Eigen::KLU< _MatrixType > Class Template Reference

Inheritance diagram for Eigen::KLU< _MatrixType >:

Public Types
enum	{ ColsAtCompileTime = MatrixType::ColsAtCompileTime , MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime }
typedef _MatrixType	MatrixType
typedef MatrixType::Scalar	Scalar
typedef MatrixType::RealScalar	RealScalar
typedef MatrixType::StorageIndex	StorageIndex
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 >	KLUMatrixType
typedef Ref< const KLUMatrixType, StandardCompressedFormat >	KLUMatrixRef

Public Member Functions
template<typename InputMatrixType >
	KLU (const InputMatrixType &matrix)
EIGEN_CONSTEXPR Index	rows () const EIGEN_NOEXCEPT
EIGEN_CONSTEXPR Index	cols () const EIGEN_NOEXCEPT
ComputationInfo	info () const
	Reports whether previous computation was successful.
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.
template<typename InputMatrixType >
void	analyzePattern (const InputMatrixType &matrix)
	Performs a symbolic decomposition on the sparcity of matrix.
const klu_common &	kluCommon () const
	Provides access to the control settings array used by KLU.
klu_common &	kluCommon ()
	Provides access to the control settings array used by UmfPack.
template<typename InputMatrixType >
void	factorize (const InputMatrixType &matrix)
	Performs a numeric decomposition of matrix.
template<typename BDerived , typename XDerived >
bool	_solve_impl (const MatrixBase< BDerived > &b, MatrixBase< XDerived > &x) const
Public Member Functions inherited from Eigen::SparseSolverBase< KLU< _MatrixType > >
	SparseSolverBase ()
	Default constructor.
KLU< _MatrixType > &	derived ()
const KLU< _MatrixType > &	derived () const
const Solve< KLU< _MatrixType >, Rhs >	solve (const MatrixBase< Rhs > &b) const
const Solve< KLU< _MatrixType >, Rhs >	solve (const SparseMatrixBase< Rhs > &b) const
void	_solve_impl (const SparseMatrixBase< Rhs > &b, SparseMatrixBase< Dest > &dest) const

Protected Types
typedef SparseSolverBase< KLU< _MatrixType > >	Base

Protected Member Functions
void	init ()
void	analyzePattern_impl ()
void	factorize_impl ()
template<typename MatrixDerived >
void	grab (const EigenBase< MatrixDerived > &A)
void	grab (const KLUMatrixRef &A)

Protected Attributes
KLUMatrixType	m_dummy
KLUMatrixRef	mp_matrix
klu_numeric *	m_numeric
klu_symbolic *	m_symbolic
klu_common	m_common
ComputationInfo	m_info
int	m_factorizationIsOk
int	m_analysisIsOk
bool	m_extractedDataAreDirty
Protected Attributes inherited from Eigen::SparseSolverBase< KLU< _MatrixType > >
bool	m_isInitialized

Member Function Documentation

analyzePattern()

template<typename _MatrixType >

template<typename InputMatrixType >

void Eigen::KLU< _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::KLU< _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::KLU< _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::KLU< _MatrixType >::info ( ) const

inline

Reports whether previous computation was successful.

Returns

Success if computation was successful, NumericalIssue if the matrix.appears to be negative.

kluCommon() [1/2]

template<typename _MatrixType >

klu_common & Eigen::KLU< _MatrixType >::kluCommon ( )

inline

Provides access to the control settings array used by UmfPack.

If this array contains NaN's, the default values are used.

See KLU documentation for details.

kluCommon() [2/2]

template<typename _MatrixType >

const klu_common & Eigen::KLU< _MatrixType >::kluCommon ( ) const

inline

Provides access to the control settings array used by KLU.

See KLU documentation for details.

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

• External/Eigen/src/KLUSupport/KLUSupport.h