freVectorSampleCharacteristicsCalculator.txx

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

  Program:   F.R.E.E. - flexible registration evaluation engine
  Version:   v.1.0.0
  Date:      $Date: 2006/09/01 12:00:00 $
  Module:    $RCSfile: freVectorSampleCharacteristicsCalculator.txx,v $
  Language:  C++



  Copyright (c) 2007 Ralf o Floca (Department of Medical Informatics,
  Institute for Medical Biometry and Informatics, University of Heidelberg,
  Germany). All rights reserved.
  See FREECopyright.txt or http://www.mi.med.uni-hd.de/free/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 _freVectorSampleCharacteristicsCalculator_txx
#define _freVectorSampleCharacteristicsCalculator_txx

#include "freVectorSampleCharacteristicsCalculator.h"

#include "itkNumericTraits.h"
#include "itkImageToListAdaptor.h"
#include "itkCovarianceCalculator.h"
#include "itkMeanCalculator.h"

namespace FREE
{

template <class TVectorField>
void
VectorSampleCharacteristicsCalculator<TVectorField>::
Compute()
{
        typedef itk::Statistics::ImageToListAdaptor< VectorFieldType > SampleType;
        typedef itk::Statistics::CovarianceCalculator< SampleType > CovarianceAlgorithmType;

        if (m_smpImage.IsNull()) return;

        typename SampleType::Pointer sample = SampleType::New();
        sample->SetImage(m_smpImage);

        typename CovarianceAlgorithmType::Pointer covarianceAlgorithm = CovarianceAlgorithmType::New();
        covarianceAlgorithm->SetInputSample( sample );
        covarianceAlgorithm->Update();

        m_Mean = *(covarianceAlgorithm->GetMean());
  m_CovarianceMatrix = *(covarianceAlgorithm->GetOutput());
        m_iMatrixSize = m_CovarianceMatrix.Cols();//must be set here because the itk implementation is non const and cannot be used in GetVariance()
};

template <class TVectorField>
void
VectorSampleCharacteristicsCalculator<TVectorField>::
ComputeMean()
{
        typedef itk::Statistics::ImageToListAdaptor< VectorFieldType > SampleType;
        typedef itk::Statistics::MeanCalculator< SampleType > MeanAlgorithmType;

        if (m_smpImage.IsNull()) return;

        typename SampleType::Pointer sample = SampleType::New();
        sample->SetImage(m_smpImage);

        typename MeanAlgorithmType::Pointer meanAlgorithm = MeanAlgorithmType::New();
        meanAlgorithm->SetInputSample( sample );
        meanAlgorithm->Update();

        m_Mean = *(meanAlgorithm->GetOutput());
};

template <class TVectorField>
void
VectorSampleCharacteristicsCalculator<TVectorField>::
ComputeCovariance(const MeanType& mean)
{
        typedef itk::Statistics::ImageToListAdaptor< VectorFieldType > SampleType;
        typedef itk::Statistics::CovarianceCalculator< SampleType > CovarianceAlgorithmType;

        if (m_smpImage.IsNull()) return;

        typename SampleType::Pointer sample = SampleType::New();
        sample->SetImage(m_smpImage);

        m_Mean = mean;

        typename CovarianceAlgorithmType::Pointer covarianceAlgorithm = CovarianceAlgorithmType::New();
        covarianceAlgorithm->SetInputSample( sample );
        covarianceAlgorithm->SetMean( &m_Mean );
        covarianceAlgorithm->Update();

  m_CovarianceMatrix = *(covarianceAlgorithm->GetOutput());
        m_iMatrixSize = m_CovarianceMatrix.Cols();//must be set here because the itk implementation is non const and cannot be used in GetVariance()
};

template <class TVectorField>
typename VectorSampleCharacteristicsCalculator<TVectorField>::MeanType
VectorSampleCharacteristicsCalculator<TVectorField>::
GetMean() const
{
        return m_Mean;
};

template <class TVectorField>
typename VectorSampleCharacteristicsCalculator<TVectorField>::MeanType
VectorSampleCharacteristicsCalculator<TVectorField>::
GetVariance() const
{
        MeanType variance(m_iMatrixSize);

        for (unsigned int i = 0; i<m_iMatrixSize; i++) variance[i] = m_CovarianceMatrix(i,i);

        return variance;
};

template <class TVectorField>
typename VectorSampleCharacteristicsCalculator<TVectorField>::CovarianceMatrixType
VectorSampleCharacteristicsCalculator<TVectorField>::
GetCovariance() const
{
        return m_CovarianceMatrix;
};

template <class TVectorField>
void
VectorSampleCharacteristicsCalculator<TVectorField>::
SetVectorField(const VectorFieldType* pField)
{
  m_smpImage = pField;
};

template <class TVectorField>
VectorSampleCharacteristicsCalculator<TVectorField>::
VectorSampleCharacteristicsCalculator()
{
  typedef typename VectorType::ValueType PixelComponentType;
        typedef typename itk::NumericTraits< PixelComponentType >::RealType PixelComponentRealType;
  
  m_Mean.Fill( itk::NumericTraits< PixelComponentRealType >::Zero );
  m_CovarianceMatrix.Fill( itk::NumericTraits< PixelComponentRealType >::Zero );
  m_iMatrixSize = 0;
};

} // namespace free

#endif

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