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89 lines
2.8 KiB
C++
89 lines
2.8 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) 2011 Gael Guennebaud <g.gael@free.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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#include "sparse_solver.h"
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#include <Eigen/IterativeLinearSolvers>
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template <typename T, typename I_>
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void test_bicgstab_T() {
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BiCGSTAB<SparseMatrix<T, 0, I_>, DiagonalPreconditioner<T> > bicgstab_colmajor_diag;
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BiCGSTAB<SparseMatrix<T, 0, I_>, IdentityPreconditioner> bicgstab_colmajor_I;
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BiCGSTAB<SparseMatrix<T, 0, I_>, IncompleteLUT<T, I_> > bicgstab_colmajor_ilut;
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// BiCGSTAB<SparseMatrix<T>, SSORPreconditioner<T> > bicgstab_colmajor_ssor;
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bicgstab_colmajor_diag.setTolerance(NumTraits<T>::epsilon() * 4);
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bicgstab_colmajor_ilut.setTolerance(NumTraits<T>::epsilon() * 4);
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CALL_SUBTEST(check_sparse_square_solving(bicgstab_colmajor_diag));
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// CALL_SUBTEST( check_sparse_square_solving(bicgstab_colmajor_I) );
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CALL_SUBTEST(check_sparse_square_solving(bicgstab_colmajor_ilut));
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// CALL_SUBTEST( check_sparse_square_solving(bicgstab_colmajor_ssor) );
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}
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// https://gitlab.com/libeigen/eigen/-/issues/2856
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void test_2856() {
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Eigen::MatrixXd D = Eigen::MatrixXd::Identity(14, 14);
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D(6, 13) = 1;
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D(13, 12) = 1;
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using CSRMatrix = Eigen::SparseMatrix<double, Eigen::RowMajor>;
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CSRMatrix A = D.sparseView();
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Eigen::VectorXd b = Eigen::VectorXd::Zero(14);
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b(12) = -1001;
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Eigen::BiCGSTAB<CSRMatrix> solver;
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solver.compute(A);
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Eigen::VectorXd x = solver.solve(b);
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Eigen::VectorXd expected = Eigen::VectorXd::Zero(14);
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expected(6) = -1001;
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expected(12) = -1001;
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expected(13) = 1001;
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VERIFY_IS_EQUAL(x, expected);
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Eigen::VectorXd residual = b - A * x;
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VERIFY(residual.isZero());
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}
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// https://gitlab.com/libeigen/eigen/-/issues/2899
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void test_2899() {
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Eigen::MatrixXd A = Eigen::MatrixXd::Zero(4, 4);
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A(0, 0) = 1;
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A(1, 0) = -1.0 / 6;
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A(1, 1) = 2.0 / 3;
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A(1, 2) = -1.0 / 6;
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A(1, 3) = -1.0 / 3;
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A(2, 1) = -1.0 / 3;
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A(2, 2) = 1;
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A(2, 3) = -2.0 / 3;
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A(3, 1) = -1.0 / 3;
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A(3, 2) = -1.0 / 3;
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A(3, 3) = 2.0 / 3;
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Eigen::VectorXd b = Eigen::VectorXd::Zero(4);
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b(0) = 0;
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b(1) = 1;
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b(2) = 1;
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b(3) = 1;
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Eigen::BiCGSTAB<Eigen::MatrixXd> solver;
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solver.compute(A);
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Eigen::VectorXd x = solver.solve(b);
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Eigen::VectorXd expected(4);
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expected << 0, 15, 18, 18;
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VERIFY_IS_APPROX(x, expected);
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Eigen::VectorXd residual = b - A * x;
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VERIFY(residual.isZero());
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}
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EIGEN_DECLARE_TEST(bicgstab) {
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CALL_SUBTEST_1((test_bicgstab_T<double, int>()));
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CALL_SUBTEST_2((test_bicgstab_T<std::complex<double>, int>()));
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CALL_SUBTEST_3((test_bicgstab_T<double, long int>()));
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CALL_SUBTEST_4(test_2856());
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CALL_SUBTEST_5(test_2899());
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}
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