aims::DiscriminantAnalysis< T > Class Template Reference

#include <aims/math/discriminantanalysis.h>

Public Member Functions
	DiscriminantAnalysis (const AimsData< T > &data, const std::vector< std::list< Point3d > > &classes, int significantEV=-1, const std::vector< double > &PIj=std::vector< double >())
	~DiscriminantAnalysis ()
std::vector< double >	posteriorProbabilities (const AimsData< double > &x, double px)
std::vector< double >	andersonScores (const AimsData< double > &x)
int	affectedTo (const AimsData< double > &x)
bool	classification (const AimsData< T > &dynamicImage, const AimsData< byte > &mask, AimsData< short > &segmented)
bool	fuzzyClassification (const AimsData< T > &dynamicImage, const AimsData< byte > &mask, AimsData< float > &fuzzySegmented, const AimsData< double > &indivPriorProbabilities=AimsData< double >())

Detailed Description

template<class T>
class aims::DiscriminantAnalysis< T >

Definition at line 109 of file discriminantanalysis.h.

Constructor & Destructor Documentation

DiscriminantAnalysis()

template<class T >

aims::DiscriminantAnalysis< T >::DiscriminantAnalysis	(	const AimsData< T > &	data,
		const std::vector< std::list< Point3d > > &	classes,
		int	significantEV = -1,
		const std::vector< double > &	PIj = std::vector<double>()
	)

Definition at line 297 of file discriminantanalysis_d.h.

References aims::DiscriminantAnalysisElement::doIt().

~DiscriminantAnalysis()

template<class T >

aims::DiscriminantAnalysis< T >::~DiscriminantAnalysis ( )

inline

Definition at line 117 of file discriminantanalysis.h.

References aims::DiscriminantAnalysisElement::_PIj, aims::DiscriminantAnalysisElement::_significantEV, and aims::mask().

Member Function Documentation

affectedTo()

template<class T >

int aims::DiscriminantAnalysis< T >::affectedTo

(

const AimsData< double > &

x

)

Definition at line 369 of file discriminantanalysis_d.h.

Referenced by aims::DiscriminantAnalysis< T >::classification().

andersonScores()

template<class T >

std::vector< double > aims::DiscriminantAnalysis< T >::andersonScores

(

const AimsData< double > &

x

)

Definition at line 352 of file discriminantanalysis_d.h.

References sum().

classification()

template<class T >

bool aims::DiscriminantAnalysis< T >::classification	(	const AimsData< T > &	dynamicImage,
		const AimsData< byte > &	mask,
		AimsData< short > &	segmented
	)

Definition at line 388 of file discriminantanalysis_d.h.

References aims::DiscriminantAnalysis< T >::affectedTo(), AimsData< T >::dimT(), AimsData< T >::dimX(), AimsData< T >::dimY(), AimsData< T >::dimZ(), ForEach3d, aims::mask(), and AimsData< T >::setSizeXYZT().

fuzzyClassification()

template<class T >

bool aims::DiscriminantAnalysis< T >::fuzzyClassification	(	const AimsData< T > &	dynamicImage,
		const AimsData< byte > &	mask,
		AimsData< float > &	fuzzySegmented,
		const AimsData< double > &	indivPriorProbabilities = AimsData<double>()
	)

Definition at line 420 of file discriminantanalysis_d.h.

References AimsData< T >::dimT(), AimsData< float >::dimT(), AimsData< T >::dimX(), AimsData< float >::dimX(), AimsData< float >::dimY(), AimsData< T >::dimY(), AimsData< float >::dimZ(), AimsData< T >::dimZ(), ForEach3d, aims::mask(), aims::DiscriminantAnalysis< T >::posteriorProbabilities(), and AimsData< float >::setSizeXYZT().

posteriorProbabilities()

template<class T >

std::vector< double > aims::DiscriminantAnalysis< T >::posteriorProbabilities	(	const AimsData< double > &	x,
		double	px
	)

Definition at line 342 of file discriminantanalysis_d.h.

Referenced by aims::DiscriminantAnalysis< T >::fuzzyClassification().

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

• aims/math/discriminantanalysis.h
• aims/math/discriminantanalysis_d.h