Review/Statistics/itkMahalanobisDistanceMembershipFunction.h

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/*=========================================================================

  Program:   Insight Segmentation & Registration Toolkit
  Module:    $RCSfile: itkMahalanobisDistanceMembershipFunction.h,v $
  Language:  C++
  Date:      $Date: 2009-05-10 18:52:26 $
  Version:   $Revision: 1.3 $

  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 {

template< class TVector >
class ITK_EXPORT MahalanobisDistanceMembershipFunction :
    public MembershipFunctionBase< TVector >
{
public:
  typedef MahalanobisDistanceMembershipFunction Self;
  typedef MembershipFunctionBase< TVector >     Superclass;
  typedef SmartPointer<Self>                    Pointer;
  typedef SmartPointer<const Self>              ConstPointer;

  itkTypeMacro(MahalanobisDistanceMembershipFunction, MembershipFunctionBase);
  itkNewMacro(Self);

  typedef TVector MeasurementVectorType;

  typedef typename Superclass::MeasurementVectorSizeType MeasurementVectorSizeType;

  typedef vnl_vector<double>  MeanVectorType;

  typedef vnl_matrix<double>  CovarianceMatrixType;

  virtual void SetMeasurementVectorSize( MeasurementVectorSizeType );

  void SetMean(const MeanVectorType &mean);
  void SetMean(const Array< double > &mean);

  const MeanVectorType & GetMean() const;

  void SetCovariance(const CovarianceMatrixType &cov); 

  itkGetConstReferenceMacro( Covariance, CovarianceMatrixType );

  void SetInverseCovariance(const CovarianceMatrixType &invcov); 

  itkGetConstReferenceMacro( InverseCovariance, CovarianceMatrixType );

  itkSetMacro( NumberOfSamples, double );

  itkGetConstMacro( NumberOfSamples, double );

  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