Remove AlgType Selected in PSO

refs #32

src/eva2/optimization/strategies/ANPSO.java

@@ -123,8 +123,8 @@ public class ANPSO extends NichePSO implements InterfaceAdditionalPopulationInfo
         getMainSwarm().setPhi1(2.05);
         getMainSwarm().setPhi2(2.05);
         getMainSwarm().setInertnessOrChi(0.7298437881283576);
-//		setMainSwarmInertness(new NoParameterAging(0.7298437881283576));
+        getMainSwarm().setAlgoType(ParticleSwarmOptimization.PSOType.Constriction);
-        setMainSwarmAlgoType(getMainSwarm().getAlgoType().setSelectedTag("Constriction")); // constriction
+        setMainSwarmAlgoType(ParticleSwarmOptimization.PSOType.Constriction); // constriction
         setMaxInitialSubSwarmSize(0); // deactivate early reinits
         setMainSwarmTopology(PSOTopology.grid);
         setMainSwarmTopologyRange(1);
@@ -905,7 +905,8 @@ public class ANPSO extends NichePSO implements InterfaceAdditionalPopulationInfo
         anpso.getMainSwarm().setPhi1(2.05);
         anpso.getMainSwarm().setPhi2(2.05);
         anpso.getMainSwarm().setInertnessOrChi(0.7298437881283576);
-        anpso.setMainSwarmAlgoType(anpso.getMainSwarm().getAlgoType().setSelectedTag("Constriction")); // constriction
+        anpso.getMainSwarm().setAlgoType(ParticleSwarmOptimization.PSOType.Constriction);
+        anpso.setMainSwarmAlgoType(ParticleSwarmOptimization.PSOType.Constriction); // constriction
         anpso.setMaxInitialSubSwarmSize(0); // deactivate early reinits
         anpso.setMainSwarmTopology(PSOTopology.grid);
         anpso.setMainSwarmTopologyRange(1);
@@ -924,7 +925,8 @@ public class ANPSO extends NichePSO implements InterfaceAdditionalPopulationInfo
         anpso.getMainSwarm().setParameterControl(new ParamAdaption[]{new LinearParamAdaption("inertnessOrChi", 0.7, 0.2)});
 //		anpso.setMainSwarmInertness(new LinearParameterAging(0.7, 0.2, evalCnt/anpso.getMainSwarmSize()));
 
-        anpso.setMainSwarmAlgoType(anpso.getMainSwarm().getAlgoType().setSelectedTag("Inertness"));
+        anpso.getMainSwarm().setAlgoType(ParticleSwarmOptimization.PSOType.Inertness);
+        anpso.setMainSwarmAlgoType(ParticleSwarmOptimization.PSOType.Inertness); // inertness
         anpso.getMainSwarm().setPhi1(1.2);
         anpso.getMainSwarm().setPhi2(0.6);  // ANPSO uses communication in the main swarm
         //Possible topologies are: "Linear", "Grid", "Star", "Multi-Swarm", "Tree", "HPSO", "Random" in that order starting by 0.
@@ -944,7 +946,8 @@ public class ANPSO extends NichePSO implements InterfaceAdditionalPopulationInfo
 
         anpso.getMainSwarm().setParameterControl(new ParamAdaption[]{new LinearParamAdaption("inertnessOrChi", 0.7, 0.2)});
 
-        anpso.setMainSwarmAlgoType(anpso.getMainSwarm().getAlgoType().setSelectedTag("Inertness"));
+        anpso.getMainSwarm().setAlgoType(ParticleSwarmOptimization.PSOType.Inertness);
+        anpso.setMainSwarmAlgoType(ParticleSwarmOptimization.PSOType.Inertness);
         anpso.getMainSwarm().setPhi1(1.2);
         anpso.getMainSwarm().setPhi2(1.2);  // ANPSO uses communication in the main swarm
         //Possible topologies are: "Linear", "Grid", "Star", "Multi-Swarm", "Tree", "HPSO", "Random" in that order starting by 0.

src/eva2/optimization/strategies/CBNPSO.java

@@ -33,17 +33,6 @@ public class CBNPSO extends ClusterBasedNichingEA implements Serializable {
 
     public CBNPSO(boolean threshAdaption) {
         this(10, 15, 0.001, 1e-10, 15, 100, threshAdaption);
-//		super();
-//		setDifferentiationCA(new ClusteringDensityBased(getClusterDiffDist(), 10, new IndividualDataMetric(ParticleSwarmOptimization.partBestPosKey)));
-//		setMergingCA(new ClusteringDensityBased(0.001, 3, new IndividualDataMetric(ParticleSwarmOptimization.partBestPosKey)));
-//		setEpsilonBound(1e-10);
-//		setHaltingWindow(15);
-//		setMaxSpeciesSize(15);
-//		setOptimizer(new ParticleSwarmOptimization(100, 2.05, 2.05, PSOTopologyEnum.grid, 2));
-//		ParamAdaption[] defAdpt = new ParamAdaption[]{getDefaultSinusoidalAdaption()};
-//		setParameterControl(defAdpt);
-//		if (threshAdaption) addParameterControl(getDefaultThreshAdaption());
-//		setPopulationSize(100);
     }
 
     public CBNPSO(int minSpecSize, int maxSpecSize, double sigmaMerge, double epsilonConv, int haltingWindow, int popSize, boolean threshAdaption) {

src/eva2/optimization/strategies/DynamicParticleSwarmOptimization.java

@@ -256,7 +256,7 @@ public class DynamicParticleSwarmOptimization extends ParticleSwarmOptimization
             for (int i = 0; i < lastVelocity.length; i++) {
                 // the component from the old velocity
                 curVelocity[i] = this.inertnessOrChi * lastVelocity[i];
-                if (algType.getSelectedTag().getID() == 1) {
+                if (algType == PSOType.Constriction) {
                     chi = inertnessOrChi;
                 } else {
                     chi = 1.;

src/eva2/optimization/strategies/NichePSO.java

@@ -94,7 +94,7 @@ public class NichePSO extends AbstractOptimizer implements InterfaceAdditionalPo
 //	protected double mainSwarmPhi2 = 0; // by default no communication in the mainswarm
     protected PSOTopology mainSwarmTopology = PSOTopology.grid; // = 1;
     protected int mainSwarmTopologyRange = 0;
-    private int mainSwarmAlgoType = 0; // 0: inertness, 1: constriction
+    private ParticleSwarmOptimization.PSOType mainSwarmAlgoType = ParticleSwarmOptimization.PSOType.Inertness; // 0: inertness, 1: constriction
     //	private InterfaceParameterAging mainSwarmParamAging = new LinearParameterAging();
     protected ParameterControlManager paramControl = new ParameterControlManager();
     boolean returnRepresentativeSolutionsOnly = true; // if true only the representatives of every subswarm are returned, else every particles pbest 
@@ -237,7 +237,8 @@ public class NichePSO extends AbstractOptimizer implements InterfaceAdditionalPo
         getMainSwarm().setGcpso(false);
 //		getMainSwarm().setAlgoType(new SelectedTag("Inertness"));
         getMainSwarm().setParameterControl(new ParamAdaption[]{getDefaultInertnessAdaption()});
-        setMainSwarmAlgoType(getMainSwarm().getAlgoType().setSelectedTag(mainSwarmAlgoType)); // set algo type, may influence aging
+        getMainSwarm().setAlgoType(mainSwarmAlgoType);
+        setMainSwarmAlgoType(mainSwarmAlgoType); // set algo type, may influence aging
 
 //		getMainSwarm().setPhi1(mainSwarmPhi1); // cognitive component "tendency to return to the best position visited so far"
 //		getMainSwarm().setPhi2(mainSwarmPhi2); // social component "tendency to be attracted towards the best position found in its neighbourhood."
@@ -263,7 +264,7 @@ public class NichePSO extends AbstractOptimizer implements InterfaceAdditionalPo
         // choose PSO-type for the subswarmoptimizer
         getSubswarmOptimizerTemplate().setGcpso(true);
         getSubswarmOptimizerTemplate().setRho(0.1); // on 2D Problems empirically better than default value 1
-        getSubswarmOptimizerTemplate().getAlgoType().setSelectedTag("Constriction");//setAlgoType(new SelectedTag("Inertness"));
+        getSubswarmOptimizerTemplate().setAlgoType(ParticleSwarmOptimization.PSOType.Constriction);
 
         //"Several studies propose different values for these parameters" (http://tracer.uc3m.es/tws/pso/parameters.html)
         //Bergh2002 p.87
@@ -974,16 +975,16 @@ public class NichePSO extends AbstractOptimizer implements InterfaceAdditionalPo
         this.mainSwarmTopologyRange = mainSwarmTopologyRange;
     }
 
-    public SelectedTag getMainSwarmAlgoType() {
+    public ParticleSwarmOptimization.PSOType getMainSwarmAlgoType() {
-        if (mainSwarmAlgoType != getMainSwarm().getAlgoType().getSelectedTagID()) {
+        if (mainSwarmAlgoType != getMainSwarm().getAlgoType()) {
             System.err.println("Error in NichePSO:getMainSwarmAlgoType() !!");
         }
         return getMainSwarm().getAlgoType();
     }
 
-    public void setMainSwarmAlgoType(SelectedTag st) {
+    public void setMainSwarmAlgoType(ParticleSwarmOptimization.PSOType st) {
         getMainSwarm().setAlgoType(st);
-        mainSwarmAlgoType = st.getSelectedTagID();
+        mainSwarmAlgoType = st;
 //		mainSwarmParamAging.setStartValue(getMainSwarm().getInertnessOrChi());
     }
 
@@ -2048,12 +2049,12 @@ public class NichePSO extends AbstractOptimizer implements InterfaceAdditionalPo
         npso.setMaxAllowedSwarmRadius(0.0001); // formally limits the swarm radius of the subswarms
 
         // Parameter for the mainswarm
-        npso.getMainSwarmAlgoType().setSelectedTag("Inertness");
+        npso.setMainSwarmAlgoType(ParticleSwarmOptimization.PSOType.Inertness);
         npso.getMainSwarm().setPhi1(1.2);
         npso.getMainSwarm().setPhi2(0); // by default no communication in the mainswarm
         npso.setMainSwarmTopologyTag(0); // this doesnt have any effect due to no communication
         npso.setMainSwarmTopologyRange(0);
-        npso.mainSwarmAlgoType = 0;
+        npso.mainSwarmAlgoType = ParticleSwarmOptimization.PSOType.Inertness;
         npso.getMainSwarm().setParameterControl(new ParamAdaption[]{getDefaultInertnessAdaption()});
 //		npso.getMainSwarm().setSpeedLimit(avgRange/2.);
 //		npso.getMainSwarm().setCheckSpeedLimit(true);
@@ -2062,7 +2063,7 @@ public class NichePSO extends AbstractOptimizer implements InterfaceAdditionalPo
         npso.getSubswarmOptimizerTemplate().setGcpso(true);
         npso.getSubswarmOptimizerTemplate().setRho(0.1); // on 2D Problems empirically better than default value 1
 //		npso.getSubswarmOptimizerTemplate().setAlgoType(new SelectedTag("Constriction"));
-        npso.getSubswarmOptimizerTemplate().setAlgoType(npso.getSubswarmOptimizerTemplate().getAlgoType().setSelectedTag("Constriction")); // constriction
+        npso.getSubswarmOptimizerTemplate().setAlgoType(ParticleSwarmOptimization.PSOType.Constriction); // constriction
         npso.getSubswarmOptimizerTemplate().setConstriction(2.05, 2.05);
 //		npso.getSubswarmOptimizerTemplate().setInertnessAging(new LinearParameterAging(0.7, 0.2, evalCnt/(10*popSize))); // expect shorter 
 
@@ -2103,12 +2104,13 @@ public class NichePSO extends AbstractOptimizer implements InterfaceAdditionalPo
         npso.setMaxAllowedSwarmRadius(0.0001); // formally limits the swarm radius of the subswarms
 
         // Parameter for the mainswarm
-        npso.setMainSwarmAlgoType(npso.getMainSwarm().getAlgoType().setSelectedTag("Inertness")); // constriction
+        npso.getMainSwarm().setAlgoType(ParticleSwarmOptimization.PSOType.Inertness);
+        npso.setMainSwarmAlgoType(ParticleSwarmOptimization.PSOType.Inertness);
         npso.getMainSwarm().setPhi1(1.2);
 //		npso.SetMainSwarmPhi2(0); // by default no communication in the mainswarm
         npso.setMainSwarmTopologyTag(0); // this doesnt have any effect due to no communication
         npso.setMainSwarmTopologyRange(0);
-        npso.mainSwarmAlgoType = 0;
+        npso.mainSwarmAlgoType = ParticleSwarmOptimization.PSOType.Inertness;
         npso.getMainSwarm().setParameterControl(new ParamAdaption[]{getDefaultInertnessAdaption()});
 //		npso.setMainSwarmInertness(new LinearParameterAging(0.7, 0.2, evalCnt/popSize));
 //		npso.getMainSwarm().setSpeedLimit(avgRange/2.);
@@ -2117,7 +2119,7 @@ public class NichePSO extends AbstractOptimizer implements InterfaceAdditionalPo
         // parameters for the subswarms
         npso.getSubswarmOptimizerTemplate().setGcpso(true);
         npso.getSubswarmOptimizerTemplate().setRho(0.01);
-        npso.getSubswarmOptimizerTemplate().setAlgoType(new SelectedTag("Constriction"));
+        npso.getSubswarmOptimizerTemplate().setAlgoType(ParticleSwarmOptimization.PSOType.Constriction);
 
         npso.getSubswarmOptimizerTemplate().setConstriction(2.05, 2.05);
 //		npso.getSubswarmOptimizerTemplate().setInertnessAging(new NoParameterAging(npso.getSubswarmOptimizerTemplate().getInertnessOrChi()));

src/eva2/optimization/strategies/ParticleSwarmOptimization.java

@@ -24,6 +24,7 @@ import eva2.tools.math.Jama.Matrix;
 import eva2.tools.math.Mathematics;
 import eva2.tools.math.RNG;
 import eva2.util.annotation.Description;
+import eva2.util.annotation.Parameter;
 
 import java.util.ArrayList;
 import java.util.Arrays;
@@ -42,10 +43,7 @@ import java.util.Vector;
 @Description("Particle Swarm Optimization by Kennedy and Eberhart.")
 public class ParticleSwarmOptimization extends AbstractOptimizer implements java.io.Serializable, InterfaceAdditionalPopulationInformer {
 
-    /**
+    public enum PSOType { Inertness, Constriction }
-     * Generated serial version uid.
-     */
-    private static final long serialVersionUID = -149996122795669589L;
     Object[] sortedPop = null;
     protected AbstractEAIndividual bestIndividual = null;
     protected boolean checkRange = true;
@@ -56,7 +54,7 @@ public class ParticleSwarmOptimization extends AbstractOptimizer implements java
      * Defines which version of PSO is applied, classical inertness or
      * constriction (using chi)
      */
-    protected SelectedTag algType;
+    protected PSOType algType;
     protected int topologyRange = 2;
     protected double initialVelocity = 0.2;
     protected double speedLimit = 0.1;
@@ -92,7 +90,6 @@ public class ParticleSwarmOptimization extends AbstractOptimizer implements java
     transient final static String sortedIndexKey = "sortedParticleIndex";
     transient final static String dmsGroupIndexKey = "dmsGroupIndex";
     protected String indentifier = "";
-    transient private Vector<InterfacePopulationChangedEventListener> changeListener;
     transient private TopoPlot topoPlot = null;
     /// sleep time so that visual plot can be followed easier
     protected int sleepTime = 0;
@@ -109,8 +106,7 @@ public class ParticleSwarmOptimization extends AbstractOptimizer implements java
 
     public ParticleSwarmOptimization() {
         topology = PSOTopology.grid;
-        algType = new SelectedTag("Inertness", "Constriction");
+        algType = PSOType.Constriction;
-        algType.setSelectedTag(1);
 
         setConstriction(getPhi1(), getPhi2());
         hideHideable();
@@ -118,9 +114,7 @@ public class ParticleSwarmOptimization extends AbstractOptimizer implements java
 
     public ParticleSwarmOptimization(ParticleSwarmOptimization a) {
         topology = a.topology;
-        if (a.algType != null) {
+        this.algType =  a.algType;
-            this.algType = (SelectedTag) a.algType.clone();
-        }
         this.population = (Population) a.population.clone();
         this.optimizationProblem = a.optimizationProblem;
         this.indentifier = a.indentifier;
@@ -145,7 +139,7 @@ public class ParticleSwarmOptimization extends AbstractOptimizer implements java
      */
     public ParticleSwarmOptimization(int popSize, double p1, double p2, PSOTopology topo, int topoRange) {
         this();
-        algType.setSelectedTag(1); // set to constriction
+        algType = PSOType.Constriction; // set to constriction
         population = new Population(popSize);
         setPhiValues(p1, p2);
         topologyRange = topoRange;
@@ -292,7 +286,7 @@ public class ParticleSwarmOptimization extends AbstractOptimizer implements java
      * @param requiredType   optional required type identifier of the individual.
      * @return double array containing the vectorial sum of particle velocities
      *         or an array containing the average absolute speed
-     * @see AbstractEAIndividual.getData(String)
+     * @see AbstractEAIndividual#getData(String)
      */
     public static double[] getPopulationVelSpeed(Population pop, int calcModeSwitch, final String velocityKey, final String typeString, final Object requiredType) {
         AbstractEAIndividual indy = (AbstractEAIndividual) pop.get(0);
@@ -742,7 +736,7 @@ public class ParticleSwarmOptimization extends AbstractOptimizer implements java
         for (int i = 0; i < personalBestPos.length; i++) {
             // the component from the old velocity
             accel[i] = 0;
-            if (algType.getSelectedTag().getID() == 1) {
+            if (algType == PSOType.Constriction) {
                 chi = inertnessOrChi;
             } else {
                 chi = 1.;
@@ -1582,7 +1576,7 @@ public class ParticleSwarmOptimization extends AbstractOptimizer implements java
         if (pSum <= 4) {
             System.err.println("error, invalid tauSum value in PSO::setConstriction");
         } else {
-            if (!getAlgoType().isSelectedString("Constriction")) {
+            if (getAlgoType() != PSOType.Constriction) {
                 System.err.println("Warning, PSO algorithm variant constriction expected!");
             }
             phi1 = tau1;
@@ -1613,9 +1607,10 @@ public class ParticleSwarmOptimization extends AbstractOptimizer implements java
      *
      * @param l
      */
+    @Parameter(description = "Acceleration for the cognition model.")
     public void setPhi1(double l) {
         this.phi1 = l;
-        if (algType.getSelectedTag().getID() == 1) {
+        if (algType == PSOType.Constriction) {
             setConstriction(getPhi1(), getPhi2());
         }
     }
@@ -1624,18 +1619,15 @@ public class ParticleSwarmOptimization extends AbstractOptimizer implements java
         return this.phi1;
     }
 
-    public String phi1TipText() {
-        return "Acceleration for the cognition model.";
-    }
-
     /**
      * This method will set greediness to move towards the best social
      *
      * @param l
      */
+    @Parameter(description = "Acceleration for the social model.")
     public void setPhi2(double l) {
         this.phi2 = l;
-        if (algType.getSelectedTag().getID() == 1) {
+        if (algType == PSOType.Constriction) {
             setConstriction(getPhi1(), getPhi2());
         }
     }
@@ -1644,10 +1636,6 @@ public class ParticleSwarmOptimization extends AbstractOptimizer implements java
         return this.phi2;
     }
 
-    public String phi2TipText() {
-        return "Acceleration for the social model.";
-    }
-
     /**
      * Set the phi1 / phi2 parameter values (and in the constriction variant,
      * adapt constriction factor).
@@ -1658,7 +1646,7 @@ public class ParticleSwarmOptimization extends AbstractOptimizer implements java
     public void setPhiValues(double phi1, double phi2) {
         this.phi1 = phi1;
         this.phi2 = phi2;
-        if (algType.isSelectedString("Constriction")) {
+        if (algType == PSOType.Constriction) {
             setConstriction(phi1, phi2);
         }
     }
@@ -1682,6 +1670,7 @@ public class ParticleSwarmOptimization extends AbstractOptimizer implements java
      *
      * @param t The type.
      */
+    @Parameter(description = "Choose the topology type")
     public void setTopology(PSOTopology t) {
         this.topology = t;
         setGOEShowProperties(getClass());
@@ -1709,35 +1698,29 @@ public class ParticleSwarmOptimization extends AbstractOptimizer implements java
         return topology;
     }
 
-    public String topologyTipText() {
-        return "Choose the topology type";
-    }
-
     /**
      * This method allows you to choose the algorithm type.
      *
      * @param s The type.
      */
-    public void setAlgoType(SelectedTag s) {
+    public void setAlgoType(PSOType s) {
         this.algType = s;
-        if (s.getSelectedTag().getID() == 1) {
+        if (algType == PSOType.Constriction) {
             setConstriction(getPhi1(), getPhi2());
         }
     }
 
-    public SelectedTag getAlgoType() {
+    @Parameter(description = "Choose the inertness or constriction method. Chi is calculated automatically in constriction.")
+    public PSOType getAlgoType() {
         return this.algType;
     }
 
-    public String algoTypeTipText() {
-        return "Choose the inertness or constriction method. Chi is calculated automatically in constriction.";
-    }
-
     /**
      * The range of the local neighbourhood.
      *
      * @param s The range.
      */
+    @Parameter(description = "The range of the neighborhood topology.")
     public void setTopologyRange(int s) {
         this.topologyRange = s;
     }
@@ -1746,15 +1729,12 @@ public class ParticleSwarmOptimization extends AbstractOptimizer implements java
         return this.topologyRange;
     }
 
-    public String topologyRangeTipText() {
-        return "The range of the neighborhood topology.";
-    }
-
     /**
      * Toggle Check Constraints.
      *
      * @param s Check Constraints.
      */
+    @Parameter(description = "Toggle whether particles are allowed to leave the range.")
     public void setCheckRange(boolean s) {
         this.checkRange = s;
     }
@@ -1763,10 +1743,6 @@ public class ParticleSwarmOptimization extends AbstractOptimizer implements java
         return this.checkRange;
     }
 
-    public String checkRangeTipText() {
-        return "Toggle whether particles are allowed to leave the range.";
-    }
-
     /**
      * @return true if swarm visualization is turned on
      */

src/eva2/optimization/strategies/StarANPSO.java

@@ -10,7 +10,8 @@ public class StarANPSO extends ANPSO {
         super();
 
         NichePSO.starNPSO(this, defaultEvalCnt);
-        setMainSwarmAlgoType(getMainSwarm().getAlgoType().setSelectedTag("Inertness"));
+        getMainSwarm().setAlgoType(ParticleSwarmOptimization.PSOType.Inertness);
+        setMainSwarmAlgoType(ParticleSwarmOptimization.PSOType.Inertness);
         getMainSwarm().setParameterControl(new ParamAdaption[]{new LinearParamAdaption("inertnessOrChi", 0.7, 0.2)});
 //		setMainSwarmInertness(new LinearParameterAging(0.7, 0.2, defaultEvalCnt/getMainSwarmSize()));