#include <irls.h>

Inheritance diagram for TooN::IRLS< Size, Precision, Reweight >:

Public Member Functions
	IRLS (int size=Size)

template<int Size2, typename Precision2 , typename Base2 >
void	add_mJ (Precision m, const Vector< Size2, Precision2, Base2 > &J)

void	operator+= (const IRLS &meas)

Matrix< Size, Size, Precision > &	get_true_C_inv ()

const Matrix< Size, Size, Precision > &	get_true_C_inv () const

Precision	get_residual ()

void	clear ()

Public Member Functions inherited from TooN::WLS< Size, Precision >
	WLS (int size=0)
	Default constructor or construct with the number of dimensions for the Dynamic case. More...

void	clear ()
	Clear all the measurements and apply a constant regularisation term. More...

void	add_prior (Precision val)

void	add_prior (const Vector< Size, Precision, B2 > &v)

void	add_prior (const Matrix< Size, Size, Precision, B2 > &m)

void	add_mJ (Precision m, const Vector< Size, Precision, B2 > &J, Precision weight=1)

void	add_mJ (const Vector< N, Precision, B1 > &m, const Matrix< Size, N, Precision, B2 > &J, const Matrix< N, N, Precision, B3 > &invcov)

void	add_mJ_rows (const Vector< N, Precision, B1 > &m, const Matrix< N, Size, Precision, B2 > &J, const Matrix< N, N, Precision, B3 > &invcov)

void	add_sparse_mJ_rows (const Vector< N, Precision, B1 > &m, const Matrix< N, S1, Precision, B2 > &J1, const int index1, const Matrix< N, N, Precision, B3 > &invcov)

void	add_sparse_mJ_rows (const Vector< N, Precision, B1 > &m, const Matrix< N, S1, Precision, B2 > &J1, const int index1, const Matrix< N, S2, Precision, B3 > &J2, const int index2, const Matrix< N, N, Precision, B4 > &invcov)

void	compute ()

void	operator+= (const WLS &meas)

Matrix< Size, Size, Precision > &	get_C_inv ()
	Returns the inverse covariance matrix. More...

const Matrix< Size, Size, Precision > &	get_C_inv () const
	Returns the inverse covariance matrix. More...

Vector< Size, Precision > &	get_mu ()
	Returns the update. With no prior, this is the result of $J^\dagger e$ . More...

const Vector< Size, Precision > &	get_mu () const
	Returns the update. With no prior, this is the result of $J^\dagger e$ . More...

Vector< Size, Precision > &	get_vector ()
	Returns the vector $J^{\mathsf T} e$ . More...

const Vector< Size, Precision > &	get_vector () const
	Returns the vector $J^{\mathsf T} e$ . More...

Cholesky< Size, Precision > &	get_decomposition ()
	Return the decomposition object used to compute $(J^{\mathsf T} J + P)^{-1}$ . More...

const Cholesky< Size, Precision > &	get_decomposition () const
	Return the decomposition object used to compute $(J^{\mathsf T} J + P)^{-1}$ . More...

Private Member Functions
	IRLS (IRLS &copyof)

int	operator= (IRLS &copyof)

Private Attributes
Precision	my_residual

Matrix< Size, Size, Precision >	my_true_C_inv

Detailed Description

template<int Size, typename Precision, template< typename Precision > class Reweight>
class TooN::IRLS< Size, Precision, Reweight >

Performs iterative reweighted least squares.

Parameters

Size	the size
Reweight	The reweighting functor. This structure must provide reweight(), true-scale() and objective() methods. Existing examples are Robust I, Robust II and ILinear.

Definition at line 107 of file irls.h.