AltNeuralNetI.h

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// $Id: AltNeuralNetI.h,v 1.3 2004/11/08 23:22:10 gmieg Exp $
//
// AltNeuralNetI.h
//
//   -- Neural Net Input abstract base class
//   -- 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 _ALT_NEURAL_NET_I_H_
#define _ALT_NEURAL_NET_I_H_

#include<string>
#include<vector>
#include<map>

#include <TNamed.h>

const int kSignal     = 1;
const int kBackground = 0;

class AltNeuralNetI: public TNamed
{
public:

  AltNeuralNetI();  
  AltNeuralNetI(const char * name, const char * title);  
  AltNeuralNetI(const AltNeuralNetI & cneti);  
 ~AltNeuralNetI();
  
  void   setInputVar(std::string varName, double varValue);  
  double getInputVar(std::string varName);
  double getTarget(void) const;
    
  void   normalizeInputs(std::map<std::string, double> norm_consts);
  bool   isWithinLimits(void);

  void   copyInputsToArray(float * inputs);    

  void   raiseSignalFlag(void);
  void   raiseBackgroundFlag(void);
  bool   isSignal(void) const;
  bool   isBackground(void) const;
  
  void   resetPattern(void);
  void   resetPatternValues(void);
  
  void   printI(const Option_t * opt);

  int    getNumberOfInputs(void) const;

  std::vector<std::string> getInputNames(void);
  
protected:

  void initPattern(const std::string * var_names, const int n_vars);

  std::string                    fTitle;
  double                         fTarget;
  std::map<std::string, double>  fSinglePattern;

private:
  
  ClassDef(AltNeuralNetI, 0)
};

#endif // _ALT_NEURAL_NET_I_H_

---