mirror/eigen
2
0
Fork 0
mirror of https://gitlab.com/libeigen/eigen.git synced 2024-12-21 07:19:46 +08:00
Code Issues Packages Projects Releases Wiki Activity

Allows Lower|Upper as a template argument of CG and MINRES: in this case the full matrix will be considered.

Browse Source
This commit is contained in:
Gael Guennebaud 2015-02-10 18:57:41 +01:00
parent f9931a0392
commit 7b35b4cacc
5 changed files with 43 additions and 13 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

13
Eigen/src/IterativeLinearSolvers/ConjugateGradient.h
View File

@ -112,9 +112,9 @@ struct traits<ConjugateGradient<_MatrixType,_UpLo,_Preconditioner> >
* This class allows to solve for A.x = b sparse linear problems using a conjugate gradient algorithm. * This class allows to solve for A.x = b sparse linear problems using a conjugate gradient algorithm.
* The sparse matrix A must be selfadjoint. The vectors x and b can be either dense or sparse. * The sparse matrix A must be selfadjoint. The vectors x and b can be either dense or sparse.
* *
* \tparam _MatrixType the type of the sparse matrix A, can be a dense or a sparse matrix. * \tparam _MatrixType the type of the matrix A, can be a dense or a sparse matrix.
* \tparam _UpLo the triangular part that will be used for the computations. It can be Lower * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower,
* or Upper. Default is Lower. * Upper, or Lower|Upper in which the full matrix entries will be considered. Default is Lower.
* \tparam _Preconditioner the type of the preconditioner. Default is DiagonalPreconditioner * \tparam _Preconditioner the type of the preconditioner. Default is DiagonalPreconditioner
* *
* The maximal number of iterations and tolerance value can be controlled via the setMaxIterations() * The maximal number of iterations and tolerance value can be controlled via the setMaxIterations()
@ -213,6 +213,10 @@ public:
template<typename Rhs,typename Dest> template<typename Rhs,typename Dest>
void _solveWithGuess(const Rhs& b, Dest& x) const void _solveWithGuess(const Rhs& b, Dest& x) const
{ {
typedef typename internal::conditional<UpLo==(Lower|Upper),
const MatrixType&,
SparseSelfAdjointView<const MatrixType, UpLo>
>::type MatrixWrapperType;
m_iterations = Base::maxIterations(); m_iterations = Base::maxIterations();
m_error = Base::m_tolerance; m_error = Base::m_tolerance;
@ -222,8 +226,7 @@ public:
m_error = Base::m_tolerance; m_error = Base::m_tolerance;
typename Dest::ColXpr xj(x,j); typename Dest::ColXpr xj(x,j);
internal::conjugate_gradient(mp_matrix->template selfadjointView<UpLo>(), b.col(j), xj, internal::conjugate_gradient(MatrixWrapperType(*mp_matrix), b.col(j), xj, Base::m_preconditioner, m_iterations, m_error);
Base::m_preconditioner, m_iterations, m_error);
} }
m_isInitialized = true; m_isInitialized = true;

6
test/conjugate_gradient.cpp
View File

@ -12,13 +12,15 @@
template<typename T> void test_conjugate_gradient_T() template<typename T> void test_conjugate_gradient_T()
{ {
ConjugateGradient<SparseMatrix<T>, Lower> cg_colmajor_lower_diag; ConjugateGradient<SparseMatrix<T>, Lower > cg_colmajor_lower_diag;
ConjugateGradient<SparseMatrix<T>, Upper> cg_colmajor_upper_diag; ConjugateGradient<SparseMatrix<T>, Upper > cg_colmajor_upper_diag;
ConjugateGradient<SparseMatrix<T>, Lower|Upper> cg_colmajor_loup_diag;
ConjugateGradient<SparseMatrix<T>, Lower, IdentityPreconditioner> cg_colmajor_lower_I; ConjugateGradient<SparseMatrix<T>, Lower, IdentityPreconditioner> cg_colmajor_lower_I;
ConjugateGradient<SparseMatrix<T>, Upper, IdentityPreconditioner> cg_colmajor_upper_I; ConjugateGradient<SparseMatrix<T>, Upper, IdentityPreconditioner> cg_colmajor_upper_I;
CALL_SUBTEST( check_sparse_spd_solving(cg_colmajor_lower_diag) ); CALL_SUBTEST( check_sparse_spd_solving(cg_colmajor_lower_diag) );
CALL_SUBTEST( check_sparse_spd_solving(cg_colmajor_upper_diag) ); CALL_SUBTEST( check_sparse_spd_solving(cg_colmajor_upper_diag) );
CALL_SUBTEST( check_sparse_spd_solving(cg_colmajor_loup_diag) );
CALL_SUBTEST( check_sparse_spd_solving(cg_colmajor_lower_I) ); CALL_SUBTEST( check_sparse_spd_solving(cg_colmajor_lower_I) );
CALL_SUBTEST( check_sparse_spd_solving(cg_colmajor_upper_I) ); CALL_SUBTEST( check_sparse_spd_solving(cg_colmajor_upper_I) );
} }

5
test/sparse_solver.h
View File

@ -161,7 +161,10 @@ int generate_sparse_spd_problem(Solver& , typename Solver::MatrixType& A, typena
dA = dM * dM.adjoint(); dA = dM * dM.adjoint();
halfA.resize(size,size); halfA.resize(size,size);
halfA.template selfadjointView<Solver::UpLo>().rankUpdate(M); if(Solver::UpLo==(Lower|Upper))
halfA = A;
else
halfA.template selfadjointView<Solver::UpLo>().rankUpdate(M);
return size; return size;
} }

7
unsupported/Eigen/src/IterativeSolvers/MINRES.h
View File

@ -250,6 +250,11 @@ namespace Eigen {
template<typename Rhs,typename Dest> template<typename Rhs,typename Dest>
void _solveWithGuess(const Rhs& b, Dest& x) const void _solveWithGuess(const Rhs& b, Dest& x) const
{ {
typedef typename internal::conditional<UpLo==(Lower|Upper),
const MatrixType&,
SparseSelfAdjointView<const MatrixType, UpLo>
>::type MatrixWrapperType;
m_iterations = Base::maxIterations(); m_iterations = Base::maxIterations();
m_error = Base::m_tolerance; m_error = Base::m_tolerance;
@ -259,7 +264,7 @@ namespace Eigen {
m_error = Base::m_tolerance; m_error = Base::m_tolerance;
typename Dest::ColXpr xj(x,j); typename Dest::ColXpr xj(x,j);
internal::minres(mp_matrix->template selfadjointView<UpLo>(), b.col(j), xj, internal::minres(MatrixWrapperType(*mp_matrix), b.col(j), xj,
Base::m_preconditioner, m_iterations, m_error); Base::m_preconditioner, m_iterations, m_error);
} }

25
unsupported/test/minres.cpp
View File

@ -14,15 +14,32 @@
template<typename T> void test_minres_T() template<typename T> void test_minres_T()
{ {
MINRES<SparseMatrix<T>, Lower, DiagonalPreconditioner<T> > minres_colmajor_diag; MINRES<SparseMatrix<T>, Lower|Upper, DiagonalPreconditioner<T> > minres_colmajor_diag;
MINRES<SparseMatrix<T>, Lower, IdentityPreconditioner > minres_colmajor_I; MINRES<SparseMatrix<T>, Lower, IdentityPreconditioner > minres_colmajor_lower_I;
MINRES<SparseMatrix<T>, Upper, IdentityPreconditioner > minres_colmajor_upper_I;
// MINRES<SparseMatrix<T>, Lower, IncompleteLUT<T> > minres_colmajor_ilut; // MINRES<SparseMatrix<T>, Lower, IncompleteLUT<T> > minres_colmajor_ilut;
//minres<SparseMatrix<T>, SSORPreconditioner<T> > minres_colmajor_ssor; //minres<SparseMatrix<T>, SSORPreconditioner<T> > minres_colmajor_ssor;
CALL_SUBTEST( check_sparse_square_solving(minres_colmajor_diag) );
CALL_SUBTEST( check_sparse_spd_solving(minres_colmajor_I) ); // CALL_SUBTEST( check_sparse_square_solving(minres_colmajor_diag) );
// CALL_SUBTEST( check_sparse_square_solving(minres_colmajor_ilut) ); // CALL_SUBTEST( check_sparse_square_solving(minres_colmajor_ilut) );
//CALL_SUBTEST( check_sparse_square_solving(minres_colmajor_ssor) ); //CALL_SUBTEST( check_sparse_square_solving(minres_colmajor_ssor) );
// Diagonal preconditioner
MINRES<SparseMatrix<T>, Lower, DiagonalPreconditioner<T> > minres_colmajor_lower_diag;
MINRES<SparseMatrix<T>, Upper, DiagonalPreconditioner<T> > minres_colmajor_upper_diag;
MINRES<SparseMatrix<T>, Upper|Lower, DiagonalPreconditioner<T> > minres_colmajor_uplo_diag;
// call tests for SPD matrix
CALL_SUBTEST( check_sparse_spd_solving(minres_colmajor_lower_I) );
CALL_SUBTEST( check_sparse_spd_solving(minres_colmajor_upper_I) );
CALL_SUBTEST( check_sparse_spd_solving(minres_colmajor_lower_diag) );
CALL_SUBTEST( check_sparse_spd_solving(minres_colmajor_upper_diag) );
// CALL_SUBTEST( check_sparse_spd_solving(minres_colmajor_uplo_diag) );
// TO DO: symmetric semi-definite matrix
// TO DO: symmetric indefinite matrix
} }
void test_minres() void test_minres()