C:/Users/albertlr/projects/TarzaNN/TarzaNN/CTSOMFeaturePlane.h

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#ifndef CTSOMFeaturePlane_H_INCLUDED
#define CTSOMFeaturePlane_H_INCLUDED

#include  <qimage.h>

#include "nowarn.h"
#include "common.h"
#include <stdlib.h>

#include "OutputImage.h"
#include "LearningFeaturePlane.h"
#include "FilterBank.h"
#include "PlaneInputWindowSet.h"
#include "MatrixOfMatrix.h"

class CTSOMFeaturePlane : public LearningFeaturePlane {
        friend class GatingUnits;
        friend class FeaturePlaneFactory;
public:
    ~CTSOMFeaturePlane();
        void read(QDataStream* inStream, QProgressDialog* progress, int* index);

        void save(QDataStream* outStream, QProgressDialog* progress, int* index);
        bool isLearning();
        
    static void compete(vector<FeaturePlaneAbstract*> _featurePlanes, Layer* theLayer, int step);
    static void competeOld(vector<FeaturePlaneAbstract*> _featurePlanes, Layer* theLayer, int step);
    FeaturePlaneInput* addFilter(Filter* f, FeaturePlaneAbstract*fp, int type, int fpOutputIndex, bool wta);
        void incWinCount(){
                winCount++;
        }
        int getWinCount(){
                return winCount;
        }

protected:
        
        CTSOMFeaturePlane( Network* net, int l, QString* name, int w, int h, int angles, int speeds, int alpha, int speed, bool isWTA, bool visible, Neuron* neuron, NotifyStrategyAbstract* notify, bool learning);
        void step();
        
        float nonlinearity(Matrix* totalActivation, OutputImage* workOutput);
    void computeGatingUnits(); 

private:
        static const char* FilterFileName;

        vector<RandomFilter*> theInputFilters;
        void saveFilters(int step, int index);

    int winCount;

        void learn();
        void learn(uint32_t x, uint32_t y);
        void updateWeights(RandomFilter* theFilter, Matrix* input, float alpha, uint32_t x, uint32_t y);

    float alpha();
        static float surround(int step);
};
#endif //CTSOMFeaturePlane_H_INCLUDED