sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
fb527d0126c428dbf2560456a4ed65f3a238d6057d956cb2bbd21bdad8832fb6 | Python | 19,991 | 579 | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
import torch.nn as nn
from mmcv.cnn import ConvModule
from mmcv.utils.parrots_wrapper import _BatchNorm
from mmcls.models.backbones import ResNet, ResNetV1d
from mmcls.models.backbones.resnet import (BasicBlock, Bottleneck, ResLayer,
... |
c1896d50549b80d6c00afb156ddd2b7599efd50232b689ab2ebeaf7df27da995 | Python | 20,003 | 521 | #!/usr/bin/env python3
#!/usr/bin/env pypy3
__doc__ = f"""Generate NIF parcellation schemes from external resources.
Usage:
parcellation [options]
Options:
-f --fail fail loudly on common common validation checks
-j --jobs=NJOBS number of parallel jobs to run [default: 9]
... |
7949fffc4c50ba2be230af8e3ae25ded1903049038d5d14aaf4bcf99254464b5 | Python | 20,026 | 435 | import numpy as np
import numpy.typing as npt
from scipy.stats import rankdata, t, f
from typing import Optional
def pearson_coefficient(
feature_arr: npt.NDArray[np.float64],
joint_dist: npt.NDArray[np.float64],
permutations: int,
) -> npt.NDArray[np.float64]:
r"""
Let X, Y be two random variable... |
d3a572d4405184dbfc9013401b61735b9b920c2677761bae388591541883030b | Python | 20,032 | 643 | import os
import copy
import h5py
import pytest
import numpy as np
from os.path import join as pjoin
from dnnbrain.io import fileio as fio
from dnnbrain.dnn import core as dcore
from dnnbrain.dnn.base import dnn_mask, array_statistic, dnn_fe
DNNBRAIN_TEST = pjoin(os.environ['DNNBRAIN_DATA'], 'test')
TMP_DIR = pjoin(o... |
5de0a2b1aae8bf17cc124620754c82c0a281fce2a24eb200e5ba631f1b512a54 | Python | 20,041 | 603 | # 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... |
7733a00911b3efa4b73e5008b24a63f8a3219ff4daa5609587a03e0a565d1242 | Python | 20,058 | 589 | import pytest
import numpy as np
from scipy.linalg import inv
from scipy.ndimage import rotate
import ardent
from ardent.lddmm import register
from ardent.lddmm.lddmm import _generate_position_field
from ardent.lddmm.lddmm import _apply_position_field
from ardent.lddmm import apply_transform
def convert(array):
... |
75aacdb09bca8d5115cd3f3bf8a58303dd85ea7a64eaa81772a54e1d09ee48b3 | Python | 20,059 | 576 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import automatic_conversion_test_base
import numpy as np
import pytest
import onnx
from onnx import helper
#####################################################################################
# Every ... |
879aa87b092907ad5cc5de422a7c67ca6ed8f41106e244e15e183f269d2a71f4 | Python | 20,065 | 405 | #!/usr/bin/env python
#
# Copyright 2006, Google Inc.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redistributions of source code must retain the above copyright
# notice, this list... |
dad088f7ed86eb3bd3eff13a0121a6974563e37b82c68c793a879d54f46461c6 | Python | 20,071 | 502 | """For analysis of correlation results
"""
from robustlink._init_plots import *
from robustlink import enhancer_gene_utils
KB = 1000
def p25(x):
return np.nanpercentile(x, 25)
def p75(x):
return np.nanpercentile(x, 75)
def estimate_frac_tps(pvalues, bin_n=100, frac_bin_null=0.20):
"""Use the median of th... |
999df52d625ca59ee13a8c6d630f813e5dd7028b72bf04af404df278a1489296 | Python | 20,112 | 639 | # 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... |
8de0bebe8f7d579aec651899897a6d9db539b4c92cd65ddf347cc2fdb0c4fe6a | Python | 20,126 | 351 | #!/usr/bin/env python3
"""
GIFT-Eval evaluation of a pretrained PatchTST-FM, zero-shot or prompt-tuned.
--mode zs bare backbone (prompt_len=0 through the same wrapper path)
--mode prompt load a train.py checkpoint (--ckpt)
Both modes share ONE predict path (PromptedPatchTSTFM.forward), so the
prompt-vs-zero... |
da756347254775fd7a14756a8d3fbbc36785976d93530744c84ecd3da6129adb | Python | 20,140 | 544 | import os
import cv2
import copy
import torch
import pytest
import numpy as np
from PIL import Image
from os.path import join as pjoin
from sklearn.svm import SVC, SVR
from sklearn.model_selection import cross_val_score
from torchvision import transforms
from dnnbrain.dnn import base as db_base
import matplotlib.pyplo... |
e785993c9162de4db08f872e719b96135e6888a8b61c1e208b7aa27f7fb719b6 | Python | 20,149 | 619 | # -*- coding: utf-8 -*-
"""
Created on Sun Dec 31 16:25:15 2017
@author: Tiger
"""
""" Retrieves validation images
"""
import numpy as np
#from PIL import Image
from os import listdir
from os.path import isfile, join
from skimage import measure
from natsort import natsort_keygen, ns
import os
import pickle
#import s... |
e755e0d762dee1f2606320822aae5bfd23c3006f3dbeb96ae4c3f004c7e431b5 | Python | 20,170 | 609 | # 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... |
39f182d1eba0e3c6a161e3443d2d6c92c52359f27a7710127b707f09bc4d5c89 | Python | 20,192 | 648 | from __future__ import annotations
import logging
from typing import TYPE_CHECKING
import numpy as np
import pytest
from mock_data_stream import MockStreamData
from pyxdf.pyxdf import _clock_sync
if TYPE_CHECKING:
from typing import Literal
@pytest.mark.parametrize("n_clock_offsets", list(range(5)))
@pytest.m... |
af4bd180f9475aeac7b665bb2582d0fcec3be3210891b26f0a302113c8610e7a | Python | 20,192 | 232 | """
Vector strength for models with SAM tones, different input configurations.
9 Dec 2020 version.
Results are printout from DataTablesVCN after selecting the data runs.
pbm
"""
data = """Cell,Configuration,frequency,dmod,dB,VectorStrength,SpikeCount,phase,phasesd,Rayleigh,RayleighP,AN_VS,maxArea,ninpu... |
6b4b6414ce04cac0a1d903d19b507a6bd0ca0766ba25c7a76b0dd3e3802d2758 | Python | 20,198 | 423 | # Options
addRawFeat = True
base_path = ''
feature_networks_integration = ['clinical', 'cna', 'exp'] # datatypes to concatanate node features from
node_networks = ['clinical', 'cna', 'exp'] # datatypes to use networks from
int_method = 'MLP' # Machine Learning method to integrate node embeddings: 'MLP' or 'XGBoost' or ... |
4dfeda0adaa4dfbcf3f16dfbd62256b9550813e5fcd28839a37db715586b571e | Python | 20,200 | 552 | #!/usr/bin/env python3
# Copyright (C) 2019 Christoph Gorgulla
# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# This file is part of VirtualFlow.
#
# VirtualFlow is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the... |
476cf8b67131d546ba093dc8c1260be05a8084547116469de3e59d936ac92f53 | Python | 20,203 | 594 |
import numpy as np
import pandas as pd
import matplotlib as mpl
from matplotlib.colors import same_color, to_rgb, to_rgba
from matplotlib.markers import MarkerStyle
import pytest
from numpy.testing import assert_array_equal
from seaborn._core.rules import categorical_order
from seaborn._core.scales import Nominal, C... |
5c6fe740b3e83d4cf5c910110b4384a633a299841cf9ee159653b5121da243c1 | Python | 20,213 | 563 | # 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... |
a1640cc3f2400ace40d7a873b6bb48ceed617ccea0cd35c5d583661218f5ef4a | Python | 20,217 | 494 | """
@file: input_representation
Created on 06.07.23
@project: CrazyAra
@author: queensgambit
Default input representation for all available lichess chess variants board states (including crazyhouse)
which is passed to the neural network. This default representation usually refers to version 1.0 of the respective MODE... |
e71a754ce5635830f1ee45f326038f4fe1b82d87b068933aca321c768c8c0e99 | Python | 20,249 | 530 | import csv
import rdflib
import augpathlib as aug
from pyontutils import sheets
from pyontutils.namespaces import TEMP, ilxtr, rdfs, skos, interlex_namespace
from neurondm.models.nlp import map_predicates, main as nlp_main, NeuronSparcNlp
from neurondm.models.apinat_npo import NeuronApinatSimple, NeuronApinatComplex
fr... |
717cd1bbdf73fc4180ae4c0f94b098cd5e49511470fdf52158376842b448465c | Python | 20,254 | 631 | # 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... |
546ee87a33690bf06f506642810c4024400af74e325f934fb3f1c62f7756bb95 | Python | 20,278 | 583 | # Copyright (c) ONNX Project Contributors
#
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
import onnx
from onnx import TensorProto, helper
from onnx.backend.test.case.base import Base
from onnx.backend.test.case.node import expect
from onnx.defs import AI_ONNX_PREVIEW_DOM... |
91df9f37e0242a77c70d43d828495884fb769f943f7adb84e1a3804bc8762fd9 | Python | 20,304 | 574 | """Unit tests for classifier base class functionality."""
__author__ = ["mloning", "fkiraly", "TonyBagnall", "MatthewMiddlehurst", "achieveordie"]
import pickle
import numpy as np
import pandas as pd
import pytest
from skbase.utils.dependencies import _check_soft_dependencies
from sklearn.model_selection import KFol... |
ebe27efaa864f5dba088c96def57d8c1cc49ebdfc146e7ebd10acc05f54dc5f7 | Python | 20,316 | 296 | import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from itertools import compress
import numpy.ma as ma
from scipy.stats import norm
from scipy import stats
import os
import scipy
import sys
from numpy import savetxt
from PIL import Image
from sklearn.linear_model import LinearRegression
sys.path.i... |
87f72a6bd079837ae5fa4a907223c5ad0364f4bab79a1f69a7debba495a6ed48 | Python | 20,339 | 462 | '''
This is the main module of EVOLVE.
It initialises the genetic algorithm search,
determines initial fitnesses for each evaluator and then loops over the generations.
.. codeauthor:: Nicholas Browning
.. codeauthor:: Simon Duerr dev@simonduerr.eu
'''
from __future__ import division
from __future__ import print_func... |
621d26ecbd83b96903a3d0e1e5d2f6f73187c044065c96811496b4a88e673344 | Python | 20,348 | 782 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Jun 26 09:30:55 2019
@author: reiters
"""
#careful to include only full AS bouts with good posture to not bias any measurement of differences
from geosketch import gs
import numpy as np
import h5py
from sklearn.decomposition import PCA
import cv2
import... |
265f50cbedbe191cc03b6dfba167a585de0bb9a6ae5ca9083f877c0e9859f604 | Python | 20,365 | 581 | # 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... |
b69f6ea296dfd35bd8cee8cb6f599122e045183719984373bab7fa204d8e789c | Python | 20,379 | 464 | from pathlib import Path
import os
from statistics import mean
import matplotlib.pyplot as plt
from akkadian.build_data import build_signs_and_transcriptions, break_into_sentences
from akkadian.data import from_key_to_text_and_line_numbers
from akkadian.parse_xml import parse_xml
from akkadian.data import increment_cou... |
b0879ebe89ab0f6c484a24846dfc195a5c85dcdd85a312ed679796e3ae85ad09 | Python | 20,431 | 404 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import json
import logging
import os
import shutil
import time
import dill
import numpy as np
import ray
from mprl.utility_services.payoff_table import PolicySpec
from mprl.utility_services.worker import Learn... |
8a7729736e47da575dd574c48676527d51c420d7b5f710f39ac89c97440cd127 | Python | 20,478 | 518 | """Functionality to compute Gromov-Wasserstein distances \
using algorithms in Peyre et al. ICML 2016."""
from __future__ import annotations
import csv
# std lib dependencies
import itertools as it
import sys
from typing import Iterator, List, Optional, TypeVar
if "ipykernel" in sys.modules:
from tqdm.notebook ... |
eae50d5bbb573d975f560acf78bbcacfefc1020762059ee6ca938dedd69e7e8c | Python | 20,494 | 650 | # 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... |
45c90417383279eb901d2c9c2ae3d637e6f777cea353b2837d9e5db2f89641a1 | Python | 20,512 | 518 | # copyright: sktime developers, BSD-3-Clause License
"""Implementation of Double Machine Learning methodology for forecasting."""
__all__ = ["DoubleMLForecaster"]
__author__ = ["geetu040", "XAheli"]
import math
import pandas as pd
from skbase.utils.dependencies import _check_soft_dependencies
from sklearn.base impor... |
4e1a08fee3e7e6319b619786a8018643cad9e863595cfca9731cc934e4e6305a | Python | 20,522 | 554 | # SPDX-License-Identifier: LGPL-3.0-or-later
"""pt_expt native-spin energy model (NeighborGraph route, autograd force_mag)."""
from typing import (
Any,
)
import torch
from torch.fx.experimental.proxy_tensor import (
make_fx,
)
from deepmd.dpmodel.model.native_spin_model import (
make_native_spin_model,
... |
08eee574da28d63683c8e88f0623234b6511935edb54e038f4a4f10d67a965e8 | Python | 20,530 | 642 | """
A special directive for generating a matplotlib plot.
.. warning::
This is a hacked version of plot_directive.py from Matplotlib.
It's very much subject to change!
Usage
-----
Can be used like this::
.. plot:: examples/example.py
.. plot::
import matplotlib.pyplot as plt
plt.plot... |
a253e9ec100b6216d3708021f722e76267add9d92ceb275538e6f05f237b7c53 | Python | 20,557 | 461 | from IPython.core.debugger import set_trace
import numpy as np
from math import *
import tensorflow as tf
import scipy as sc
from scipy.linalg import block_diag
from src.utilities.helper_classes import integrate_simp_cumsum, vander, diagonalize
tf.keras.backend.set_floatx('float32')
#### User-defined parameters
cla... |
1d72e96085d6bd3d03d597b78dcff4bfb25bc6ad0d6c268c7483e2be4258f763 | Python | 20,569 | 445 | import sys
import hashlib
from collections import defaultdict
import rdflib
def bnodes(ts):
return set(e for t in ts for e in t if isinstance(e, rdflib.BNode))
class IdentityBNode(rdflib.BNode):
# TODO this requires a new serialization rule which 'disambiguates'
# subgraphs with the same identity that a... |
727b1180f91b0c583211a1dd6073760ce787d745b63a17620d16d219763cf618 | Python | 20,593 | 442 | import sys
import numpy as np
import torch
import time
import pickle
from sns_toolbox.neurons import NonSpikingNeuron, SpikingNeuron
from sns_toolbox.connections import NonSpikingSynapse, SpikingSynapse
from sns_toolbox.networks import Network
# Personal stuff to send an email once data collection is finished
# sys.p... |
0bbeb378e92d79556c738974096725a336e0f7a2e3a97c3c6d118d3179e3a0c4 | Python | 20,635 | 440 | # GNU LESSER GENERAL PUBLIC LICENSE
# Version 3, 29 June 2007
#
# Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/>
# Everyone is permitted to copy and distribute verbatim copies
# of this license document, but changing it is not allowed.
#
#
# This vers... |
45e4cbaf959a6f94714b195636372cf267e77f5d79a8ed109eb733ac7ccdacab | Python | 20,642 | 396 | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Mon Mar 6 10:45:19 2017
@author: tpisano
Goal is to register 1p/2p timeseries to 2p volume to LS signal to ABA
To do:
1) Incorporate resolution of each image
2) Utilize ability to select region of atlas to register to
Possibly have to use elast... |
de53fc37c1e8919d3f1d46e339c0bc07eba25bb2d85b2355e5abd2ad53120237 | Python | 20,645 | 523 | """Base class for clustering."""
__author__ = ["chrisholder", "TonyBagnall", "achieveordie"]
__all__ = ["BaseClusterer"]
import time
import numpy as np
from skbase.utils.dependencies import _check_estimator_deps
from sktime.base import BaseEstimator
from sktime.datatypes import check_is_scitype, convert_to, scitype... |
79075525e713e8c9fa1a9c3ba5b0674a3fb995fe3b1f187b21cf3bbbe7b6f66a | Python | 20,662 | 473 | import os
from quicknat import QuickNat
import nibabel as nib
import numpy as np
import logging
import torch
import csv
import utils.common_utils as common_utils
import utils.data_utils as du
log = logging.getLogger(__name__)
def dice_confusion_matrix(vol_output, ground_truth, num_classes, no_samples=10, mode='train'... |
5d850a1ae8c16a0c56fdc84d858f7be475884d008c940525b823a3f3a25c9e67 | Python | 20,673 | 432 | # Copyright 2007 Zachary Pincus
# This file is part of CellTool.
#
# CellTool is free software; you can redistribute it and/or modify
# it under the terms of version 2 of the GNU General Public License as
# published by the Free Software Foundation.
from . import svg_draw
import numpy
import copy
_GENERIC_DECENDER = ... |
b870fe10757d7a4214453f81755b8755440a6d3e9f621e39d1831c401c99f526 | Python | 20,675 | 493 | #!/usr/bin/env python3
import rdflib
from pyontutils.namespaces import ilxtr, rdfs
from neurondm.core import LocalNameManager
from neurondm.lang import Phenotype, EntailedPhenotype, Neuron, NeuronEBM, Config
slp = 'ilxtr:hasSomaLocatedIn'
sllp = 'ilxtr:hasSomaLocatedInLayer'
alp = 'ilxtr:hasAxonLocatedIn'
dlp = 'ilxtr... |
e4a5df3a131434ac3b81bd366bb7a21431a4ece0b7416564dc2793993e963840 | Python | 20,680 | 550 | # 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... |
a2add05d0d12b5e830f201a19b3cae458524f20eea86b10b5c82f868c261bd49 | Python | 20,686 | 544 | # SPDX-License-Identifier: LGPL-3.0-or-later
"""Parity tests for SeZM LAMMPS multi-rank (edge-based) inference.
The parallel path expands the descriptor node set to the extended region and
refreshes ghost-node features through ``deepmd_export::border_op`` between
interaction blocks. A single process can emulate one MP... |
b00450544e2231d4ac162e3b1f0da94445e88f3b73c7062d0671f154634bc2a6 | Python | 20,711 | 660 | # 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... |
891d3e89f1cbe39a203584adb1033dee374850cd2b58ba94e1a791addeba8217 | Python | 20,716 | 507 | import logging
import numpy as np
from ray.rllib.models.modelv2 import ModelV2
from ray.rllib.models.tf.tf_modelv2 import TFModelV2
from ray.rllib.models.tf.misc import normc_initializer, get_activation_fn
from ray.rllib.models.catalog import ModelCatalog
from ray.rllib.policy.rnn_sequencing import add_time_dimension
... |
178250601519128954780746928e5e2fde48ab3bcdb9290384a477649241fdf3 | Python | 20,761 | 468 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Jul 4 11:38:51 2021
@author: Mesfin Diro
"""
import os.path as osp
from typing import Callable, List, Optional
import torch
from torch_geometric.data import InMemoryDataset, Data
import numpy as np
import re
from tqdm import tqdm
#from tqdm.notebook im... |
779f0d704d567bc38b1bad72e8ef894b98780bf4300e72761a31b46ba1cc4e25 | Python | 20,809 | 458 | #!/usr/bin/env python
############################################################################
# Copyright (c) 2015-2019 Saint Petersburg State University
# Copyright (c) 2011-2015 Saint Petersburg Academic University
# All Rights Reserved
# See file LICENSE for details.
###########################################... |
63afad3bd42db6a24de6341cee60a06ece8cf66198bab90703d473b009b8a212 | Python | 20,834 | 399 | from __future__ import print_function
import pickle
import warnings
import numpy as np
from emgProcessing import emg2feature
from stageLabelAndOneHot import constructPastStagesOneHots, oneHot2stageLabel
# from processFeatures import trimFeatures
class StagePredictor(object):
def __init__(self, params, extractor, ... |
857af77530f6a34dbfac109ba4d7227f54f2dabc7110c705877858cd31d206c9 | Python | 20,841 | 589 | # 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... |
2431515249e9f01df2ba61fe0ec44274dbdb058fd23eed49817859235d668c9f | Python | 20,889 | 421 | #-------------------------------------------------------------------------------
# elftools: dwarf/locationlists.py
#
# DWARF location lists section decoding (.debug_loc)
#
# Eli Bendersky (eliben@gmail.com)
# This code is in the public domain
#---------------------------------------------------------------------------... |
c6ccba965c014815014c30ed5ab999441ce59f30a722df99b0c2d286e111ef4a | Python | 20,893 | 424 | """
@file: builder_util_symbol.py
Created on 06.12.19
@project: CrazyAra
@author: queensgambit
Utility methods for building the neural network using MXNet symbol API
"""
import math
import mxnet as mx
from DeepCrazyhouse.configs.main_config import main_config
def get_act(data, act_type, name):
"""Wrapper method... |
ef19d5c6e8ddb0ca51595ea9e6c9ef5da4aec5eb567a0a9a65f75456ae18ce41 | Python | 20,908 | 550 | # SPDX-License-Identifier: LGPL-3.0-or-later
"""Expansion of the ``bridging_method`` sugar into its canonical config form.
A bridged model IS a linear composition: the learned model plus an
analytical inner potential, summed by ``linear_ener``. The canonical
config spelling is therefore::
"model": {
"type... |
82a4c36eece92cca6fa8615e3e295232884de8cd60c9e5a4ed5c4dd69d5a46c5 | Python | 20,917 | 509 | # 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... |
b1a7bbfaf263c65cc920ff5ff5f6bfb764cdc58f80c2c926093f0e6112981697 | Python | 20,938 | 445 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import json
import logging
import os
import shutil
import time
import dill
import numpy as np
import ray
from mprl.utility_services.payoff_table import PolicySpec
from mprl.utility_services.worker import Learn... |
0ae657a93c41a18835b76e836ec2c4b4a1b970290d2fcd21b416e69b95c95928 | Python | 21,045 | 395 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import json
import logging
import os
import shutil
import time
from socket import gethostname
import dill
import numpy as np
import ray
from mprl.utility_services.payoff_table import PolicySpec
from mprl.utili... |
a0894bd237c8323c3a270d232027a106bac2b1e3ebd6fbbca20e4d1655f18bd2 | Python | 21,045 | 395 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import json
import logging
import os
import shutil
import time
from socket import gethostname
import dill
import numpy as np
import ray
from mprl.utility_services.payoff_table import PolicySpec
from mprl.utili... |
4e0f45ec9b3027a256c3a1a02fe9660df3e08d483acd9990733ed833a3d30aae | Python | 21,053 | 617 | # copyright: sktime developers, BSD-3-Clause License (see LICENSE file)
"""ARAR forecasting model."""
__all__ = ["ARARForecaster"]
__author__ = ["Akai01"]
import math
import warnings
import numpy as np
import pandas as pd
from scipy.stats import norm
from sktime.forecasting.base import BaseForecaster
def _setup_p... |
a126982a50d1a130880d0b04d750cb6e7b74bd3b4ef719f3ecd5cb1d3013b0d0 | Python | 21,081 | 600 | """Testing advanced functionality of the base class."""
# copyright: sktime developers, BSD-3-Clause License (see LICENSE file)
__author__ = ["fkiraly", "ciaran-g"]
from functools import reduce
from operator import mul
import numpy as np
import pandas as pd
import pytest
from pandas.testing import assert_series_equ... |
02b01026c101c17521f034d6959400627d1633971b9293db53bf44818685d296 | Python | 21,084 | 632 | # SPDX-License-Identifier: LGPL-3.0-or-later
import argparse
import copy
import json
import logging
from pathlib import (
Path,
)
from typing import (
Any,
)
import h5py
import paddle
import paddle.distributed as dist
import paddle.distributed.fleet as fleet
import paddle.version
from deepmd import (
__ve... |
6489e6dfc79103e3d3e0b2f973eb95d21539caa4c058bf2e7735f24970e434a2 | Python | 21,108 | 466 | import os
import re
import glob
import numpy as np
import pandas as pd
import dask.dataframe as ddf
import tensorflow as tf
from dask.diagnostics import ProgressBar
import logging
import multiprocessing
from tqdm import tqdm
from lpcomp import LigandProteinComplex
import runner
class FeatureGenerator(object):
"""... |
fb5fbc5bc9036294bddbf2b44545a1a5cda28a089cff75c6b80fbf5e01093125 | Python | 21,120 | 640 | """
author: derricw
2/4/13
core.py
This is just a set of random helper functions that are used by a lot of other files,
as well as the default configuration of various components.
"""
import itertools
import logging
import os
import sys
import platform
import ctypes
import ctypes.util
import ConfigParser
import ... |
0243506e5b3f41a4fc8a1f5804f4512f16ca7a98e80eb13cec1db8b1730e19c7 | Python | 21,128 | 427 | """
@file: builder_util_symbol.py
Created on 06.12.19
@project: CrazyAra
@author: queensgambit
Utility methods for building the neural network using MXNet symbol API
"""
import math
import mxnet as mx
from DeepCrazyhouse.configs.main_config import main_config
def get_act(data, act_type, name):
"""Wrapper method... |
72f2b8fcd832e4c6be5691bff6922cc143b69379107ad1e9b16ef71917044078 | Python | 21,144 | 504 | # SPDX-License-Identifier: LGPL-3.0-or-later
"""Single-rank LAMMPS ``pair_style deepmd`` on the ZBL-BRIDGED DPA4
NeighborGraph (graph-schema) ``.pt2`` (``deeppot_dpa4_zbl_graph.pt2``,
``source/tests/infer/gen_dpa4_zbl.py``).
``bridging_method: ZBL`` builds a COMPOSITION -- ``LinearEnergyModel`` over
``[learned DPA4, I... |
e1c61eb6470f96b422b825da7bde2d9f9d5dd662f1b8f20dac93240050a3841d | Python | 21,180 | 567 | """ShapeDTW classifier.
Nearest neighbour classifier that extracts shapee features.
"""
import numpy as np
import pandas as pd
# Tuning
from sklearn.model_selection import GridSearchCV, KFold
# Classifiers
from sktime.classification.base import BaseClassifier
from sktime.classification.distance_based._time_series_n... |
20e8e79c609094a351318b3bcc72e96fee5004364bf8da48dea4a466c2325ae4 | Python | 21,237 | 443 | #!/usr/bin/env python
"""
Program : rbh_tools.py
Language : python
Date : 2024-02-07
Author : Darrin T. Schultz
Email : darrin.schultz@univie.ac.at
Github : https://github.com/conchoecia/odp
Support : For issues or questions, please search if the topic has been discussed already
on github and op... |
e28f3011870870570d32f00afb85b90b77a52b774155de1269b97d5d67c8f387 | Python | 21,249 | 570 | # SPDX-License-Identifier: LGPL-3.0-or-later
"""Reciprocal-space topologies of the periodic frames of a batch.
A long-range module that serves periodic systems evaluates the lattice sum of
its pair kernel in reciprocal space, which needs the cell of every frame and
the absolute node positions rather than pair displace... |
04b753d3958e8f5be6362ea72e6e8bf52bace576c3eab4eb8693e1149b48670c | Python | 21,250 | 283 | # the program to train and test model and do a rule-based ensembling of the masked and non-masked models, with or without document structure, for rare disease entity linking filtering.
# this program also export the models for later use in the subsequent steps of this project - to be used in step9_processing_all_docume... |
9442d5385a841c13731fa1ef3e40640ff82f2fce5730f1c91e5aaf0f389a8657 | Python | 21,250 | 485 | import numpy as np
import pandas as pd
import scipy.special as sc
from scipy.stats import uniform
from scipy.stats import nbinom
from scipy.stats import gamma
from scipy.stats import norm
from scipy.stats import beta
from scipy.stats import binom
import time
from scipy.stats import poisson
from joblib import... |
2b1ce94fc3d664bdfeabfe238fb72fe6f64b25283388bf23980b5e507100c7ed | Python | 21,261 | 592 | from __future__ import annotations
import argparse
import json
import time
from pathlib import Path
import numpy as np
import torch
from scipy import sparse
from torch.utils.data import DataLoader, TensorDataset
from .data import choose_input_genes, load_dataset, normalize_log_cpm
from .grouping import Pseudocluster... |
b144c8a618dba37b94c0e3d79f23ac2aad197dd6cafabbc22b6a9aa360eb679c | Python | 21,297 | 686 | # 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... |
c66c8e7da5f97ef53df44857305ee81a10e7ef503bf04b00fa3938d062011a54 | Python | 21,315 | 715 | import numpy as np
import pandas as pd
try:
import statsmodels.distributions as smdist
except ImportError:
smdist = None
import pytest
from numpy.testing import assert_array_equal, assert_array_almost_equal
from seaborn._statistics import (
KDE,
Histogram,
ECDF,
EstimateAggregator,
Letter... |
4f613c71230f351e957d92b63c3a86b5a4bfaa1dcc78e22bcc919e7fb3277bcb | Python | 21,323 | 617 | from __future__ import print_function
import os
import re
from pathlib import Path
import collections
import numpy as np
from neuron import h
import neuron
import pyqtgraph as pg
try:
basestring
except NameError:
basestring = str
class HocReader(object):
def __init__(self, hoc):
"""
Pr... |
5edef31550e9a20fff81dfc937e58adfa52a5141eadc7068c3456c0432ee0cf6 | Python | 21,339 | 398 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import json
import logging
import os
import shutil
import time
from socket import gethostname
from termcolor import colored
import dill
import numpy as np
import ray
from mprl.utility_services.payoff_table imp... |
0269a4cca6eec021d92871853e3f217313f0af3dc9d521b7c7b5a0d928a7e0de | Python | 21,348 | 519 | # 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
#
# ... |
45e90fd7dadd6bfa21577c6aea9897bb24dae5e74a647d8dc0e54b3410c6bfc8 | Python | 21,352 | 672 | """
Tests of section/segment areas with 3d geometry
Partially done to try to understand how Neuron calculates and uses area
Also done to determine how to do the rescaling.
This code is the basis for adjust_areas.py, which is used to adjust the
areas in the models dynamicall (upon loading, with reference to the tables
o... |
4a9c444b4e2ecbc46deb87a479f2d56be243bb5108d7760ea5f2e004d10922c9 | Python | 21,359 | 415 | import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from itertools import compress
import numpy.ma as ma
from scipy.stats import norm
from scipy import stats
import os
import scipy
import sys
sys.path.insert(1, "/Users/hyung/Research23_Network_Analysis/mBIN/Python/NetworkAnalysisGeneral/Code/Support... |
05ced3eb4d6edb3f4eb69abb9481b793247d9c9faf4bceec94824b83a4e01854 | Python | 21,365 | 541 | """The Elastic Ensemble (EE).
An ensemble of elastic nearest neighbour classifiers.
"""
__author__ = ["jasonlines", "TonyBagnall"]
__all__ = ["ElasticEnsemble"]
import time
from itertools import product
import numpy as np
import pandas as pd
from sklearn.metrics import accuracy_score
from sklearn.model_selection im... |
49eff189d29a7bca2e05f43395f25a3f76842ff2c18d817764eb4b36f117aaf0 | Python | 21,367 | 677 | """
Functions for feature extraction
"""
import cv2
import numpy as np
import pandas as pd
import uuid
import math
from shapely.geometry import Polygon
from scipy.spatial import distance, Voronoi, Delaunay
from sklearn.neighbors import KDTree
from .bam_utils import get_enclosing_ellipse, ellipse_to_circle, apply_tra... |
9a1e504a34abc22aaad56d8718fcf5b9f01c45f2e81f254283187eda51d81e80 | Python | 21,372 | 532 | # 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 ConvTranspose(Base):
@staticmethod
def export() -> None:
... |
192dd5f3860c98e8ec50a299aada5e167cbaa71b032524f8faa12b44f3c37b90 | Python | 21,405 | 558 | """Greedy Gaussian Segmentation (GGS).
The method approximates solutions for the problem of breaking a
multivariate time series into segments, where the data in each segment
could be modeled as independent samples from a multivariate Gaussian
distribution. It uses a dynamic programming search algorithm with
a heuristi... |
dfa1bcb7c7f123c1dd037c2092ca888618aeefe576bce55cf887cac690bcc325 | Python | 21,424 | 356 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# Copyright © 2013 Charles E. Vejnar
#
# This Source Code Form is subject to the terms of the Mozilla Public
# License, v. 2.0. If a copy of the MPL was not distributed with this
# file, You can obtain one at https://www.mozilla.org/MPL/2.0/.
#
"""Create trackhub"""
i... |
649a4fe23d27f53af11fa63ef15946b6dd8ef2f0a0caf39986cafefe1e790c77 | Python | 21,436 | 460 | """
Based on this:
https://github.com/mitragithub/Registration/blob/master/atlas_free_rigid_alignment.m
"""
'''
- take sequence of arrays, arbitrary shapes
- resample to max of dimensions per dimension into single array
- create a new 3D array where each slice is replaced with a weighted average of its n nearest neig... |
96367368ad9a559ccf52ce5a22e925f8bee57b4401fa0a20b2164a41120168b8 | Python | 21,452 | 691 | # Copyright 2026 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... |
d1541c4f5f8768304bd54fd38ac492a9924928409f2655a8a27b506c3e31f0e8 | Python | 21,494 | 583 | from typing import Dict, List, Tuple, Union
import torch
import numpy as np
import logging
from lgn.cg_lib import CGModule, ZonalFunctionsRel, ZonalFunctions
from lgn.cg_lib.cg_dict import CGDict
from lgn.cg_lib.zonal_functions import normsq4, rep_to_p
from lgn.g_lib import GTau, GVec
from lgn.models.lgn_cg import LG... |
4a2d5c8f4811e2861f2cf2b04aa4baa262cc86b2287c1e30a09e26b5e863689c | Python | 21,500 | 486 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Zero-shot Tabby latent anomaly detection on TSB-AD.
The foundation model is loaded ONCE per worker and reused for every config and
every series -- there is no per-series fitting, so the detector is zero-shot.
Scoring embeds each series with the frozen encoder and score... |
9f419da804353e20691a61ff9697cfa9575e8918a320bab9d715d795ce57a63d | Python | 21,500 | 465 | """
transform dicom data to bids style
"""
import os, glob, string, logging, argparse, subprocess, json
from tqdm import tqdm
import pandas as pd
import numpy as np
from os.path import join as pjoin
class bcolors:
WARNING = '\033[33m'
FAIL = '\033[41m'
BOLD_NODE = '\033[1;32m'
BOLD = '\033[1;34m'
... |
42547967dd0935403ec3c1a16eb64a4343308cf5a8597d1564acd59f36f0bb39 | Python | 21,517 | 586 | #!/usr/bin/env python3
"""This module provide the necessary tools to parse CONTCAR and POSCAR files
and convert them to molecules """
import xml.etree.ElementTree
import itertools
import os
from shutil import move
from collections import namedtuple, Counter
import numpy as np
from pyRDTP import molecule
def read_from... |
5f88804280c61bad4dd5f0ab5a05d72bb07484030526c07772781174640eee49 | Python | 21,521 | 794 | """
Module for generating rdkit molobj/smiles/molecular graph from free atoms
Implementation by Jan H. Jensen, based on the paper
Yeonjoon Kim and Woo Youn Kim
"Universal Structure Conversion Method for Organic Molecules: From Atomic Connectivity
to Three-Dimensional Geometry"
Bull. Korean Chem. Soc. ... |
55a37cd6277c062afd72e1fc541bbdc2e2c6aae21bf5fb9bdd8edc7df05286f1 | Python | 21,533 | 490 | from xiangqi_board.xiangqi_board import XiangqiBoard
from DeepCrazyhouse.src.domain.variants.constants import LABELS_XIANGQI
from ucci_util import xiangqi_board_move_to_ucci, mirror_ucci
import time
import re
import zarr
import math
import logging
import numpy as np
import pandas as pd
from numcodecs import Blosc
cla... |
93060d8e8e3ea23d63f91239d17b56c5c27d17dd0db37e9d82a91b77ca446996 | Python | 21,537 | 609 | """ pattern_summary:
Compute the input patterns, and generate a summary figure
breaking the cells down by 'drivers' and 'coincidence'
for different input patterns.
This also has the routines for plotting panel 4F.
This module is part of *vcnmodel*.
Support::
NIH grants:
DC R01 DC015901 (Spirou, Manis, Ellis... |
771db100873c81f88adb1ee7fa2bffaab0eb102a43ffb65cde2d979de468e1f2 | Python | 21,542 | 558 | import logging
import numpy as np
from ray.rllib.models.modelv2 import ModelV2
from ray.rllib.models.tf.tf_modelv2 import TFModelV2
from ray.rllib.models.tf.misc import normc_initializer, get_activation_fn
from ray.rllib.models.catalog import ModelCatalog
from ray.rllib.policy.rnn_sequencing import add_time_dimension
... |
78d59fcdbe8e6a54b2e417d368d816cc2b980440e79bd46d2dc1f92a075ff70b | Python | 21,571 | 530 | #!/usr/bin/env python3
# SPDX-License-Identifier: LGPL-3.0-or-later
"""Generate the COMBINED native-spin + ZBL-bridging DPA4 .pt2 fixture.
One archive, ``deeppot_dpa4_spin_zbl_graph.pt2``: a native-spin
(``scheme="native"``) DPA4 that is ALSO bridged (``bridging_method: "ZBL"``),
i.e. a ``LinearEnergyModel`` over ``[l... |
e961db5f1a7301673201eb647784d9620c2b54318bf61f5d1620935351c8684c | Python | 21,577 | 449 | #!/usr/bin/env python
import logging
import os
import importlib
import sys
import numpy as np
import pandas as pd
import attention_model
import torch
from torch.utils import data
import torch_visual
from torch import save, load
from time import time
import random
import my_data
from torch import cuda, device
import to... |
1c2f280d88a352a3583fd7382b64ebe5f7b1307768ff2fc570e7be185d3d3e5d | Python | 21,593 | 384 | """
Connections are the mechanisms for data transmission between neurons. They can either define an individual conductance-
based synapse, or a pattern of synapses which is tiled between two populations.
"""
import numpy as np
"""
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
8ab959ef9499f03ff3e72ce6e0b345c792e5bf87958c713f569012bed458e9ff | Python | 21,593 | 610 | # 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... |
d397d171e7d1ad006fc49a2634edeb6ce9472d21dc29aca15938ad79ac58dd95 | Python | 21,594 | 444 | import time
import json
import os
import json
import joblib
from io import BytesIO
import base64
import boto3
import math
import io
import cv2
import numpy as np
# Grab environment variables
TEST_ID = os.environ['TEST_ID']
DETECTION_ENDPOINT_NAME = os.environ['DETECTION_ENDPOINT_NAME']
CLASSIFICATION_ENDPOINT_NAME = ... |
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