Eigen::SparseLU< _MatrixType, Backend > Class Template Reference

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Detailed Description

template<typename _MatrixType, typename Backend = DefaultBackend>
class Eigen::SparseLU< _MatrixType, Backend >

LU decomposition of a sparse matrix and associated features.

Parameters:

_MatrixType

the type of the matrix of which we are computing the LU factorization

See also:

class FullPivLU, class SparseLLT

Definition at line 46 of file SparseExtra.

Inheritance diagram for Eigen::SparseLU< _MatrixType, Backend >:

List of all members.

Public Types
typedef _MatrixType	MatrixType
Public Member Functions
	SparseLU (int flags=0)
	Creates a dummy LU factorization object with flags flags.
	SparseLU (const _MatrixType &matrix, int flags=0)
	Creates a LU object and compute the respective factorization of matrix using flags flags.
void	setPrecision (RealScalar v)
	Sets the relative threshold value used to prune zero coefficients during the decomposition.
RealScalar	precision () const
void	setFlags (int f)
	Sets the flags.
int	flags () const
void	setOrderingMethod (int m)
int	orderingMethod () const
void	compute (const _MatrixType &matrix)
	Computes/re-computes the LU factorization.
template<typename BDerived , typename XDerived >
bool	solve (const MatrixBase< BDerived > &b, MatrixBase< XDerived > *x, const int transposed=SvNoTrans) const
	Computes *x = U^-1 L^-1 b.
bool	succeeded (void) const
template<typename BDerived , typename XDerived >
bool	solve (const MatrixBase< BDerived > &b, MatrixBase< XDerived > *x) const
Protected Types
enum	{ MatrixLUIsDirty = 0x10000 }
typedef _MatrixType::Scalar	Scalar
typedef NumTraits< typename _MatrixType::Scalar >::Real	RealScalar
typedef SparseMatrix< Scalar >	LUMatrixType
Protected Attributes
RealScalar	m_precision
int	m_flags
int	m_status
bool	m_succeeded

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Member Typedef Documentation

template<typename _MatrixType, typename Backend = DefaultBackend>

typedef SparseMatrix<Scalar> Eigen::SparseLU< _MatrixType, Backend >::LUMatrixType [protected]

Definition at line 51 of file SparseExtra.

template<typename _MatrixType, typename Backend = DefaultBackend>

typedef _MatrixType Eigen::SparseLU< _MatrixType, Backend >::MatrixType

Reimplemented in Eigen::SparseLU< _MatrixType, UmfPack >.

Definition at line 58 of file SparseExtra.

template<typename _MatrixType, typename Backend = DefaultBackend>

typedef NumTraits<typename _MatrixType::Scalar>::Real Eigen::SparseLU< _MatrixType, Backend >::RealScalar [protected]

Reimplemented in Eigen::SparseLU< MatrixType, SuperLU >, and Eigen::SparseLU< _MatrixType, UmfPack >.

Definition at line 50 of file SparseExtra.

template<typename _MatrixType, typename Backend = DefaultBackend>

typedef _MatrixType::Scalar Eigen::SparseLU< _MatrixType, Backend >::Scalar [protected]

Reimplemented in Eigen::SparseLU< MatrixType, SuperLU >, and Eigen::SparseLU< _MatrixType, UmfPack >.

Definition at line 49 of file SparseExtra.

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Member Enumeration Documentation

template<typename _MatrixType, typename Backend = DefaultBackend>

anonymous enum [protected]

Enumerator:

MatrixLUIsDirty

Definition at line 53 of file SparseExtra.

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Constructor & Destructor Documentation

template<typename _MatrixType, typename Backend = DefaultBackend>

Eigen::SparseLU< _MatrixType, Backend >::SparseLU

(

int

flags = 0

)

[inline]

Creates a dummy LU factorization object with flags flags.

Reimplemented in Eigen::SparseLU< MatrixType, SuperLU >, and Eigen::SparseLU< _MatrixType, UmfPack >.

Definition at line 61 of file SparseExtra.

template<typename _MatrixType, typename Backend = DefaultBackend>

Eigen::SparseLU< _MatrixType, Backend >::SparseLU	(	const _MatrixType &	matrix,
		int	flags = 0
	)		[inline]

Creates a LU object and compute the respective factorization of matrix using flags flags.

Reimplemented in Eigen::SparseLU< MatrixType, SuperLU >, and Eigen::SparseLU< _MatrixType, UmfPack >.

Definition at line 69 of file SparseExtra.

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Member Function Documentation

template<typename MatrixType>

void Eigen::SparseLU< MatrixType >::compute

(

const MatrixType &

matrix

)

Computes/re-computes the LU factorization.

Computes / recomputes the LU decomposition of matrix a using the default algorithm.

Reimplemented in Eigen::SparseLU< MatrixType, SuperLU >, and Eigen::SparseLU< _MatrixType, UmfPack >.

Definition at line 143 of file SparseExtra.

template<typename _MatrixType, typename Backend = DefaultBackend>

int Eigen::SparseLU< _MatrixType, Backend >::flags

(

)

const [inline]

Returns:

the current flags

Definition at line 103 of file SparseExtra.

template<typename _MatrixType, typename Backend = DefaultBackend>

int Eigen::SparseLU< _MatrixType, Backend >::orderingMethod

(

)

const [inline]

Definition at line 111 of file SparseExtra.

template<typename _MatrixType, typename Backend = DefaultBackend>

RealScalar Eigen::SparseLU< _MatrixType, Backend >::precision

(

)

const [inline]

Returns:

the current precision.

See also:

setPrecision()

Definition at line 91 of file SparseExtra.

template<typename _MatrixType, typename Backend = DefaultBackend>

void Eigen::SparseLU< _MatrixType, Backend >::setFlags

(

int

f

)

[inline]

Sets the flags.

Possible values are:

• CompleteFactorization
• IncompleteFactorization
• MemoryEfficient
• one of the ordering methods
• etc...

See also:

flags()

Definition at line 101 of file SparseExtra.

template<typename _MatrixType, typename Backend = DefaultBackend>

void Eigen::SparseLU< _MatrixType, Backend >::setOrderingMethod

(

int

m

)

[inline]

Definition at line 105 of file SparseExtra.

template<typename _MatrixType, typename Backend = DefaultBackend>

void Eigen::SparseLU< _MatrixType, Backend >::setPrecision

(

RealScalar

v

)

[inline]

Sets the relative threshold value used to prune zero coefficients during the decomposition.

Setting a value greater than zero speeds up computation, and yields to an imcomplete factorization with fewer non zero coefficients. Such approximate factors are especially useful to initialize an iterative solver.

Note that the exact meaning of this parameter might depends on the actual backend. Moreover, not all backends support this feature.

See also:

precision()

Definition at line 86 of file SparseExtra.

template<typename _MatrixType , typename Backend >

template<typename BDerived , typename XDerived >

bool Eigen::SparseLU< _MatrixType, Backend >::solve	(	const MatrixBase< BDerived > &	b,
		MatrixBase< XDerived > *	x,
		const int	transposed = SvNoTrans
	)		const

Computes *x = U^-1 L^-1 b.

Returns:

the lower triangular matrix L

the upper triangular matrix U

If transpose is set to SvTranspose or SvAdjoint, the solution of the transposed/adjoint system is computed instead.

Not all backends implement the solution of the transposed or adjoint system.

Reimplemented in Eigen::SparseLU< MatrixType, SuperLU >.

Definition at line 158 of file SparseExtra.

template<typename _MatrixType, typename Backend = DefaultBackend>

template<typename BDerived , typename XDerived >

bool Eigen::SparseLU< _MatrixType, Backend >::solve	(	const MatrixBase< BDerived > &	b,
		MatrixBase< XDerived > *	x
	)		const

Definition at line 327 of file UmfPackSupport.

template<typename _MatrixType, typename Backend = DefaultBackend>

bool Eigen::SparseLU< _MatrixType, Backend >::succeeded

(

void

)

const [inline]

Returns:

true if the factorization succeeded

Definition at line 130 of file SparseExtra.

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Member Data Documentation

template<typename _MatrixType, typename Backend = DefaultBackend>

int Eigen::SparseLU< _MatrixType, Backend >::m_flags [protected]

Definition at line 134 of file SparseExtra.

template<typename _MatrixType, typename Backend = DefaultBackend>

RealScalar Eigen::SparseLU< _MatrixType, Backend >::m_precision [protected]

Definition at line 133 of file SparseExtra.

template<typename _MatrixType, typename Backend = DefaultBackend>

int Eigen::SparseLU< _MatrixType, Backend >::m_status [mutable, protected]

Definition at line 135 of file SparseExtra.

template<typename _MatrixType, typename Backend = DefaultBackend>

bool Eigen::SparseLU< _MatrixType, Backend >::m_succeeded [protected]

Definition at line 136 of file SparseExtra.