Rasmus Munk LarsenandRasmus Munk Larsen
f7a1c99acb
libeigen/eigen!2609 Co-authored-by: Rasmus Munk Larsen <rmlarsen@gmail.com>
67 lines
2.7 KiB
C++
67 lines
2.7 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, typename I_>
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void test_conjugate_gradient_T() {
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typedef SparseMatrix<T, 0, I_> SparseMatrixType;
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ConjugateGradient<SparseMatrixType, Lower> cg_colmajor_lower_diag;
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ConjugateGradient<SparseMatrixType, Upper> cg_colmajor_upper_diag;
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ConjugateGradient<SparseMatrixType, Lower | Upper> cg_colmajor_loup_diag;
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ConjugateGradient<SparseMatrixType, Lower, IdentityPreconditioner> cg_colmajor_lower_I;
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ConjugateGradient<SparseMatrixType, Upper, IdentityPreconditioner> cg_colmajor_upper_I;
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CALL_SUBTEST(check_sparse_spd_solving(cg_colmajor_lower_diag));
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CALL_SUBTEST(check_sparse_spd_solving(cg_colmajor_upper_diag));
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CALL_SUBTEST(check_sparse_spd_solving(cg_colmajor_loup_diag));
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CALL_SUBTEST(check_sparse_spd_solving(cg_colmajor_lower_I));
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CALL_SUBTEST(check_sparse_spd_solving(cg_colmajor_upper_I));
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}
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// Regression for issue #1704: default-constructing an iterative solver
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// templated on a fixed-size MatrixType tripped a resize(0,0) size assertion.
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template <typename MatrixType>
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void test_default_construct_fixed_size() {
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ConjugateGradient<MatrixType> cg;
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BiCGSTAB<MatrixType> bicg;
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LeastSquaresConjugateGradient<MatrixType> lscg;
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}
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void test_conjugate_gradient_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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ConjugateGradient<Matrix2d, Lower | Upper, 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(conjugate_gradient) {
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CALL_SUBTEST_1((test_conjugate_gradient_T<double, int>()));
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CALL_SUBTEST_2((test_conjugate_gradient_T<std::complex<double>, int>()));
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CALL_SUBTEST_3((test_conjugate_gradient_T<double, long int>()));
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CALL_SUBTEST_4(test_default_construct_fixed_size<Matrix3d>());
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CALL_SUBTEST_5(test_conjugate_gradient_extreme_rhs());
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}
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