#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);
Eigen::VectorXd b(n), x;
b.setRandom();
{
x = cg.solve(b);
std::cout << "CG: #iterations: " << cg.iterations() << ", estimated error: " << cg.error() << std::endl;
}
{
x = bicg.solve(b);
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:159
A conjugate gradient solver for sparse (or dense) self-adjoint problems.
Definition ConjugateGradient.h:159
Derived & derived()
Definition EigenBase.h:46
Derived & compute(const EigenBase< MatrixDerived > &A)
Definition IterativeSolverBase.h:238
Base class for all dense matrices, vectors, and expressions.
Definition MatrixBase.h:50
Expression of the product of two arbitrary matrices or vectors.
Definition Product.h:75
A versatible sparse matrix representation.
Definition SparseMatrix.h:98
Namespace containing all symbols from the Eigen library.
Definition Core:141
const int Dynamic
Definition Constants.h:22
Definition EigenBase.h:30