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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: $RCSfile: itkExpectationMaximizationMixtureModelEstimator.h,v $
Language: C++
Date: $Date: 2009-03-04 15:23:47 $
Version: $Revision: 1.13 $
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 __itkExpectationMaximizationMixtureModelEstimator_h
#define __itkExpectationMaximizationMixtureModelEstimator_h
#include "itkMembershipFunctionBase.h"
#include "itkMixtureModelComponentBase.h"
namespace itk {
namespace Statistics {
/** \class ExpectationMaximizationMixtureModelEstimator
* \brief This class generates the parameter estimates for a mixture
* model using expectation maximization strategy.
*
* The first template argument is the type of the target sample
* data. This estimator expects one or more mixture model component
* objects of the classes derived from the
* MixtureModelComponentBase. The actual component (or module)
* parameters are updated by each component. Users can think this
* class as a strategy or a integration point for the EM
* procedure. The initial proportion (SetInitialProportions), the
* input sample (SetSample), the mixture model components
* (AddComponent), and the maximum iteration (SetMaximumIteration) are
* required. The EM procedure terminates when the current iteration
* reaches the maximum iteration or the model parameters converge.
*
* <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, GaussianMixtureModelComponent
*/
template< class TSample >
class ITK_EXPORT ExpectationMaximizationMixtureModelEstimator : public Object
{
public:
/** Standard class typedef */
typedef ExpectationMaximizationMixtureModelEstimator Self;
typedef Object Superclass;
typedef SmartPointer< Self > Pointer;
typedef SmartPointer<const Self> ConstPointer;
/** Standard macros */
itkTypeMacro(ExpectationMaximizationMixtureModelEstimator,
Object);
itkNewMacro(Self);
/** TSample template argument related typedefs */
typedef typename TSample::MeasurementType MeasurementType;
typedef typename TSample::MeasurementVectorType MeasurementVectorType;
/** Type of the mixture model component base class */
typedef MixtureModelComponentBase< TSample > ComponentType;
/** Type of the component pointer storage */
typedef std::vector< ComponentType* > ComponentVectorType;
/** Type of the membership function base class */
typedef MembershipFunctionBase< MeasurementVectorType >
ComponentMembershipFunctionType;
/** Type of the array of the proportion values */
typedef Array< double > ProportionVectorType;
/** Sets the target data that will be classified by this */
void SetSample(const TSample* sample);
/** Returns the target data */
const TSample* GetSample() const;
/** Set/Gets the initial proportion values. The size of proportion
* vector should be same as the number of component (or classes) */
void SetInitialProportions(ProportionVectorType &propotion);
ProportionVectorType* GetInitialProportions();
/** Gets the result proportion values */
ProportionVectorType* GetProportions();
/** Set/Gets the maximum number of iterations. When the optimization
* process reaches the maximum number of interations, even if the
* class parameters aren't converged, the optimization process
* stops. */
void SetMaximumIteration(int numberOfIterations);
int GetMaximumIteration();
/** Gets the current iteration. */
int GetCurrentIteration()
{ return m_CurrentIteration; }
/** Adds a new component (or class). */
int AddComponent(ComponentType* component);
/** Gets the total number of classes currently plugged in. */
unsigned int GetNumberOfComponents();
/** Runs the optimization process. */
void Update();
/** Termination status after running optimization */
enum TERMINATION_CODE { CONVERGED = 0, NOT_CONVERGED = 1 };
/** Gets the termination status */
TERMINATION_CODE GetTerminationCode();
/** Gets the membership function specified by componentIndex
argument. */
ComponentMembershipFunctionType* GetComponentMembershipFunction(int componentIndex);
protected:
ExpectationMaximizationMixtureModelEstimator();
virtual ~ExpectationMaximizationMixtureModelEstimator() {}
void PrintSelf(std::ostream& os, Indent indent) const;
bool CalculateDensities();
double CalculateExpectation();
bool UpdateComponentParameters();
bool UpdateProportions();
/** Starts the estimation process */
void GenerateData();
private:
/** Target data sample pointer*/
const TSample* m_Sample;
int m_MaxIteration;
int m_CurrentIteration;
TERMINATION_CODE m_TerminationCode;
ComponentVectorType m_ComponentVector;
ProportionVectorType m_InitialProportions;
ProportionVectorType m_Proportions;
}; // end of class
} // end of namespace Statistics
} // end of namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkExpectationMaximizationMixtureModelEstimator.txx"
#endif
#endif
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