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

  Program:   Insight Segmentation & Registration Toolkit
  Module:    itkGaussianMixtureModelComponent.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 __itkGaussianMixtureModelComponent_h
#define __itkGaussianMixtureModelComponent_h

#include "itkMixtureModelComponentBase.h"
#include "itkGaussianMembershipFunction.h"
#include "itkWeightedMeanSampleFilter.h"
#include "itkWeightedCovarianceSampleFilter.h"

namespace itk { 
namespace Statistics {
  
/** \class GaussianMixtureModelComponent
 * \brief is a component (derived from MixtureModelComponentBase) for
 * Gaussian class. This class is used in
 * ExpectationMaximizationMixtureModelEstimator. 
 *
 * On every iteration of EM estimation, this class's GenerateData
 * method is called to compute the new distribution parameters.
 *
 * <b>Recent API changes:</b>
 * The static const macro to get the length of a measurement vector,
 * \c MeasurementVectorSize  has been removed to allow the length of a measurement
 * vector to be specified at run time. It is now obtained at run time from the
 * sample set as input. Please use the function 
 * GetMeasurementVectorSize() to get the length. 
 * 
 * \sa MixtureModelComponentBase, ExpectationMaximizationMixtureModelEstimator
 */

template< class TSample >
class ITK_EXPORT GaussianMixtureModelComponent :
    public MixtureModelComponentBase< TSample >
{
public:
  /**Standard class typedefs. */
  typedef GaussianMixtureModelComponent             Self;
  typedef MixtureModelComponentBase< TSample >      Superclass;
  typedef SmartPointer<Self>                        Pointer;
  typedef SmartPointer<const Self>                  ConstPointer;

  /**Standard Macros */
  itkTypeMacro(GaussianMixtureModelComponent, MixtureModelComponentBase);
  itkNewMacro(Self);


  /** Typedefs from the superclass */
  typedef typename Superclass::MeasurementVectorType            MeasurementVectorType;
  typedef typename Superclass::MeasurementVectorSizeType        MeasurementVectorSizeType;
  typedef typename Superclass::MembershipFunctionType           MembershipFunctionType;
  typedef typename Superclass::WeightArrayType                  WeightArrayType;
  typedef typename Superclass::ParametersType                   ParametersType;

  /** Type of the membership function. Gaussian density function */
  typedef GaussianMembershipFunction< MeasurementVectorType > 
  NativeMembershipFunctionType;
  
  /** Types of the mean and the covariance calculator that will update
   *  this component's distribution parameters */
  typedef WeightedMeanSampleFilter< TSample >       MeanEstimatorType;
  typedef WeightedCovarianceSampleFilter< TSample > CovarianceEstimatorType;

  /** Type of the mean vector */
  typedef typename MeanEstimatorType::OutputType MeanType;

  /** Type of the covariance matrix */
  typedef typename CovarianceEstimatorType::OutputType CovarianceType;

  /** Sets the input sample */
  void SetSample(const TSample* sample);

  /** Sets the component's distribution parameters. */
  void SetParameters(const ParametersType &parameters);
  
protected:
  GaussianMixtureModelComponent();
  virtual ~GaussianMixtureModelComponent() {}
  void PrintSelf(std::ostream& os, Indent indent) const;
  
  /** Returns the sum of squared changes in parameters between
   * iterations */
  double CalculateParametersChange();

  /** Computes the new distribution parameters */
  void GenerateData();

private:
  typename NativeMembershipFunctionType::Pointer m_GaussianMembershipFunction;

  typename MeanEstimatorType::MeasurementVectorType    m_Mean;
  typename CovarianceEstimatorType::MatrixType         m_Covariance;
  typename MeanEstimatorType::Pointer                  m_MeanEstimator;
  typename CovarianceEstimatorType::Pointer            m_CovarianceEstimator;
}; // end of class
    
} // end of namespace Statistics 
} // end of namespace itk 

#ifndef ITK_MANUAL_INSTANTIATION
#include "itkGaussianMixtureModelComponent.txx"
#endif

#endif