#include <itkGaussianMixtureModelComponent.h>

Inheritance diagram for itk::Statistics::GaussianMixtureModelComponent< TSample >:

Collaboration diagram for itk::Statistics::GaussianMixtureModelComponent< TSample >:

Public Types
typedef SmartPointer< const Self >	ConstPointer
typedef WeightedCovarianceSampleFilter < TSample >	CovarianceEstimatorType
typedef CovarianceEstimatorType::OutputType	CovarianceMatrixType
typedef WeightedMeanSampleFilter < TSample >	MeanEstimatorType
typedef MeanEstimatorType::OutputType	MeanVectorType
typedef Superclass::MeasurementVectorSizeType	MeasurementVectorSizeType
typedef Superclass::MeasurementVectorType	MeasurementVectorType
typedef Superclass::MembershipFunctionType	MembershipFunctionType
typedef GaussianMembershipFunction < MeasurementVectorType >	NativeMembershipFunctionType
typedef Superclass::ParametersType	ParametersType
typedef SmartPointer< Self >	Pointer
typedef GaussianMixtureModelComponent	Self
typedef MixtureModelComponentBase < TSample >	Superclass
typedef Superclass::WeightArrayType	WeightArrayType
Public Member Functions
void	SetParameters (const ParametersType &parameters)
void	SetSample (const TSample *sample)
Protected Member Functions
double	CalculateParametersChange ()
	GaussianMixtureModelComponent ()
void	GenerateData ()
void	PrintSelf (std::ostream &os, Indent indent) const
virtual	~GaussianMixtureModelComponent ()
Private Attributes
CovarianceEstimatorType::MatrixType	m_Covariance
CovarianceEstimatorType::Pointer	m_CovarianceEstimator
NativeMembershipFunctionType::Pointer	m_GaussianMembershipFunction
MeanEstimatorType::MeasurementVectorType	m_Mean
MeanEstimatorType::Pointer	m_MeanEstimator
virtual const char *	GetNameOfClass () const
virtual ::itk::LightObject::Pointer	CreateAnother (void) const
static Pointer	New ()

Detailed Description

template<class TSample>
class itk::Statistics::GaussianMixtureModelComponent< TSample >

is a component (derived from MixtureModelComponentBase) for Gaussian class. This class is used in ExpectationMaximizationMixtureModelEstimator.

On every iteration of EM estimation, this class's GenerateData method is called to compute the new distribution parameters.

Recent API changes: The static const macro to get the length of a measurement vector, MeasurementVectorSize has been removed to allow the length of a measurement vector to be specified at run time. It is now obtained at run time from the sample set as input. Please use the function GetMeasurementVectorSize() to get the length.

See also:: MixtureModelComponentBase, ExpectationMaximizationMixtureModelEstimator

Definition at line 50 of file itkGaussianMixtureModelComponent.h.

Member Typedef Documentation

template<class TSample >

typedef SmartPointer< const Self > itk::Statistics::GaussianMixtureModelComponent< TSample >::ConstPointer

Reimplemented from itk::Statistics::MixtureModelComponentBase< TSample >.

Definition at line 58 of file itkGaussianMixtureModelComponent.h.

template<class TSample >

typedef WeightedCovarianceSampleFilter< TSample > itk::Statistics::GaussianMixtureModelComponent< TSample >::CovarianceEstimatorType

Definition at line 79 of file itkGaussianMixtureModelComponent.h.

template<class TSample >

typedef CovarianceEstimatorType::OutputType itk::Statistics::GaussianMixtureModelComponent< TSample >::CovarianceMatrixType

Type of the covariance matrix

Definition at line 85 of file itkGaussianMixtureModelComponent.h.

template<class TSample >

typedef WeightedMeanSampleFilter< TSample > itk::Statistics::GaussianMixtureModelComponent< TSample >::MeanEstimatorType

Types of the mean and the covariance calculator that will update this component's distribution parameters

Definition at line 78 of file itkGaussianMixtureModelComponent.h.

template<class TSample >

typedef MeanEstimatorType::OutputType itk::Statistics::GaussianMixtureModelComponent< TSample >::MeanVectorType

Type of the mean vector

Definition at line 82 of file itkGaussianMixtureModelComponent.h.

template<class TSample >

typedef Superclass::MeasurementVectorSizeType itk::Statistics::GaussianMixtureModelComponent< TSample >::MeasurementVectorSizeType

Reimplemented from itk::Statistics::MixtureModelComponentBase< TSample >.

Definition at line 67 of file itkGaussianMixtureModelComponent.h.

template<class TSample >

typedef Superclass::MeasurementVectorType itk::Statistics::GaussianMixtureModelComponent< TSample >::MeasurementVectorType

Typedefs from the superclass

Reimplemented from itk::Statistics::MixtureModelComponentBase< TSample >.

Definition at line 62 of file itkGaussianMixtureModelComponent.h.

template<class TSample >

typedef Superclass::MembershipFunctionType itk::Statistics::GaussianMixtureModelComponent< TSample >::MembershipFunctionType

typedef for the MembershipFunctionBase

Reimplemented from itk::Statistics::MixtureModelComponentBase< TSample >.

Definition at line 68 of file itkGaussianMixtureModelComponent.h.

template<class TSample >

typedef GaussianMembershipFunction< MeasurementVectorType > itk::Statistics::GaussianMixtureModelComponent< TSample >::NativeMembershipFunctionType

Type of the membership function. Gaussian density function

Definition at line 74 of file itkGaussianMixtureModelComponent.h.

template<class TSample >

typedef Superclass::ParametersType itk::Statistics::GaussianMixtureModelComponent< TSample >::ParametersType

Reimplemented from itk::Statistics::MixtureModelComponentBase< TSample >.

Definition at line 70 of file itkGaussianMixtureModelComponent.h.

template<class TSample >

typedef SmartPointer< Self > itk::Statistics::GaussianMixtureModelComponent< TSample >::Pointer

Reimplemented from itk::Statistics::MixtureModelComponentBase< TSample >.

Definition at line 57 of file itkGaussianMixtureModelComponent.h.

template<class TSample >

typedef GaussianMixtureModelComponent itk::Statistics::GaussianMixtureModelComponent< TSample >::Self

Standard class typedefs.

Reimplemented from itk::Statistics::MixtureModelComponentBase< TSample >.

Definition at line 55 of file itkGaussianMixtureModelComponent.h.

template<class TSample >

typedef MixtureModelComponentBase< TSample > itk::Statistics::GaussianMixtureModelComponent< TSample >::Superclass

Reimplemented from itk::Statistics::MixtureModelComponentBase< TSample >.

Definition at line 56 of file itkGaussianMixtureModelComponent.h.

template<class TSample >

typedef Superclass::WeightArrayType itk::Statistics::GaussianMixtureModelComponent< TSample >::WeightArrayType

typedef of strorage for the weights

Reimplemented from itk::Statistics::MixtureModelComponentBase< TSample >.

Definition at line 69 of file itkGaussianMixtureModelComponent.h.

Constructor & Destructor Documentation

template<class TSample >

itk::Statistics::GaussianMixtureModelComponent< TSample >::GaussianMixtureModelComponent ( ) [protected]

template<class TSample >

virtual itk::Statistics::GaussianMixtureModelComponent< TSample >::~GaussianMixtureModelComponent ( ) [inline, protected, virtual]

Definition at line 95 of file itkGaussianMixtureModelComponent.h.

Member Function Documentation

template<class TSample >

double itk::Statistics::GaussianMixtureModelComponent< TSample >::CalculateParametersChange ( ) [protected]

Returns the sum of squared changes in parameters between iterations

template<class TSample >

virtual::itk::LightObject::Pointer itk::Statistics::GaussianMixtureModelComponent< TSample >::CreateAnother ( void ) const [virtual]

Standard Macros

Reimplemented from itk::Object.

template<class TSample >

void itk::Statistics::GaussianMixtureModelComponent< TSample >::GenerateData ( ) [protected, virtual]

Computes the new distribution parameters

Implements itk::Statistics::MixtureModelComponentBase< TSample >.

template<class TSample >

virtual const char* itk::Statistics::GaussianMixtureModelComponent< TSample >::GetNameOfClass ( ) const [virtual]

Standard Macros

Reimplemented from itk::Statistics::MixtureModelComponentBase< TSample >.

template<class TSample >

static Pointer itk::Statistics::GaussianMixtureModelComponent< TSample >::New ( ) [static]

Standard Macros

Reimplemented from itk::Object.

template<class TSample >

void itk::Statistics::GaussianMixtureModelComponent< TSample >::PrintSelf	(	std::ostream &	os,
		Indent	indent
	)		const `[protected, virtual]`

Methods invoked by Print() to print information about the object including superclasses. Typically not called by the user (use Print() instead) but used in the hierarchical print process to combine the output of several classes.

Reimplemented from itk::Statistics::MixtureModelComponentBase< TSample >.

template<class TSample >

void itk::Statistics::GaussianMixtureModelComponent< TSample >::SetParameters ( const ParametersType & parameters )