A sparse LU factorization and solver based on UmfPack. More...

#include <UmfPackSupport.h>

Inheritance diagram for Eigen::UmfPackLU< _MatrixType >:

Public Types
typedef _MatrixType	MatrixType

typedef MatrixType::Scalar	Scalar

typedef MatrixType::RealScalar	RealScalar

typedef MatrixType::Index	Index

typedef Matrix< Scalar, Dynamic, 1 >	Vector

typedef Matrix< int, 1, MatrixType::ColsAtCompileTime >	IntRowVectorType

typedef Matrix< int, MatrixType::RowsAtCompileTime, 1 >	IntColVectorType

typedef SparseMatrix< Scalar >	LUMatrixType

typedef SparseMatrix< Scalar, ColMajor, int >	UmfpackMatrixType

Public Member Functions
	UmfPackLU (const MatrixType &matrix)

Index	rows () const

Index	cols () const

ComputationInfo	info () const
	Reports whether previous computation was successful. More...

const LUMatrixType &	matrixL () const

const LUMatrixType &	matrixU () const

const IntColVectorType &	permutationP () const

const IntRowVectorType &	permutationQ () const

template<typename InputMatrixType >
void	compute (const InputMatrixType &matrix)
	Computes the sparse Cholesky decomposition of matrix Note that the matrix should be column-major, and in compressed format for best performance. More...

template<typename Rhs >
const internal::solve_retval< UmfPackLU, Rhs >	solve (const MatrixBase< Rhs > &b) const

template<typename Rhs >
const internal::sparse_solve_retval< UmfPackLU, Rhs >	solve (const SparseMatrixBase< Rhs > &b) const

template<typename InputMatrixType >
void	analyzePattern (const InputMatrixType &matrix)
	Performs a symbolic decomposition on the sparcity of matrix. More...

template<typename InputMatrixType >
void	factorize (const InputMatrixType &matrix)
	Performs a numeric decomposition of matrix. More...

template<typename BDerived , typename XDerived >
bool	_solve (const MatrixBase< BDerived > &b, MatrixBase< XDerived > &x) const

Scalar	determinant () const

void	extractData () const

Protected Member Functions
void	init ()

template<typename InputMatrixType >
void	grapInput_impl (const InputMatrixType &mat, internal::true_type)

template<typename InputMatrixType >
void	grapInput_impl (const InputMatrixType &mat, internal::false_type)

template<typename InputMatrixType >
void	grapInput (const InputMatrixType &mat)

void	analyzePattern_impl ()

void	factorize_impl ()

Protected Attributes
LUMatrixType	m_l

LUMatrixType	m_u

IntColVectorType	m_p

IntRowVectorType	m_q

UmfpackMatrixType	m_copyMatrix

const Scalar *	m_valuePtr

const int *	m_outerIndexPtr

const int *	m_innerIndexPtr

void *	m_numeric

void *	m_symbolic

ComputationInfo	m_info

bool	m_isInitialized

int	m_factorizationIsOk

int	m_analysisIsOk

bool	m_extractedDataAreDirty

Detailed Description

template<typename _MatrixType>
class Eigen::UmfPackLU< _MatrixType >

A sparse LU factorization and solver based on UmfPack.

This class allows to solve for A.X = B sparse linear problems via a LU factorization using the UmfPack library. The sparse matrix A must be squared and full rank. The vectors or matrices X and B can be either dense or sparse.

Warning: The input matrix A should be in a compressed and column-major form. Otherwise an expensive copy will be made. You can call the inexpensive makeCompressed() to get a compressed matrix.

Template Parameters

_MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>

See also: Sparse solvers

Member Function Documentation

§ analyzePattern()

template<typename _MatrixType>

template<typename InputMatrixType >

void Eigen::UmfPackLU< _MatrixType >::analyzePattern ( const InputMatrixType & matrix )

inline

Performs a symbolic decomposition on the sparcity of matrix.

This function is particularly useful when solving for several problems having the same structure.

See also: factorize(), compute()

§ compute()

template<typename _MatrixType>

template<typename InputMatrixType >

void Eigen::UmfPackLU< _MatrixType >::compute ( const InputMatrixType & matrix )

inline

Computes the sparse Cholesky decomposition of matrix Note that the matrix should be column-major, and in compressed format for best performance.

See also: SparseMatrix::makeCompressed().

§ factorize()

template<typename _MatrixType>

template<typename InputMatrixType >

void Eigen::UmfPackLU< _MatrixType >::factorize ( const InputMatrixType & matrix )

inline

Performs a numeric decomposition of matrix.

The given matrix must has the same sparcity than the matrix on which the pattern anylysis has been performed.

See also: analyzePattern(), compute()

§ info()

template<typename _MatrixType>

ComputationInfo Eigen::UmfPackLU< _MatrixType >::info ( ) const

inline

Reports whether previous computation was successful.

Returns: Success if computation was succesful, NumericalIssue if the matrix.appears to be negative.

§ solve() [1/2]

template<typename _MatrixType>

template<typename Rhs >

const internal::solve_retval<UmfPackLU, Rhs> Eigen::UmfPackLU< _MatrixType >::solve ( const MatrixBase< Rhs > & b ) const

inline

Returns: the solution x of \( A x = b \) using the current decomposition of A.

See also: compute()

§ solve() [2/2]

template<typename _MatrixType>

template<typename Rhs >

const internal::sparse_solve_retval<UmfPackLU, Rhs> Eigen::UmfPackLU< _MatrixType >::solve ( const SparseMatrixBase< Rhs > & b ) const

inline

Returns: the solution x of \( A x = b \) using the current decomposition of A.

See also: compute()

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

vendor/eigen/Eigen/src/UmfPackSupport/UmfPackSupport.h

Public Types

Public Member Functions

Protected Member Functions

Protected Attributes

Detailed Description

template<typename _MatrixType> class Eigen::UmfPackLU< _MatrixType >

Member Function Documentation

§ analyzePattern()

§ compute()

§ factorize()

§ info()

§ solve() [1/2]

§ solve() [2/2]

template<typename _MatrixType>
class Eigen::UmfPackLU< _MatrixType >