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82 lines
3.1 KiB
C++
82 lines
3.1 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) 2015-2016 Gael Guennebaud <gael.guennebaud@inria.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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// #define EIGEN_DONT_VECTORIZE
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// #define EIGEN_MAX_ALIGN_BYTES 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_incomplete_cholesky_T() {
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typedef SparseMatrix<T, 0, I_> SparseMatrixType;
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ConjugateGradient<SparseMatrixType, Lower, IncompleteCholesky<T, Lower, AMDOrdering<I_> > > cg_illt_lower_amd;
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ConjugateGradient<SparseMatrixType, Lower, IncompleteCholesky<T, Lower, NaturalOrdering<I_> > > cg_illt_lower_nat;
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ConjugateGradient<SparseMatrixType, Upper, IncompleteCholesky<T, Upper, AMDOrdering<I_> > > cg_illt_upper_amd;
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ConjugateGradient<SparseMatrixType, Upper, IncompleteCholesky<T, Upper, NaturalOrdering<I_> > > cg_illt_upper_nat;
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ConjugateGradient<SparseMatrixType, Upper | Lower, IncompleteCholesky<T, Lower, AMDOrdering<I_> > > cg_illt_uplo_amd;
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CALL_SUBTEST(check_sparse_spd_solving(cg_illt_lower_amd));
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CALL_SUBTEST(check_sparse_spd_solving(cg_illt_lower_nat));
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CALL_SUBTEST(check_sparse_spd_solving(cg_illt_upper_amd));
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CALL_SUBTEST(check_sparse_spd_solving(cg_illt_upper_nat));
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CALL_SUBTEST(check_sparse_spd_solving(cg_illt_uplo_amd));
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}
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template <int>
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void bug1150() {
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// regression for bug 1150
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for (int N = 1; N < 20; ++N) {
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Eigen::MatrixXd b(N, N);
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b.setOnes();
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Eigen::SparseMatrix<double> m(N, N);
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m.reserve(Eigen::VectorXi::Constant(N, 4));
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for (int i = 0; i < N; ++i) {
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m.insert(i, i) = 1;
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m.coeffRef(i, i / 2) = 2;
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m.coeffRef(i, i / 3) = 2;
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m.coeffRef(i, i / 4) = 2;
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}
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Eigen::SparseMatrix<double> A;
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A = m * m.transpose();
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Eigen::ConjugateGradient<Eigen::SparseMatrix<double>, Eigen::Lower | Eigen::Upper,
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Eigen::IncompleteCholesky<double> >
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solver(A);
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VERIFY(solver.preconditioner().info() == Eigen::Success);
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VERIFY(solver.info() == Eigen::Success);
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}
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}
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void test_non_spd() {
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Eigen::SparseMatrix<double> A(2, 2);
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A.insert(0, 0) = 0;
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A.insert(1, 1) = 3;
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Eigen::IncompleteCholesky<double> solver(A);
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// Recover original matrix.
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Eigen::MatrixXd M = solver.permutationP().transpose() *
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(solver.scalingS().asDiagonal().inverse() *
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(solver.matrixL() * solver.matrixL().transpose() -
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solver.shift() * Eigen::MatrixXd::Identity(A.rows(), A.cols())) *
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solver.scalingS().asDiagonal().inverse()) *
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solver.permutationP();
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VERIFY_IS_APPROX(A.toDense(), M);
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}
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EIGEN_DECLARE_TEST(incomplete_cholesky) {
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CALL_SUBTEST_1((test_incomplete_cholesky_T<double, int>()));
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CALL_SUBTEST_2((test_incomplete_cholesky_T<std::complex<double>, int>()));
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CALL_SUBTEST_3((test_incomplete_cholesky_T<double, long int>()));
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CALL_SUBTEST_4((bug1150<0>()));
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CALL_SUBTEST_4(test_non_spd());
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}
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