add a generic unit test for sparse SPD problems

This commit is contained in:
Gael Guennebaud 2011-10-09 21:50:02 +02:00
parent 2fc1b58cd2
commit 1beb8a6564
4 changed files with 192 additions and 0 deletions

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@ -92,6 +92,9 @@ ei_add_test(sparse_llt "" "${SPARSE_LIBS}")
ei_add_test(sparse_ldlt "" "${SPARSE_LIBS}")
ei_add_test(sparse_lu_legacy "" "${SPARSE_LIBS}")
ei_add_test(simplicial_cholesky)
ei_add_test(conjugate_gradient)
if(UMFPACK_FOUND)
ei_add_test(umfpack_support "" "${UMFPACK_ALL_LIBS}")
endif()

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@ -0,0 +1,47 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2011 Gael Guennebaud <g.gael@free.fr>
//
// Eigen is free software; you can redistribute it and/or
// modify it under the terms of the GNU Lesser General Public
// License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#include "sparse_llt.h"
#include <Eigen/IterativeSolvers>
template<typename T> void test_conjugate_gradient_T()
{
ConjugateGradient<SparseMatrix<T>, Lower> cg_colmajor_lower_diag;
ConjugateGradient<SparseMatrix<T>, Upper> cg_colmajor_upper_diag;
ConjugateGradient<SparseMatrix<T>, Lower, IdentityPreconditioner> cg_colmajor_lower_I;
ConjugateGradient<SparseMatrix<T>, Upper, IdentityPreconditioner> cg_colmajor_upper_I;
sparse_llt(cg_colmajor_lower_diag);
sparse_llt(cg_colmajor_upper_diag);
sparse_llt(cg_colmajor_lower_I);
sparse_llt(cg_colmajor_upper_I);
}
void test_conjugate_gradient()
{
for(int i = 0; i < g_repeat; i++) {
CALL_SUBTEST_1(test_conjugate_gradient_T<double>());
CALL_SUBTEST_2(test_conjugate_gradient_T<std::complex<double> >());
}
}

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@ -0,0 +1,50 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2011 Gael Guennebaud <g.gael@free.fr>
//
// Eigen is free software; you can redistribute it and/or
// modify it under the terms of the GNU Lesser General Public
// License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#include "sparse_llt.h"
template<typename T> void test_simplicial_cholesky_T()
{
SimplicialCholesky<SparseMatrix<T>, Lower> chol_colmajor_lower;
SimplicialCholesky<SparseMatrix<T>, Upper> chol_colmajor_upper;
SimplicialLLt<SparseMatrix<T>, Lower> llt_colmajor_lower;
SimplicialLDLt<SparseMatrix<T>, Upper> llt_colmajor_upper;
SimplicialLDLt<SparseMatrix<T>, Lower> ldlt_colmajor_lower;
SimplicialLDLt<SparseMatrix<T>, Upper> ldlt_colmajor_upper;
sparse_llt(chol_colmajor_lower);
sparse_llt(chol_colmajor_upper);
sparse_llt(llt_colmajor_lower);
sparse_llt(llt_colmajor_upper);
sparse_llt(ldlt_colmajor_lower);
sparse_llt(ldlt_colmajor_upper);
}
void test_simplicial_cholesky()
{
for(int i = 0; i < g_repeat; i++) {
CALL_SUBTEST_1(test_simplicial_cholesky_T<double>());
CALL_SUBTEST_2(test_simplicial_cholesky_T<std::complex<double> >());
}
}

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@ -0,0 +1,92 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2011 Gael Guennebaud <g.gael@free.fr>
//
// Eigen is free software; you can redistribute it and/or
// modify it under the terms of the GNU Lesser General Public
// License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#include "sparse.h"
#include <Eigen/SparseExtra>
template<typename LLtSolver, typename Rhs, typename DenseMat, typename DenseRhs>
void check_sllt(LLtSolver& llt, const typename LLtSolver::MatrixType& A, const Rhs& b, const DenseMat& dA, const DenseRhs& db)
{
typedef typename LLtSolver::MatrixType Mat;
typedef typename Mat::Scalar Scalar;
DenseRhs refX = dA.ldlt().solve(db);
//Scalar refDet = dA.determinant();
Rhs x(b.rows(), b.cols());
Rhs oldb = b;
llt.compute(A);
if (llt.info() != Success)
{
std::cerr << "sparse LLt: factorization failed\n";
return;
}
x = llt.solve(b);
if (llt.info() != Success)
{
std::cerr << "sparse LLt: solving failed\n";
return;
}
VERIFY(oldb.isApprox(b) && "sparse LLt: the rhs should not be modified!");
VERIFY(refX.isApprox(x,test_precision<Scalar>()));
if(A.cols()<30)
{
//std::cout << refDet << " == " << lu.determinant() << "\n";
//VERIFY_IS_APPROX(refDet,llt.determinant());
}
}
template<typename LLtSolver> void sparse_llt(LLtSolver& llt)
{
typedef typename LLtSolver::MatrixType Mat;
typedef typename Mat::Scalar Scalar;
typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
typedef Matrix<Scalar,Dynamic,1> DenseVector;
std::vector<Vector2i> zeroCoords;
std::vector<Vector2i> nonzeroCoords;
int size = internal::random<int>(1,300);
double density = (std::max)(8./(size*size), 0.01);
//int rhsSize = internal::random<int>(1,10);
Mat m2(size, size);
DenseMatrix refMat2(size, size);
DenseVector b = DenseVector::Random(size);
DenseVector refX(size), x(size);
initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag, &zeroCoords, &nonzeroCoords);
Mat m3 = m2 * m2.adjoint(), m3_half(size,size);
DenseMatrix refMat3 = refMat2 * refMat2.adjoint();
m3_half.template selfadjointView<LLtSolver::UpLo>().rankUpdate(m2,0);
check_sllt(llt, m3, b, refMat3, b);
check_sllt(llt, m3_half, b, refMat3, b);
}