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authorGravatar Gael Guennebaud <g.gael@free.fr>2015-02-10 18:57:41 +0100
committerGravatar Gael Guennebaud <g.gael@free.fr>2015-02-10 18:57:41 +0100
commitc6e8caf0900ae303e9e7399bed00af705015ff17 (patch)
tree384831cf695f94eb5fca5744a1b05a9cf8930e85
parentd10d6a40dda3fb5ac9f401b8e6d9cede3f3ca34a (diff)
Allows Lower|Upper as a template argument of CG and MINRES: in this case the full matrix will be considered.
-rw-r--r--Eigen/src/IterativeLinearSolvers/ConjugateGradient.h11
-rw-r--r--test/conjugate_gradient.cpp6
-rw-r--r--test/sparse_solver.h5
-rw-r--r--unsupported/Eigen/src/IterativeSolvers/MINRES.h7
-rw-r--r--unsupported/test/minres.cpp2
5 files changed, 23 insertions, 8 deletions
diff --git a/Eigen/src/IterativeLinearSolvers/ConjugateGradient.h b/Eigen/src/IterativeLinearSolvers/ConjugateGradient.h
index 3e024bda1..4857dd9e9 100644
--- a/Eigen/src/IterativeLinearSolvers/ConjugateGradient.h
+++ b/Eigen/src/IterativeLinearSolvers/ConjugateGradient.h
@@ -113,8 +113,8 @@ struct traits<ConjugateGradient<_MatrixType,_UpLo,_Preconditioner> >
* The matrix A must be selfadjoint. The matrix A and the vectors x and b can be either dense or sparse.
*
* \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
- * or Upper. Default is Lower.
+ * \tparam _UpLo the triangular part that will be used for the computations. It can be 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
*
* The maximal number of iterations and tolerance value can be controlled via the setMaxIterations()
@@ -197,6 +197,10 @@ public:
template<typename Rhs,typename Dest>
void _solve_with_guess_impl(const Rhs& b, Dest& x) const
{
+ typedef typename internal::conditional<UpLo==(Lower|Upper),
+ Ref<const MatrixType>&,
+ SparseSelfAdjointView<const Ref<const MatrixType>, UpLo>
+ >::type MatrixWrapperType;
m_iterations = Base::maxIterations();
m_error = Base::m_tolerance;
@@ -206,8 +210,7 @@ public:
m_error = Base::m_tolerance;
typename Dest::ColXpr xj(x,j);
- internal::conjugate_gradient(mp_matrix.template selfadjointView<UpLo>(), b.col(j), xj,
- Base::m_preconditioner, m_iterations, m_error);
+ internal::conjugate_gradient(MatrixWrapperType(mp_matrix), b.col(j), xj, Base::m_preconditioner, m_iterations, m_error);
}
m_isInitialized = true;
diff --git a/test/conjugate_gradient.cpp b/test/conjugate_gradient.cpp
index 869051b31..019cc4d64 100644
--- a/test/conjugate_gradient.cpp
+++ b/test/conjugate_gradient.cpp
@@ -12,13 +12,15 @@
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 > cg_colmajor_lower_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>, Upper, IdentityPreconditioner> cg_colmajor_upper_I;
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_loup_diag) );
CALL_SUBTEST( check_sparse_spd_solving(cg_colmajor_lower_I) );
CALL_SUBTEST( check_sparse_spd_solving(cg_colmajor_upper_I) );
}
diff --git a/test/sparse_solver.h b/test/sparse_solver.h
index 887ff02a9..6cf99e0b0 100644
--- a/test/sparse_solver.h
+++ b/test/sparse_solver.h
@@ -195,7 +195,10 @@ int generate_sparse_spd_problem(Solver& , typename Solver::MatrixType& A, typena
dA = dM * dM.adjoint();
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;
}
diff --git a/unsupported/Eigen/src/IterativeSolvers/MINRES.h b/unsupported/Eigen/src/IterativeSolvers/MINRES.h
index a34902001..65cffc255 100644
--- a/unsupported/Eigen/src/IterativeSolvers/MINRES.h
+++ b/unsupported/Eigen/src/IterativeSolvers/MINRES.h
@@ -250,6 +250,11 @@ namespace Eigen {
template<typename Rhs,typename Dest>
void _solve_with_guess_impl(const Rhs& b, Dest& x) const
{
+ typedef typename internal::conditional<UpLo==(Lower|Upper),
+ Ref<const MatrixType>&,
+ SparseSelfAdjointView<const Ref<const MatrixType>, UpLo>
+ >::type MatrixWrapperType;
+
m_iterations = Base::maxIterations();
m_error = Base::m_tolerance;
@@ -259,7 +264,7 @@ namespace Eigen {
m_error = Base::m_tolerance;
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);
}
diff --git a/unsupported/test/minres.cpp b/unsupported/test/minres.cpp
index 81b762c37..f6e526bbd 100644
--- a/unsupported/test/minres.cpp
+++ b/unsupported/test/minres.cpp
@@ -21,6 +21,7 @@ template<typename T> void test_minres_T()
// 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, DiagonalPreconditioner<T> > minres_colmajor_uplo_diag;
// call tests for SPD matrix
CALL_SUBTEST( check_sparse_spd_solving(minres_colmajor_lower_I) );
@@ -28,6 +29,7 @@ template<typename T> void test_minres_T()
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