nn_mlp_tool.h

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//
// Multi-layered perceptron tool class
//


#ifndef NN_MLP_TOOL_H
#define NN_MLP_TOOL_H

#include <boost/numeric/ublas/matrix.hpp>
#include <boost/numeric/ublas/vector.hpp>
#include <boost/shared_ptr.hpp>
#include <cmath>
#include <stdarg.h>
#include "object.h"
#include "mimasexception.h"

namespace mimas {


class nn_mlp_tool : public object
{
   public:
      typedef boost::numeric::ublas::matrix< double > Matrix;
      typedef boost::numeric::ublas::vector< double > Vector;
  private:
    typedef double (nn_mlp_tool::*ptrToFuncType)(double); 
      boost::shared_array< ptrToFuncType > ptrToTransferFunc;
    boost::shared_array< ptrToFuncType > ptrToTransferFuncDeriv;
      boost::shared_array< Matrix > weight; 
    boost::shared_array< Vector > bias; 
    boost::shared_array< Vector > y; 
    boost::shared_array< Vector > net; 
    boost::shared_array< Vector > delta; 
    boost::shared_array< Matrix > prevWeightChange; 
    boost::shared_array< Vector > prevBiasChange; 
      boost::shared_array< int > numnodes; 
    bool network_initialised; 
    bool debugtrain; 
    int numlayers; 
    //double learningRate, momentum; ///< learning rate and momentum
    int iterations; 
    void init(void); 
    double deltaRule( Matrix& pat, int p) throw (mimasexception); // perform delta rule on row p of pattern matrix pat

  public:
    nn_mlp_tool(void); 
    ~nn_mlp_tool(void); 
    void init(int nodes, ...) throw (mimasexception); 
    void clear(void); 
    void showConfig(void); 
      Matrix feedForward( Matrix& pat) throw (mimasexception); 

    // io functions
    void save (const char *fn) throw (mimasexception); 
    void load (const char *fn) throw (mimasexception); 


    // accessor functions
    void setIterations(int i) throw (mimasexception); 
    int getIterations(void); 
    
    // training methods
      Matrix trainOnline( Matrix& pat, double learningRate=0.3, double momentum=0.05, double weightDecay=0.0) throw (mimasexception); 
      Matrix trainBatch(Matrix& pat, double learningRate=0.3, double momentum=0.05, double weightDecay=0.0) throw (mimasexception); 
    Matrix trainQprop(Matrix& pat, double learningRate=0.0005, double momentum=0.05, double maxFactor=2.0) throw (mimasexception); 
      Matrix trainRprop(Matrix& pat, double etapos=1.2, double etaneg=0.5) throw (mimasexception); 

    // set transfer function for a layers
    void setTransferFuncLayer(ptrToFuncType newfunc, int layer) throw (mimasexception); 
    void setTransferFuncDerivLayer(ptrToFuncType newfunc, int layer) throw (mimasexception); 
    
    // user selectable transfer functions and the derivatives of the functions
    virtual double transferFunc(double val); 
    virtual double transferFuncDeriv(double val); 
    double transferFuncTanh(double val); 
    double transferFuncDerivTanh(double val); 
    double transferFuncLinear(double val); 
    double transferFuncDerivLinear(double val); 

    // debugging options
    void setDebug(bool val); 
  
};

}
#endif

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