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

calculates sample mean. More...

#include <itkGaussianMixtureModelComponent.h>

Inheritance diagram for itk::Statistics::GaussianMixtureModelComponent:

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

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List of all members.

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virtual const char * GetClassName () const
Pointer New ()

Public Types

typedef GaussianMixtureModelComponent Self
typedef MixtureModelComponentBase<
TSample > 
Superclass
typedef SmartPointer< SelfPointer
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 ()

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.


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.


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.


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 >.


The documentation for this class was generated from the following file:
Generated at Wed Mar 12 01:22:36 2003 for ITK by doxygen 1.2.15 written by Dimitri van Heesch, © 1997-2000