Rasmus Munk LarsenandRasmus Munk Larsen
f7a1c99acb
libeigen/eigen!2609 Co-authored-by: Rasmus Munk Larsen <rmlarsen@gmail.com>
77 lines
2.8 KiB
C++
77 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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// SPDX-License-Identifier: 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>
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void test_least_square_diagonal_preconditioner_zero_columns() {
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SparseMatrix<T, RowMajor> mat(3, 3);
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mat.insert(0, 0) = T(2);
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mat.insert(2, 2) = T(4);
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mat.makeCompressed();
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LeastSquareDiagonalPreconditioner<T> precond(mat);
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Matrix<T, 3, 1> rhs = Matrix<T, 3, 1>::Ones();
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Matrix<T, 3, 1> expected;
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expected << T(0.25), T(1), T(0.0625);
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VERIFY_IS_APPROX(precond.solve(rhs), expected);
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}
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template <typename T>
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void test_lscg_T() {
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LeastSquaresConjugateGradient<SparseMatrix<T> > lscg_colmajor_diag;
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LeastSquaresConjugateGradient<SparseMatrix<T>, IdentityPreconditioner> lscg_colmajor_I;
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LeastSquaresConjugateGradient<SparseMatrix<T, RowMajor> > lscg_rowmajor_diag;
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LeastSquaresConjugateGradient<SparseMatrix<T, RowMajor>, IdentityPreconditioner> lscg_rowmajor_I;
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CALL_SUBTEST(check_sparse_square_solving(lscg_colmajor_diag));
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CALL_SUBTEST(check_sparse_square_solving(lscg_colmajor_I));
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CALL_SUBTEST(check_sparse_leastsquare_solving(lscg_colmajor_diag));
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CALL_SUBTEST(check_sparse_leastsquare_solving(lscg_colmajor_I));
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CALL_SUBTEST(check_sparse_square_solving(lscg_rowmajor_diag));
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CALL_SUBTEST(check_sparse_square_solving(lscg_rowmajor_I));
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CALL_SUBTEST(check_sparse_leastsquare_solving(lscg_rowmajor_diag));
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CALL_SUBTEST(check_sparse_leastsquare_solving(lscg_rowmajor_I));
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}
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void test_lscg_extreme_rhs() {
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const Matrix2d mat = Matrix2d::Identity();
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const Vector2d direction = (Vector2d() << 1, -1).finished();
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LeastSquaresConjugateGradient<Matrix2d, IdentityPreconditioner> solver(mat);
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solver.setTolerance(1e-12);
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for (double scale : {1e-200, 1e200}) {
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const Vector2d rhs = scale * direction;
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const Vector2d guess = 0.5 * rhs;
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Vector2d x = solver.solve(rhs);
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VERIFY_IS_EQUAL(solver.info(), Success);
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VERIFY(x.allFinite());
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VERIFY_IS_APPROX(x / scale, direction);
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x = solver.solveWithGuess(rhs, guess);
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VERIFY_IS_EQUAL(solver.info(), Success);
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VERIFY(x.allFinite());
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VERIFY_IS_APPROX(x / scale, direction);
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}
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}
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EIGEN_DECLARE_TEST(lscg) {
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CALL_SUBTEST_1(test_lscg_T<double>());
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CALL_SUBTEST_2(test_lscg_T<std::complex<double> >());
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CALL_SUBTEST_3(test_least_square_diagonal_preconditioner_zero_columns<double>());
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CALL_SUBTEST_4(test_least_square_diagonal_preconditioner_zero_columns<std::complex<double> >());
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CALL_SUBTEST_5(test_lscg_extreme_rhs());
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}
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