#include <iostream>
#include <Eigen/Core>
#include <Eigen/Dense>
#include <Eigen/IterativeLinearSolvers>
#include <unsupported/Eigen/IterativeSolvers>
class MatrixReplacement;
namespace internal {
template<>
struct traits<MatrixReplacement> : public Eigen::internal::traits<Eigen::SparseMatrix<double> >
{};
}
}
public:
typedef double Scalar;
typedef double RealScalar;
typedef int StorageIndex;
enum {
IsRowMajor = false
};
Index rows()
const {
return mp_mat->rows(); }
Index cols()
const {
return mp_mat->cols(); }
template<typename Rhs>
}
MatrixReplacement() : mp_mat(0) {}
void attachMyMatrix(const SparseMatrix<double> &mat) {
mp_mat = &mat;
}
const SparseMatrix<double> my_matrix() const { return *mp_mat; }
private:
const SparseMatrix<double> *mp_mat;
};
namespace internal {
template<typename Rhs>
struct generic_product_impl<MatrixReplacement, Rhs, SparseShape, DenseShape, GemvProduct>
: generic_product_impl_base<MatrixReplacement,Rhs,generic_product_impl<MatrixReplacement,Rhs> >
{
typedef typename Product<MatrixReplacement,Rhs>::Scalar Scalar;
template<typename Dest>
static void scaleAndAddTo(Dest& dst, const MatrixReplacement& lhs, const Rhs& rhs, const Scalar& alpha)
{
assert(alpha==Scalar(1) && "scaling is not implemented");
EIGEN_ONLY_USED_FOR_DEBUG(alpha);
for(
Index i=0; i<lhs.cols(); ++i)
dst += rhs(i) * lhs.my_matrix().col(i);
}
};
}
}
int main()
{
int n = 10;
S = S.transpose()*S;
MatrixReplacement A;
A.attachMyMatrix(S);
{
std::cout <<
"CG: #iterations: " << cg.
iterations() <<
", estimated error: " << cg.
error() << std::endl;
}
{
std::cout <<
"BiCGSTAB: #iterations: " << bicg.
iterations() <<
", estimated error: " << bicg.
error() << std::endl;
}
{
Eigen::GMRES<MatrixReplacement, Eigen::IdentityPreconditioner> gmres;
gmres.compute(A);
x = gmres.solve(b);
std::cout << "GMRES: #iterations: " << gmres.iterations() << ", estimated error: " << gmres.error() << std::endl;
}
{
Eigen::DGMRES<MatrixReplacement, Eigen::IdentityPreconditioner> gmres;
gmres.compute(A);
x = gmres.solve(b);
std::cout << "DGMRES: #iterations: " << gmres.iterations() << ", estimated error: " << gmres.error() << std::endl;
}
{
Eigen::MINRES<MatrixReplacement, Eigen::Lower|Eigen::Upper, Eigen::IdentityPreconditioner> minres;
minres.compute(A);
x = minres.solve(b);
std::cout << "MINRES: #iterations: " << minres.iterations() << ", estimated error: " << minres.error() << std::endl;
}
}
A bi conjugate gradient stabilized solver for sparse square problems.
Definition: BiCGSTAB.h:161
A conjugate gradient solver for sparse (or dense) self-adjoint problems.
Definition: ConjugateGradient.h:161
static const RandomReturnType Random()
Definition: Random.h:114
Derived & derived()
Definition: EigenBase.h:48
RealScalar error() const
Definition: IterativeSolverBase.h:310
Derived & compute(const EigenBase< MatrixDerived > &A)
Definition: IterativeSolverBase.h:243
Index iterations() const
Definition: IterativeSolverBase.h:301
Base class for all dense matrices, vectors, and expressions.
Definition: MatrixBase.h:52
The matrix class, also used for vectors and row-vectors.
Definition: Matrix.h:182
Derived & setRandom(Index size)
Definition: Random.h:152
Expression of the product of two arbitrary matrices or vectors.
Definition: Product.h:77
A versatible sparse matrix representation.
Definition: SparseMatrix.h:100
const Solve< Derived, Rhs > solve(const MatrixBase< Rhs > &b) const
Definition: SparseSolverBase.h:92
Namespace containing all symbols from the Eigen library.
Definition: Core:139
EIGEN_DEFAULT_DENSE_INDEX_TYPE Index
The Index type as used for the API.
Definition: Meta.h:59
const Product< MatrixDerived, PermutationDerived, AliasFreeProduct > operator*(const MatrixBase< MatrixDerived > &matrix, const PermutationBase< PermutationDerived > &permutation)
Definition: PermutationMatrix.h:517
const int Dynamic
Definition: Constants.h:24
Definition: EigenBase.h:32