// @(#)root/tmva $Id: GeneticAlgorithm.h 20882 2007-11-19 11:31:26Z rdm $ // 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 - 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 #include #include #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& 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 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& fRanges; // parameter ranges mutable MsgLogger fLogger; // message logger ClassDef(GeneticAlgorithm, 0) // Genetic algorithm controller }; } // namespace TMVA #endif