/usr/include/InsightToolkit/Review/Statistics/itkMahalanobisDistanceMembershipFunction.h is in libinsighttoolkit3-dev 3.20.1-1.
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Program: Insight Segmentation & Registration Toolkit
Module: itkMahalanobisDistanceMembershipFunction.h
Language: C++
Date: $Date$
Version: $Revision$
Copyright (c) Insight Software Consortium. All rights reserved.
See ITKCopyright.txt or http://www.itk.org/HTML/Copyright.htm for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
PURPOSE. See the above copyright notices for more information.
=========================================================================*/
#ifndef __itkMahalanobisDistanceMembershipFunction_h
#define __itkMahalanobisDistanceMembershipFunction_h
#include <vnl/vnl_vector.h>
#include <vnl/vnl_vector_ref.h>
#include <vnl/vnl_transpose.h>
#include <vnl/vnl_matrix.h>
#include <vnl/algo/vnl_matrix_inverse.h>
#include <vnl/algo/vnl_determinant.h>
#include "itkArray.h"
#include "itkMembershipFunctionBase.h"
namespace itk {
namespace Statistics {
/** \class MahalanobisDistanceMembershipFunction
* \brief MahalanobisDistanceMembershipFunction class represents MahalanobisDistance Density Function.
*
* This class keeps parameter to define MahalanobisDistance Density Function and has
* method to return the probability density
* of an instance. MeasurementVectorSize is the dimension of measurement space.
* double is type of measurement.
*/
template< class TVector >
class ITK_EXPORT MahalanobisDistanceMembershipFunction :
public MembershipFunctionBase< TVector >
{
public:
/** Standard class typedefs */
typedef MahalanobisDistanceMembershipFunction Self;
typedef MembershipFunctionBase< TVector > Superclass;
typedef SmartPointer<Self> Pointer;
typedef SmartPointer<const Self> ConstPointer;
/** Strandard macros */
itkTypeMacro(MahalanobisDistanceMembershipFunction, MembershipFunctionBase);
itkNewMacro(Self);
/** Typedef alias for the measurement vectors */
typedef TVector MeasurementVectorType;
/** Typedef to represent the length of measurement vectors */
typedef typename Superclass::MeasurementVectorSizeType MeasurementVectorSizeType;
/** Type used for representing the mean vector */
typedef vnl_vector<double> MeanVectorType;
/** Type used for representing the covariance matrix */
typedef vnl_matrix<double> CovarianceMatrixType;
/** Set the length of each measurement vector. */
virtual void SetMeasurementVectorSize( MeasurementVectorSizeType );
/** Method to set mean */
void SetMean(const MeanVectorType &mean);
void SetMean(const Array< double > &mean);
/** Method to get mean */
const MeanVectorType & GetMean() const;
/**
* Method to set covariance matrix
* Also, this function calculates inverse covariance and pre factor of
* MahalanobisDistance Distribution to speed up GetProbability */
void SetCovariance(const CovarianceMatrixType &cov);
/** Method to get covariance matrix */
itkGetConstReferenceMacro( Covariance, CovarianceMatrixType );
/**
* Method to set covariance matrix
* Also, this function calculates inverse covariance and pre factor of
* MahalanobisDistance Distribution to speed up GetProbability */
void SetInverseCovariance(const CovarianceMatrixType &invcov);
/** Method to get covariance matrix */
itkGetConstReferenceMacro( InverseCovariance, CovarianceMatrixType );
/** Method to set the number of samples */
itkSetMacro( NumberOfSamples, double );
/** Method to get the number of samples */
itkGetConstMacro( NumberOfSamples, double );
/**
* Method to get probability of an instance. The return value is the
* value of the density function, not probability. */
double Evaluate(const MeasurementVectorType &measurement) const;
protected:
MahalanobisDistanceMembershipFunction(void);
virtual ~MahalanobisDistanceMembershipFunction(void) {}
void PrintSelf(std::ostream& os, Indent indent) const;
private:
MeanVectorType m_Mean; // mean
CovarianceMatrixType m_Covariance; // covariance matrix
// inverse covariance matrix which is automatically calculated
// when covariace matirx is set. This speed up the GetProbability()
CovarianceMatrixType m_InverseCovariance;
// Number of samples defining this density
double m_NumberOfSamples;
// pre_factor which is automatically calculated
// when covariace matirx is set. This speeds up the GetProbability()
double m_PreFactor;
double m_Epsilon;
double m_DoubleMax;
mutable vnl_matrix< double > m_TempVec;
mutable vnl_matrix< double > m_TempMat;
void CalculateInverseCovariance();
};
} // end of namespace Statistics
} // end namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkMahalanobisDistanceMembershipFunction.txx"
#endif
#endif
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