nn_assoc.h

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#include <boost/numeric/ublas/matrix.hpp>
#include <boost/numeric/ublas/vector.hpp>
#include "object.h"
#include "values.h"


#ifndef NN_ASSOC_H
#define NN_ASSOC_H

namespace mimas {
  class nn_assoc: public object
{
  public:
      typedef boost::numeric::ublas::matrix< double > Matrix;
      typedef boost::numeric::ublas::vector< double > Vector;

  private:
    Matrix weights;
    

   
  public:
    nn_assoc(void); 
    void train(Matrix& input_data, Matrix& target_data); 
      Vector recall(Vector& x); 
    void useWeights(Matrix& weight_matrix); 
    Matrix getWeights(void); 
};


nn_assoc::nn_assoc()
{
}

void nn_assoc::train(Matrix& x, Matrix& y)
{
  Matrix s, t, curweights;

   MMERROR( x.size1() == y.size1(), mimasexception, ,
            "nn_assoc::train - input/output matrix rows not equal" );

  // initialise weight matrix
  weights.resize( x.size2(), y.size2() );
  curweights.resize( x.size2(), y.size2() );

   // The following line was breaking charRecog (uninitialised matrix!).
   // weights = weights + prod( trans( x ), y );
   weights = prod( trans( x ), y );

  //weights.save("hebb.weights");
}

nn_assoc::Vector nn_assoc::recall(Vector& x)
{
   MMERROR( x.size() == weights.size1(),
            mimasexception, ,
            "nn_assoc::recall - input vector has incorrect dimensions" );

  Vector y( prod( x, weights ) );

  double ymax=-1.0;
  double ymin=MAXDOUBLE;

  for (int i=0; i<(signed)y.size(); i++)
  {
    if ((ymax) < y(i)) ymax=y(i);
    if ((ymin) > y(i)) ymin=y(i);
  }

  return y;
  
  
}


// use the weights given by weight_matrix;
void nn_assoc::useWeights(Matrix& weight_matrix)
{
   //if (weights.initialised()) weights.clear();
  weights=weight_matrix;
}


// return the weights that are stored 
nn_assoc::Matrix nn_assoc::getWeights(void)
{
  return weights;
}
}
#endif

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