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A have a symmetric matrix M with meaningful upper triangular part and arbitrary strict lower triangular part (in my case it is zero). I use development branch function M.selfadjointView<Eigen::UpperTriangular>().rankUpdate (values) at a previous step instead of Eigen2 M.part<Eigen::SelfAdjoint>() += values * values.transpose() one. I would like to use Cholesky decomposition. When I call Eigen::LDLT<Matrix> ldltOfM = M.selfadjointView<Eigen::UpperTriangular>().ldlt(), a linker issues the error message: “unresolved external symbol SelfAjointView<>::ldlt()”. There is reference “Cholesky module” before SelfAjointView::ldlt() member declaration, but I have not fond the implementation.
What is wrong?
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