animaClassificationStrategy.h

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#pragma once

#include "animaRandomInitializer.h"
#include "animaGaussianREMEstimator.h"
#include <itkGaussianMembershipFunction.h>
#include <map>

namespace anima
{

template <typename TInputImage, typename TMaskImage>
class ClassificationStrategy: public itk::ProcessObject
{
public:

    typedef ClassificationStrategy  Self;
    typedef itk::ProcessObject Superclass;
    typedef itk::SmartPointer <Self> Pointer;
    typedef itk::SmartPointer <const Self> ConstPointer;

    itkNewMacro(Self);

    itkTypeMacro(ClassificationStrategy, itk::ProcessObject);

    typedef TInputImage InputImageType;

    typedef TMaskImage MaskImageType;

    typedef GaussianREMEstimator<InputImageType,MaskImageType> GaussianREMEstimatorType;
    typedef typename GaussianREMEstimatorType::Pointer  GaussianREMEstimatorPointerType;

    typedef itk::VariableLengthVector<double> MeasurementVectorType;
    typedef itk::Statistics::GaussianMembershipFunction< MeasurementVectorType > GaussianFunctionType;

    void Update() ITK_OVERRIDE;

    void SetEstimator( GaussianREMEstimatorPointerType theValue ){m_Estimator=theValue;}


    void SetInitializer( RandomInitializer::Pointer theValue ){ m_RandomInitializer = theValue;}


    RandomInitializer* getInitializer(){ return m_RandomInitializer;}

    bool GetSolutionMap(std::map< double,std::vector<GaussianFunctionType::Pointer> > &solution, std::map< double, std::vector<double> > &solutionAlpha, int step=-1);

    void SetStrategy(  std::vector< unsigned int >& ems, std::vector<unsigned int> &iters );

    itkSetMacro(EM_Mode, bool);
    itkGetMacro(EM_Mode, bool);

    void SetNumberOfIterations(std::vector<unsigned int> NumberOfIterations){m_NumberOfIterations=NumberOfIterations;}
    std::vector<unsigned int> GetNumberOfIterations() const {return m_NumberOfIterations;}

    void SetNumberOfEstimators(std::vector<unsigned int> NumberOfEstimators){m_NumberOfEstimators=NumberOfEstimators;}
    std::vector<unsigned int> GetNumberOfEstimators() const {return m_NumberOfEstimators;}


protected:

    ClassificationStrategy(const Self&); //purposely not implemented
    void operator=(const Self&); //purposely not implemented

    ClassificationStrategy()
    {
        m_NumberOfIterations.resize(1,100);
        m_NumberOfEstimators.resize(1,1);
        m_EM_Mode=true;
    }

    virtual ~ClassificationStrategy(){}


    bool sameModel( std::vector<GaussianFunctionType::Pointer> &mod1,std::vector<GaussianFunctionType::Pointer> &mod2);

    GaussianREMEstimatorPointerType m_Estimator;

    RandomInitializer::Pointer m_RandomInitializer;

    std::vector< std::map<double, std::vector<GaussianFunctionType::Pointer> > > m_ListGaussianModels;
    std::vector< std::map<double, std::vector<double> > > m_ListAlphas;

    std::vector<unsigned int> m_NumberOfIterations;

    std::vector<unsigned int> m_NumberOfEstimators;

    bool m_EM_Mode;

};

}


#include "animaClassificationStrategy.hxx"