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82f0ce2726
This provide several advantages: - more flexibility in designing unit tests - unit tests can be glued to speed up compilation - unit tests are compiled with same predefined macros, which is a requirement for zapcc
46 lines
1.7 KiB
C++
46 lines
1.7 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@inria.fr>
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//
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// This Source Code Form is subject to the terms of the Mozilla
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// Public License v. 2.0. If a copy of the MPL was not distributed
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// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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// SparseLU solve does not accept column major matrices for the destination.
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// However, as expected, the generic check_sparse_square_solving routines produces row-major
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// rhs and destination matrices when compiled with EIGEN_DEFAULT_TO_ROW_MAJOR
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#ifdef EIGEN_DEFAULT_TO_ROW_MAJOR
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#undef EIGEN_DEFAULT_TO_ROW_MAJOR
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#endif
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#include "sparse_solver.h"
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#include <Eigen/SparseLU>
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#include <unsupported/Eigen/SparseExtra>
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template<typename T> void test_sparselu_T()
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{
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SparseLU<SparseMatrix<T, ColMajor> /*, COLAMDOrdering<int>*/ > sparselu_colamd; // COLAMDOrdering is the default
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SparseLU<SparseMatrix<T, ColMajor>, AMDOrdering<int> > sparselu_amd;
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SparseLU<SparseMatrix<T, ColMajor, long int>, NaturalOrdering<long int> > sparselu_natural;
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check_sparse_square_solving(sparselu_colamd, 300, 100000, true);
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check_sparse_square_solving(sparselu_amd, 300, 10000, true);
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check_sparse_square_solving(sparselu_natural, 300, 2000, true);
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check_sparse_square_abs_determinant(sparselu_colamd);
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check_sparse_square_abs_determinant(sparselu_amd);
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check_sparse_square_determinant(sparselu_colamd);
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check_sparse_square_determinant(sparselu_amd);
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}
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EIGEN_DECLARE_TEST(sparselu)
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{
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CALL_SUBTEST_1(test_sparselu_T<float>());
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CALL_SUBTEST_2(test_sparselu_T<double>());
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CALL_SUBTEST_3(test_sparselu_T<std::complex<float> >());
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CALL_SUBTEST_4(test_sparselu_T<std::complex<double> >());
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}
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