Is there an implementation of the conjugate gradient method in Eigen?

Thanks.

I'm polishing the one I have for a commit very very soon...

btw, there is also a SimplicialCholesky for directly solving Ax=b with A sparse and selfadjoint... Much faster than a conjugate gradient if the matrix is very sparse (e.g., 2 dimensional Poisson equation) and not too large ...

How do I use SimplicialCholesky by the way? I couldn't find any examples/documentation.

Thanks.

once you filled the upper of lower triangular part (or both) of your selfadjoint matrix:

Eigen::SimplicialCholesky<MatrixType,Eigen::Lower> solver(A);

x = solver.solve(b);
if(solver.info()!=Success)
{
// did not worked
}