| // 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/. |
| // SPDX-License-Identifier: MPL-2.0 |
| |
| #include "sparse_solver.h" |
| #include <Eigen/IterativeLinearSolvers> |
| |
| template <typename T> |
| void test_least_square_diagonal_preconditioner_zero_columns() { |
| SparseMatrix<T, RowMajor> mat(3, 3); |
| mat.insert(0, 0) = T(2); |
| mat.insert(2, 2) = T(4); |
| mat.makeCompressed(); |
| |
| LeastSquareDiagonalPreconditioner<T> precond(mat); |
| Matrix<T, 3, 1> rhs = Matrix<T, 3, 1>::Ones(); |
| Matrix<T, 3, 1> expected; |
| expected << T(0.25), T(1), T(0.0625); |
| |
| VERIFY_IS_APPROX(precond.solve(rhs), expected); |
| } |
| |
| template <typename T> |
| void test_lscg_T() { |
| LeastSquaresConjugateGradient<SparseMatrix<T> > lscg_colmajor_diag; |
| LeastSquaresConjugateGradient<SparseMatrix<T>, IdentityPreconditioner> lscg_colmajor_I; |
| LeastSquaresConjugateGradient<SparseMatrix<T, RowMajor> > lscg_rowmajor_diag; |
| LeastSquaresConjugateGradient<SparseMatrix<T, RowMajor>, IdentityPreconditioner> lscg_rowmajor_I; |
| |
| CALL_SUBTEST(check_sparse_square_solving(lscg_colmajor_diag)); |
| CALL_SUBTEST(check_sparse_square_solving(lscg_colmajor_I)); |
| |
| CALL_SUBTEST(check_sparse_leastsquare_solving(lscg_colmajor_diag)); |
| CALL_SUBTEST(check_sparse_leastsquare_solving(lscg_colmajor_I)); |
| |
| CALL_SUBTEST(check_sparse_square_solving(lscg_rowmajor_diag)); |
| CALL_SUBTEST(check_sparse_square_solving(lscg_rowmajor_I)); |
| |
| CALL_SUBTEST(check_sparse_leastsquare_solving(lscg_rowmajor_diag)); |
| CALL_SUBTEST(check_sparse_leastsquare_solving(lscg_rowmajor_I)); |
| } |
| |
| void test_lscg_extreme_rhs() { |
| const Matrix2d mat = Matrix2d::Identity(); |
| const Vector2d direction = (Vector2d() << 1, -1).finished(); |
| LeastSquaresConjugateGradient<Matrix2d, IdentityPreconditioner> solver(mat); |
| solver.setTolerance(1e-12); |
| |
| for (double scale : {1e-200, 1e200}) { |
| const Vector2d rhs = scale * direction; |
| const Vector2d guess = 0.5 * rhs; |
| Vector2d x = solver.solve(rhs); |
| VERIFY_IS_EQUAL(solver.info(), Success); |
| VERIFY(x.allFinite()); |
| VERIFY_IS_APPROX(x / scale, direction); |
| |
| x = solver.solveWithGuess(rhs, guess); |
| VERIFY_IS_EQUAL(solver.info(), Success); |
| VERIFY(x.allFinite()); |
| VERIFY_IS_APPROX(x / scale, direction); |
| } |
| } |
| |
| EIGEN_DECLARE_TEST(lscg) { |
| CALL_SUBTEST_1(test_lscg_T<double>()); |
| CALL_SUBTEST_2(test_lscg_T<std::complex<double> >()); |
| CALL_SUBTEST_3(test_least_square_diagonal_preconditioner_zero_columns<double>()); |
| CALL_SUBTEST_4(test_least_square_diagonal_preconditioner_zero_columns<std::complex<double> >()); |
| CALL_SUBTEST_5(test_lscg_extreme_rhs()); |
| } |