featureoperator.java

著名的开源仿真软件yale

/*
 *  YALE - Yet Another Learning Environment
 *  Copyright (C) 2002, 2003
 *      Simon Fischer, Ralf Klinkenberg, Ingo Mierswa, 
 *          Katharina Morik, Oliver Ritthoff
 *      Artificial Intelligence Unit
 *      Computer Science Department
 *      University of Dortmund
 *      44221 Dortmund,  Germany
 *  email: [e-mail]
 *  web:   http://yale.cs.uni-dortmund.de/
 *
 *  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 2 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, write to the Free Software
 *  Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307
 *  USA.
 */
package edu.udo.cs.yale.operator.features;

import edu.udo.cs.yale.example.ExampleSet;
import edu.udo.cs.yale.example.AttributeWeightedExampleSet;
import edu.udo.cs.yale.operator.parameter.*;
import edu.udo.cs.yale.operator.Value;
import edu.udo.cs.yale.operator.OperatorException;
import edu.udo.cs.yale.operator.UserError;

import edu.udo.cs.yale.operator.OperatorChain;
import edu.udo.cs.yale.operator.Operator;
import edu.udo.cs.yale.operator.OperatorException;
import edu.udo.cs.yale.operator.IOObject;
import edu.udo.cs.yale.operator.IOContainer;
import edu.udo.cs.yale.operator.IODescription;
import edu.udo.cs.yale.operator.IllegalInputException;
import edu.udo.cs.yale.operator.performance.PerformanceVector;
import edu.udo.cs.yale.tools.LogService;
import edu.udo.cs.yale.tools.Tools;

import java.util.List;
import java.util.Iterator;

/** This class is the superclass of all feature selection and generation operators.
 *  It provides an easy to use plug-in interface for operators that modify populations.
 *  Subclasses just have to supply lists of <tt>PopulationOperators</tt> by overriding
 *  <tt>getPreEvalutaionPopulationOperators()</tt> and <tt>getPostEvalutaionPopulationOperators()</tt>
 *  during a loop which will terminate if <tt>solutionGoodEnough()</tt> returns true.
 *
 *  <h4>Values:</h4>
 *  <ul>
 *    <li><tt>generation</tt> number of the the current generation
 *    <li><tt>best</tt> all generations' best individual's performance
 *    <li><tt>performance</tt> this generstion's best individual's performance
 *  </ul>
 *
 *  <h4>Operator-Input</h4>
 *  <ol>
 *    <li><tt>ExampleSet</tt> the original example set
 *  </ol>
 *  <h4>Operator-Output</h4>
 *  <ol>
 *    <li><tt>ExampleSet</tt> the best example set
 *    <li><tt>PerformanceVector</tt> its performance
 *  </ol>
 *
 *  @author simon
 *  @version $Id: FeatureOperator.java,v 2.11 2003/08/29 00:39:32 mierswa Exp $ <br>
 */
public abstract class FeatureOperator extends OperatorChain {

    private static final Class[] OUTPUT_CLASSES = { ExampleSet.class, FeatureWeights.class, PerformanceVector.class };
    private static final Class[] INPUT_CLASSES = { ExampleSet.class };

    private int evalCount;
    private int evalSum;
    private Population population;

    public FeatureOperator() {
	addValue(new Value("generation", "The number of the current generation.") {
		public double getValue() {
		    if (population == null) return 0;
		    return population.getGeneration();
		}
	    });
	addValue(new Value("performance", "The performance of the current generation (main criterion).") {
		public double getValue() {
		    if (population == null) return Double.NaN;
		    if (population.lastBest() == null) return Double.NaN;
		    PerformanceVector pv = (PerformanceVector)population.lastBest().getUserData("performance");
		    if (pv == null) return Double.NaN;
		    return pv.getMainCriterion().getValue();
		}
	    });
	addValue(new Value("best", "The performance of the best individual ever (main criterion).") {
		public double getValue() {
  		    if (population == null) return Double.NaN;
		    AttributeWeightedExampleSet eSet = population.bestEver();
		    if (eSet != null) {
			PerformanceVector pv = (PerformanceVector)eSet.getUserData("performance");
			if (pv == null) return Double.NaN;
			return pv.getMainCriterion().getValue();
		    } else {
			return Double.NaN;
		    }
		}
	    });
    }

    /** Create an initial population. The example set will be cloned
     *  before the method is invoked. */
    public abstract Population createInitialPopulation(ExampleSet es);

    /** Must return a list of <tt>PopulationOperator</tt>s. All operators
     *  are applied to the population in their order within the list before
     *  the population is evaluated. */
    public abstract List getPreEvaluationPopulationOperators();

    /** Must return a list of <tt>PopulationOperator</tt>s. All operators
     *  are applied to the population in their order within the list after
     *  the population is evaluated. */ 
    public abstract List getPostEvaluationPopulationOperators();

    /** Has to return true if the main loop can be stopped because
     *  a solution is concidered to be good enough according to
     *  some criterion. */
    public abstract boolean solutionGoodEnough(Population pop) throws OperatorException;

    public void initApply() throws OperatorException {
	super.initApply();
    }

    public Class[] getOutputClasses() { return OUTPUT_CLASSES; }
    public Class[] getInputClasses() { return INPUT_CLASSES; }

    
    /** Returns true if and only if all inner operators accept their precessors' ouput
     *  as input. */
    public Class[] checkIO(Class[] input) throws IllegalInputException {
	Class[] innerOutput = getOperator(0).checkIO(input);
	if (!IODescription.containsClass(PerformanceVector.class, innerOutput)) {
	    throw new IllegalInputException(getOperator(0).getName() + " does not provide PerformanceVector", this);
	}
	return OUTPUT_CLASSES;
    }


    /** Applies the feature operator:
     *  <ol>
     *    <li>create an initial population
     *    <li>evaluate the initial population
     *    <li>loop as long as solution is not good enough
     *    <ol>
     *      <li>apply all pre evaluation operators
     *      <li>evaluate the population
     *      <li>update the population's best individual
     *      <li>apply all post evaluation operators
     *    </ol>
     *    <li>return all generation's best individual
     *  </ol>
     */
    public IOObject[] apply() throws OperatorException {
	evalCount = evalSum = 0;

	ExampleSet es = (ExampleSet)getInput().getInput(ExampleSet.class);
	population = createInitialPopulation((ExampleSet)es.clone());
	LogService.logMessage(getName() + ": initial population has " + population.getNumberOfIndividuals() + " individuals.", 
			      LogService.OPERATOR);
	evaluate(population);
	population.updateEvaluation();
	inApplyLoop();

	while (!solutionGoodEnough(population)) {
	    if (isMaximumReached()) { break; }
	    population.nextGeneration();
	    applyOpList(getPreEvaluationPopulationOperators(), population);

	    LogService.logMessage(Tools.ordinalNumber(population.getGeneration()) + " generation has " + 
				  population.getNumberOfIndividuals() + " individuals.", LogService.OPERATOR);
	    LogService.logMessage(getName() + ": evaluating "+ Tools.ordinalNumber(population.getGeneration()) + " population.", 
				  LogService.OPERATOR);

	    evaluate(population);
	    population.updateEvaluation();
	    inApplyLoop();
	    applyOpList(getPostEvaluationPopulationOperators(), population);
	}

	LogService.logMessage(getName() + " finished. " + evalCount+"/"+evalSum + " evaluations." , LogService.TASK);

	AttributeWeightedExampleSet weightedResultSet = population.bestEver();
	FeatureWeights weights = new FeatureWeights();
 	for (int i = 0; i < weightedResultSet.getNumberOfAttributes(); i++)
 	    weights.addWeight(weightedResultSet.getAttribute(i).getName(), weightedResultSet.getWeight(i));
	ExampleSet result = weightedResultSet.createExampleSet();

	return new IOObject[] { result, weights, (PerformanceVector)population.bestEver().getUserData("performance") };
    }


    /** Applies all PopulationOperators in opList to the population. */
    void applyOpList(List opList, Population population) throws OperatorException {
	Iterator i = opList.listIterator();
	while (i.hasNext()) {
	    PopulationOperator op = (PopulationOperator)i.next();
	    try {
		op.operate(population);
	    } catch (Exception e) {
		throw new UserError(this, e, 108, e.getMessage());
	    }
	}
    }

    /** Evaluates all individuals in the population by applying the inner operators. */
    void evaluate(Population population) throws OperatorException {
	
	Operator operatorChain = getOperator(0);

	for (int i=0 ; i < population.getNumberOfIndividuals(); i++){
	    evalSum++;

	    //ExampleSet individual = population.get(i).createExampleSet();
	    AttributeWeightedExampleSet individual = population.get(i);
	    if (individual.getUserData("performance") == null) {
		evalCount++;

		IOObject[] operatorChainInput = new IOObject[] { individual.createExampleSet() };
		
		PerformanceVector performanceVector = 
		    (PerformanceVector)operatorChain.apply(getInput().append(operatorChainInput)).getInput(PerformanceVector.class);
		
		individual.setUserData("performance", performanceVector);
	    }
	}
    }

    private boolean isMaximumReached() {
	AttributeWeightedExampleSet eSet = population.bestEver();
	if (eSet != null) {
	    PerformanceVector pv = (PerformanceVector)eSet.getUserData("performance");
	    if (pv == null) return false;
	    else return pv.getMainCriterion().getMaxFitness() == pv.getMainCriterion().getFitness();
	} else return false;
    }

    /** Returns the highest possible value for the maximum number of innner operators. */
    public int getMaxNumberOfInnerOperators() { return 1; }
    /** Returns 0 for the minimum number of innner operators. */
    public int getMinNumberOfInnerOperators() { return 1; }


    public int getNumberOfSteps() {
	return 1;
    }

}