block-tridiagonal.hpp File Reference

#include "aligator/gar/blk-matrix.hpp"
#include "aligator/eigen-macros.hpp"
#include "aligator/tracy.hpp"

Include dependency graph for block-tridiagonal.hpp:

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Namespaces
namespace	aligator
	Main package namespace.
namespace	aligator::gar

Functions
template<typename MatrixType >
MatrixType::PlainObject	aligator::gar::blockTridiagToDenseMatrix (const std::vector< MatrixType > &subdiagonal, const std::vector< MatrixType > &diagonal, const std::vector< MatrixType > &superdiagonal)
template<typename MatrixType , typename InputType , typename OutType , typename Scalar = typename MatrixType::Scalar>
bool	aligator::gar::blockTridiagMatMul (const std::vector< MatrixType > &Asub, const std::vector< MatrixType > &Adiag, const std::vector< MatrixType > &Asuper, const BlkMatrix< InputType, -1, 1 > &b, BlkMatrix< OutType, -1, 1 > &c, const Scalar beta)
template<typename MatrixType , typename RhsType , typename DecType >
bool	aligator::gar::symmetricBlockTridiagSolve (std::vector< MatrixType > &subdiagonal, std::vector< MatrixType > &diagonal, const std::vector< MatrixType > &superdiagonal, BlkMatrix< RhsType, -1, 1 > &rhs, std::vector< DecType > &facs)
	Solve a symmetric block-tridiagonal \(Ax=b\) problem by in-place factorization. The subdiagonal will be used to store factorization coefficients.
template<typename MatrixType , typename RhsType , typename DecType >
bool	aligator::gar::blockTridiagRefinementStep (const std::vector< MatrixType > &transposedUfacs, const std::vector< MatrixType > &superdiagonal, const std::vector< DecType > &diagonalFacs, BlkMatrix< RhsType, -1, 1 > &rhs)
	Given the decomposed matrix data, just perform the backward-forward step of the algorithm.
template<typename MatrixType , typename RhsType , typename DecType >
bool	aligator::gar::symmetricBlockTridiagSolveDownLooking (std::vector< MatrixType > &subdiagonal, std::vector< MatrixType > &diagonal, std::vector< MatrixType > &superdiagonal, BlkMatrix< RhsType, -1, 1 > &rhs, std::vector< DecType > &facs)
	Solve a symmetric block-tridiagonal \(Ax=b\) problem by in-place factorization. The subdiagonal will be used to store factorization coefficients. This version starts by looking down from the top-left corner of the matrix.