25#ifndef ROOT_TMVA_GeneticPopulation
26#define ROOT_TMVA_GeneticPopulation
73 void Print( std::ostream & out,
Int_t utilIndex = -1 );
#define ClassDef(name, id)
1-D histogram with a float per channel (see TH1 documentation)}
Cut optimisation interface class for genetic algorithm.
Population definition for genetic algorithm.
void Mutate(Double_t probability=20, Int_t startIndex=0, Bool_t near=kFALSE, Double_t spread=0.1, Bool_t mirror=kFALSE)
Mutates the individuals in the genePool.
Int_t GetPopulationSize() const
virtual ~GeneticPopulation()
destructor
Int_t fPopulationSizeLimit
std::vector< TMVA::GeneticGenes > & GetGenePool()
const std::vector< TMVA::GeneticGenes > & GetGenePool() const
std::vector< TMVA::GeneticRange * > fRanges
TRandom3 * fRandomGenerator
void Sort()
sort the genepool according to the fitness of the individuals
void MakeCopies(int number)
Produces offspring which is are copies of their parents.
void TrimPopulation()
trim the population to the predefined size
GeneticGenes * GetGenes(Int_t index)
gives back the "Genes" of the population with the given index.
GeneticPopulation(const std::vector< TMVA::Interval * > &ranges, Int_t size, UInt_t seed=0)
Constructor.
std::vector< TMVA::GeneticRange * > & GetRanges()
void Print(Int_t untilIndex=-1)
make a little printout of the individuals up to index "untilIndex" this means, .
const std::vector< TMVA::GeneticRange * > & GetRanges() const
void MakeChildren()
Creates children out of members of the current generation.
void GiveHint(std::vector< Double_t > &hint, Double_t fitness=0)
add an individual (a set of variables) to the population if there is a set of variables which is know...
std::vector< TMVA::GeneticGenes > fGenePool
void AddPopulation(GeneticPopulation *strangers)
add another population (strangers) to the one of this GeneticPopulation
void SetRandomSeed(UInt_t seed=0)
the random seed of the random generator
GeneticGenes MakeSex(GeneticGenes male, GeneticGenes female)
this function takes two individuals and produces offspring by mixing (recombining) their coefficients...
TH1F * VariableDistribution(Int_t varNumber, Int_t bins, Int_t min, Int_t max)
give back a histogram with the distribution of the coefficients.
Double_t GetFitness() const
ostringstream derivative to redirect and format output
Random number generator class based on M.
create variable transformations