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#include <iostream>
#include <StormEigen/Core>
#include <StormEigen/Dense>
#include <StormEigen/IterativeLinearSolvers>
#include <unsupported/StormEigen/IterativeSolvers>
class MatrixReplacement; using StormEigen::SparseMatrix;
namespace StormEigen { namespace internal { // MatrixReplacement looks-like a SparseMatrix, so let's inherits its traits:
template<> struct traits<MatrixReplacement> : public StormEigen::internal::traits<StormEigen::SparseMatrix<double> > {}; } }
// Example of a matrix-free wrapper from a user type to Eigen's compatible type
// For the sake of simplicity, this example simply wrap a StormEigen::SparseMatrix.
class MatrixReplacement : public StormEigen::EigenBase<MatrixReplacement> { public: // Required typedefs, constants, and method:
typedef double Scalar; typedef double RealScalar; typedef int StorageIndex; enum { ColsAtCompileTime = StormEigen::Dynamic, MaxColsAtCompileTime = StormEigen::Dynamic, IsRowMajor = false };
Index rows() const { return mp_mat->rows(); } Index cols() const { return mp_mat->cols(); }
template<typename Rhs> StormEigen::Product<MatrixReplacement,Rhs,StormEigen::AliasFreeProduct> operator*(const Eigen::MatrixBase<Rhs>& x) const { return StormEigen::Product<MatrixReplacement,Rhs,StormEigen::AliasFreeProduct>(*this, x.derived()); }
// Custom API:
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; };
// Implementation of MatrixReplacement * StormEigen::DenseVector though a specialization of internal::generic_product_impl:
namespace StormEigen { namespace internal {
template<typename Rhs> struct generic_product_impl<MatrixReplacement, Rhs, SparseShape, DenseShape, GemvProduct> // GEMV stands for matrix-vector
: 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) { // This method should implement "dst += alpha * lhs * rhs" inplace,
// however, for iterative solvers, alpha is always equal to 1, so let's not bother about it.
assert(alpha==Scalar(1) && "scaling is not implemented");
// Here we could simply call dst.noalias() += lhs.my_matrix() * rhs,
// but let's do something fancier (and less efficient):
for(Index i=0; i<lhs.cols(); ++i) dst += rhs(i) * lhs.my_matrix().col(i); } };
} }
int main() { int n = 10; StormEigen::SparseMatrix<double> S = StormEigen::MatrixXd::Random(n,n).sparseView(0.5,1); S = S.transpose()*S;
MatrixReplacement A; A.attachMyMatrix(S);
StormEigen::VectorXd b(n), x; b.setRandom();
// Solve Ax = b using various iterative solver with matrix-free version:
{ StormEigen::ConjugateGradient<MatrixReplacement, StormEigen::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; }
{ StormEigen::BiCGSTAB<MatrixReplacement, StormEigen::IdentityPreconditioner> bicg; bicg.compute(A); x = bicg.solve(b); std::cout << "BiCGSTAB: #iterations: " << bicg.iterations() << ", estimated error: " << bicg.error() << std::endl; }
{ StormEigen::GMRES<MatrixReplacement, StormEigen::IdentityPreconditioner> gmres; gmres.compute(A); x = gmres.solve(b); std::cout << "GMRES: #iterations: " << gmres.iterations() << ", estimated error: " << gmres.error() << std::endl; }
{ StormEigen::DGMRES<MatrixReplacement, StormEigen::IdentityPreconditioner> gmres; gmres.compute(A); x = gmres.solve(b); std::cout << "DGMRES: #iterations: " << gmres.iterations() << ", estimated error: " << gmres.error() << std::endl; }
{ StormEigen::MINRES<MatrixReplacement, StormEigen::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; } }
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