MarginalCovarianceCholesky

computing the marginal covariance given a cholesky factor (lower triangle of the factor) More...

Collaboration diagram for MarginalCovarianceCholesky:

Public Member Functions
void	computeCovariance (g_type **covBlocks, const Buffer< int > &blockIndices)
	compute the marginal cov for the given block indices, write the result to the covBlocks memory (which has to be provided by the caller).
void	computeCovariance (SparseBlockMatrix< MatrixX< g_type > > &spinv, const Buffer< int > &rowBlockIndices, const Buffer< std::pair< int, int > > &blockIndices)
	compute the marginal cov for the given block indices, write the result in spinv).
void	setCholeskyFactor (int n, int *Lp, int *Li, g_type *Lx, int *permInv)
	set the CCS representation of the cholesky factor along with the inverse permutation used to reduce the fill-in.

Protected Types
typedef Dictionary< int, g_type >	LookupMap
	hash struct for storing the matrix elements needed to compute the covariance

Protected Member Functions
g_type	computeEntry (int r, int c)
	compute one entry in the covariance, r and c are values after applying the permutation, and upper triangular.
int	computeIndex (int r, int c) const
	compute the index used for hashing

Protected Attributes
int *	_Ai
	row indices of the CCS storage
int *	_Ap
	column pointer of the CCS storage
g_type *	_Ax
	values of the cholesky factor
Buffer< g_type >	_diag
	cache 1 / H_ii to avoid recalculations
LookupMap	_map
	hash look up table for the already computed entries
int	_n
	L is an n X n matrix.
int *	_perm
	permutation of the cholesky factor. Variable re-ordering for better fill-in

Detailed Description

computing the marginal covariance given a cholesky factor (lower triangle of the factor)

Definition at line 43 of file marginal_covariance_cholesky.h.

Member Function Documentation

computeEntry()

g_type MarginalCovarianceCholesky::computeEntry ( int r, int c )

protected

compute one entry in the covariance, r and c are values after applying the permutation, and upper triangular.

May issue recursive calls to itself to compute the missing values.

setCholeskyFactor()

void MarginalCovarianceCholesky::setCholeskyFactor	(	int	n,
		int *	Lp,
		int *	Li,
		g_type *	Lx,
		int *	permInv )

set the CCS representation of the cholesky factor along with the inverse permutation used to reduce the fill-in.

permInv might be 0, will then not permute the entries.

The pointers provided by the user need to be still valid when calling computeCovariance(). The pointers are owned by the caller, MarginalCovarianceCholesky does not free the pointers.

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

• GraphOptimization/Headers/marginal_covariance_cholesky.h