ruleset.java

package keel.Algorithms.Fuzzy_Rule_Learning.Genetic.ClassifierSLAVE2;

import java.io.*;

import org.core.Files;


public class ruleset {
	
	/**	
	 * <p>
	 * It contains the methods for handling the set of learned rules
	 * </p>
	 */

	int reservado;
	int n_rule;
	genetcode[][] rule;
	vectorvar[] domain;
	double[] peso;
	
	
	
	ruleset (){
		reservado = 10;
		n_rule = 0;
		rule = new genetcode[reservado][];
		peso = new double[reservado];
		domain = null;	
	}
	

	ruleset (vectorvar x){
		reservado = 10;
		n_rule = 0;
		rule = new genetcode[reservado][];
		peso = new double[reservado];
		domain = new vectorvar[1];
		domain[0] = x;
	}


	ruleset (ruleset x){
		reservado = x.reservado;
		n_rule = x.n_rule;
		rule = new genetcode[reservado][];
		peso = new double[reservado];
		for (int i=0; i<n_rule; i++){
			rule[i] = new genetcode[1];
			rule[i][0] = x.rule[i][0];
			peso[i] = x.peso[i];
		}
	}
	
	
	public void AddDomain (vectorvar x){
		domain = new vectorvar[1];
		domain[0] = x;
	}
	

	void Realloc (){
		genetcode[][] aux = new genetcode[2*reservado+1][];
		double[] p = new double[2*reservado+1];

		for (int i=0; i<n_rule; i++){
			aux[i] = rule[i];
			rule[i] = null;
			p[i] = peso[i];
		}
		rule = aux;
		peso = p;
		reservado = 2*reservado+1;	
	}
	
	

	/**
	 * <p>
	 * Add a new rule "x" to the last position of the set of learned rules
	 * with its weight associated "weight".
	 * </p>
	 * @param x genetcode The genetic information of the rule which is going to be added
	 * @param weight double The weight of the rule
	 */
	
	public void Add (genetcode x, double weight) {
		if (reservado == n_rule){
			Realloc();
		}
		rule[n_rule] = new genetcode[1];
		rule[n_rule][0] = x;
		peso[n_rule] = weight;
		n_rule++;
	}

	
	/**
	 * <p>
	 * Associates the weight "weight" to the rule "rule"
	 * </p>
	 * @param rule int The selected rule
	 * @param weight double The weight of the rule
	 */
	
	public void Add_Weight (int rule, double weight) {
	   peso[rule] = weight;
	}
	
	
	public double Get_Weight (int rule){
		return peso[rule];
	}

	
	
	/**
	 * <p>
	 * Removes the last rule of the set of learned rules.
	 * </p>
	 */
	
	public void Remove(){
		n_rule--;
	}


	

	/**
	 * <p>
	 * Returns the number of rules of the ruleset
	 * </p>
	 * @return int The number of rules
	 */
	
	public int N_rule(){
		return n_rule;
	}
	
	
	
	
	/**
	 * <p>
	 * Returns the average number of variables per rule.
	 * </p>
	 * @return double The average number of variables per rule
	 */
	
	public double Variables_per_rule (){
		int b, r;
		int[] nb;
		int[] nr;
		char[][] mb;
		double cont = 0;
		double[][] mr;
		int donde, z, n_casos;
		char[] s;
		
		for (int i=0; i<n_rule; i++){
			r = rule[i][0].GetReal1 ();
			nr = rule[i][0].GetReal2 ();
			mr = rule[i][0].GetReal3 ();
			
			b = rule[i][0].GetBinary1 ();
			nb = rule[i][0].GetBinary2 ();
			mb = rule[i][0].GetBinary3 ();
			donde = 0;
			s = new char[nb[0]];
			for (int j=0; j<nb[0]; j++)
				s[j] = mb[0][j];

			for (int j=0; j<domain[0].N_Antecedent(); j++){
				if (domain[0].IsAntecedent (j)) {
					n_casos = domain[0].SizeDomain (j);
					for (z=0; z<n_casos && s[donde+z]=='1'; z++);

					if (z!=n_casos && mr[0][j]>=mr[0][nr[0]-1])
						cont++;
					donde += n_casos;
				}
			}

		}

		return cont/n_rule;
	}
	
	

	
	/**
	 * <p>
	 * Returns the rate of variables used in rules related to all variables involved.
	 * </p>
	 * @return double The rate of variables used in rules related to all variables involved
	 */
	
	public double Variables_Used (){
		int b;
		int[] nb;
		char[][] mb;
		double cont = 0;
		int r;
		int[] nr;
		double[][] mr;

		int[] used= new int[domain[0].N_Antecedent()];

		for (int j=0; j<domain[0].N_Antecedent(); j++)
			used[j] = 0;

		int donde, z, n_casos;
		char[] s;
		
		for (int i=0; i<n_rule; i++){
			r = rule[i][0].GetReal1 ();
			nr = rule[i][0].GetReal2 ();
			mr = rule[i][0].GetReal3 ();
			
			b = rule[i][0].GetBinary1 ();
			nb = rule[i][0].GetBinary2 ();
			mb = rule[i][0].GetBinary3 ();
			donde = 0;
			s = new char[nb[0]];
			for (int j=0; j<nb[0]; j++)
				s[j] = mb[0][j];

			for (int j=0; j<domain[0].N_Antecedent(); j++){
				if (domain[0].IsAntecedent (j)) {
					n_casos = domain[0].SizeDomain (j);
					for(z=0; z<n_casos && s[donde+z]=='1';z++);

					if (z != n_casos && mr[0][j]>=mr[0][nr[0]-1])
						used[j]++;	
					donde += n_casos;
				}
			}

		}

		for (int j=0; j<domain[0].N_Antecedent(); j++)	
			if (used[j] > 0)
				cont = cont+1;

		return cont;
	}




	/**
	 * <p>
	 * Returns in "frec" the times that each variable appears in the rule base.
	 * </p>
	 * @param frec int[] Vector with the information required
	 * @return int[] Vector with the times that each variable appears in the rule base
	 */

	public double Frecuence_each_Variables (int[] frec){
		int b;
		int[] nb;
		char[][] mb;
		double cont = 0;
		int r;
		int[] nr;
		double[][] mr;

		for (int j=0; j<domain[0].N_Antecedent(); j++)
			frec[j] = 0;

		int donde, z, n_casos;
		char[] s;
		for (int i=0; i<n_rule; i++){
			r = rule[i][0].GetReal1 ();
			nr = rule[i][0].GetReal2 ();
			mr = rule[i][0].GetReal3 ();
			
			b = rule[i][0].GetBinary1 ();
			nb = rule[i][0].GetBinary2 ();
			mb = rule[i][0].GetBinary3 ();
			donde = 0;
			s = new char[nb[0]];
			for (int j=0; j<nb[0]; j++)
				s[j] = mb[0][j];

			for (int j=0; j<domain[0].N_Antecedent(); j++){
				if (domain[0].IsAntecedent (j)) {
					n_casos = domain[0].SizeDomain (j);
					for(z=0; z<n_casos && s[donde+z]=='1';z++);

					if (z != n_casos && mr[0][j]>=mr[0][nr[0]-1])
						frec[j]++;
					donde += n_casos;
				}
			}

	 }

		for (int j=0; j<domain[0].N_Antecedent(); j++)
			if (frec[j] > 0)
				cont = cont+1;



		return cont/(1.0*domain[0].N_Antecedent());
	}

	
	
	/**
	 * <p>
	 * Returns the number of conditions per rule base.
	 * </p>
	 * @return int The number of conditions per rule base.
	 */

	public int Conditions_per_RB (){
		int r, b;
		int[] nr;
		int[] nb;
		char[][] mb;
		double[][] mr;

		r = rule[0][0].GetReal1 ();
		nr = rule[0][0].GetReal2 ();
		mr = rule[0][0].GetReal3 ();
		
		int donde, z, n_casos, medida=0;
		char[] s;
		
		for (int i=0; i<n_rule; i++){
			r = rule[i][0].GetReal1 ();
			nr = rule[i][0].GetReal2 ();
			mr = rule[i][0].GetReal3 ();
			
			b = rule[i][0].GetBinary1 ();
			nb = rule[i][0].GetBinary2 ();
			mb = rule[i][0].GetBinary3 ();
			donde = 0;
			s = new char[nb[0]];
			for (int j=0; j<nb[0]; j++)
				s[j] = mb[0][j];

			for (int j=0; j<domain[0].N_Antecedent(); j++){
				if (domain[0].IsAntecedent (j)){
					n_casos = domain[0].SizeDomain (j);
					for(z=0; z<n_casos && s[donde+z]=='1';z++);

					if (z != n_casos && mr[0][j]>=mr[0][nr[0]-1])
						medida++;
					donde += n_casos;
				}
			}

		}

		return medida;

	}
	
	


	/**
	 * <p>
	 * Returns the class of the rule that better adapts to the example "v", the adaptation
	 * degree "grado" and the ordinal of the fired rule "regla_disparada".
	 * </p>
	 * @param v vectordouble The selected example
	 * @param grado Double_t The adaptation degree
	 * @param regla_disparada Int_t The ordinal of the fired rule
	 * @return int The class of the rule that better adapts to the example
	 */

	public int InferenceC (vectordouble v, Double_t grado, Int_t regla_disparada){
		int b, n;
		int[] nb;
		int[] nn;
		int[][] nnn;
		char[][] mb;
		double max = 0, aux;
		int re = -1;
		String regla;
		int r;
		int[] nr;
		double[][] mr;
		
		for (int i=0; i<n_rule; i++){
			b = rule[i][0].GetBinary1 ();
			nb = rule[i][0].GetBinary2 ();
			mb = rule[i][0].GetBinary3 ();
			
			char[] s = new char[nb[0]];
			
			for (int j=0; j<nb[0]; j++)
				s[j] = mb[0][j];

			regla = new String (s);
			
			r = rule[i][0].GetReal1 ();
			nr = rule[i][0].GetReal2 ();
			mr = rule[i][0].GetReal3 ();
			
			aux = domain[0].Adaptation (v,regla, mr[0], mr[0][nr[0]-1]);

			if (aux > max){
				max = aux;
				re = i;
				grado.value = aux;
			}
			else{
				if (re!=-1 && aux>0 && aux==max && peso[i]>peso[re]) {
					max = aux;
					re = i;
					grado.value = aux;
				}
			}	
		}

		regla_disparada.value = re;

		if (re!=-1) {
			n = rule[re][0].GetInteger1 ();
			nn = rule[re][0].GetInteger2 ();
			nnn = rule[re][0].GetInteger3 ();
			return nnn[0][0];
		}
		else
			return -1;
	}
	
	

	
	

	
	
	public String SPrint (int i){
		String buffer = "";
		int b, n;
		int[] nb;
		int[] nn;
		int[][] nnn;
		char[][] mb;
		String regla;
		int n_ant;
		int r;
		int[] nr;
		double[][] mr;
		
		// extraer la componente binaria
		b = rule[i][0].GetBinary1 ();
		nb = rule[i][0].GetBinary2 ();
		mb = rule[i][0].GetBinary3 ();
		
		char[] s = new char[nb[0]];
		
		for (int j=0; j<nb[0]; j++)
			s[j]=mb[0][j];

		regla = new String (s);

		n = rule[i][0].GetInteger1 ();
		nn = rule[i][0].GetInteger2 ();
		nnn = rule[i][0].GetInteger3 ();
		
		r = rule[i][0].GetReal1 ();
		nr = rule[i][0].GetReal2 ();
		mr = rule[i][0].GetReal3 ();
		
		n_ant = domain[0].N_Antecedent ();
		
		int z = 0;
		int j = 0;
		int donde = 0;
		int n_casos = 0;
		char[] regla_aux;
		
		regla_aux = regla.toCharArray ();
		
		buffer += "IF\n";
		
		while (j<n_ant){	
			if (domain[0].IsActive (j) && domain[0].IsAntecedent (j)){	
				n_casos=domain[0].SizeDomain (j);
				for(z=0; z<n_casos && regla_aux[donde+z]=='1';z++);
				if (z != n_casos){
					buffer += "\t";
					buffer += domain[0].SPrintVar (j);
					buffer += " = {";
					for(int t=donde; t<donde+n_casos;t++){
						if (regla_aux[t]=='1'){
							buffer += " ";
							buffer += domain[0].SPrintDomain (j,t-donde);
						}
					}
					buffer += "}\n";
				}

			}
			donde += n_casos;
			j++;
		}

		//Conclusion de la regla
		buffer += "THEN ";
		buffer += domain[0].SPrintVar (domain[0].Consequent ());
		buffer += " IS ";
		buffer += domain[0].SPrintDomain (domain[0].Consequent (), nnn[0][0]);
		buffer += "   W ";
		buffer += peso[i];
		buffer += "\n";

		return buffer;

	}
	
	

	
	

	/**
	 * <p>
	 * Writes each rule of the rule base in file "fich".
	 * </p>
	 * @param fich OutputStream Output file
	 */
	
	public void SaveRuleInterpreted_append (OutputStream fich) throws IOException{
		String regla;
		byte[] buf;
		
		for (int i=0; i<n_rule; i++){
			regla = SPrint (i);
			regla = regla+"\n";
			buf = regla.getBytes();
			fich.write (buf);
		}

	}
	
	
	/**
	 * <p>
	 * Writes each rule of the rule base in file "fich".
	 * </p>
	 * @param fich String Name of the output file
	 */
	
	public void SaveRuleInterpreted_append (String fich) throws IOException{
		String regla;
		byte[] buf;
		
		
		for (int i=0; i<n_rule; i++){
			regla = SPrint (i);
			regla = regla+"\n";
			Files.addToFile (fich, regla);
		}

	}
	
	
	

	
}