itk::Statistics::GaussianDensityFunction< TMeasurementVector > Class Template Reference

GaussianDensityFunction class represents Gaussian Density Function. More...

#include <itkGaussianDensityFunction.h>

Inheritance diagram for itk::Statistics::GaussianDensityFunction:

[legend]Collaboration diagram for itk::Statistics::GaussianDensityFunction< TMeasurementVector >:

[legend]List of all members.

[NOHEADER]
virtual const char *	GetClassName () const
Pointer	New ()
Public Types
typedef GaussianDensityFunction	Self
typedef DensityFunction< TMeasurementVector >	Superclass
typedef SmartPointer< Self >	Pointer
typedef TMeasurementVector	MeasurementVectorType
typedef Vector< double, itkGetStaticConstMacro(VectorDimension)	MeanType )
typedef Matrix< double, itkGetStaticConstMacro(VectorDimension), itkGetStaticConstMacro(VectorDimension)	CovarianceType )
Public Methods
	itkStaticConstMacro (VectorDimension, unsigned int, TMeasurementVector::Length)
MeanType *	GetMean () const
void	SetCovariance (CovarianceType *cov)
CovarianceType *	GetCovariance () const
double	Evaluate (const MeasurementVectorType &measurement) const
void	SetMean (MeanType *mean)
Protected Methods
	GaussianDensityFunction (void)
virtual	~GaussianDensityFunction (void)
void	PrintSelf (std::ostream &os, Indent indent) const

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Detailed Description

template<class TMeasurementVector>
class itk::Statistics::GaussianDensityFunction< TMeasurementVector >

GaussianDensityFunction class represents Gaussian Density Function.

This class keeps parameter to define Gaussian Density Function and has method to return the probability density of an instance (pattern) . If the all element of the covariance matrix is zero the "usual" density calculations ignored. if the measurement vector to be evaluated is equal to the mean, then the Evaluate method will return maximum value of double and return 0 for others

Definition at line 46 of file itkGaussianDensityFunction.h.

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Member Typedef Documentation

template<class TMeasurementVector> typedef Matrix< double, itkGetStaticConstMacro(VectorDimension), itkGetStaticConstMacro(VectorDimension) itk::Statistics::GaussianDensityFunction< TMeasurementVector >::CovarianceType)

Definition at line 68 of file itkGaussianDensityFunction.h.

template<class TMeasurementVector> typedef Vector< double, itkGetStaticConstMacro(VectorDimension) itk::Statistics::GaussianDensityFunction< TMeasurementVector >::MeanType)

Definition at line 67 of file itkGaussianDensityFunction.h.

template<class TMeasurementVector> typedef TMeasurementVector itk::Statistics::GaussianDensityFunction< TMeasurementVector >::MeasurementVectorType

Typedef alias for the measurement vectors Definition at line 61 of file itkGaussianDensityFunction.h.

template<class TMeasurementVector> typedef SmartPointer<Self> itk::Statistics::GaussianDensityFunction< TMeasurementVector >::Pointer

Reimplemented from itk::Statistics::DensityFunction< TMeasurementVector >. Definition at line 53 of file itkGaussianDensityFunction.h.

template<class TMeasurementVector> typedef GaussianDensityFunction itk::Statistics::GaussianDensityFunction< TMeasurementVector >::Self

Standard class typedefs Reimplemented from itk::Statistics::DensityFunction< TMeasurementVector >. Definition at line 51 of file itkGaussianDensityFunction.h.

template<class TMeasurementVector> typedef DensityFunction< TMeasurementVector > itk::Statistics::GaussianDensityFunction< TMeasurementVector >::Superclass

Reimplemented from itk::Statistics::DensityFunction< TMeasurementVector >. Definition at line 52 of file itkGaussianDensityFunction.h.

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Constructor & Destructor Documentation

template<class TMeasurementVector> itk::Statistics::GaussianDensityFunction< TMeasurementVector >::GaussianDensityFunction (  void    )  [protected]

template<class TMeasurementVector> virtual itk::Statistics::GaussianDensityFunction< TMeasurementVector >::~GaussianDensityFunction (  void    )  [inline, protected, virtual]

Definition at line 99 of file itkGaussianDensityFunction.h.

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Member Function Documentation

template<class TMeasurementVector> double itk::Statistics::GaussianDensityFunction< TMeasurementVector >::Evaluate (  const MeasurementVectorType &    measurement )  const

y Method to get probability of an instance. The return value is the value of the density function, not probability.

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

Strandard macros Reimplemented from itk::Statistics::DensityFunction< TMeasurementVector >.

template<class TMeasurementVector> CovarianceType* itk::Statistics::GaussianDensityFunction< TMeasurementVector >::GetCovariance (    )  const

Method to get covariance matrix

template<class TMeasurementVector> MeanType* itk::Statistics::GaussianDensityFunction< TMeasurementVector >::GetMean (  void    )  const [inline]

Method to get mean Definition at line 82 of file itkGaussianDensityFunction.h.

template<class TMeasurementVector> itk::Statistics::GaussianDensityFunction< TMeasurementVector >::itkStaticConstMacro (  VectorDimension   , unsigned    int, TMeasurementVector::Length    )

Dimension of the each individual pixel vector.

template<class TMeasurementVector> Pointer itk::Statistics::GaussianDensityFunction< TMeasurementVector >::New (    )  [static]

Strandard macros Reimplemented from itk::Object.

template<class TMeasurementVector> void itk::Statistics::GaussianDensityFunction< TMeasurementVector >::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::DensityFunction< TMeasurementVector >.

template<class TMeasurementVector> void itk::Statistics::GaussianDensityFunction< TMeasurementVector >::SetCovariance (  CovarianceType *    cov )

Method to set covariance matrix Also, this function calculates inverse covariance and pre factor of Gaussian Distribution to speed up GetProbability

template<class TMeasurementVector> void itk::Statistics::GaussianDensityFunction< TMeasurementVector >::SetMean (  MeanType *    mean )  [inline]

Method to set mean Definition at line 71 of file itkGaussianDensityFunction.h.

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

• itkGaussianDensityFunction.h

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