net.sourceforge.cilib.measurement.single.diversity.Diversity Maven / Gradle / Ivy
/** __ __
* _____ _/ /_/ /_ Computational Intelligence Library (CIlib)
* / ___/ / / / __ \ (c) CIRG @ UP
* / /__/ / / / /_/ / http://cilib.net
* \___/_/_/_/_.___/
*/
package net.sourceforge.cilib.measurement.single.diversity;
import java.util.Iterator;
import net.sourceforge.cilib.algorithm.Algorithm;
import net.sourceforge.cilib.algorithm.population.SinglePopulationBasedAlgorithm;
import net.sourceforge.cilib.entity.Entity;
import net.sourceforge.cilib.measurement.Measurement;
import net.sourceforge.cilib.measurement.single.diversity.centerinitialisationstrategies.CenterInitialisationStrategy;
import net.sourceforge.cilib.measurement.single.diversity.centerinitialisationstrategies.SpatialCenterInitialisationStrategy;
import net.sourceforge.cilib.measurement.single.diversity.normalisation.DiversityNormalisation;
import net.sourceforge.cilib.measurement.single.diversity.normalisation.NormalisationParameter;
import net.sourceforge.cilib.type.types.Real;
import net.sourceforge.cilib.type.types.container.Vector;
import net.sourceforge.cilib.util.distancemeasure.DistanceMeasure;
import net.sourceforge.cilib.util.distancemeasure.EuclideanDistanceMeasure;
/**
* TODO: Add JavaDoc.
*
*/
public class Diversity implements Measurement {
private static final long serialVersionUID = 7417526206433000209L;
protected DistanceMeasure distanceMeasure;
protected CenterInitialisationStrategy populationCenter;
protected DiversityNormalisation normalisationParameter;
public Diversity() {
distanceMeasure = new EuclideanDistanceMeasure();
populationCenter = new SpatialCenterInitialisationStrategy();
normalisationParameter = new NormalisationParameter();
}
public Diversity(Diversity other) {
this.distanceMeasure = other.distanceMeasure;
this.populationCenter = other.populationCenter;
this.normalisationParameter = other.normalisationParameter;
}
@Override
public Diversity getClone() {
return new Diversity(this);
}
@Override
public Real getValue(Algorithm algorithm) {
SinglePopulationBasedAlgorithm populationBasedAlgorithm = (SinglePopulationBasedAlgorithm) algorithm;
int numberOfEntities = populationBasedAlgorithm.getTopology().length();
Vector center = populationCenter.getCenter(populationBasedAlgorithm.getTopology());
Iterator extends Entity> populationIterator = populationBasedAlgorithm.getTopology().iterator();
double distanceSum = 0.0;
while (populationIterator.hasNext()) {
Vector currentEntityPosition = (Vector) (((Entity) populationIterator.next()).getCandidateSolution());
distanceSum += distanceMeasure.distance(center, currentEntityPosition);
}
distanceSum /= numberOfEntities;
distanceSum /= normalisationParameter.getNormalisationParameter(populationBasedAlgorithm);
return Real.valueOf(distanceSum);
}
/**
* @return the distanceMeasure
*/
public DistanceMeasure getDistanceMeasure() {
return distanceMeasure;
}
/**
* @param distanceMeasure the distanceMeasure to set
*/
public void setDistanceMeasure(DistanceMeasure distanceMeasure) {
this.distanceMeasure = distanceMeasure;
}
/**
* @return the normalisationParameter
*/
public DiversityNormalisation getNormalisationParameter() {
return normalisationParameter;
}
/**
* @param normalisationParameter the normalisationParameter to set
*/
public void setNormalisationParameter(DiversityNormalisation normalisationParameter) {
this.normalisationParameter = normalisationParameter;
}
/**
* @return the populationCenter
*/
public CenterInitialisationStrategy getPopulationCenter() {
return populationCenter;
}
/**
* @param populationCenter the populationCenter to set
*/
public void setPopulationCenter(CenterInitialisationStrategy populationCenter) {
this.populationCenter = populationCenter;
}
}
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