// @(#)root/tmva $Id: GeneticAlgorithm.h,v 1.2 2007/06/20 09:41:24 brun Exp $    
// Author: Peter Speckmayer

/**********************************************************************************
 * Project: TMVA - a Root-integrated toolkit for multivariate data analysis       *
 * Package: TMVA                                                                  *
 * Class  : GeneticAlgorithm                                                      *
 * Web    : http://tmva.sourceforge.net                                           *
 *                                                                                *
 * Description:                                                                   *
 *      Base definition for genetic algorithm                                     *
 *                                                                                *
 * Authors (alphabetical):                                                        *
 *      Peter Speckmayer <speckmay@mail.cern.ch>  - CERN, Switzerland             *
 *                                                                                *
 * Copyright (c) 2005:                                                            *
 *      CERN, Switzerland                                                         * 
 *      MPI-K Heidelberg, Germany                                                 * 
 *                                                                                *
 * Redistribution and use in source and binary forms, with or without             *
 * modification, are permitted according to the terms listed in LICENSE           *
 * (http://tmva.sourceforge.net/LICENSE)                                          *
 **********************************************************************************/

#ifndef ROOT_TMVA_GeneticAlgorithm
#define ROOT_TMVA_GeneticAlgorithm

//////////////////////////////////////////////////////////////////////////
//                                                                      //
// GeneticAlgorithm                                                     //
//                                                                      //
// Base definition for genetic algorithm                                //
//                                                                      //
//////////////////////////////////////////////////////////////////////////

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

#include <stdio.h>
#include <iostream>

#ifndef ROOT_TMVA_IFitterTarget
#include "TMVA/IFitterTarget.h"
#endif
#ifndef ROOT_TMVA_GeneticPopulation
#include "TMVA/GeneticPopulation.h"
#endif
#ifndef ROOT_TMVA_Types
#include "TMVA/Types.h"
#endif
#ifndef ROOT_TMVA_MsgLogger
#include "TMVA/MsgLogger.h"
#endif

namespace TMVA {
     
   class IFitterTarget;
   class Interval;

   class GeneticAlgorithm {

   public:
    
      GeneticAlgorithm( IFitterTarget& target, Int_t populationSize, 
                        const std::vector<TMVA::Interval*>& ranges, UInt_t seed = 0 );
      virtual ~GeneticAlgorithm() {}

      void Init();

      virtual Bool_t   HasConverged(Int_t steps = 10, Double_t ratio = 0.1);
      virtual Double_t SpreadControl(Int_t steps, Int_t ofSteps,
                                     Double_t factor);
      virtual Double_t NewFitness(Double_t oldValue, Double_t newValue);
      virtual Double_t CalculateFitness();
      Double_t         DoRenewFitness();
      virtual Double_t RenewFitness(std::vector < Double_t > factors,
                                    std::vector < Double_t > results);
      virtual void Evolution();
      void Finalize();
      
      GeneticPopulation& GetGeneticPopulation() { return fPopulation; } 
      Double_t GetSpread() const { return fSpread; }

      void SetSpread(Double_t s) { fSpread = s; }

      Int_t    fConvCounter;           // converging? ... keeps track of the number of improvements

   protected:
   
      IFitterTarget&    fFitterTarget; // the fitter target
      GeneticPopulation fPopulation;   // contains and controls the "individual"
      
      Double_t fConvValue;             // keeps track of the quantity of improvement

      // spread-control (stepsize)
      // successList keeps track of the improvements to be able
      
      std::deque <Int_t> fSuccessList; // to adjust the stepSize      
      Double_t fLastResult;            // remembers the last obtained result (for internal use)

      Double_t fSpread;                // regulates the spread of the value change at mutation (sigma)
      Bool_t   fMirror;                // new values for mutation are mirror-mapped if outside of constraints
      Bool_t   fSexual;                // allow sexual recombination of individual
      Bool_t   fFirstTime;             // if true its the first time, so no evolution yet
      Int_t    fPopulationSize;        // the size of the population

      const std::vector<TMVA::Interval*>& fRanges; // parameter ranges

      mutable MsgLogger            fLogger;        // message logger
      
      ClassDef(GeneticAlgorithm, 0)  // Base definition for genetic algorithm
   };
   
} // namespace TMVA

#endif