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93 lines
3.1 KiB
C++
93 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) 2008-2010 Gael Guennebaud <g.gael@free.fr>
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//
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// Eigen is free software; you can redistribute it and/or
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// modify it under the terms of the GNU Lesser General Public
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// License as published by the Free Software Foundation; either
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// version 3 of the License, or (at your option) any later version.
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//
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// Alternatively, you can redistribute it and/or
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// modify it under the terms of the GNU General Public License as
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// published by the Free Software Foundation; either version 2 of
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// the License, or (at your option) any later version.
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//
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// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
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// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
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// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
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// GNU General Public License for more details.
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//
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// You should have received a copy of the GNU Lesser General Public
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// License and a copy of the GNU General Public License along with
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// Eigen. If not, see <http://www.gnu.org/licenses/>.
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#include "sparse.h"
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#include <Eigen/SparseExtra>
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#ifdef EIGEN_CHOLMOD_SUPPORT
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#include <Eigen/CholmodSupport>
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#endif
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template<typename Scalar> void sparse_ldlt(int rows, int cols)
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{
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double density = std::max(8./(rows*cols), 0.01);
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typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
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typedef Matrix<Scalar,Dynamic,1> DenseVector;
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SparseMatrix<Scalar> m2(rows, cols);
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DenseMatrix refMat2(rows, cols);
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DenseVector b = DenseVector::Random(cols);
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DenseVector refX(cols), x(cols);
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initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag|MakeUpperTriangular, 0, 0);
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for(int i=0; i<rows; ++i)
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m2.coeffRef(i,i) = refMat2(i,i) = ei_abs(ei_real(refMat2(i,i)));
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refX = refMat2.template selfadjointView<Upper>().ldlt().solve(b);
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typedef SparseMatrix<Scalar,Upper|SelfAdjoint> SparseSelfAdjointMatrix;
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x = b;
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SparseLDLT<SparseSelfAdjointMatrix> ldlt(m2);
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if (ldlt.succeeded())
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ldlt.solveInPlace(x);
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else
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std::cerr << "warning LDLT failed\n";
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VERIFY_IS_APPROX(refMat2.template selfadjointView<Upper>() * x, b);
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VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LDLT: default");
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#ifdef EIGEN_CHOLMOD_SUPPORT
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x = b;
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SparseLDLT<SparseSelfAdjointMatrix, Cholmod> ldlt2(m2);
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if (ldlt2.succeeded())
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ldlt2.solveInPlace(x);
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else
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std::cerr << "warning LDLT failed\n";
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VERIFY_IS_APPROX(refMat2.template selfadjointView<Upper>() * x, b);
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VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LDLT: cholmod solveInPlace");
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SparseLDLT<SparseSelfAdjointMatrix, Cholmod> ldlt3(m2);
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if (ldlt3.succeeded())
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x = ldlt3.solve(b);
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else
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std::cerr << "warning LDLT failed\n";
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VERIFY_IS_APPROX(refMat2.template selfadjointView<Upper>() * x, b);
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VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LDLT: cholmod solve");
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#endif
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}
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void test_sparse_ldlt()
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{
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for(int i = 0; i < g_repeat; i++) {
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CALL_SUBTEST_1(sparse_ldlt<double>(8, 8) );
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int s = ei_random<int>(1,300);
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CALL_SUBTEST_2(sparse_ldlt<std::complex<double> >(s,s) );
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CALL_SUBTEST_1(sparse_ldlt<double>(s,s) );
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}
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}
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