Hi,
I want to post the following post to the list.
I want to use conjugate gradient algorithm implemented in RcppEigen package for
solving large sparse matrices.
Since I am new to Rcpp and C++, I just started with the dense matrices.
// [[Rcpp::depends(RcppEigen)]]
#include <Rcpp.h>
#include <RcppEigen.h>
#include <Eigen/IterativeLinearSolvers>
using Eigen::SparseMatrix;
using Eigen::MappedSparseMatrix;
using Eigen::Map;
using Eigen::MatrixXd;
using Eigen::VectorXd;
using Rcpp::as;
using Eigen::ConjugateGradient;
typedef Eigen::MappedSparseMatrix<double> MSpMat;
// [[Rcpp::export]]
VectorXd getEigenValues(SEXP As, SEXP bs) {
const Map<MatrixXd> A(as<Map<MatrixXd> > (As));
const Map<VectorXd> b(as<Map<VectorXd> > (bs));
ConjugateGradient<MatrixXd> cg;
cg.compute(A);
VectorXd x=cg.solve(b);
return x;
}
This works as expected. Therefore, I thought to extend this to suit to sparse
matrices.
// [[Rcpp::depends(RcppEigen)]]
#include <Rcpp.h>
#include <RcppEigen.h>
#include <Eigen/IterativeLinearSolvers>
using Eigen::SparseMatrix;
using Eigen::MappedSparseMatrix;
using Eigen::Map;
using Eigen::MatrixXd;
using Eigen::VectorXd;
using Rcpp::as;
using Eigen::ConjugateGradient;
typedef Eigen::MappedSparseMatrix<double> MSpMat;
// [[Rcpp::export]]
VectorXd getEigenValues(SEXP As, SEXP bs) {
const MSpMat A = as<MSpMat>(As);
const Map<VectorXd> b(as<Map<VectorXd> > (bs));
ConjugateGradient<SparseMatrix<double> > cg;
cg.compute(A);
VectorXd x=cg.solve(b);
return x;
}
However, this tends to give really strange results. The code in itself is also
not giving any errors. Hope someone could help me to correct this error.
Thanks.
Regards,
Shanika Wickramasuriya_______________________________________________
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