ITK  4.0.0
Insight Segmentation and Registration Toolkit
Public Types | Public Member Functions | Protected Member Functions | Private Attributes
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 >:
Collaboration diagram for itk::Statistics::GaussianMixtureModelComponent< TSample >:

List of all members.

Public Types

typedef SmartPointer< const SelfConstPointer
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< SelfPointer
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

Definition at line 79 of file itkGaussianMixtureModelComponent.h.

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.

Type of the mean vector

Definition at line 82 of file itkGaussianMixtureModelComponent.h.

Typedefs from the superclass

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

Definition at line 62 of file itkGaussianMixtureModelComponent.h.

Type of the membership function. Gaussian density function

Definition at line 74 of file itkGaussianMixtureModelComponent.h.

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

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

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)

Sets the component's distribution parameters.

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

Sets the input sample

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


Member Data Documentation

Definition at line 110 of file itkGaussianMixtureModelComponent.h.

Definition at line 114 of file itkGaussianMixtureModelComponent.h.

Definition at line 106 of file itkGaussianMixtureModelComponent.h.

Definition at line 108 of file itkGaussianMixtureModelComponent.h.

Definition at line 112 of file itkGaussianMixtureModelComponent.h.


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