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

provides component (module) type specific functionalities for GoodnessOfFitMixtureModelCostFunction. More...

#include <itkGoodnessOfFitComponentBase.h>

Inheritance diagram for itk::Statistics::GoodnessOfFitComponentBase< TInputSample >:

[legend]Collaboration diagram for itk::Statistics::GoodnessOfFitComponentBase< TInputSample >:

[legend]List of all members.

Public Types
typedef GoodnessOfFitComponentBase	Self
typedef Object	Superclass
typedef SmartPointer< Self >	Pointer
typedef SmartPointer< const Self >	ConstPointer
typedef TInputSample	InputSampleType
typedef TInputSample::MeasurementType	MeasurementType
typedef TInputSample::MeasurementVectorType	MeasurementVectorType
typedef Subsample< TInputSample >	ResampledSampleType
typedef Histogram< float, 1 >	HistogramType
typedef HistogramType::Pointer	HistogramPointer
typedef Array< double >	ParametersType
typedef FixedArray< double, itkGetStaticConstMacro(MeasurementVectorSize)	CenterType )
typedef double	RadiusType
typedef Vector< double, itkGetStaticConstMacro(MeasurementVectorSize)	MeanType )
typedef double	StandardDeviationType
Public Member Functions
virtual const char *	GetClassName () const
	itkStaticConstMacro (MeasurementVectorSize, unsigned int, TInputSample::MeasurementVectorSize)
virtual unsigned int	GetNumberOfParameters () const =0
void	SetUseExpectedHistogram (bool flag)
virtual CenterType *	GetCenter ()=0
virtual RadiusType *	GetRadius ()=0
virtual MeanType *	GetMean ()=0
virtual RadiusType *	GetStandardDeviation ()=0
virtual void	CreateHistograms ()
virtual void	Resample ()
ResampledSampleType *	GetResampledSample ()
virtual unsigned int	GetResampledSampleSize ()
virtual void	CalculateProjectionAxes ()=0
virtual void	Project (int projectionAxisIndex)
virtual void	UpdateExpectedHistogram ()
double *	GetTotalObservedScale ()
virtual double	GetCumulativeProbability (double x) const =0
virtual double	GetProbabilityDensity (MeasurementVectorType &measurements) const =0
virtual double	GetProportion () const
HistogramPointer	GetObservedHistogram ()
HistogramPointer	GetExpectedHistogram ()
virtual void	PrintParameters (std::ostream &os) const =0
virtual ParametersType	GetFullParameters () const =0
virtual void	SetInputSample (TInputSample *sample)
TInputSample *	GetInputSample ()
virtual void	SetParameters (const ParametersType &parameters)
ParametersType *	GetParameters ()
void	SetHistogramNumberOfBins (int numberOfBins)
int	GetHistogramNumberOfBins ()
void	SetHistogramUseEquiProbableBins (bool flag)
bool	GetHistogramUseEquiProbableBins ()
void	SetHistogramBinOverlap (double overlap)
double	GetHistogramBinOverlap ()
void	SetHistogramExtent (double extent)
double	GetHistogramExtent ()
Protected Types
typedef NeighborhoodSampler< TInputSample >	ResamplerType
typedef SampleToHistogramProjectionFilter< ResampledSampleType, float >	ProjectorType
typedef FixedArray< double, itkGetStaticConstMacro(MeasurementVectorSize)	ProjectionAxisType )
typedef FixedArray< ProjectionAxisType, itkGetStaticConstMacro(MeasurementVectorSize)	ProjectionAxisArrayType )
Protected Member Functions
	GoodnessOfFitComponentBase ()
virtual	~GoodnessOfFitComponentBase ()
virtual void	PrintSelf (std::ostream &os, Indent indent) const
ProjectionAxisArrayType *	GetProjectionAxes ()
virtual void	CreateEquiRangeBins ()
virtual void	CreateEquiProbableBins ()

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Detailed Description

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

provides component (module) type specific functionalities for GoodnessOfFitMixtureModelCostFunction.

This defines common iterfaces for each subclasses and provides common functionalities across different types of components (e.g. GaussianGoodnessOfFitComponent)

The primary role of a GoodnessOfFitComponent is to create an 1D histogram (called an observed histogram ) of the input sample after resampling the input using spherical kernel and projecting the resampled sample along base axes, and to create corresponding 1D histogram (expected histogram) that has the same histogram configuration as the observed histogram but has the expected frequencies from the given component parameters.

You can set up the two histograms' configuration by calling SetHistogramNumberOfBins, SetHistogramUseEquiProbableBins, SetHistogramBingOverlap, SetHistogramExtent. After you change the histogram configuration, call the CreateHistograms method to allocate histograms. If you set the UseExpectedHistogram flag to false by callsing SetUseExpectedHistogram(false), the CreateHistograms method won't create the expected histogram. The decision should be made by the GoodnessOfFitFunction object that will be plugged-in to the GoodnessOfFitMixtureModelCostFunction. So the method shouldn't be called manually.

This base class provides default implementations for the resampling and projection using helper classes (NeighborhoodSampler, SampleToHistogramProjectionFilter).

To determine the base axis, call the CalculateProjectionAxes method. each subclass should implement it.

Another group of functions includes probability function such as GetProbabilityDensity(MeasurementVectorType) multivariate probability density function of the subclass GetCumulativeProbability(MeasurementType) univariate cumulative probabilty function

To see how all this methods are used in order, take a look at the implementation of the GetValue method of the GoodnessOfFitMixtureModelCostFunction class.

See also:

GoodnessOfFitMixtureModelCostFunction, GoodnessOfFitFunctionBase, GaussianGoodnessOfFitComponent, NeighborhoodSampler, SampleToHistogramProjectionFilter

Definition at line 80 of file itkGoodnessOfFitComponentBase.h.

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Member Typedef Documentation

template<class TInputSample> typedef FixedArray< double, itkGetStaticConstMacro(MeasurementVectorSize) itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::CenterType)

Type of the center position for the hyperspherical neighborhood sampling Reimplemented in itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >. Definition at line 118 of file itkGoodnessOfFitComponentBase.h.

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

Reimplemented from itk::Object. Reimplemented in itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >. Definition at line 88 of file itkGoodnessOfFitComponentBase.h.

template<class TInputSample> typedef HistogramType::Pointer itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::HistogramPointer

Definition at line 109 of file itkGoodnessOfFitComponentBase.h.

template<class TInputSample> typedef Histogram< float, 1 > itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::HistogramType

Histogram type that will be used for observed and expected histogram Definition at line 108 of file itkGoodnessOfFitComponentBase.h.

template<class TInputSample> typedef TInputSample itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::InputSampleType

TInputSample type alias Definition at line 94 of file itkGoodnessOfFitComponentBase.h.

template<class TInputSample> typedef Vector< double, itkGetStaticConstMacro(MeasurementVectorSize) itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::MeanType)

Type of the mean of the distribution Reimplemented in itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >. Definition at line 125 of file itkGoodnessOfFitComponentBase.h. Referenced by itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetHistogramExtent().

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

Typedefs from the TInputSample Reimplemented in itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >. Definition at line 101 of file itkGoodnessOfFitComponentBase.h.

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

Reimplemented in itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >. Definition at line 102 of file itkGoodnessOfFitComponentBase.h. Referenced by itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetTotalObservedScale().

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

Type of the array of component parameters Reimplemented in itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >. Definition at line 112 of file itkGoodnessOfFitComponentBase.h.

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

Reimplemented from itk::Object. Reimplemented in itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >. Definition at line 87 of file itkGoodnessOfFitComponentBase.h.

template<class TInputSample> typedef FixedArray< ProjectionAxisType, itkGetStaticConstMacro(MeasurementVectorSize) itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::ProjectionAxisArrayType) [protected]

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 in itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >. Definition at line 260 of file itkGoodnessOfFitComponentBase.h.

template<class TInputSample> typedef FixedArray< double, itkGetStaticConstMacro(MeasurementVectorSize) itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::ProjectionAxisType) [protected]

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 Definition at line 257 of file itkGoodnessOfFitComponentBase.h.

template<class TInputSample> typedef SampleToHistogramProjectionFilter< ResampledSampleType, float > itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::ProjectorType [protected]

default projection filter type Definition at line 250 of file itkGoodnessOfFitComponentBase.h.

template<class TInputSample> typedef double itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::RadiusType

Type of the radius of the hyperspherical neighborhood sampling Reimplemented in itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >. Definition at line 121 of file itkGoodnessOfFitComponentBase.h. Referenced by itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetHistogramExtent().

template<class TInputSample> typedef Subsample< TInputSample > itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::ResampledSampleType

Resample() output type Reimplemented in itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >. Definition at line 105 of file itkGoodnessOfFitComponentBase.h. Referenced by itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetHistogramExtent().

template<class TInputSample> typedef NeighborhoodSampler< TInputSample > itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::ResamplerType [protected]

default resampler type and realted types Definition at line 246 of file itkGoodnessOfFitComponentBase.h.

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

Standard class typedefs Reimplemented from itk::Object. Reimplemented in itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >. Definition at line 85 of file itkGoodnessOfFitComponentBase.h.

template<class TInputSample> typedef double itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::StandardDeviationType

Type of standard deviation of the distribution Reimplemented in itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >. Definition at line 128 of file itkGoodnessOfFitComponentBase.h.

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

Reimplemented from itk::Object. Reimplemented in itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >. Definition at line 86 of file itkGoodnessOfFitComponentBase.h.

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Constructor & Destructor Documentation

template<class TInputSample> itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GoodnessOfFitComponentBase (   )  [protected]

template<class TInputSample> virtual itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::~GoodnessOfFitComponentBase (   )  [protected, virtual]

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Member Function Documentation

template<class TInputSample> virtual void itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::CalculateProjectionAxes (   )  [pure virtual]

Calculates the longest axis based on eigen analysis Implemented in itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >.

template<class TInputSample> virtual void itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::CreateEquiProbableBins (   )  [protected, virtual]

Creates an empty histogram with bins having same probability based on the distribution parameters

template<class TInputSample> virtual void itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::CreateEquiRangeBins (   )  [protected, virtual]

Creates an empty histogram with bins having same interval

template<class TInputSample> virtual void itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::CreateHistograms (   )  [virtual]

Generates the histogram (expected and observed)

template<class TInputSample> virtual CenterType* itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetCenter (   )  [pure virtual]

Gets the center position for the neighborhood sampling Implemented in itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >.

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

Run-time type information (and related methods). Reimplemented from itk::Object. Reimplemented in itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >.

template<class TInputSample> virtual double itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetCumulativeProbability (  double  x  )  const [pure virtual]

Gets the probability of x. univariate function Implemented in itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >.

template<class TInputSample> HistogramPointer itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetExpectedHistogram (   )

Gets the expected historm

template<class TInputSample> virtual ParametersType itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetFullParameters (   )  const [pure virtual]

Gest the parameters of this component Implemented in itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >.

template<class TInputSample> double itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetHistogramBinOverlap (   )  [inline]

Set/Get the overlapping effects extent. Definition at line 164 of file itkGoodnessOfFitComponentBase.h.

template<class TInputSample> double itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetHistogramExtent (   )  [inline]

Set/Gets the extent of histogram from the mean in terms of standard deivation Definition at line 171 of file itkGoodnessOfFitComponentBase.h. References itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::MeanType, itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::RadiusType, and itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::ResampledSampleType.

template<class TInputSample> int itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetHistogramNumberOfBins (   )  [inline]

Set/Gets the nubmer of bins of histograms (expected and observed) Definition at line 150 of file itkGoodnessOfFitComponentBase.h.

template<class TInputSample> bool itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetHistogramUseEquiProbableBins (   )  [inline]

Set/Gets the flag that indicates the probability of each bins in the histograms should be equal. This can be achieved by varying the interval of bins. Definition at line 158 of file itkGoodnessOfFitComponentBase.h.

template<class TInputSample> TInputSample* itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetInputSample (   )

Set/Gets the input sample

template<class TInputSample> virtual MeanType* itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetMean (   )  [pure virtual]

Gets the mean of the distribution Implemented in itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >.

template<class TInputSample> virtual unsigned int itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetNumberOfParameters (   )  const [pure virtual]

Gets the total number of parameters for this component Implemented in itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >.

template<class TInputSample> HistogramPointer itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetObservedHistogram (   )

Gets the observed historm

template<class TInputSample> ParametersType* itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetParameters (  void   )  [inline]

Set/Gets the component parameters Definition at line 140 of file itkGoodnessOfFitComponentBase.h.

template<class TInputSample> virtual double itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetProbabilityDensity (  MeasurementVectorType &  measurements  )  const [pure virtual]

Gets the probability density of measurements. multivariate function Implemented in itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >.

template<class TInputSample> ProjectionAxisArrayType* itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetProjectionAxes (   )  [inline, protected]

Definition at line 263 of file itkGoodnessOfFitComponentBase.h.

template<class TInputSample> virtual double itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetProportion (   )  const [inline, virtual]

Gets the proportion of this component among multiple components. Definition at line 225 of file itkGoodnessOfFitComponentBase.h.

template<class TInputSample> virtual RadiusType* itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetRadius (   )  [pure virtual]

Gets the radius for the neighborhood sampling Implemented in itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >.

template<class TInputSample> ResampledSampleType* itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetResampledSample (   )  [inline]

Gets the sampled data set Definition at line 194 of file itkGoodnessOfFitComponentBase.h.

template<class TInputSample> virtual unsigned int itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetResampledSampleSize (   )  [virtual]

Gest the size of the sampled data set

template<class TInputSample> virtual RadiusType* itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetStandardDeviation (   )  [pure virtual]

Gets the standard deviation of the distribution Implemented in itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >.

template<class TInputSample> double* itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::GetTotalObservedScale (   )  [inline]

Gets the total scale of the observed histogram Definition at line 212 of file itkGoodnessOfFitComponentBase.h. References itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::MeasurementVectorType.

template<class TInputSample> itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::itkStaticConstMacro (  MeasurementVectorSize  , unsigned  int, TInputSample::MeasurementVectorSize  )

Vector length constant Reimplemented in itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >.

template<class TInputSample> virtual void itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::PrintParameters (  std::ostream &  os  )  const [pure virtual]

Prints component parameters. For debugging Implemented in itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >.

template<class TInputSample> virtual void itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::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::Object. Reimplemented in itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >.

template<class TInputSample> virtual void itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::Project (  int  projectionAxisIndex  )  [virtual]

Projects measurement vectors onto the projection axis calculated by the CalculateProjectionAxes method.

template<class TInputSample> virtual void itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::Resample (   )  [virtual]

Samples measurement vectors using the center and radius

template<class TInputSample> void itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::SetHistogramBinOverlap (  double  overlap  )

Set/Get the overlapping effects extent.

template<class TInputSample> void itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::SetHistogramExtent (  double  extent  )

Set/Gets the extent of histogram from the mean in terms of standard deivation

template<class TInputSample> void itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::SetHistogramNumberOfBins (  int  numberOfBins  )

Set/Gets the nubmer of bins of histograms (expected and observed)

template<class TInputSample> void itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::SetHistogramUseEquiProbableBins (  bool  flag  )

Set/Gets the flag that indicates the probability of each bins in the histograms should be equal. This can be achieved by varying the interval of bins.

template<class TInputSample> virtual void itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::SetInputSample (  TInputSample *  sample  )  [virtual]

Set/Gets the input sample

template<class TInputSample> virtual void itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::SetParameters (  const ParametersType &  parameters  )  [virtual]

Set/Gets the component parameters Reimplemented in itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >.

template<class TInputSample> void itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::SetUseExpectedHistogram (  bool  flag  )

Sets the flag that indicates this component uses the histogram generated with expected distribution from the parameters.

template<class TInputSample> virtual void itk::Statistics::GoodnessOfFitComponentBase< TInputSample >::UpdateExpectedHistogram (   )  [virtual]

Fills up the expected histogram based on the distribution parameters

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

• itkGoodnessOfFitComponentBase.h

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