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Diffstat (limited to 'test/eigen2/eigen2_sparse_solvers.cpp')
| -rw-r--r-- | test/eigen2/eigen2_sparse_solvers.cpp | 200 |
1 files changed, 0 insertions, 200 deletions
diff --git a/test/eigen2/eigen2_sparse_solvers.cpp b/test/eigen2/eigen2_sparse_solvers.cpp deleted file mode 100644 index 3aef27ab4..000000000 --- a/test/eigen2/eigen2_sparse_solvers.cpp +++ /dev/null @@ -1,200 +0,0 @@ -// This file is part of Eigen, a lightweight C++ template library -// for linear algebra. Eigen itself is part of the KDE project. -// -// Copyright (C) 2008 Daniel Gomez Ferro <dgomezferro@gmail.com> -// -// This Source Code Form is subject to the terms of the Mozilla -// Public License v. 2.0. If a copy of the MPL was not distributed -// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. - -#include "sparse.h" - -template<typename Scalar> void -initSPD(double density, - Matrix<Scalar,Dynamic,Dynamic>& refMat, - SparseMatrix<Scalar>& sparseMat) -{ - Matrix<Scalar,Dynamic,Dynamic> aux(refMat.rows(),refMat.cols()); - initSparse(density,refMat,sparseMat); - refMat = refMat * refMat.adjoint(); - for (int k=0; k<2; ++k) - { - initSparse(density,aux,sparseMat,ForceNonZeroDiag); - refMat += aux * aux.adjoint(); - } - sparseMat.startFill(); - for (int j=0 ; j<sparseMat.cols(); ++j) - for (int i=j ; i<sparseMat.rows(); ++i) - if (refMat(i,j)!=Scalar(0)) - sparseMat.fill(i,j) = refMat(i,j); - sparseMat.endFill(); -} - -template<typename Scalar> void sparse_solvers(int rows, int cols) -{ - double density = std::max(8./(rows*cols), 0.01); - typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix; - typedef Matrix<Scalar,Dynamic,1> DenseVector; - // Scalar eps = 1e-6; - - DenseVector vec1 = DenseVector::Random(rows); - - std::vector<Vector2i> zeroCoords; - std::vector<Vector2i> nonzeroCoords; - - // test triangular solver - { - DenseVector vec2 = vec1, vec3 = vec1; - SparseMatrix<Scalar> m2(rows, cols); - DenseMatrix refMat2 = DenseMatrix::Zero(rows, cols); - - // lower - initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag|MakeLowerTriangular, &zeroCoords, &nonzeroCoords); - VERIFY_IS_APPROX(refMat2.template marked<LowerTriangular>().solveTriangular(vec2), - m2.template marked<LowerTriangular>().solveTriangular(vec3)); - - // lower - transpose - initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag|MakeLowerTriangular, &zeroCoords, &nonzeroCoords); - VERIFY_IS_APPROX(refMat2.template marked<LowerTriangular>().transpose().solveTriangular(vec2), - m2.template marked<LowerTriangular>().transpose().solveTriangular(vec3)); - - // upper - initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag|MakeUpperTriangular, &zeroCoords, &nonzeroCoords); - VERIFY_IS_APPROX(refMat2.template marked<UpperTriangular>().solveTriangular(vec2), - m2.template marked<UpperTriangular>().solveTriangular(vec3)); - - // upper - transpose - initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag|MakeUpperTriangular, &zeroCoords, &nonzeroCoords); - VERIFY_IS_APPROX(refMat2.template marked<UpperTriangular>().transpose().solveTriangular(vec2), - m2.template marked<UpperTriangular>().transpose().solveTriangular(vec3)); - } - - // test LLT - { - // TODO fix the issue with complex (see SparseLLT::solveInPlace) - SparseMatrix<Scalar> m2(rows, cols); - DenseMatrix refMat2(rows, cols); - - DenseVector b = DenseVector::Random(cols); - DenseVector refX(cols), x(cols); - - initSPD(density, refMat2, m2); - - refMat2.llt().solve(b, &refX); - typedef SparseMatrix<Scalar,LowerTriangular|SelfAdjoint> SparseSelfAdjointMatrix; - if (!NumTraits<Scalar>::IsComplex) - { - x = b; - SparseLLT<SparseSelfAdjointMatrix> (m2).solveInPlace(x); - VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: default"); - } - #ifdef EIGEN_CHOLMOD_SUPPORT - x = b; - SparseLLT<SparseSelfAdjointMatrix,Cholmod>(m2).solveInPlace(x); - VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: cholmod"); - #endif - if (!NumTraits<Scalar>::IsComplex) - { - #ifdef EIGEN_TAUCS_SUPPORT - x = b; - SparseLLT<SparseSelfAdjointMatrix,Taucs>(m2,IncompleteFactorization).solveInPlace(x); - VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: taucs (IncompleteFactorization)"); - x = b; - SparseLLT<SparseSelfAdjointMatrix,Taucs>(m2,SupernodalMultifrontal).solveInPlace(x); - VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: taucs (SupernodalMultifrontal)"); - x = b; - SparseLLT<SparseSelfAdjointMatrix,Taucs>(m2,SupernodalLeftLooking).solveInPlace(x); - VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: taucs (SupernodalLeftLooking)"); - #endif - } - } - - // test LDLT - if (!NumTraits<Scalar>::IsComplex) - { - // TODO fix the issue with complex (see SparseLDLT::solveInPlace) - SparseMatrix<Scalar> m2(rows, cols); - DenseMatrix refMat2(rows, cols); - - DenseVector b = DenseVector::Random(cols); - DenseVector refX(cols), x(cols); - - //initSPD(density, refMat2, m2); - initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag|MakeUpperTriangular, 0, 0); - refMat2 += refMat2.adjoint(); - refMat2.diagonal() *= 0.5; - - refMat2.ldlt().solve(b, &refX); - typedef SparseMatrix<Scalar,UpperTriangular|SelfAdjoint> SparseSelfAdjointMatrix; - x = b; - SparseLDLT<SparseSelfAdjointMatrix> ldlt(m2); - if (ldlt.succeeded()) - ldlt.solveInPlace(x); - VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LDLT: default"); - } - - // test LU - { - static int count = 0; - SparseMatrix<Scalar> m2(rows, cols); - DenseMatrix refMat2(rows, cols); - - DenseVector b = DenseVector::Random(cols); - DenseVector refX(cols), x(cols); - - initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag, &zeroCoords, &nonzeroCoords); - - LU<DenseMatrix> refLu(refMat2); - refLu.solve(b, &refX); - #if defined(EIGEN_SUPERLU_SUPPORT) || defined(EIGEN_UMFPACK_SUPPORT) - Scalar refDet = refLu.determinant(); - #endif - x.setZero(); - // // SparseLU<SparseMatrix<Scalar> > (m2).solve(b,&x); - // // VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LU: default"); - #ifdef EIGEN_SUPERLU_SUPPORT - { - x.setZero(); - SparseLU<SparseMatrix<Scalar>,SuperLU> slu(m2); - if (slu.succeeded()) - { - if (slu.solve(b,&x)) { - VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LU: SuperLU"); - } - // std::cerr << refDet << " == " << slu.determinant() << "\n"; - if (count==0) { - VERIFY_IS_APPROX(refDet,slu.determinant()); // FIXME det is not very stable for complex - } - } - } - #endif - #ifdef EIGEN_UMFPACK_SUPPORT - { - // check solve - x.setZero(); - SparseLU<SparseMatrix<Scalar>,UmfPack> slu(m2); - if (slu.succeeded()) { - if (slu.solve(b,&x)) { - if (count==0) { - VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LU: umfpack"); // FIXME solve is not very stable for complex - } - } - VERIFY_IS_APPROX(refDet,slu.determinant()); - // TODO check the extracted data - //std::cerr << slu.matrixL() << "\n"; - } - } - #endif - count++; - } - -} - -void test_eigen2_sparse_solvers() -{ - for(int i = 0; i < g_repeat; i++) { - CALL_SUBTEST_1( sparse_solvers<double>(8, 8) ); - CALL_SUBTEST_2( sparse_solvers<std::complex<double> >(16, 16) ); - CALL_SUBTEST_1( sparse_solvers<double>(101, 101) ); - } -} |