sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
ac4e4e5d703a2701f1e6529f48bc2478535751356578f8c8f1372b0befa11f48 | Python | 5,750 | 112 | # Copyright 2020 Forschungszentrum Jülich GmbH and Aix-Marseille Université
# "Licensed to the Apache Software Foundation (ASF) under one or more contributor license agreements; and to You under the Apache License, Version 2.0. "
from mpi4py import MPI
import os
import json
from nest_elephant_tvb.utils import create_... |
fd60649bc2fa1cc5fa8cfc3a10023d931502e1d5b5c4f87c78f3858858df773b | Python | 5,754 | 113 | # from vis.visualization import visualize_cam
# import matplotlib.cm as cm
from lime import lime_image
from tensorflow.keras import Model
import tensorflow as tf, numpy as np, cv2.cv2 as cv2
# deprecated GradCAM function
# def generate_heatmap(model, input_image):
# grads = visualize_cam(model, layer_idx=-1, filte... |
b955e0908e82f2e59d355c9c7f22c7e8feb19ab7a3c90135d82985df0ca1814c | Python | 5,756 | 144 | """The kernel density estimation classifier on manifolds.
Lead author: Yann Cabanes.
"""
import math
from sklearn.neighbors import RadiusNeighborsClassifier
import geomstats.backend as gs
def wrap(function):
"""Wrap a function to first convert args to arrays."""
def wrapped_function(*args, **kwargs):
... |
46b9b00f075b69a0b99398eca501515f26393618c9c8b7416b9124f144d44895 | Python | 5,760 | 130 | import sys
from miscFuncs import *
vcfSnpFileName1, vcfSnpFileName2, vcfAllSitesFileName1, vcfAllSitesFileName2, maskedFaFileName, qualThreshold, outVcfPrefix = sys.argv[1:]
qualThreshold = int(qualThreshold)
def addSnpLocsInVcfFile(vcfFileName, snpLocs, outGenos, quals):
with open(vcfFileName) as vcfFile:
... |
894099880bc992d3488c9cf09589d2d28215549fd4aa38d0db976166a2d3f7b4 | Python | 5,761 | 141 | from PymoNNto.Exploration.Network_UI.TabBase import *
from PymoNNto.Exploration.Visualization.Module_visualizer import *
class module_visualizer_tab(TabBase):
def add_recorder_variables(self, neuron_group, Network_UI):
return
def initialize(self, Network_UI):
self.di_modules=[]
group... |
b310e94f5bf67210eaf2dc65a91ee8c4bb69f2fa29555a888a6e888f8d2644e0 | Python | 5,763 | 162 | from typing import Sequence, Union
import torch
import torch.nn as nn
from monai.networks.blocks.convolutions import Convolution, ResidualUnit
from monai.networks.layers.factories import Act, Norm
from monai.networks.layers.simplelayers import SkipConnection
from monai.utils import alias, export
class UNet_double(nn... |
1373e41360b198530fb3b3d0ca1395e57991c244cfa461c7bfb52282981e070d | Python | 5,765 | 180 | from typing import Any, Optional, Sequence, Tuple, Type
from types import TracebackType
from typing_extensions import Protocol, Self, Literal
from abc import ABC, abstractmethod
from threading import local
from overrides import override, EnforceOverrides
import pypika
import pypika.queries
from chromadb.config import S... |
2c51fcd1efe6e852dc5ed0bf91b393c4c2273f0f934a1e7388067fe22cec0027 | Python | 5,769 | 151 | # Copyright (C) 2024 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
class DigitRecognizerCNN(nn.Module):
"""
A Convolutional Neural Network (CNN) model for digit recognition.
This model consists of two convolut... |
5856f95fbe050ab274a76656e3e8b650947afaad02ad4a44e93c87b19332d9d6 | Python | 5,772 | 180 | """General purpose (numerical) utilities for spike detection and plotting.
"""
import numpy as np
from sanpy.bAnalysisResults import HALF_HEIGHTS
from sanpy.sanpyLogger import get_logger
logger = get_logger(__name__)
def throwOutAboveBelow(
vm,
spikeTimes,
spikeErrors,
peakWindow_pnts,
onlyPea... |
61b489e2a1a2150f0a064efc580786a7b7dad6e36b8de0a2b4f24f410e3108b2 | Python | 5,776 | 163 | # Copyright (c) 2022 PaddlePaddle 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 appli... |
68562c0a90d4640df69eb5ec1748d0fd9ed10611c4437219930f625ba3f1e2a8 | Python | 5,776 | 211 | import torch
import torch.nn as nn
import torchvision.transforms as transforms
import torchvision.datasets as dsets
import torch.nn.functional as F
import numpy as np
from torch.autograd import Variable
from torch.optim.lr_scheduler import StepLR,MultiStepLR
import matplotlib.pyplot as plt
import math
from sklearn.util... |
35e502903105cad3722f374b4ee3bd5e5f2cdc37462a51b53ef1c7d031092259 | Python | 5,779 | 156 | # Copyright (c) 2021 PaddlePaddle 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 appli... |
8c42d8a84c08f1a6bd5a7713027981efbea046dc802dbbf28426c4f9a2b47d79 | Python | 5,779 | 185 |
import os
import random
import numpy as np
from tqdm import tqdm
import torch
from torchvision import transforms
from skimage.metrics import (
mean_squared_error,
structural_similarity,
peak_signal_noise_ratio
)
from pytorch_radon import Radon, IRadon
from pytorch_radon.filters import LearnableFilter
f... |
1e13ae4a19a7e6faf32ffb1e8ec20e4b4b802e70c5b01999b1649961f28e52fa | Python | 5,781 | 174 | import numpy as np
import nibabel as nib
import glob
import os
from scipy.ndimage import binary_dilation
from src.ni_functions import get_atlas_coords, image_overlaps
import sys
def select_rois_from_lobe_partitions(lp_path, area):
image_names = glob.glob(os.path.join(lp_path, area, "*.nii.gz"))
image_roi_lab... |
07c5a99a331bb4a684077b07f6b7181d72eee9c28a1361ff6cdc3f7022e46783 | Python | 5,782 | 153 | # -*- coding: utf-8 -*-
import os
import argparse
import logging
import os
import numpy as np
import logging, argparse
from data_functions import load_data, get_windows
import h5py
import matplotlib.pyplot as plt
from format_unet_data_h5 import Formatter
from collections import deque
from calc_stats_ms import *
fr... |
17ec749242ad0a358a9fd82c02f88448c3b2d1846b1a0f16ab08c6b483581193 | Python | 5,783 | 170 | # Copyright 2020-2024 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
"""Pipeline module."""
import numpy as np
class Transformer:
"""Base class for data transformation.
This class defines the basic structure of a data transformer. It should be
subclassed when implementing new types of data tr... |
b68ea2fddfb466a8f56c301c8b5ffe1b94086138ef3d82cc4d84760fc1dfdbbe | Python | 5,783 | 160 | """
Code for perform generalization evaluation.
First executes the training of the model, and saves in Results folder
returns pkl with results and heatmaps
function to Sh in func_test_models
"""
import argparse
import logging
import subprocess as sp
import pandas as pd
import seaborn as sns
import matplotlib.pyplot... |
3dea970c5403c6c8a34cc6ac9fb50d790371eee33e65cdd9a578bb009b6b46ba | Python | 5,784 | 210 | ## IMPORT BASIC LIBS FOR SCRIPT
import scipy as sc
from scipy import io
import pickle
import numpy as np
import h5py
import pandas as pd
import os
from sys import argv
## TREATING ARGV VARS
nPats = int(argv[1]) # NUMBER OF SUBJECTS
pipe = argv[2] # PIPELINE
## COMMAND TO ALLOW THE USE OF HDF5 IN NETWORK (HPC) STOR... |
ee698e7a39ba373318f929699f0669b7c433645a93d319d16fa157168413dfe6 | Python | 5,785 | 160 | """
Code for perform generalization evaluation.
First executes the training of the model, and saves in Results folder
returns pkl with results and heatmaps
function to Sh in func_test_models
"""
import argparse
import logging
import subprocess as sp
import pandas as pd
import seaborn as sns
import matplotlib.pyplot... |
c9b625c12571462653d7ab0ef736d4847137a2476f5da896b9325b71dd02c132 | Python | 5,786 | 117 | """How much of a motif is chance, and how much of a lift is publicity.
Two quantities `docs/denoising.md` uses, computed rather than asserted.
The chance-recruitment rate says what fraction of a motif's members a non-convergent record would
supply for free. TCRNET already estimates the background neighbour probabilit... |
0409e9ab6e5cd16f928f0fe945dee3b845ee3089045cb001cf5ea0fc8eb8ef7f | Python | 5,788 | 135 | # Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved.
#
# This work is licensed under the Creative Commons Attribution-NonCommercial
# 4.0 International License. To view a copy of this license, visit
# http://creativecommons.org/licenses/by-nc/4.0/ or send a letter to
# Creative Commons, PO Box 1866, Mountain ... |
ba844c478a64de1578cdd2e23343c8d2771fe2b16e6f17f31920ef72f828fd71 | Python | 5,788 | 139 | #### group_binfile_parcellation.py
# Copyright (C) 2010 R. Cameron Craddock (cameron.craddock@gmail.com)
#
# This script is a part of the pyClusterROI python toolbox for the spatially
# constrained clustering of fMRI data. It performs group level normalized
# clustering of connectivity matrices. This is one of two meth... |
527b2ddd2bb894401a2bd813d9e5d515a89663fb7c31a0cadea004165cd9056b | Python | 5,789 | 167 | import unittest
import pytest
import torch
import torch.utils.data as tud
from reinvent.models import TransformerAdapter, Mol2MolModel
from reinvent.models.transformer.core.dataset.paired_dataset import PairedDataset
from reinvent.models.transformer.core.vocabulary import SMILESTokenizer
from reinvent.runmodes.create... |
cf8a995eb98bcd223c7ac1a1f635118e00b89d5968ab44afdc87fb7b4c4c33f0 | Python | 5,794 | 167 | import logging
import time
from pathlib import Path
from multiprocessing import Process, Queue
import json
from ScanImageTiffReader import ScanImageTiffReader
from .utils import get_nchannels, get_nvols, get_tslice, slice_movie
from .workers import RealTimeQueue
logger = logging.getLogger('live2p')
def append_to_qu... |
29caf98d0039be09e97b2c87701593127fe86b954b89b75c50fc34cf9d466968 | Python | 5,797 | 159 | import torch
import numpy as np
import copy
import sys
import time
import torch.distributed as dist
from metroem import loss
from pdb import set_trace as st
def align_sample(model, bundle, train=False):
tgt = bundle['tgt'].unsqueeze(1)
src = bundle['src'].unsqueeze(1)
src_field = None
if 'src_field... |
7be682433785f146d24389faefdc8656b89593d687c33bf66f76710dc3e5d145 | Python | 5,798 | 164 | import numpy as np
import numba
from numba import jit, prange, f4, u1, c8
import math
@jit("void(f4[:,:,:])",nopython=True,parallel=True,cache=True,fastmath=True)
def fastlog(f):
'''Step 1 of FFT-based spatial filtering: computing the log of the input video.
Inputs:
f(numpy.ndarray of float32, shape... |
a24d4ab00a0ed1b0d4c0f64fd89e7ea1ebd0e9ed222669d7bc6eabbd5c30f3f7 | Python | 5,800 | 191 | import click
from corgie import scheduling
from corgie.log import logger as corgie_logger
from corgie.data_backends import pass_data_backend
from corgie.layers import get_layer_types, DEFAULT_LAYER_TYPE, str_to_layer_type
from corgie.boundingcube import get_bcube_from_coords
from corgie import argparsers
from corgie.a... |
a5b7be1eed6995c9f9164913a74de1eea349b3e8a771e91e807a55fc945580e3 | Python | 5,801 | 211 | """
NN METRICS
====================
Support for metrics based in neural networks. To the
date of release, support for Keras models is included.
This module has been entirely created by Carlos Outeiral.
"""
import numpy as np
import rdkit.Chem.AllChem as Chem
import tensorflow as tf
from keras.layers import Dense, D... |
b51367e83647c2bb1f31a4ae30e862636e2e0039f61295299c8b609dcaeb8609 | Python | 5,804 | 177 | # -*- coding: utf-8 -*-
#
#
# PyRates software framework for flexible implementation of neural
# network model_templates and simulations. See also:
# https://github.com/pyrates-neuroscience/PyRates
#
# Copyright (C) 2017-2018 the original authors (Richard Gast and
# Daniel Rose), the Max-Planck-Institute for Human Cogn... |
d7ee72830524b02b07a5fadbc2548a51c10e69dd621326c370435d582dd82353 | Python | 5,810 | 128 | import os
import sys
import pandas
import json
import itertools
import logging
from utils import enumerate_isomers
from pubchem_utils import get_map_inchikey_to_canonicalSMILES, get_map_isomericSMILES_to_inchikey
class IsoRetriever:
def __init__(self):
self.auxillary_dir = 'Data'
self.log_dir = ... |
3ad7dc214b2f6873c91054eaadd156112aeafd1cbad1711fc45e85d063fb7e81 | Python | 5,811 | 158 | # Copyright (c) 2019 PaddlePaddle 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 appli... |
b0d725dd31712096caf701550085f396b912c6ac798d0cde74cfd5b748e34c8d | Python | 5,811 | 150 | # Copyright (c) 2020 PaddlePaddle 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
#
# Un... |
77cf7a2d58943f968d2ea7f9910b002ec91d20d7ba4d669ffe3729b765ee3f6b | Python | 5,812 | 156 | from typing import List # Union, Dict, List, Tuple, Optional
import numpy as np
import logging
logger = logging.getLogger(__name__)
from load_heka_python.load_heka import LoadHeka
def hekaLoad(path : str, group_idx : int = 0, series_idx : int = 2) -> dict:
"""Load a heka file and return a dictionary with the l... |
004a23f3e498631d9fa6787da1d56ba95a422c731ec48ae6a6e98d20f7a6a313 | Python | 5,813 | 146 | # Copyright (c) 2021 PaddlePaddle 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
#
# Un... |
ae63d994a55122c07cabdece2f2c66a380b5af504ebe9cd1c2c237e85586a11d | Python | 5,819 | 173 | import jax
import jax.numpy as np
import jax.random as random
from jax.nn import log_softmax
from functools import partial
def sparser(W_in, W_mask):
"""
Calculate sparsity-inducing loss.
This loss function encourages sparsity in the weights of a model
by penalizing the squared weig... |
3eb7138458621a13517d96e48fae7ed4e1595d6ac364ecef46a85889d640ce1d | Python | 5,820 | 158 | import itertools
import numpy as np
import torch
import torch.nn.functional as F
import torch.nn as nn
def JSE_loss(zs, zs_n=None, batch=None, sigma=None, neg_by_crpt=False, **kwargs):
'''The Jensen-Shannon Estimator of Mutual Information used in contrastive learning. The
implementation follows the paper `Lea... |
c00c7a2b5847f613ee3823d0eb90d84be4c0add1c2f21ce343c6bfbb0455668e | Python | 5,822 | 179 | """Statistical Manifold of beta distributions with the Fisher metric.
Lead author: Alice Le Brigant.
"""
from scipy.stats import beta
import geomstats.backend as gs
from geomstats.information_geometry.base import ScipyUnivariateRandomVariable
from geomstats.information_geometry.dirichlet import (
DirichletDistri... |
c41fd908e1c1f3c6244279f080b8f1ad6bd62b58a65e71a0983d942457a474f1 | Python | 5,825 | 156 | from warnings import warn
from copy import deepcopy
import torch
import numpy as np
import torch.nn as nn
from odl.tomo import fbp_op
from dival.reconstructors.standard_learned_reconstructor import (
StandardLearnedReconstructor)
from dival.reconstructors.networks.unet import UNet
from dival.datasets.fbp_dataset ... |
0b067a894cfcc05a0989d0a47791c09f8dc7c5ba898f9b797be0430b568d6995 | Python | 5,827 | 159 | # ==============================================================================
# Copyright 2025 Technical University of Denmark
# Author: Nikolas Borrel-Jensen
#
# All Rights Reserved.
#
# Licensed under the MIT License.
# ==============================================================================
import os
import... |
a4ad43bd873db386ffeb869ece69aa6103b3d3b7ab23b33b1c8bd88df5077399 | Python | 5,830 | 156 | """
Numerical Simulations
=====================
In this tutorial, you will learn the different options that PyRates provides for performing numerical simulations.
Given a dynamical system with state vector :math:`\\mathbf{y}`, the evolution of which is given by
.. math::
\\dot{\\mathbf{y}} = \\mathbf{f}(\\mathbf{... |
10cb934cc668c90276a4f0c3c6185e31eb65b5fa39de36cc9ec83e395da21e73 | Python | 5,835 | 151 | '''
Example showing hardware-timed continuous analog output without using a callback function
pynidaqmx.ao.hardwareContinuousVoltageNoCallback
Purpose
Demonstrates how to do hardware-timed continuous analog output without a callback function.
To achieve this we use sample regeneration. The buffer contents is pl... |
23a4dd3020bfb27a16f59d2c948f14515047d646b4da63c68944f509b8e5c537 | Python | 5,835 | 156 | """Test suite for the auto-07p Fortran emission path.
Covers the YAML-order preservation (issue: param-order scrambling resulted in
`parnames = {1: 'p4', 2: 'p2', 3: 'p1', 4: 'p3'}` instead of the declared
`{1: 'p1', 2: 'p2', 3: 'p3', 4: 'p4'}`) and the sub-routine signature / auto
wrapper consistency.
"""
import os
... |
cb824440b25f521349497fc254bde9818ee3a53017d6c68f13deaef8136f7107 | Python | 5,838 | 209 | """The vector space of lower triangular matrices.
Lead author: Saiteja Utpala.
"""
import geomstats.backend as gs
from geomstats.geometry.base import LevelSet, MatrixVectorSpace
from geomstats.geometry.matrices import Matrices, MatricesMetric
class LowerTriangularMatrices(MatrixVectorSpace):
"""Class for the ve... |
565d1966d10dc3a31e939fedda60d4a1772a04ff450d5e591d99c8b383b27db6 | Python | 5,839 | 165 | '''SqueezeNet in PyTorch.
See the paper "SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size" for more details.
'''
import math
import torch
import torch.nn as nn
import torch.nn.init as init
import torch.nn.functional as F
from torch.autograd import Variable
from functools import parti... |
0ca7187146ca9646b49aa63678d6bd8526e4772572ed8ced171e861d23e5bf57 | Python | 5,841 | 119 | # Copyright 2020 Forschungszentrum Jülich GmbH and Aix-Marseille Université
# "Licensed to the Apache Software Foundation (ASF) under one or more contributor license agreements; and to You under the Apache License, Version 2.0. "
from mpi4py import MPI
import os
import json
import time
import numpy as np
from nest_el... |
93cca0be8536740ffdc4ddaf3f1221c0f12517c08344af1a78fa7fd543fdda23 | Python | 5,841 | 184 | """Class to implement simply the Fisher-Rao metric on information manifolds."""
from scipy.integrate import quad_vec
import geomstats.backend as gs
from geomstats.geometry.riemannian_metric import RiemannianMetric
class FisherRaoMetric(RiemannianMetric):
r"""Class to derive the information metric from the pdf i... |
9b1625051b9eafc918c11c662ef2cdcecda654b1690e6c0742aef92007e94a0c | Python | 5,842 | 128 | # This file is a part of the `nequip` package. Please see LICENSE and README at the root for information on using it.
from ._base_datamodule import NequIPDataModule
from nequip.data import AtomicDataDict
from nequip.utils import download_url, extract_zip
from nequip.utils.logger import RankedLogger
import os
from typi... |
586271d4ea460cd08c645e8f35d43a96efea5890f3dfbe8c8e9fecbe55a75c3c | Python | 5,845 | 150 | from PymoNNto.Exploration.Network_UI.TabBase import *
class multi_group_plot_tab(TabBase):
def __init__(self, variables, title='Multi Group', timesteps=500):
super().__init__(title)
self.timesteps = timesteps
self.original_variables=variables
self.variables = []
self.curve... |
5052f615a40f3b76327cdbc6a3bfbc544beb598998d849debc13a61d163bb945 | Python | 5,849 | 165 |
from torch import nn
import argparse
from typing import Dict, Tuple
from . import register_cls_models
from .base_cls import BaseEncoder
from .config.ehfr_net import get_configuration
from ...layers import ConvLayer, LinearLayer, GlobalPool, Identity
from ...modules import HBlock as Block
@register_cls_models("ehfr_... |
f2f1c7e74f7359fdf0f53c35e97d4e0253322b9b7dc2e9a009982e6f642d01e9 | Python | 5,856 | 139 | # Copyright (c) 2023 PaddlePaddle 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 appli... |
4ad5fd831ad9bb7d4c9bd49a328975ee346f27f4241289346cf9880b851cd217 | Python | 5,857 | 181 | # Copyright 2020-2024 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
"""KCPipeline module."""
import copy as co
import gzip as gz
import numpy as np
from sklearn import cluster
from openfl.pipelines.pipeline import TransformationPipeline, Transformer
class KmeansTransformer(Transformer):
"""K-means ... |
78eb4ed055df6d0210501fe1dcf00cd47f5460151a8e63a025673c7874d4af9c | Python | 5,858 | 214 | """Complex manifold module.
In other words, a topological space that locally resembles
Hermitian space near each point.
Lead author: Yann Cabanes.
"""
import abc
import inspect
import geomstats.backend as gs
class ComplexManifold(abc.ABC):
r"""Class for complex manifolds.
Parameters
----------
di... |
59fef45966aa7ac8038d9d4a2500df1c6b7621e7aa22fc982af07c471cd67193 | Python | 5,861 | 151 | # Copyright (c) 2020 PaddlePaddle 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 appli... |
c28777ad0d32b384049e51ccf04f888430714259ac61ee77cd1b48c51a163ce2 | Python | 5,861 | 178 | import contextlib
import pytest
import torch
from nequip.model.utils import (
_EAGER_MODEL_KEY,
_TRAIN_TIME_COMPILE_KEY,
_COMPILE_MODE_OPTIONS,
fresh_model_builder_context,
get_current_compile_mode,
model_builder,
override_model_compile_mode,
)
class _ToyModel(torch.nn.Module):
"""Mi... |
4741d91125814761584a8fdcc300555e1bed904dcb52b8c415e3504319185bfa | Python | 5,870 | 181 | import sys
from chromadb.proto.utils import RetryOnRpcErrorClientInterceptor
import grpc
import time
from chromadb.ingest import (
Producer,
Consumer,
ConsumerCallbackFn,
)
from chromadb.proto.convert import to_proto_submit
from chromadb.proto.logservice_pb2 import PushLogsRequest, PullLogsRequest, LogReco... |
36482c63de732dcdd82bd852a71a6d158c95abf9acf907a8909b4cf60a7c3814 | Python | 5,873 | 181 | """A collection of RDKit wrappers for various types of SMILES conversions"""
import sys
import random
from typing import List, Tuple, Optional
from rdkit.Chem import (
AllChem,
MolFromSmiles,
MolToSmiles,
MolStandardize,
)
from rdkit.Chem.rdchem import Mol
from rdkit.Chem.rdmolops import RenumberAtoms... |
55d6c62bf2db68a06603d540e414aa12c95d2f0a0c9aba06ee1f22faf30c734d | Python | 5,880 | 178 | #
# calculation of synthetic accessibility score as described in:
#
# Estimation of Synthetic Accessibility Score of Drug-like Molecules based on Molecular Complexity and Fragment Contributions
# Peter Ertl and Ansgar Schuffenhauer
# Journal of Cheminformatics 1:8 (2009)
# http://www.jcheminf.com/content/1/1/8
#
# seve... |
69d29e8b14baffafad52b4e6fd609c9e52ca63ec84fd9212d131ca8aed615914 | Python | 5,882 | 210 | """Reference implementations for correlation matrices."""
import numpy as np
from ivac.utils import get_nfeatures
# equilibrium IVAC
def c0_all(trajs):
nfeatures = get_nfeatures(trajs)
numer = np.zeros((nfeatures, nfeatures))
denom = 0.0
for traj in trajs:
numer += traj.T @ traj
den... |
8eb6f95cc365814cb74fee0a9ad49b67afd823ef397d774f809ccdd317033faa | Python | 5,884 | 156 | import os.path as osp
import pickle
from sklearn.utils import shuffle
import numpy as np
import random
import rdkit.Chem as Chem
from rdkit.Chem.Scaffolds import MurckoScaffold
import csv
import codecs
import torch
from torch_geometric.data import Data
class JunctionTreeData(Data):
def __inc__(self, key, item):... |
edebc3434001b0696bc2490ddcf84dc0db875fc473ac601ba78442286a9b852f | Python | 5,891 | 171 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Dec 12 15:25:17 2018
@author: ngritti
"""
import time, os, glob
from tqdm import tqdm
import numpy as np
from skimage.io import imread
import seaborn as sns
import pandas as pd
import matplotlib.pyplot as plt
from skimage.metrics import structural_simil... |
cf72a97bfdfe7f7a0f9621553fe250ce1329b2cc97b23b0133b0c99a5cc9560a | Python | 5,892 | 164 | """Tests for persistent SanPy interface preferences."""
import json
from pathlib import Path
from types import SimpleNamespace
from unittest.mock import Mock
from sanpy.interface import preferences
from sanpy.interface.bTableView import DEFAULT_HIDDEN_FILE_COLUMNS
from sanpy.sanpy_paths import SanPyPaths
def test_e... |
a23cd80121724bc0bb322e4d5ebee7e31067550d9b2de5e1b9de25dfe66ddab7 | Python | 5,893 | 109 | """Audit aligned score forecasts with paired per-epitope and macro differences.
Input TSV columns: endpoint, epitope, case, label, predictor, score.
Every predictor must cover identical cases/labels. Keep private case tables and
outputs outside Git. No fitting occurs here.
"""
import argparse
from pathlib import Path
... |
c9d108fe89c9a2eec483678146a856fdc2601a9a0f7c0b6812131ff2e5091b5a | Python | 5,893 | 176 | import torch
from nequip.train import HuberLoss, StratifiedHuberForceLoss
from nequip.train.metrics import MaximumAbsoluteError
import pytest
LARGE_FORCE_MAGNITUDE_SCALING = 200
EXTREMELY_LARGE_FORCE_MAGNITUDE_MASK = 15000
@pytest.mark.parametrize("reduction", ["mean", "sum"])
@pytest.mark.parametrize("delta", [0.... |
7f551ff833e8a56061447700bf42249ccade5643998bba7b17c50302b62f0807 | Python | 5,894 | 143 | """
This script serves as a guideline for the reproduction of the data shown in 4.2.2.
The data there presented was obtained with a pre-release version of SHIP, which
has then been updated since. This script converts the work done before to a
version that uses the new release of SHIP. However, the hyperparameter
... |
c98699daeb369a2770e90205fa37cbdbc7eac2eea68c51292228efe0ecfc9aae | Python | 5,895 | 196 | """Group actions."""
import math
from abc import ABC, abstractmethod
import geomstats.backend as gs
from geomstats.geometry.matrices import Matrices
from geomstats.geometry.special_orthogonal import SpecialOrthogonal
from geomstats.vectorization import get_batch_shape
class GroupAction(ABC):
"""Base class for g... |
ff4d756799fb71797f0c1c29a03fe8dd95bee50c3c6d18f442b96f1168535054 | Python | 5,896 | 193 | # network without using the permutation.
import numpy as np
import matplotlib.pyplot as plt
import torch
import h5py
import torch.nn as nn
from torch.utils import data
# number of available gpu
ngpu = 1
batch_size = 32
dataRoot = "../../data"
labelFiles = "labels-1.h5"
matFiles = "matrices-1.h5"
labelsh5 = h5py... |
316ab2650d901527ca506ee66c7ac8c4c4ad53caf3fd2b785a915f030037d306 | Python | 5,904 | 128 | # This file is a part of the `nequip` package. Please see LICENSE and README at the root for information on using it.
from ._base_datamodule import NequIPDataModule
from nequip.utils import download_url, extract_zip, extract_tar
from nequip.utils.logger import RankedLogger
from nequip.data import AtomicDataDict
import... |
374ed8209b92f82b47300ac0b50750d5ca343e06278302f60bd697614496a40a | Python | 5,905 | 127 | from DeepPurpose import utils, dataset
from DeepPurpose import DTI as models
import warnings
import itertools
import numpy as np
import pandas as pd
import wandb
from tqdm import tqdm
import sys
warnings.filterwarnings("ignore")
import random
import argparse
import threading
import os
def main(cuda_id, num_workers, so... |
502f80dbf200ca75bf47af22ba92087146c34f5a42b365293db7d289b17ad95f | Python | 5,912 | 190 | import geomstats.backend as gs
from geomstats.test.data import TestData
from .base import LevelSetTestData
from .invariant_metric import InvariantMetricMatrixTestData
from .lie_group import LieGroupTestData, MatrixLieGroupTestData
from .mixins import ProjectionMixinsTestData
point_1 = gs.array([0.1, 0.2, 0.3])
point_... |
4c7eadac99775c4d13e4bafbb91d51858217405edcc5ada024d5962b0fd5b21f | Python | 5,913 | 151 | # Copyright (c) 2024 PaddlePaddle 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 appli... |
8dca8cb48681ffb3538d1c964f971e3d2832681cdfa535536f629401fa023b49 | Python | 5,915 | 131 | # This file is a part of the `nequip` package. Please see LICENSE and README at the root for information on using it.
import torch
from nequip.nn.model_modifier_utils import (
is_model_modifier,
is_persistent_model_modifier,
)
import inspect
import contextvars
import contextlib
from hydra.utils import get_met... |
cb75183b0b6319f4cebd1d33a05b814a8e9ad710b6c1ce26044a120edb13c7c6 | Python | 5,917 | 157 | # Copyright (c) 2022 PaddlePaddle 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 appli... |
3292158e8ae6620ccf5ee65dfd5be7b688497844e22936f0e3e652c8df3b595f | Python | 5,919 | 152 | # Copyright (c) 2020 PaddlePaddle 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
#
# Un... |
39a439fa803e8993cf62ba5af8a9180b2406d4411242cc40de1abe51298e3d40 | Python | 5,926 | 180 | import pytest
from unittest.mock import MagicMock
from chromadb.api.shared_system_client import SharedSystemClient
from chromadb.api.base_http_client import BaseHTTPClient
from chromadb.config import System
from typing import Optional, Dict, Generator
@pytest.fixture(autouse=True)
def clear_cache() -> Generator[None,... |
c1f704ac26c03dd98f1b7746d4295c1aa1ce5948a8e17ebc2d061f67fd393668 | Python | 5,933 | 173 | # This file is a part of the `nequip` package. Please see LICENSE and README at the root for information on using it.
"""
Model ASE integration test mixin for ``nequip-compile`` workflows.
This mixin provides tests for compiled-model ASE integration workflows including:
- ``nequip-compile`` in TorchScript mode (where ... |
7001b65044949c72b50dd00fb9b63e2b757b8cf1966e1c63be156b83b454c023 | Python | 5,934 | 147 | from copy import deepcopy
import config
import numpy as np
from data.dataset import Brats184, Brats313, GanBrats, GanBratsFromFolder, label_mapping
from matplotlib import pyplot as plt
modalities = ('T1', 'T1CE', 'T2', 'FLAIR')
label_colors = {'background': 'k', 'necrotic_non_enhancing_tumor_core': 'b',
... |
840f906e3d3efa2a121270d12b9d16ca34a68dd80ed56d7c368fe5f5b4968b1f | Python | 5,937 | 171 | import torch
import numpy as np
from . import EnvironmentPipeline
def select_multinomial(pipeline: EnvironmentPipeline, **kwargs) -> int:
# language=rst
"""
Selects an action probabilistically based on spiking activity from a network layer.
:param pipeline: EnvironmentPipeline with environment that ... |
e6300a223e66cab80cc88cddf021fd049cf394856ec52a93377e8cd322cc9860 | Python | 5,938 | 119 | # Copyright 2020 Forschungszentrum Jülich GmbH and Aix-Marseille Université
# "Licensed to the Apache Software Foundation (ASF) under one or more contributor license agreements; and to You under the Apache License, Version 2.0. "
from mpi4py import MPI
import os
import json
import time
import numpy as np
from nest_el... |
e8d82287513a78d7efe00eed0967e1df12cad74be07e6c61ce09d15eb34887e6 | Python | 5,939 | 147 | from typing import Optional
import config
import numpy as np
import torch
from matplotlib import pyplot as plt
from tqdm import tqdm
from data.dataset import Brats2021Test, MrSliceDataset, label_mapping
from data.transforms import get_transforms
from data.utils import plot_img_and_target
from learning.metrics import ... |
906bb876b5a08b9608c2bdf04fbc0541b6c803c898536e56f24c515392199e02 | Python | 5,942 | 169 | # Author: Youzhi Luo (yzluo@tamu.edu)
# Updated by: Anmol Anand (aanand@tamu.edu)
import torch
import torch.nn.functional as F
from torch.nn import Linear, Sequential, ReLU, BatchNorm1d as BN
from torch_geometric.nn import GINConv, GCNConv, global_mean_pool, JumpingKnowledge, global_max_pool, global_add_pool
from dig.... |
25c23f584c79d23becc68354fe38b50cbc9bd0538c04f93414ac63ad46542ac0 | Python | 5,943 | 160 | import os
import torch
import numpy as np
import pandas as pd
import pickle as cPickle
import random
from sklearn.utils import shuffle
def load_DEAP(data_dir, n_subjects = 26, single_subject = False, load_all = False, only_phys = False, only_EEG = True, label_type = [0, 2]):
## label_type [arousal: 0, valence: 1, ... |
571de5e2677133666a4da76acc3e48333f9dd5313bbcd10ec7946ac0b153fc6b | Python | 5,946 | 173 | # pylint: disable=protected-access, redefined-outer-name
from __future__ import absolute_import
import copy
import json
from pathlib import Path
import hypothesis.strategies as st
import pytest
import snakemake
from hypothesis import HealthCheck, assume, example, given, settings
from pytest_mock.plugin import MockerF... |
ec87deeec0709535def4dc18f93847812b2882d8fbe0c1d4994021b7a4b4a739 | Python | 5,946 | 184 | import numpy as np
from typing import List, Dict, Any, cast, Union
from chromadb.utils.results import (
_transform_embeddings,
_add_query_fields,
_add_get_fields,
query_result_to_dfs,
get_result_to_df,
)
from chromadb.api.types import (
QueryResult,
GetResult,
)
from numpy.typing import NDAr... |
6c27e5404e13c9f2b236e7e7946c2f52afbd577a21f8e86270473ec82178bfb9 | Python | 5,947 | 109 | import argparse
import torch
import torch.nn.functional as F
from texttable import Texttable
import sys
from datasets import *
from train_eval import run_classification, run_regression
from torch_scatter import scatter_mean
from model import *
parser = argparse.ArgumentParser()
parser.add_argument('--dataset', typ... |
cb8aed2a9253861ed8cc9170a0ef5c810bb198758a8f530d783cc7e45979fcdd | Python | 5,947 | 163 | """The Mol2Mol sampling module"""
__all__ = ["Mol2MolSampler"]
from typing import List, Tuple
import logging
from rdkit import Chem
import torch.utils.data as tud
from .sampler import Sampler, validate_smiles
from . import params
from reinvent.models.transformer.core.dataset.dataset import Dataset
from reinvent.mode... |
574b493d22e9778be9b98cf99d114b5217946d9165911e01cb971b1e47d87356 | Python | 5,948 | 162 | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... |
9659c41cc3c7240b845064e2c2109584e9303798ab3e669512c5622268a4a03a | Python | 5,948 | 138 | # Author: Youzhi Luo (yzluo@tamu.edu)
# Updated by: Anmol Anand (aanand@tamu.edu)
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch_scatter import scatter
from .genet import Readout
from dig.auggraph.method.GraphAug.constants import *
class GMNConv(nn.Module):
def __init__(self, node_... |
9c23fca808f478db04bfa122bbd47ec46c3481fbc4677ce8e6030857dfe7ad8f | Python | 5,953 | 167 | """LogNormal Distribution."""
import geomstats.backend as gs
from geomstats.geometry.euclidean import CanonicalEuclideanMetric, Euclidean
from geomstats.geometry.hermitian_matrices import expmh, powermh
from geomstats.geometry.matrices import Matrices, MatricesMetric
from geomstats.geometry.spd_matrices import (
S... |
b3518224dc1cf0f94fd352b311f4b38ae3dd4effb9cedd6545a30ded36a1719b | Python | 5,954 | 194 | # -*- coding: utf-8 -*-
import os
import argparse
import logging
import h5py
import numpy as np
from scipy.special import expit
from evaluate_unet_windowed import cm_analysis
from sklearn.metrics import roc_curve, roc_auc_score, precision_recall_curve, average_precision_score, confusion_matrix, accuracy_score
import... |
cd67ac7e6f5a4f8fbea1e3d415fffb3d03ad01eb84912c814fd4b06495f51a4e | Python | 5,954 | 170 | # Copyright 2020-2025 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import pytest
import logging
import os
import time
import concurrent.futures
import tests.end_to_end.utils.federation_helper as fh
import tests.end_to_end.utils.helper as helper
import tests.end_to_end.utils.wf_helper as wf_helper
log = lo... |
34ce71f565ac0359097be627982987b7417cb51f0e921b32922be824691fe725 | Python | 5,957 | 100 | """Independent structure-file audit rejects changed and missing raw inputs."""
import gzip
import hashlib
import io
import tarfile
import polars as pl
import pytest
from vdjdb.validate.structure_files import check_archives, check_links, check_supplemental, verify_inputs
def test_streamed_archive_members_and_pinned_... |
5ff766c301579f538cd833a4a2c005d19dbe2b0018f7b623e58fa32b87fadde7 | Python | 5,964 | 205 | """Module exposing estimator base class."""
from sklearn.base import BaseEstimator, ClassifierMixin, TransformerMixin
from sklearn.metrics import euclidean_distances
from sklearn.utils.multiclass import unique_labels
from sklearn.utils.validation import check_array, check_is_fitted, check_X_y
import geomstats.backend... |
a768130bd4fd24eb1698a8073008cc1ee882c6056b1c0fb3409311599494e7c3 | Python | 5,966 | 213 | import torch
import torch.nn as nn
import torchvision.transforms as transforms
import torchvision.datasets as dsets
import torch.nn.functional as F
import numpy as np
from torch.autograd import Variable
from torch.optim.lr_scheduler import StepLR,MultiStepLR
import matplotlib.pyplot as plt
import math
from sklearn.util... |
8bde38645daf040ee491c22a9dd6ad8edaad63265c038b8f1ba462c5758196c1 | Python | 5,969 | 166 | # Copyright 2020-2024 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
"""Assigner module."""
import logging
from functools import wraps
logger = logging.getLogger(__name__)
class Assigner:
r"""
The task assigner maintains a list of tasks.
Also it decides the policy for which collaborator shou... |
bb207a10096ffc9f952a72669c04c3e7ee9e04fb4bf98c51b02764fc1d722c63 | Python | 5,969 | 211 | import click
import procspec
from corgie.log import logger as corgie_logger
from corgie.boundingcube import get_bcube_from_coords
from corgie import scheduling, helpers, stack
from corgie.argparsers import (
LAYER_HELP_STR,
corgie_optgroup,
corgie_option,
create_stack_from_spec,
)
class MultiSectionCo... |
ae7f3ed3310fdba2e92f125d8d646d9b53eb72135c9d66d6104198195d051137 | Python | 5,976 | 205 |
from unittest.mock import MagicMock
import unittest
from sleepy.test.core import TestBase
import numpy as np
class NavigatorTest(unittest.TestCase):
def standardScenario(points):
"""Set up a standard scenario for mocking.
"""
settings = TestBase.getSettings()
dataS... |
685b94cfce89e5172e7bf0de386d693c1aa4a901c94ad6ab95b53d6c00a9bb0e | Python | 5,977 | 150 | """ Makes a data set in klepto files with MEL frequencies from the TIMIT speech corpus"""
#"""https://github.com/philipperemy/timit core test set"""#
'''
the preprocessing code refers to the work(Yin, B., Corradi, F. & Bohté, S. M. Accurate and efficient time-domain classification with adaptive spiking recurrent neural... |
3e7d5dbb76396fb68ffd602a98536b256aa76066e05f46ede26bc6918bd6b964 | Python | 5,978 | 205 | import torch as T
import torch.nn as nn
from Networks.network import Network
from monai.networks.nets.unet import UNet
class UNet_student(Network):
def __init__(self):
super(UNet_student, self).__init__()
#self._build()
self.model = T.nn.Sequential(UNet(3, 1, 1, (32, 64, 128, 256), (2, 2, 2... |
52ff1362485ce28c6f83a9346dd1fd30c0eb0c97983a6ec4b52feb12e818dcbc | Python | 5,987 | 168 | """
Unit tests to test data loaders. These primarily check that the data loaders return values
with expected shapes and ranges.
"""
import unittest
import numpy as np
import torch
from foldingdiff import datasets, utils
class TestCathCanonical(unittest.TestCase):
"""
Tests for the cath canonical angles dat... |
92dab9a68be59c594d85e661db2154324c28571ee46c160dbd8d17ccd1ccd57c | Python | 5,987 | 247 | import pickle as pk
import os
import tensorflow.compat.v1 as tf
tf.disable_v2_behavior()
import numpy as np
import sys
def check_create_save_dir(save_dir):
if not os.path.exists(save_dir):
os.makedirs(save_dir)
else:
print(
'SAVE DIRECTORY ALREADY EXISTS, TERMINATE P... |
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