LinearSolverEigen< MatrixType >

linear solver which uses the sparse Cholesky solver from Eigen More...

Collaboration diagram for LinearSolverEigen< MatrixType >:

Classes
class	CholeskyDecomposition
	Sub-classing Eigen's SimplicialLDLT to perform ordering with a given ordering. More...

Public Types
typedef Eigen::PermutationMatrix< Eigen::Dynamic, Eigen::Dynamic, int >	PermutationMatrix
	Permutation matrix type.
typedef Eigen::SparseMatrix< g_type, Eigen::ColMajor >	SparseMatrix
	Column-major Eigen sparse matrix type.
typedef Eigen::Triplet< g_type >	Triplet
	Triplet type for sparse matrix construction.

Public Member Functions
	LinearSolverEigen ()
	Default constructor.
bool	blockOrdering () const
	do the AMD ordering on the blocks or on the scalar matrix
virtual bool	init ()
	Resets the solver for a new factorization.
bool	solve (const SparseBlockMatrix< MatrixType > &A, g_type *x, g_type *b)
	Solves the linear system Ax = b using sparse Cholesky decomposition.

Public Attributes
SparseOptimizer	optimizer
	The sparse optimizer instance.

Protected Member Functions
void	computeSymbolicDecomposition (const SparseBlockMatrix< MatrixType > &A)
	compute the symbolic decompostion of the matrix only once.

Protected Attributes
bool	_blockOrdering
	Whether to use block-level AMD ordering.
CholeskyDecomposition	_cholesky
	The Cholesky decomposition.
bool	_init
	Whether the symbolic decomposition needs to be (re)computed.
SparseMatrix	_sparseMatrix
	The Eigen sparse matrix representation.

Detailed Description

template<typename MatrixType>
class LinearSolverEigen< MatrixType >

linear solver which uses the sparse Cholesky solver from Eigen

Has no dependencies except Eigen. Hence, should compile almost everywhere without to much issues. Performance should be similar to CSparse, I guess.

Definition at line 46 of file linear_solver_eigen.h.

Member Function Documentation

computeSymbolicDecomposition()

template<typename MatrixType>

void LinearSolverEigen< MatrixType >::computeSymbolicDecomposition ( const SparseBlockMatrix< MatrixType > & A )

inlineprotected

compute the symbolic decompostion of the matrix only once.

Since A has the same pattern in all the iterations, we only compute the fill-in reducing ordering once and re-use for all the following iterations.

Definition at line 141 of file linear_solver_eigen.h.

References _blockOrdering, _cholesky, and _sparseMatrix.

Referenced by solve().

init()

template<typename MatrixType>

virtual bool LinearSolverEigen< MatrixType >::init ( )

inlinevirtual

Resets the solver for a new factorization.

Returns

True always.

Definition at line 91 of file linear_solver_eigen.h.

References _init.

solve()

template<typename MatrixType>

bool LinearSolverEigen< MatrixType >::solve ( const SparseBlockMatrix< MatrixType > & A, g_type * x, g_type * b )

inline

Solves the linear system Ax = b using sparse Cholesky decomposition.

Parameters

[in]	A	The sparse block matrix (symmetric, positive definite).
[out]	x	The solution vector.
[in]	b	The right-hand side vector.

Returns

True on success, false if the matrix is not positive definite.

Definition at line 102 of file linear_solver_eigen.h.

References _cholesky, _init, _sparseMatrix, and computeSymbolicDecomposition().

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The documentation for this class was generated from the following file:

• GraphOptimization/Headers/linear_solver_eigen.h