SparseLDLT Class Template Reference
[Sparse module]

List of all members.

---

Detailed Description

template<typename MatrixType, int Backend = DefaultBackend>
class Eigen::SparseLDLT< MatrixType, Backend >

LDLT Cholesky decomposition of a sparse matrix and associated features.

Parameters:

MatrixType

the type of the matrix of which we are computing the LDLT Cholesky decomposition

See also:

class LDLT, class LDLT

Public Member Functions
bool	_numeric (const MatrixType &matrix)
void	_symbolic (const MatrixType &matrix)
void	compute (const MatrixType &matrix)
int	flags () const
const CholMatrixType &	matrixL (void) const
RealScalar	precision () const
void	setPrecision (RealScalar v)
void	settagss (int f)
template<typename Derived>
bool	solveInPlace (MatrixBase< Derived > &b) const
	SparseLDLT (const MatrixType &matrix, int flags=0)
	SparseLDLT (int flags=0)
bool	succeeded (void) const
VectorType	vectorD (void) const
Protected Types
enum	{   SupernodalFactorIsDirty,   MatrixLIsDirty }
typedef SparseMatrix< Scalar, LowerTriangular|UnitDiagBit >	CholMatrixType
typedef NumTraits< typename MatrixType::Scalar >::Real	RealScalar
typedef MatrixType::Scalar	Scalar
typedef Matrix< Scalar, MatrixType::ColsAtCompileTime, 1 >	VectorType
Protected Attributes
VectorType	m_diag
int	m_flags
CholMatrixType	m_matrix
VectorXi	m_nonZerosPerCol
VectorXi	m_parent
RealScalar	m_precision
int	m_status
bool	m_succeeded

---

Constructor & Destructor Documentation

SparseLDLT

(

int

flags = 0

)

[inline]

Creates a dummy LDLT factorization object with flags flags.

SparseLDLT	(	const MatrixType &	matrix,
		int	flags = 0
	)			[inline]

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

---

Member Function Documentation

bool _numeric

(

const MatrixType &

matrix

)

[inline]

Perform the actual factorization using the previously computed symbolic factorization

void _symbolic

(

const MatrixType &

matrix

)

[inline]

Perform a symbolic factorization

void compute

(

const MatrixType &

a

)

[inline]

Computes/re-computes the LDLT factorization

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

int flags

(

)

const [inline]

Returns:

the current flags

const CholMatrixType& matrixL

(

void

)

const [inline]

Returns:

the lower triangular matrix L

RealScalar precision

(

)

const [inline]

Returns:

the current precision.

See also:

setPrecision()

void 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.

Warning:

if precision is greater that zero, the LDLT factorization is not guaranteed to succeed even if the matrix is positive definite.

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

See also:

precision()

void settagss

(

int

f

)

[inline]

Sets the flags. Possible values are:

• CompleteFactorization
• IncompleteFactorization
• MemoryEfficient (hint to use the memory most efficient method offered by the backend)
• SupernodalMultifrontal (implies a complete factorization if supported by the backend, overloads the MemoryEfficient flags)
• SupernodalLeftLooking (implies a complete factorization if supported by the backend, overloads the MemoryEfficient flags)

See also:

flags()

bool solveInPlace

(

MatrixBase< Derived > &

b

)

const [inline]

Computes b = L^-T L^-1 b

bool succeeded

(

void

)

const [inline]

Returns:

true if the factorization succeeded

VectorType vectorD

(

void

)

const [inline]

Returns:

the coefficients of the diagonal matrix D

---

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

• Sparse