Eigen::VectorXf testEigen2(const Eigen::MatrixXf &A,const Eigen::VectorXf &b){
Eigen::VectorXf x(size);
Eigen::ConjugateGradient<Eigen::MatrixXf > cg;
cg.compute(A);
x = cg.solve(b);
std::cout << "#iterations: " << cg.iterations() << std::endl;
std::cout << "estimated error: " << cg.error() << std::endl;
return x;
}
int main()
{
int n = 10;
Eigen::SparseMatrix<double> S = Eigen::MatrixXd::Random(n,n).sparseView(0.5,1);
S = S.transpose()*S;
MatrixReplacement A;
A.attachMyMatrix(S);
Eigen::VectorXd b(n), x;
b.setRandom();
// Solve Ax = b using various iterative solver with matrix-free version:
{
Eigen::ConjugateGradient<MatrixReplacement, Eigen::Lower|Eigen::Upper, Eigen::IdentityPreconditioner> cg;
cg.compute(A);
x = cg.solve(b);
std::cout << "CG: #iterations: " << cg.iterations() << ", estimated error: " << cg.error() << std::endl;
}
{
Eigen::BiCGSTAB<MatrixReplacement, Eigen::IdentityPreconditioner> bicg;
bicg.compute(A);
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;
}
}
std::pair<unsigned int, Real>
EigenSparseLinearSolver<T>::solve (SparseMatrix<T> &matrix_in,
NumericVector<T> &solution_in,
NumericVector<T> &rhs_in,
const double tol,
const unsigned int m_its)
{
START_LOG("solve()", "EigenSparseLinearSolver");
this->init ();
// Make sure the data passed in are really Eigen types
EigenSparseMatrix<T>& matrix = libmesh_cast_ref<EigenSparseMatrix<T>&>(matrix_in);
EigenSparseVector<T>& solution = libmesh_cast_ref<EigenSparseVector<T>&>(solution_in);
EigenSparseVector<T>& rhs = libmesh_cast_ref<EigenSparseVector<T>&>(rhs_in);
// Close the matrix and vectors in case this wasn't already done.
matrix.close();
solution.close();
rhs.close();
std::pair<unsigned int, Real> retval(0,0.);
// Solve the linear system
switch (this->_solver_type)
{
// Conjugate-Gradient
case CG:
{
Eigen::ConjugateGradient<EigenSM> solver (matrix._mat);
solver.setMaxIterations(m_its);
solver.setTolerance(tol);
solution._vec = solver.solveWithGuess(rhs._vec,solution._vec);
libMesh::out << "#iterations: " << solver.iterations() << std::endl;
libMesh::out << "estimated error: " << solver.error() << std::endl;
retval = std::make_pair(solver.iterations(), solver.error());
break;
}
// Bi-Conjugate Gradient Stabilized
case BICGSTAB:
{
Eigen::BiCGSTAB<EigenSM> solver (matrix._mat);
solver.setMaxIterations(m_its);
solver.setTolerance(tol);
solution._vec = solver.solveWithGuess(rhs._vec,solution._vec);
libMesh::out << "#iterations: " << solver.iterations() << std::endl;
libMesh::out << "estimated error: " << solver.error() << std::endl;
retval = std::make_pair(solver.iterations(), solver.error());
break;
}
// // Generalized Minimum Residual
// case GMRES:
// {
// libmesh_not_implemented();
// break;
// }
// Unknown solver, use BICGSTAB
default:
{
libMesh::err << "ERROR: Unsupported Eigen Solver: "
<< Utility::enum_to_string(this->_solver_type) << std::endl
<< "Continuing with BICGSTAB" << std::endl;
this->_solver_type = BICGSTAB;
STOP_LOG("solve()", "EigenSparseLinearSolver");
return this->solve (matrix,
solution,
rhs,
tol,
m_its);
}
}
STOP_LOG("solve()", "EigenSparseLinearSolver");
return retval;
}