Eigen::PastixLU< _MatrixType, IsStrSym > Class Template Reference

Interface to the PaStix solver. More...

#include <PaStiXSupport.h>

Public Types
typedef _MatrixType	MatrixType
typedef PastixBase< PastixLU< MatrixType > >	Base
typedef Base::ColSpMatrix	ColSpMatrix
typedef MatrixType::StorageIndex	StorageIndex

Public Member Functions
	PastixLU (const MatrixType &matrix)
void	compute (const MatrixType &matrix)
void	analyzePattern (const MatrixType &matrix)
void	factorize (const MatrixType &matrix)

Protected Member Functions
void	init ()
void	grabMatrix (const MatrixType &matrix, ColSpMatrix &out)

Protected Attributes
ColSpMatrix	m_transposedStructure
bool	m_structureIsUptodate
Array< int, IPARM_SIZE, 1 >	m_iparm
Array< double, DPARM_SIZE, 1 >	m_dparm

Detailed Description

template<typename _MatrixType, bool IsStrSym>
class Eigen::PastixLU< _MatrixType, IsStrSym >

Interface to the PaStix solver.

Sparse direct LU solver based on PaStiX library.

This class is used to solve the linear systems A.X = B via the PaStix library. The matrix can be either real or complex, symmetric or not.

See also

TutorialSparseDirectSolvers

This class is used to solve the linear systems A.X = B with a supernodal LU factorization in the PaStiX library. The matrix A should be squared and nonsingular PaStiX requires that the matrix A has a symmetric structural pattern. This interface can symmetrize the input matrix otherwise. The vectors or matrices X and B can be either dense or sparse.

Template Parameters

_MatrixType	the type of the sparse matrix A, it must be a SparseMatrix<>
IsStrSym	Indicates if the input matrix has a symmetric pattern, default is false NOTE : Note that if the analysis and factorization phase are called separately, the input matrix will be symmetrized at each call, hence it is advised to symmetrize the matrix in a end-user program and set IsStrSym to true

\implsparsesolverconcept

See also

TutorialSparseSolverConcept, class SparseLU

Member Function Documentation

analyzePattern()

template<typename _MatrixType , bool IsStrSym>

void Eigen::PastixLU< _MatrixType, IsStrSym >::analyzePattern ( const MatrixType &  matrix )

inline

Compute the LU symbolic factorization of matrix using its sparsity pattern. Several ordering methods can be used at this step. See the PaStiX user's manual. The result of this operation can be used with successive matrices having the same pattern as matrix

See also

factorize()

compute()

template<typename _MatrixType , bool IsStrSym>

void Eigen::PastixLU< _MatrixType, IsStrSym >::compute ( const MatrixType &  matrix )

inline

Compute the LU supernodal factorization of matrix. iparm and dparm can be used to tune the PaStiX parameters. see the PaStiX user's manual

See also

analyzePattern() factorize()

factorize()

template<typename _MatrixType , bool IsStrSym>

void Eigen::PastixLU< _MatrixType, IsStrSym >::factorize ( const MatrixType &  matrix )

inline

Compute the LU supernodal factorization of matrix WARNING The matrix matrix should have the same structural pattern as the same used in the analysis phase.

See also

analyzePattern()

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

• PaStiXSupport.h