itk::Statistics::GaussianMixtureModelComponent< TSample > Class Template Reference

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

#include <itkGaussianMixtureModelComponent.h>

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

[legend]Collaboration diagram for itk::Statistics::GaussianMixtureModelComponent< TSample >:

[legend]List of all members.

[NOHEADER]
virtual const char *	GetClassName () const
Pointer	New ()
Public Types
typedef GaussianMixtureModelComponent	Self
typedef MixtureModelComponentBase< TSample >	Superclass
typedef SmartPointer< Self >	Pointer
typedef SmartPointer< const Self >	ConstPointer
typedef Superclass::MeasurementVectorType	MeasurementVectorType
typedef Superclass::MembershipFunctionType	MembershipFunctionType
typedef Superclass::WeightArrayType	WeightArrayType
typedef Superclass::ParametersType	ParametersType
typedef GaussianDensityFunction< MeasurementVectorType >	NativeMembershipFunctionType
typedef WeightedMeanCalculator< TSample >	MeanEstimatorType
typedef WeightedCovarianceCalculator< TSample >	CovarianceEstimatorType
typedef MeanEstimatorType::OutputType	MeanType
typedef CovarianceEstimatorType::OutputType	CovarianceType
Public Member Functions
	itkStaticConstMacro (MeasurementVectorSize, unsigned int, TSample::MeasurementVectorSize)
void	SetSample (const TSample *sample)
void	SetParameters (const ParametersType &parameters)
Protected Member Functions
	GaussianMixtureModelComponent ()
virtual	~GaussianMixtureModelComponent ()
void	PrintSelf (std::ostream &os, Indent indent) const
double	CalculateParametersChange ()
void	GenerateData ()

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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.

See also:

MixtureModelComponentBase, ExpectationMaximizationMixtureModelEstimator

Definition at line 41 of file itkGaussianMixtureModelComponent.h.

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Member Typedef Documentation

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

Reimplemented from itk::Statistics::MixtureModelComponentBase< TSample >. Definition at line 49 of file itkGaussianMixtureModelComponent.h.

template<class TSample> typedef WeightedCovarianceCalculator< TSample > itk::Statistics::GaussianMixtureModelComponent< TSample >::CovarianceEstimatorType

Definition at line 73 of file itkGaussianMixtureModelComponent.h.

template<class TSample> typedef CovarianceEstimatorType::OutputType itk::Statistics::GaussianMixtureModelComponent< TSample >::CovarianceType

Type of the covariance matrix Definition at line 79 of file itkGaussianMixtureModelComponent.h. Referenced by itk::Statistics::GaussianMixtureModelComponent< TSample >::~GaussianMixtureModelComponent().

template<class TSample> typedef WeightedMeanCalculator< 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 72 of file itkGaussianMixtureModelComponent.h.

template<class TSample> typedef MeanEstimatorType::OutputType itk::Statistics::GaussianMixtureModelComponent< TSample >::MeanType

Type of the mean vector Definition at line 76 of file itkGaussianMixtureModelComponent.h. Referenced by itk::Statistics::GaussianMixtureModelComponent< TSample >::~GaussianMixtureModelComponent().

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

Typedefs from the superclass Reimplemented from itk::Statistics::MixtureModelComponentBase< TSample >. Definition at line 61 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 62 of file itkGaussianMixtureModelComponent.h.

template<class TSample> typedef GaussianDensityFunction< MeasurementVectorType > itk::Statistics::GaussianMixtureModelComponent< TSample >::NativeMembershipFunctionType

Type of the membership function. Gaussian density function Definition at line 68 of file itkGaussianMixtureModelComponent.h.

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

Reimplemented from itk::Statistics::MixtureModelComponentBase< TSample >. Definition at line 64 of file itkGaussianMixtureModelComponent.h.

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

Reimplemented from itk::Statistics::MixtureModelComponentBase< TSample >. Definition at line 48 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 46 of file itkGaussianMixtureModelComponent.h.

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

Reimplemented from itk::Statistics::MixtureModelComponentBase< TSample >. Definition at line 47 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 63 of file itkGaussianMixtureModelComponent.h.

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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 89 of file itkGaussianMixtureModelComponent.h. References itk::Statistics::GaussianMixtureModelComponent< TSample >::CovarianceType, and itk::Statistics::GaussianMixtureModelComponent< TSample >::MeanType.

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

Computes the new distribution parameters Reimplemented from itk::Statistics::MixtureModelComponentBase< TSample >.

template<class TSample> virtual const char* itk::Statistics::GaussianMixtureModelComponent< TSample >::GetClassName (   )  const [virtual]

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

template<class TSample> itk::Statistics::GaussianMixtureModelComponent< TSample >::itkStaticConstMacro (  MeasurementVectorSize  , unsigned  int, TSample::MeasurementVectorSize  )

Measurement length constant

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

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

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  )  [virtual]

Sets the component's distribution parameters. Reimplemented from itk::Statistics::MixtureModelComponentBase< TSample >.

template<class TSample> void itk::Statistics::GaussianMixtureModelComponent< TSample >::SetSample (  const TSample *  sample  )  [virtual]

Sets the input sample Reimplemented from itk::Statistics::MixtureModelComponentBase< TSample >.

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

• itkGaussianMixtureModelComponent.h

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