SimplicialCholesky< _MatrixType, _UpLo > Class Template Reference

A direct sparse Cholesky factorization. More...

List of all members.

Classes
struct	keep_diag
Public Types
enum	{ UpLo }
typedef SparseMatrix< Scalar, ColMajor, Index >	CholMatrixType
typedef MatrixType::Index	Index
typedef _MatrixType	MatrixType
typedef MatrixType::RealScalar	RealScalar
typedef MatrixType::Scalar	Scalar
typedef Matrix< Scalar, MatrixType::ColsAtCompileTime, 1 >	VectorType
Public Member Functions
void	analyzePattern (const MatrixType &a)
Index	cols () const
SimplicialCholesky &	compute (const MatrixType &matrix)
template<typename Stream >
void	dumpMemory (Stream &s)
void	factorize (const MatrixType &a)
ComputationInfo	info () const
	Reports whether previous computation was successful.
const PermutationMatrix < Dynamic > &	permutationP () const
const PermutationMatrix < Dynamic > &	permutationPinv () const
Index	rows () const
SimplicialCholesky &	setMode (SimplicialCholeskyMode mode)
	SimplicialCholesky (const MatrixType &matrix)
template<typename Rhs >
const internal::solve_retval < SimplicialCholesky, Rhs >	solve (const MatrixBase< Rhs > &b) const
Protected Attributes
bool	m_analysisIsOk
VectorType	m_diag
bool	m_factorizationIsOk
ComputationInfo	m_info
bool	m_isInitialized
bool	m_LDLt
CholMatrixType	m_matrix
VectorXi	m_nonZerosPerCol
PermutationMatrix< Dynamic >	m_P
VectorXi	m_parent
PermutationMatrix< Dynamic >	m_Pinv

---

Detailed Description

template<typename _MatrixType, int _UpLo = Lower>
class Eigen::SimplicialCholesky< _MatrixType, _UpLo >

A direct sparse Cholesky factorization.

This class allows to solve for A.X = B sparse linear problems via a LL^T or LDL^T Cholesky factorization. The sparse matrix A must be selfadjoint and positive definite. 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<>
_UpLo	the triangular part that will be used for the computations. It can be Lower or Upper. Default is Lower.

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Member Function Documentation

void analyzePattern

(

const MatrixType &

a

)

Returns:

the solution x of using the current decomposition of A.

See also:

compute() 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()

SimplicialCholesky& compute

(

const MatrixType &

matrix

)

[inline]

Computes the sparse Cholesky decomposition of matrix

void factorize

(

const MatrixType &

a

)

Performs a numeric decomposition of matrix

The given matrix must has the same sparcity than the matrix on which the symbolic decomposition has been performed.

See also:

analyzePattern()

ComputationInfo info

(

)

const [inline]

Reports whether previous computation was successful.

Returns:

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

const PermutationMatrix<Dynamic>& permutationP

(

)

const [inline]

Returns:

the permutation P

See also:

permutationPinv()

const PermutationMatrix<Dynamic>& permutationPinv

(

)

const [inline]

Returns:

the inverse P^-1 of the permutation P

See also:

permutationP()

const internal::solve_retval<SimplicialCholesky, Rhs> solve

(

const MatrixBase< Rhs > &

b

)

const [inline]

Returns:

the solution x of using the current decomposition of A.

See also:

compute()

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