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

calculates sample mean. More...

#include <itkGaussianMixtureModelComponent.h>

Inheritance diagram for itk::Statistics::GaussianMixtureModelComponent:

[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 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 Methods
	itkStaticConstMacro (MeasurementVectorSize, unsigned int, TSample::MeasurementVectorSize)
void	SetSample (TSample *sample)
void	SetParameters (const ParametersType &parameters)
Protected Methods
	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 >

calculates sample mean.

You plug in the target sample data using SetSample method. Then call the GenerateData method to run the alogithm.

The return value that the GetOutput method where is the number of measurement vectors in the target

Definition at line 42 of file itkGaussianMixtureModelComponent.h.

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Member Typedef Documentation

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

Definition at line 68 of file itkGaussianMixtureModelComponent.h.

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

Definition at line 71 of file itkGaussianMixtureModelComponent.h. Referenced by itk::Statistics::GaussianMixtureModelComponent< TSample >::~GaussianMixtureModelComponent().

template<class TSample> typedef WeightedMeanCalculator< TSample > itk::Statistics::GaussianMixtureModelComponent< TSample >::MeanEstimatorType

Definition at line 67 of file itkGaussianMixtureModelComponent.h.

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

Definition at line 70 of file itkGaussianMixtureModelComponent.h. Referenced by itk::Statistics::GaussianMixtureModelComponent< TSample >::~GaussianMixtureModelComponent().

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

Reimplemented from itk::Statistics::MixtureModelComponentBase< TSample >. Definition at line 60 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 61 of file itkGaussianMixtureModelComponent.h.

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

Definition at line 65 of file itkGaussianMixtureModelComponent.h.

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

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

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

Reimplemented from itk::Statistics::MixtureModelComponentBase< TSample >. Definition at line 49 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 47 of file itkGaussianMixtureModelComponent.h.

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

Reimplemented from itk::Statistics::MixtureModelComponentBase< TSample >. Definition at line 48 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 62 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 79 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]

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

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]

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

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

stores the sample pointer 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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