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#ifndef SOMModel_h
#define SOMModel_h
#include "DimensionalityReductionModel.h"
#include "otbSOMMap.h"
#include "otbSOM.h"
#include "itkEuclideanDistanceMetric.h" // the distance function
#include "otbCzihoSOMLearningBehaviorFunctor.h"
#include "otbCzihoSOMNeighborhoodBehaviorFunctor.h"
namespace otb
{
template <class TInputValue, unsigned int MapDimension>
class ITK_EXPORT SOMModel: public DimensionalityReductionModel<TInputValue,TInputValue>
{
public:
typedef SOMModel Self;
typedef DimensionalityReductionModel<TInputValue,TInputValue> Superclass;
typedef itk::SmartPointer<Self> Pointer;
typedef itk::SmartPointer<const Self> ConstPointer;
typedef typename Superclass::InputValueType InputValueType;
typedef typename Superclass::InputSampleType InputSampleType;
typedef typename Superclass::InputListSampleType InputListSampleType;
typedef typename InputListSampleType::Pointer ListSamplePointerType;
typedef typename Superclass::TargetValueType TargetValueType;
typedef typename Superclass::TargetSampleType TargetSampleType;
typedef typename Superclass::TargetListSampleType TargetListSampleType;
typedef SOMMap<itk::VariableLengthVector<TInputValue>,itk::Statistics::EuclideanDistanceMetric<itk::VariableLengthVector<TInputValue>>, MapDimension> MapType;
typedef typename MapType::SizeType SizeType;
typedef typename MapType::SpacingType SpacingType;
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typedef otb::SOM<InputListSampleType, MapType> EstimatorType;
typedef Functor::CzihoSOMLearningBehaviorFunctor SOMLearningBehaviorFunctorType;
typedef Functor::CzihoSOMNeighborhoodBehaviorFunctor SOMNeighborhoodBehaviorFunctorType;
itkNewMacro(Self);
itkTypeMacro(SOMModel, DimensionalityReductionModel);
/** Accessors */
itkSetMacro(NumberOfIterations, unsigned int);
itkGetMacro(NumberOfIterations, unsigned int);
itkSetMacro(BetaInit, double);
itkGetMacro(BetaInit, double);
itkSetMacro(BetaEnd, double);
itkGetMacro(BetaEnd, double);
itkSetMacro(MinWeight, InputValueType);
itkGetMacro(MinWeight, InputValueType);
itkSetMacro(MaxWeight, InputValueType);
itkGetMacro(MaxWeight, InputValueType);
itkSetMacro(MapSize, SizeType);
itkGetMacro(MapSize, SizeType);
itkSetMacro(NeighborhoodSizeInit, SizeType);
itkGetMacro(NeighborhoodSizeInit, SizeType);
itkSetMacro(RandomInit, bool);
itkGetMacro(RandomInit, bool);
itkSetMacro(Seed, unsigned int);
itkGetMacro(Seed, unsigned int);
itkGetObjectMacro(ListSample, InputListSampleType);
itkSetObjectMacro(ListSample, InputListSampleType);
bool CanReadFile(const std::string & filename);
bool CanWriteFile(const std::string & filename);
void Save(const std::string & filename, const std::string & name="") ITK_OVERRIDE;
void Load(const std::string & filename, const std::string & name="") ITK_OVERRIDE;
void Train() ITK_OVERRIDE;
//void Dimensionality_reduction() {}; // Dimensionality reduction is done by DoPredict
unsigned int GetDimension() { return MapType::ImageDimension;};
protected:
SOMModel();
~SOMModel() ITK_OVERRIDE;
virtual TargetSampleType DoPredict(const InputSampleType& input) const ITK_OVERRIDE;
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private:
typename MapType::Pointer m_SOMMap;
/** Map Parameters used for training */
SizeType m_MapSize;
/** Number of iterations */
unsigned int m_NumberOfIterations;
/** Initial learning coefficient */
double m_BetaInit;
/** Final learning coefficient */
double m_BetaEnd;
/** Initial neighborhood size */
SizeType m_NeighborhoodSizeInit;
/** Minimum initial neuron weights */
InputValueType m_MinWeight;
/** Maximum initial neuron weights */
InputValueType m_MaxWeight;
/** Random initialization bool */
bool m_RandomInit;
/** Seed for random initialization */
unsigned int m_Seed;
/** The input list sample */
ListSamplePointerType m_ListSample;
/** Behavior of the Learning weightening (link to the beta coefficient) */
SOMLearningBehaviorFunctorType m_BetaFunctor;
/** Behavior of the Neighborhood extent */
SOMNeighborhoodBehaviorFunctorType m_NeighborhoodSizeFunctor;
};
} // end namespace otb
#ifndef OTB_MANUAL_INSTANTIATION
#include "SOMModel.txx"
#endif
#endif