| // This file is part of Eigen, a lightweight C++ template library |
| // for linear algebra. |
| // |
| // Copyright (C) 2011 Gael Guennebaud <g.gael@free.fr> |
| // Copyright (C) 2012 desire Nuentsa <desire.nuentsa_wakam@inria.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 "../../test/sparse_solver.h" |
| #include <unsupported/Eigen/IterativeSolvers> |
| |
| template <typename T> |
| void test_dgmres_T() { |
| DGMRES<SparseMatrix<T>, DiagonalPreconditioner<T> > dgmres_colmajor_diag; |
| DGMRES<SparseMatrix<T>, IdentityPreconditioner> dgmres_colmajor_I; |
| DGMRES<SparseMatrix<T>, IncompleteLUT<T> > dgmres_colmajor_ilut; |
| // GMRES<SparseMatrix<T>, SSORPreconditioner<T> > dgmres_colmajor_ssor; |
| |
| CALL_SUBTEST(check_sparse_square_solving(dgmres_colmajor_diag)); |
| // CALL_SUBTEST( check_sparse_square_solving(dgmres_colmajor_I) ); |
| CALL_SUBTEST(check_sparse_square_solving(dgmres_colmajor_ilut)); |
| // CALL_SUBTEST( check_sparse_square_solving(dgmres_colmajor_ssor) ); |
| } |
| |
| // Regression: Arnoldi breakdown used to divide by zero (producing NaN in the |
| // Krylov basis) and solve a singular triangular system, silently returning |
| // Inf with info() == Success. Exercise both the pathological (rank-deficient |
| // pivot) and benign (exact Krylov subspace) breakdown paths. |
| template <typename T> |
| void test_dgmres_breakdown_T() { |
| typedef SparseMatrix<T> Mat; |
| typedef Matrix<T, 2, 1> Vec; |
| |
| // Nilpotent A with singular Hessenberg pivot on the first step. |
| Mat A(2, 2); |
| A.insert(0, 1) = T(1); |
| A.makeCompressed(); |
| Vec b; |
| b << T(1), T(0); |
| |
| DGMRES<Mat, IdentityPreconditioner> solver; |
| solver.compute(A); |
| Vec x = solver.solve(b); |
| VERIFY(x.allFinite()); |
| VERIFY(solver.info() != Success); |
| |
| // Diagonal A with b in an eigenspace: Arnoldi converges after one step. |
| Mat D(2, 2); |
| D.insert(0, 0) = T(2); |
| D.insert(1, 1) = T(2); |
| D.makeCompressed(); |
| Vec d; |
| d << T(2), T(2); |
| |
| DGMRES<Mat, DiagonalPreconditioner<T> > solver2; |
| solver2.compute(D); |
| Vec y = solver2.solve(d); |
| VERIFY_IS_EQUAL(solver2.info(), Success); |
| VERIFY_IS_APPROX(y, (Vec() << T(1), T(1)).finished()); |
| } |
| |
| EIGEN_DECLARE_TEST(dgmres) { |
| CALL_SUBTEST_1(test_dgmres_T<double>()); |
| CALL_SUBTEST_2(test_dgmres_T<std::complex<double> >()); |
| CALL_SUBTEST_3(test_dgmres_breakdown_T<double>()); |
| CALL_SUBTEST_4(test_dgmres_breakdown_T<std::complex<double> >()); |
| } |