AltNeuralNetFunc.cxx

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// $Id: AltNeuralNetFunc.cxx,v 1.1 2003/10/22 18:18:01 costas Exp $
//
// AltNeuralNetFunc.cxx
//
//   -- Generic Interface to a Neural Network Function
//   -- This is adapted for AltReco from my Neural Network Foundation Classes
//      (NNFC) package that I use for some of my Neural Net analyses.
//      NNFC is not intended to be part of the minos offline, so I just adapted
//      this single file here.
//
// Costas Andreopoulos <C.V.Andreopoulos@rl.ac.uk>
// CCLRC, Rutherford Appleton Laboratory
// July 01, 2003

#ifndef __CINT__
#include "Api.h"
#endif

#include<sstream>

#include "AltNeuralNetFunc.h"

#include "LeakChecker/Lea.h"
#include "MessageService/MsgService.h"

ClassImp(AltNeuralNetFunc)

//_______________________________________________________________________________
CVSID("$Id: AltNeuralNetFunc.cxx,v 1.1 2003/10/22 18:18:01 costas Exp $");
//_______________________________________________________________________________
AltNeuralNetFunc::AltNeuralNetFunc() :
TNamed()
{
  MSG("AltNeuralNet",Msg::kDebug) 
                 << "Begin of AltNeuralNetFunc::AltNeuralNetFunc() ctor" << endl;
  LEA_CTOR;
}
//_______________________________________________________________________________
AltNeuralNetFunc::AltNeuralNetFunc(const char * name, const char * title) :
TNamed(name, title)
{
  MSG("AltNeuralNet",Msg::kDebug) 
     << "Begin of AltNeuralNetFunc::AltNeuralNetFunc("
                                 << "const char *, const char * ) ctor" << endl;

  fTitle = std::string(title);
      
  LEA_CTOR;
}
//_______________________________________________________________________________
AltNeuralNetFunc::~AltNeuralNetFunc()
{
  MSG("AltNeuralNet",Msg::kDebug) 
                << "Begin of AltNeuralNetFunc::~AltNeuralNetFunc() dtor" << endl;
                           
  LEA_DTOR;
}
//_______________________________________________________________________________
double AltNeuralNetFunc::run( 
                        double (*neural_net)(double *), AltNeuralNetI * pattern )
{
  float network_out = -1;

  const int kInputs = pattern->getNumberOfInputs();  
  float * inputs = new float[kInputs];  
  
  pattern->copyInputsToArray(inputs);

#ifndef __CINT__
  G__CallFunc func;
  switch(G__isinterpretedp2f( (void*)neural_net )) {
  
  //using interface method
  case G__COMPILEDINTERFACEMETHOD:
     func.SetFunc( (G__InterfaceMethod)neural_net );
     func.SetArg((long)inputs);
     network_out = func.ExecDouble( (void*)NULL );
     break;
  default:
     exit(1);   
  }  
#else
  network_out = neural_net(inputs);
#endif
  
  return network_out;
}
//_______________________________________________________________________________

---