gml_TGaussian2 Class Template Reference

#include <gml_Gaussian2.h>

Collaboration diagram for gml_TGaussian2:

Detailed Description

Compute and maintain a gaussian representation (approximation) of a set of 2-dimensionnal samples.


Public Member Functions
	gml_TGaussian2 ()
	Constructor: zero the fields.
gml_TError	Init ()
	Setup the structure.
void	Reset ()
	Zero the structure.
void	Dispose ()
	Do nothing.
void	Clone (gml_TGaussian2< T > *gauss)
	Set this to be the exact copy of gauss.
void	Add (gml_TGaussian2< T > *gauss)
	Adds the distribution of gauss in this.
void	AddSample (T *s)
	Adds a sample in the set. s must point to an array of two T values.
void	AddSample (T x, T y)
	Adds a sample in the set.
void	AddSample (T x, T y, T weight)
	Adds a weighted sample in the set.
T	Samples ()
	Return the total number of samples added.
gml_TError	UpdateStats ()
	Compute mean, covariance, and inverse covariance. Returns an error if the covariance matrix could not be inverted.
T	GetMahaSquared (T x, T y)
	Returns the squared mahalanobis distance from (x, y) to the gaussian.
T	Value (T x, T y)
	Return the gaussian's value at (x, y).
void	GetMean (T *m)
	Calculates the mean of the gaussian and puts the result in m. m must point to an array of two T values.
void	GetVar (T *m)
	Calculates the covariance matrix of the gaussian and puts the result in m. m must point to an array of four T values.
Public Attributes
T	fCount
	number of samples added to set
T	fSum [2]
	sum of samples by components
T	fSumSq [2]
	sum of samples squared by components
T	fMixSum
	sum of component products
T	fMean [2]
T	fCovariance [4]
T	fInvCovariance [4]

Returns the squared mahalanobis distance from (x, y) to the gaussian.

Return the gaussian's value at (x, y).

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