)
from deepmd.utils.argcheck import (
normalize,
)
from deepmd.utils.model_preset im... |
bee15268233b2eb262bad46d9c6b28bb5206bd1918634545131393ecb8d6c0fd | Python | 8,264 | 233 | """Tests for the pretrain input path on BaseDetector.
Tests that apply to any detector, for instance state, clone, and no-op
behaviour, are in ``TestAllDetectors``.
"""
__author__ = ["yash-sangwan"]
import numpy as np
import pandas as pd
import pytest
from sktime.datatypes import check_is_scitype
from sktime.detect... |
434b1f47f0a2d8813f83ff2fcf4a77ad59eda7c1a6cdb84fb71c0321c515796e | Python | 8,267 | 214 | import argparse
from importlib.metadata import PackageNotFoundError, version
from pathlib import Path
from graynet import config_graynet as cfg
from graynet.domain import RunConfig
from graynet.exporters import export_csv, export_graphml
from graynet.pipeline import run
from graynet.utils import as_path, check_atlas, ... |
22aeecfcde25fa87a4322b01bf7786f5ef9f9ad035be4f9e8f18d958985f757b | Python | 8,279 | 224 | # SPDX-License-Identifier: LGPL-3.0-or-later
"""Complete intra-frame pair topology for interactions without a cutoff.
A module whose interaction acts between every two atoms of a system, such as
a non-periodic long-range module, cannot read its geometry from the
short-range :class:`~deepmd.dpmodel.utils.neighbor_graph... |
486d3a0a92bae134437fbc6ddf2047ef87da6114f0ebeee55c818b3096be4cb9 | Python | 8,280 | 268 |
from scripts_tool import data_handler as dh
from scripts_tool import utils
import numpy as np
import pandas as pd
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import seaborn as sns
def generate_heatmap(config, from_pickle=False):
import pickle
from scripts_tool import models_util
... |
acf91a964fd419001693d10c107fc237fb2a82bcf20e24639dbc3ddf9cfdd185 | Python | 8,282 | 147 | import argparse
import os
from configparser import ConfigParser
import pkg_resources
def set_seed(SEED):
os.environ['PYTHONHASHSEED'] = str(SEED)
from numpy.random import seed
seed(SEED)
from tensorflow.random import set_seed
set_seed(SEED)
def get_CFG_reader():
cfg = ConfigParser()
assert pkg_... |
15ada828ba559cfbafaa4ddba1502d2ff0b7c90a5bc113e3b663a86c5d4615cc | Python | 8,286 | 197 | # Copyright 2022 Diagnostic Image Analysis Group, Radboudumc, Nijmegen, The Netherlands
#
# 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... |
3c1064e6462a27bcc4602432c192ff6d26d2c22d7ce76f473bffdfcdae35c0c3 | Python | 8,287 | 177 | import logging
import grpc
import time
import threading
from typing import Union
from mprl.utility_services.lock_server.protobuf.lock_server_pb2 import LockRequest, LockConfirmation, LockWorkerPing, LockReplaceRequest, NameFilter, LockList
from mprl.utility_services.lock_server.protobuf.lock_server_pb2_grpc import Lo... |
590c0b7a380e3a28eee7b72c3ad38fba0d403aabd4b6a1516e87e5e0287af36d | Python | 8,288 | 238 | from argparse import Namespace
from typing import Optional, Tuple
import torch
import numpy as np
from .jet_features import plot_jet_p_cartesian, plot_jet_p_polar
from .particle_features import plot_p_cartesian, plot_p_polar
from .jet_images import plot_jet_image
from .utils import (
get_p_polar,
get_p_cartesi... |
c4a185074e59dee4be70269357da1f20223e1bcc31a77edbf11dc6c6d6099c9d | Python | 8,293 | 170 | import random
import matplotlib.pyplot as plt
import numpy as np
import torch
from gpytGPE.gpe import GPEmul
from Historia.history import hm
from Historia.shared.design_utils import get_minmax, lhd, read_labels
from Historia.shared.plot_utils import get_col, interp_col
SEED = 8
def main():
# ------------------... |
da7e46ee016b1be92cd149bfdaf2242e7f83fae3b908c740310ef45bb2e74377 | Python | 8,296 | 257 | # This code was adapted from https://github.com/ryanwongsa/kaggle-birdsong-recognition/blob/master/src/models/sed_models.py,
# which is licensed under the MIT license. The original author of this code is Ryan Wong (https://github.com/ryanwongsa).
from typing import Dict, Tuple, Union
import torch
import torch.nn as n... |
c8bf53ef1ed36a55898376ae1800bbd058f333a537639f8382eaa07147b3999f | Python | 8,300 | 219 | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import os
import warnings
from numbers import Number
import mmcv
import numpy as np
import torch
from mmcv import DictAction
from mmcv.parallel import MMDataParallel, MMDistributedDataParallel
from mmcv.runner import get_dist_info, init_dist, load_checkpo... |
adcd2ba95e6038e6e4476fa5693911b7af1ed4a299ba408d518100acd63b561f | Python | 8,302 | 253 | """ Summary
This script parses the metainformation to generate a dataset. First the
arxiv-metadata-oai-snapshot.json
file from the arXiv dataset is parsed. The author names are extracted and
only authors who gave a full (>= 2 letters, no initials like L.B.) first
and lastname are considered. This is to reduce the au... |
59e27f05c92da84e54eae36f76036a94214be5db7c50e495ff0af4dfa8ed5de5 | Python | 8,305 | 272 | # SPDX-License-Identifier: LGPL-3.0-or-later
"""Topologies an atomic model declares beside its neighbor graph.
An interaction that the short-range neighbor graph cannot describe reads a
topology of its own, declared by name (see
:meth:`~deepmd.dpmodel.atomic_model.base_atomic_model.BaseAtomicModel.required_topologies`... |
eeef855975ce96495aff7db54efa777932436d44b4f93c92be3690ff7d49187c | Python | 8,306 | 313 | import os
import json
from pathlib import Path
from ElastixLib.utils import createTempDirectory
import slicer
from typing import List, Union, Dict
# for caching instead of persistently creating new preset for each node in the scene
InScenePresets = {}
ID_KEY = "id"
MODALITY_KEY = "modality"
DESCRIPTION_KEY = "descr... |
d920b4e82440fef894fdfec74dbd12b0f6310ad8902bc2cb1a933d8ba4058300 | Python | 8,308 | 238 | # 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... |
e64c99331f3283ccf655d28850dc3d3d83f0414fd7e18319a16ef8aa07dd0abe | Python | 8,310 | 198 | #!/usr/bin/env python3
from Bio.PDB import PDBParser
from Bio.PDB.MMCIFParser import FastMMCIFParser
from Bio.SeqUtils import seq1
from Bio.PDB import DSSP
import numpy as np
import warnings
import pandas as pd
import argparse
import logging.config
import sys
import csv
from pathlib import Path, PurePath
import tempfi... |
11b001abf99e062dbe95dad88f7014d0965a9be50b426a5b892f19ac34179427 | Python | 8,318 | 243 | # 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... |
ac76e4c9bb1eae7280b5d63bec25c9e843a39646aba889aaf58f89fdefb6ef23 | Python | 8,327 | 188 | #!/usr/bin/env python
import dxpy, dx_utils, os, subprocess, re, matplotlib, pylab, multiprocessing
matplotlib.use('Agg')
import pylab
import os
GENERATOR_FILENAME = 'generators.txt'
MAX_KMER_COVERAGE = 1000
NUM_LINES_TO_SNIFF = 1000
GENOMESCOPE_MIN_COL = 30
GENOMESCOPE_MAX_COL = 48
def _run_cmd(cmd):
print subpr... |
822b3c695b4060a032df9c19880f275fb788bfd3f6eab9a8017710d7eea71bc2 | Python | 8,332 | 233 | # 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... |
816f955ab769e472e0e43fed5b8d740b95e402b77b5bc74db64febc1bfb6b576 | Python | 8,335 | 246 | # Copyright 2019-2021 The AmpliGraph Authors. All Rights Reserved.
#
# This file is Licensed under the Apache License, Version 2.0.
# A copy of the Licence is available in LICENCE, or at:
#
# http://www.apache.org/licenses/LICENSE-2.0
#
import ampligraph.datasets
import ampligraph.latent_features
from ampligraph.ev... |
c3ad7f815d91e3e8188c3e859b67a21e8564bd246900adccc8e739ebbea5ec44 | Python | 8,336 | 272 | # Copyright (c) ONNX Project Contributors
#
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import importlib.util
import sys
from datetime import date
from pathlib import Path
from urllib.parse import parse_qs, urlsplit
import pytest
SCRIPT_PATH = (
Path(__file__).parents[2]
/ ".agen... |
ea2f1ceddd7d2155e8eec090d464564fc1511a32c1bee23a26487b69cb590d27 | Python | 8,337 | 309 | """
[Legacy]
optimize_dynamics.py
Routine which attempted to determine network parameters
using basic desirable network characteristics as objectives.
"""
import smtplib
import numpy as np
import matplotlib.pyplot as plt
from test_utilities import mmcs, dynamic_parameterise
from extended_ring_model import *
from dict... |
a1f991255c09d2a108dd4880407e9e8f0713261d508e72546dec2c0d13f93972 | Python | 8,342 | 198 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
from typing import TYPE_CHECKING, Any
import pytest
import onnx.shape_inference
from onnx import (
GraphProto,
ModelProto,
NodeProto,
TensorProto,
TypeProto,
ValueInfoProto,
... |
4f99bd8da846232854b23d3e5aab12b902306df6efa0b1a58ac53de6308f163d | Python | 8,343 | 257 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Jul 7 23:30:33 2021
Run gridsearch to fit SHJ
@author: robert.mok
"""
import os
import sys
import numpy as np
import torch
import itertools as it
import time
from scipy import stats
import pickle
location = 'cluster' # 'mbp' or 'cluster' (cbu clust... |
895f4688a1ebd20c6739655360a08748c8b64a0a66ce9bf982abc39383411c11 | Python | 8,343 | 295 | # BASILISK: A generative, probabilistic model of side chains in proteins
#
# Copyright (C) 2010 Tim Harder and Jes Frellsen
#
# BASILISK is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 ... |
cd3002ef562e33ad49b5a05b2e13ef8dfeb9027a518219f66829ff140bb8544f | Python | 8,344 | 240 | #!/usr/bin/env python3
#!/usr/bin/env pypy3
"""Format ontology files using a uniform ttl serializer from rdflib
Usage:
ttlfmt [options]
ttlfmt [options] <file>...
Options:
-h --help print this
-v --verbose do something fun!
-a --vanilla use the regular rdflib turtle serializer
-y -... |
57a570e63347819008b9f387b10002fbc830b838182a2761017f85ed592bdad2 | Python | 8,346 | 247 | # 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... |
8488a67a1434d0a42c099579c004646b62a66063e8af7bb7a160cf0217f3b9e6 | Python | 8,347 | 273 | """M5 competition dataset."""
from pathlib import Path
import pandas as pd
from sktime.datasets._data_io import _reduce_memory_usage
from sktime.datasets._dataset_downloader import DatasetDownloader
from sktime.datasets.forecasting._base import BaseForecastingDataset
class M5Dataset(BaseForecastingDataset):
""... |
4207aaf7ee116f5d2e4aa4efb93bfc4fffc15081289aac64ec2a449e1718b46a | Python | 8,349 | 238 | """run_infer.py
Process slides with IGUANA.
Usage:
run_infer.py [--gpu=<id>] [--model_path=<path>] [--model_name=<str>] [--data_dir=<path>] \
[--data_info=<path>] [--stats_dir=<path>] [--output_dir=<path>] [--batch_size=<n>] \
[--fold_nr=<n>] [--split_nr=<n>] [--num_workers=<n>]
run_infer.py (-h | --help)... |
7e513b76e6633776a42c99856ad40be803e1dd0db54edb1a1e6ac8a13e192693 | Python | 8,349 | 329 | import re
import numpy as np
def extract_data_from_logfile(tag, parameters):
params_compiled_list = [
re.compile(r"[-]" + f"{p}" + r"\s+=\s+(\S+)$") for p in parameters
]
p0 = re.compile(r"[=]+\sInitialization\sdone[\s\S]+")
p0_lv = re.compile(r"LV\sCavity\svolume\s=\s(\d+\.\d+)")
p0_rv =... |
a5c4fd76d1568a3f9b628982405087e68fb3b63c3a7146ab10567c532081e68e | Python | 8,355 | 301 | import argparse
from multiprocessing import Manager
import os
from pathlib import Path
import warnings
import hydra
from joblib import Parallel
import numpy as np
import pandas as pd
import pytorch_lightning as pl
from pytorch_lightning.callbacks import ModelCheckpoint
from pytorch_lightning.utilities.warnings import ... |
84e2b321e1da6a7d588e02756f5b0ed89e69aa07a2c193d93504d47949b2b65b | Python | 8,356 | 261 | # copyright: sktime developers, BSD-3-Clause License (see LICENSE file)
"""
Base class template for data sets.
class name: BaseDataset
Scitype defining methods:
loading dataset - load()
loading object from dataset - load(*args)
Inspection methods:
hyper-parameter inspection - get_para... |
b0ca887e666c728697748b41f2f290268ad980f115607ec023b1a9eb2be3f25d | Python | 8,357 | 243 | # An extension to: Mocapy
#
# Copyright (C) 2007 Jes Frellsen, Ida Moltke and Martin Thiim
#
# This library is free software: you can redistribute it and/or
# modify it under the terms of the GNU General Public License as
# published by the Free Software Foundation, either version 3 of the
# License, or (at... |
f14fbed6a34c192837171634f572dd904a0e6dfa521f1e716026e1fce2930251 | Python | 8,358 | 186 | import numpy as np
import pandas as pd
import collections as col
import logging
import os
import re
import sys
import scipy.spatial
import parallel as par
import click
sys.path.insert(0, '../../..')
import atom3d.datasets.datasets as da
import atom3d.splits.splits as spl
import atom3d.util.file as fi
import atom3d.uti... |
07887b6279fb93879a7a3755c799aa4c3bf45ac3a38e83cdb36807267273a391 | Python | 8,360 | 256 | # 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 argmax_use_numpy(data: np.ndarray, axis: int = 0, keepdims: int = 1) -> ... |
cbfe04d03919315d2c0034bfb36053767718556d863f34a5cdb4fe10368b2680 | Python | 8,360 | 307 | # 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 ...seed import (
GLOBAL_SEED,
)
from ..common import (
eval_model,
)
dtype = paddle.float64
model_se_e... |
7096846332bf5247b7c12b1891696dad35828ef67b683ec087f8f694d863dcac | Python | 8,366 | 227 | # Copyright (c) OpenMMLab. All rights reserved.
import copy
from abc import ABCMeta, abstractmethod
import mmcv
import numpy as np
from torch.utils.data import Dataset
from mmcls.core.evaluation import precision_recall_f1, support
from mmcls.models.losses import accuracy
from .pipelines import Compose
from sklearn.me... |
87d167af8849debb91476ec8e94341992a2ddda8625bdf4e8dfafd5d777a0ec7 | Python | 8,369 | 148 | # this program calculates the binary filtering of UMLS concept extraction for radiology reports from the 'for validation - 1000 docs - ori - MIMIC-III-rad.xlsx' sheet.
from sklearn.metrics import precision_score, recall_score, f1_score, confusion_matrix
import numpy as np
import pandas as pd
import sys
# input... |
6ce2d757fd2e0b2a8595aa1f1633eda04097bf309bbafbd01d7a325c3f5237a7 | Python | 8,371 | 223 | from scripts import data_handler as dh
from scripts import ensemble_util
import numpy as np
import scipy as sp
import os
from keras.models import load_model, Model
import keras
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import pandas as pd
import pickle
def postprocess(config)... |
7264dea945385c9079bf3d5fddfc980e573e0e12d8615473a5c0815b6250dfea | Python | 8,377 | 208 | """
This plots figure 6f of the paper.
This is the psychometric fit of the behaviour output of the naive model.
Internal notes:
This is from notebook 21.22
Note that it currently requires xarray == 0.19.0
TODO: there are some pickle files that should be convereted to something more readable
"""
import pandas as pd
... |
949bdf1fdd94dc12cb2fd86211a5d9423588a14187b18c608aa92edcfa89e8a3 | Python | 8,377 | 249 | # SPDX-License-Identifier: LGPL-3.0-or-later
"""JSON Schema for model presets and grouped data input forms."""
import json
import re
from typing import (
Any,
)
from deepmd.utils.model_preset_data import (
MODEL_PRESETS,
)
_REGIONS = ("type_map", "descriptor", "fitting_net")
def with_data_groups(schema: di... |
e87f8f816b17c29ad010cb4f19db36556809ebfae464b4061e9cf962bfd7e27e | Python | 8,378 | 243 | # 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
#
# ... |
93c78c663720f931195eafc3d9e8be0379cb8c912b578b68b5ef014bf44b8be1 | Python | 8,382 | 215 | # 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... |
14619439a662850f3e4219148984822eb12cbed6ae0bd63d965abae638424875 | Python | 8,385 | 284 | # 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... |
997dcd63de4b6cf1179c4df6b8306022d96e701a101b1d99bf6602c20c680186 | Python | 8,391 | 245 | # SAFE TEAM
#
#
# distributed under license: CC BY-NC-SA 4.0 (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.txt) #
#
from compiler_provenance.utils import __padAndFilter as padAndFilter
from asm_embedding.InstructionsConverter import InstructionsConverter
from asm_embedding.FunctionNormalizer import Func... |
b25210892a0ab73b6ab1bc550b291d25d7e01e5ae7a1bff556740c7361ae672f | Python | 8,391 | 206 | #!/usr/bin/env python
import sys
import os
import re
import math
from os.path import isfile, join, isdir
import time
from kn_common import pipetools,pipedef
from kn_pipeline_class import CPipeError,CPipeStep
class CPipeStepAxonFilt(CPipeStep):
jobids=[];
def wait_for_jobs(self,progress_scale=(0,1))... |
2d881a87bb2ebff8658fd334d41b8a5d5ef195eea53be0f1e060ba7ee84e91f3 | Python | 8,393 | 188 |
#funkcija za feature selection i optimiaciju ELM parametara (broj neurona u skrivenom sloju i weights i biases)
#Funkcija moze da radi samo fs+hyper-parameter tuning ili samo hyper-parameter tuning
# 1. Ako je nfeatures=0 i features_list=[naka lista] onda se radi samo hyper-parameters tuning sa odredjenim subset fe... |
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