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itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample > Class Template Reference

provides implemenations of GoodnessOfFitComponentBase's methods for a Gaussian component. More...

#include <itkGaussianGoodnessOfFitComponent.h>

Inheritance diagram for itk::Statistics::GaussianGoodnessOfFitComponent:

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List of all members.

Public Types

typedef GaussianGoodnessOfFitComponent Self
typedef GoodnessOfFitComponentBase<
TInputSample > 
Superclass
typedef SmartPointer< SelfPointer
typedef SmartPointer< const
Self
ConstPointer
typedef TInputSample::MeasurementType MeasurementType
typedef TInputSample::MeasurementVectorType MeasurementVectorType
typedef Superclass::CenterType CenterType
typedef Superclass::RadiusType RadiusType
typedef Superclass::MeanType MeanType
typedef Superclass::StandardDeviationType StandardDeviationType
typedef Superclass::ResampledSampleType ResampledSampleType
typedef Superclass::ProjectionAxisArrayType ProjectionAxisArrayType
typedef Array< double > ParametersType
typedef GaussianDensityFunction<
MeasurementVectorType
ProbabilityDensityFunctionType
typedef ProbabilityDensityFunctionType::CovarianceType CovarianceType
typedef WeightedCovarianceCalculator<
ResampledSampleType
CovarianceCalculatorType
typedef SymmetricEigenSystem<
double, itkGetStaticConstMacro(MeasurementVectorSize) 
ProjectionAxisCalculatorType )

Public Methods

virtual const char * GetClassName () const
 itkStaticConstMacro (MeasurementVectorSize, unsigned int, TInputSample::MeasurementVectorSize)
unsigned int GetNumberOfParameters () const
void SetParameters (const ParametersType &parameter)
CenterTypeGetCenter ()
RadiusTypeGetRadius ()
MeanTypeGetMean ()
StandardDeviationTypeGetStandardDeviation ()
double GetCumulativeProbability (double x) const
double GetProbabilityDensity (MeasurementVectorType &measurements) const
void PrintParameters (std::ostream &os) const
ParametersType GetFullParameters () const

Static Public Methods

Pointer New ()

Protected Methods

 GaussianGoodnessOfFitComponent ()
virtual ~GaussianGoodnessOfFitComponent ()
virtual void CalculateProjectionAxes ()

Detailed Description

template<class TInputSample>
class itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >

provides implemenations of GoodnessOfFitComponentBase's methods for a Gaussian component.

Among the GoodnessOfFitComponentBase's methods, this class provides implementations for the CalculateProjectionAxess, the GetCumulativeProbability (univariate CDF), and the GetProbabilityDensity (multivariate PDF)methods.

The CalculateProjectionAxes method creats an array of projection axes that are the eigen vectors generated from the weighted covariance matrix of the resampled sample using a spherical kernel.

See also:
GoodnessOfFitComponentBase, GoodnessOfFitMixtureModelCostFunction

Definition at line 45 of file itkGaussianGoodnessOfFitComponent.h.


Member Typedef Documentation

template<class TInputSample>
typedef Superclass::CenterType itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::CenterType
 

typedefs from Superclass

Reimplemented from itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

Definition at line 69 of file itkGaussianGoodnessOfFitComponent.h.

template<class TInputSample>
typedef SmartPointer< const Self > itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::ConstPointer
 

Reimplemented from itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

Definition at line 53 of file itkGaussianGoodnessOfFitComponent.h.

template<class TInputSample>
typedef WeightedCovarianceCalculator< ResampledSampleType > itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::CovarianceCalculatorType
 

Covariance calculator type. the output of this calculator is a covariance matrix that is used as the input of the Projection calculator

Definition at line 88 of file itkGaussianGoodnessOfFitComponent.h.

template<class TInputSample>
typedef ProbabilityDensityFunctionType::CovarianceType itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::CovarianceType
 

Definition at line 82 of file itkGaussianGoodnessOfFitComponent.h.

template<class TInputSample>
typedef Superclass::MeanType itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::MeanType
 

Reimplemented from itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

Definition at line 71 of file itkGaussianGoodnessOfFitComponent.h.

template<class TInputSample>
typedef TInputSample::MeasurementType itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::MeasurementType
 

Reimplemented from itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

Definition at line 65 of file itkGaussianGoodnessOfFitComponent.h.

template<class TInputSample>
typedef TInputSample::MeasurementVectorType itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::MeasurementVectorType
 

Reimplemented from itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

Definition at line 66 of file itkGaussianGoodnessOfFitComponent.h.

template<class TInputSample>
typedef Array< double > itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::ParametersType
 

Reimplemented from itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

Definition at line 75 of file itkGaussianGoodnessOfFitComponent.h.

template<class TInputSample>
typedef SmartPointer< Self > itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::Pointer
 

Reimplemented from itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

Definition at line 52 of file itkGaussianGoodnessOfFitComponent.h.

template<class TInputSample>
typedef GaussianDensityFunction< MeasurementVectorType > itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::ProbabilityDensityFunctionType
 

Weight function type. The density values are used as weights of each instance (measurement vector) for the Covariance calulator

Definition at line 80 of file itkGaussianGoodnessOfFitComponent.h.

template<class TInputSample>
typedef Superclass::ProjectionAxisArrayType itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::ProjectionAxisArrayType
 

projection axis array type. The type of output from CalculateProjectionAxis(). The number of projection axis are fixed equal to the number of components of a measurement vector

Reimplemented from itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

Definition at line 74 of file itkGaussianGoodnessOfFitComponent.h.

template<class TInputSample>
typedef SymmetricEigenSystem< double, itkGetStaticConstMacro(MeasurementVectorSize) itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::ProjectionAxisCalculatorType)
 

Default projection axis calculator type

Definition at line 92 of file itkGaussianGoodnessOfFitComponent.h.

template<class TInputSample>
typedef Superclass::RadiusType itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::RadiusType
 

Reimplemented from itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

Definition at line 70 of file itkGaussianGoodnessOfFitComponent.h.

template<class TInputSample>
typedef Superclass::ResampledSampleType itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::ResampledSampleType
 

Resample() output type

Reimplemented from itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

Definition at line 73 of file itkGaussianGoodnessOfFitComponent.h.

template<class TInputSample>
typedef GaussianGoodnessOfFitComponent itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::Self
 

Standard class typedefs

Reimplemented from itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

Definition at line 50 of file itkGaussianGoodnessOfFitComponent.h.

template<class TInputSample>
typedef Superclass::StandardDeviationType itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::StandardDeviationType
 

Reimplemented from itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

Definition at line 72 of file itkGaussianGoodnessOfFitComponent.h.

template<class TInputSample>
typedef GoodnessOfFitComponentBase< TInputSample > itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::Superclass
 

Reimplemented from itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

Definition at line 51 of file itkGaussianGoodnessOfFitComponent.h.


Constructor & Destructor Documentation

template<class TInputSample>
itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::GaussianGoodnessOfFitComponent   [protected]
 

template<class TInputSample>
virtual itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::~GaussianGoodnessOfFitComponent   [protected, virtual]
 


Member Function Documentation

template<class TInputSample>
virtual void itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::CalculateProjectionAxes   [protected, virtual]
 

Calculates the base axes for projection

Implements itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

template<class TInputSample>
CenterType* itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::GetCenter   [virtual]
 

Implements itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

template<class TInputSample>
virtual const char* itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::GetClassName   const [virtual]
 

Run-time type information (and related methods).

Reimplemented from itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

template<class TInputSample>
double itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::GetCumulativeProbability double    x const [virtual]
 

Univariate (standard) cumulative probability function

Implements itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

template<class TInputSample>
ParametersType itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::GetFullParameters   const [virtual]
 

Gets the full distribution parameters which consists of mean vector and covariance matrix in a single array

Implements itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

template<class TInputSample>
MeanType* itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::GetMean   [virtual]
 

Implements itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

template<class TInputSample>
unsigned int itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::GetNumberOfParameters void    const [inline, virtual]
 

Gets the size of parameters which consists of mean and standard deviation

Implements itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

Definition at line 96 of file itkGaussianGoodnessOfFitComponent.h.

References itkGetStaticConstMacro.

template<class TInputSample>
double itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::GetProbabilityDensity MeasurementVectorType   measurements const [virtual]
 

Multivariate probability density function

Implements itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

template<class TInputSample>
RadiusType* itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::GetRadius   [virtual]
 

Implements itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

template<class TInputSample>
StandardDeviationType* itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::GetStandardDeviation   [virtual]
 

Implements itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

template<class TInputSample>
itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::itkStaticConstMacro MeasurementVectorSize   ,
unsigned    int,
TInputSample::MeasurementVectorSize   
 

typedefs from input sample

Reimplemented from itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

template<class TInputSample>
Pointer itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::New   [static]
 

Method for creation through the object factory.

Reimplemented from itk::Object.

template<class TInputSample>
void itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::PrintParameters std::ostream &    os const [virtual]
 

Implements itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.

template<class TInputSample>
void itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >::SetParameters const ParametersType   parameter [virtual]
 

Sets the component distribution parameters

Reimplemented from itk::Statistics::GoodnessOfFitComponentBase< TInputSample >.


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