/***********************************************************************
This file is part of KEEL-software, the Data Mining tool for regression,
classification, clustering, pattern mining and so on.
Copyright (C) 2004-2010
F. Herrera (herrera@decsai.ugr.es)
L. S�nchez (luciano@uniovi.es)
J. Alcal�-Fdez (jalcala@decsai.ugr.es)
S. Garc�a (sglopez@ujaen.es)
A. Fern�ndez (alberto.fernandez@ujaen.es)
J. Luengo (julianlm@decsai.ugr.es)
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see http://www.gnu.org/licenses/
**********************************************************************/
/**
* <p>
* @author Written by Luciano S�nchez (Universisty of Oviedo) 25/01/2004
* @author Modified by M.R. Su�rez (University of Oviedo) 18/12/2008
* @author Modified by Enrique A. de la Cal (University of Oviedo) 21/12/2008
* @version 1.0
* @since JDK1.5
* </p>
*/
package keel.Algorithms.Fuzzy_Rule_Learning.Genetic.Shared.Model;
import org.core.*;
import keel.Algorithms.Fuzzy_Rule_Learning.Genetic.Shared.Node.*;
import keel.Algorithms.Fuzzy_Rule_Learning.Genetic.Shared.Individual.*;
import keel.Algorithms.Fuzzy_Rule_Learning.Shared.Fuzzy.*;
import keel.Algorithms.Fuzzy_Rule_Learning.Genetic.Shared.OptimLocal.*;
import keel.Algorithms.Fuzzy_Rule_Learning.Genetic.Shared.Algorithms.*;
import keel.Algorithms.Fuzzy_Rule_Learning.Genetic.Shared.Genotypes.*;
import keel.Algorithms.Shared.Exceptions.*;
import keel.Algorithms.Shared.Parsing.*;
public class RegSymFuzzyGP extends GeneticIndividualForSymbRegr {
static double KMIN, KMAX;
static int constType;
/**
* <p>
* Constructor. Generate a new fuzzy system of symbolic regression
* </p>
* @param kmin Minimum k
* @param kmax Maximum k
* @param ne Number of inputs
* @param typectes Type of constant
* @param NCTES Number of constant
* @param MAXH Maximum height
* @param tf Type of fitness
* @param r Random
*/
public RegSymFuzzyGP(double kmin, double kmax, int ne, int typectes, int NCTES, int MAXH, int tf, Randomize r) {
super(tf);
KMIN=kmin; KMAX=kmax;
GenotypeFuzzyGPRegSym gf=new GenotypeFuzzyGPRegSym(kmin,kmax,ne,typectes,NCTES,MAXH,r);
g=gf;
//The object of class Model shares the tree defined in the genotype
constType=typectes;
m=new FuzzyGPRegSymModel((NodeExprHold)(gf.getRootNode()),kmin,kmax,1,typectes);
}
/**
* <p>
* Constructor. Generate a new fuzzy system of symbolic regession from another one
* </p>
* @param p The fuzzy system of symbolic regession
*/
public RegSymFuzzyGP(RegSymFuzzyGP p) {
super(p.fitnessType);
g=p.g.clone();
GenotypeFuzzyGPRegSym gf=(GenotypeFuzzyGPRegSym)(g);
m=new FuzzyGPRegSymModel((NodeExprHold)(gf.getRootNode()),KMIN,KMAX,1,constType);
}
/**
* <p>
* This method clone a fuzzy system of symbolic regession
* </p>
*/
public GeneticIndividual clone() {
return new RegSymFuzzyGP(this);
}
/**
* <p>
* This method assing the properties of a fuzzy system of symbolic regession to another one
* </p>
* @param p The fuzzy system of symbolic regession
*/
public void set(RegSymFuzzyGP p) {
g=p.g.clone();
GenotypeFuzzyGPRegSym gf=(GenotypeFuzzyGPRegSym)(g);
m=new FuzzyGPRegSymModel((NodeExprHold)(gf.getRootNode()),KMIN,KMAX,1,constType);
}
/**
* <p>
* This method generate a genetic individual from a fuzzy system of symbolic regession
* </p>
* @return The genetic individua
*/
public GeneticIndividual FuzzyGPRegresionSimbolicaClona() {
return new RegSymFuzzyGP(this);
}
/**
* <p>
* This method obtain the parameters of a genetic individual from the genotype
* </p>
*/
public void parametersFromGenotype() {
GenotypeFuzzyGPRegSym gf=(GenotypeFuzzyGPRegSym)(g);
m=new FuzzyGPRegSymModel((NodeExprHold)(gf.getRootNode()),KMAX,KMIN,1,constType);
}
/**
* <p>
* This method generate a random genotype and obtain the parameters from another one
* </p>
*/
public void Random() {
g.Random();
parametersFromGenotype();
}
/**
* <p>
* This method implement the mutation operation
* </p>
* @param alpha Index mutation
* @param IDMUTA Type of mutation
* @throws invalidMutation message if error
*/
public void mutation(double alpha,int IDMUTA) throws invalidMutation {
g.mutation(alpha, IDMUTA);
parametersFromGenotype();
}
/**
* <p>
* This method implement the cross operation.
* The cross generates two objects of class 'individuogen'
* </p>
* @param p2 Genetic individual
* @param p3 Genetic individual
* @param p4 Genetic individual
* @param IDCRUCE Type of cross
* @throws invalidCrossover Message if error
*/
public void crossover(GeneticIndividual p2, GeneticIndividual p3, GeneticIndividual p4, int IDCRUCE) throws invalidCrossover {
RegSymFuzzyGP f2=(RegSymFuzzyGP)(p2);
RegSymFuzzyGP f3=(RegSymFuzzyGP)(p3);
RegSymFuzzyGP f4=(RegSymFuzzyGP)(p4);
g.crossover(f2.g,f3.g,f4.g, IDCRUCE);
//The crossover generates two objects of class 'individuogen'
f3.parametersFromGenotype();
f4.parametersFromGenotype();
}
/**
* <p>
* This method is for debug
* </p>
*/
public void debug() { g.debug(); } // Overload debug from IndividuoGenModel
/**
* <p>
* This method modifies constant part for this individual with parameter passed
* </p>
* @param ctes The constant
*/
public void setConsts(double[] ctes) {
// It modifies constant part for this individual with parameter "ctes"
GenotypeFuzzyGPRegSym gf=(GenotypeFuzzyGPRegSym)g;
gf.setChain(ctes);
}
/**
* <p>
* This methods return a copy of the constant part
* </p>
* @return The constant part
*/
public double[] getConsts() {
//It returns a copy of constant part
GenotypeFuzzyGPRegSym gf=(GenotypeFuzzyGPRegSym)g;
return gf.getChainValue();
}
/**
* This method returns information about used constant
* @return A vector marked in the position where constants were used
*/
public boolean[] getUsedConsts() {
//It marks constants in string that appears in genotype
GenotypeFuzzyGPRegSym gf=(GenotypeFuzzyGPRegSym)g;
return gf.getUsedConstants();
}
/**
* <p>
* This method calculates a local optimization
* </p>
* @param MAXITER Maximum iterations
* @param idoptimization Type of optimization
* @throws invalidOptim Message if error
*/
public void localOptimization(int MAXITER, int idoptimization) throws invalidOptim {
if (idoptimization!=OperatorIdent.AMEBA)
throw new invalidOptim("Optimizacion local no implementada en RegSymFuzzyGP");
double consts[] = getConsts();
int total=0;
boolean usedctes[] = getUsedConsts();
for (int i=0;i<usedctes.length;i++)
if (usedctes[i]) total++;
// There's nothing to optimize
if (total==0) return;
FUNGPRS f = new FUNGPRS(this,usedctes,consts);
Ameba ameba = new Ameba();
ameba.itera(f, consts, MAXITER*total);
setConsts(consts);
}
}