[eigen] Sparse non-SPD symmetric solving |

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Hi,
I want to solve a symmetric, non-definite positive sparse linear
system. My input is a matrix whose values are stored into the upper
part.
I wonder if the following is the best way to solve the system. I am
concerned about my handling of the symmetric matrix: should I use the
adjoint view or try to build an adjoint matrix from the beginning?
Eigen::SparseMatrix<double> A;
A.setFromTriplets(...);
Eigen::SparseLU<Eigen::SparseMatrix<double>> solver;
solver.isSymmetric(true);
solver.compute(A.selfadjointView(Eigen::Upper)).solve(b);
Thanks,
--
Alberto