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TooN::Lapack_Cholesky< Size, Precision > Class Template Reference

Decomposes a positive-semidefinite symmetric matrix A (such as a covariance) into L*L^T, where L is lower-triangular. More...

#include <Lapack_Cholesky.h>

Public Member Functions

template<class P2 , class B2 >
 Lapack_Cholesky (const Matrix< Size, Size, P2, B2 > &m)
 
 Lapack_Cholesky (int size)
 Constructor for Size=Dynamic.
 
template<class P2 , class B2 >
void compute (const Matrix< Size, Size, P2, B2 > &m)
 
void do_compute ()
 
int rank () const
 
template<int Size2, typename P2 , typename B2 >
Vector< Size, Precision > backsub (const Vector< Size2, P2, B2 > &v) const
 
template<int Size2, int Cols2, typename P2 , typename B2 >
Matrix< Size, Cols2, Precision, ColMajorbacksub (const Matrix< Size2, Cols2, P2, B2 > &m) const
 
template<int Size2, typename P2 , typename B2 >
Precision mahalanobis (const Vector< Size2, P2, B2 > &v) const
 
Matrix< Size, Size, Precision > get_L () const
 
Precision determinant () const
 
Matrix get_inverse () const
 

Detailed Description

template<int Size, typename Precision = DefaultPrecision>
class TooN::Lapack_Cholesky< Size, Precision >

Decomposes a positive-semidefinite symmetric matrix A (such as a covariance) into L*L^T, where L is lower-triangular.

Also can compute A = S*S^T, with S lower triangular. The LDL^T form is faster to compute than the class Cholesky decomposition. The decomposition can be used to compute A^-1*x, A^-1*M, M*A^-1*M^T, and A^-1 itself, though the latter rarely needs to be explicitly represented. Also efficiently computes det(A) and rank(A). It can be used as follows:

// Declare some matrices.
Matrix<3> A = ...; // we'll pretend it is pos-def
Matrix<2,3> M;
Matrix<2> B;
Vector<3> y = make_Vector(2,3,4);
// create the Cholesky decomposition of A
Cholesky<3> chol(A);
// compute x = A^-1 * y
x = cholA.backsub(y);
//compute A^-1
Matrix<3> Ainv = cholA.get_inverse();

Cholesky decomposition of a symmetric matrix. Only the lower half of the matrix is considered This uses the non-sqrt version of the decomposition giving symmetric M = L*D*L.T() where the diagonal of L contains ones

Parameters
Sizethe size of the matrix
Precisionthe precision of the entries in the matrix and its decomposition

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