eigen/test/bicgstab.cpp
2025-02-21 10:27:29 -08:00

89 lines
2.8 KiB
C++

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