Renamed init to initialize.

Added @Parameter annotation to EAIndividual

src/eva2/optimization/individuals/AbstractEAIndividual.java

@@ -14,6 +14,7 @@ import eva2.problems.InterfaceOptimizationProblem;
 import eva2.tools.EVAERROR;
 import eva2.tools.math.RNG;
 import eva2.util.annotation.Hidden;
+import eva2.util.annotation.Parameter;
 
 import java.util.*;
 
@@ -275,7 +276,7 @@ public abstract class AbstractEAIndividual implements IndividualInterface, java.
      *
      * @param opt The optimization problem that is to be solved.
      */
-    public void init(InterfaceOptimizationProblem opt) {
+    public void initialize(InterfaceOptimizationProblem opt) {
         initializationOperator.initialize(this, opt);
         this.mutationOperator.initialize(this, opt);
         this.crossoverOperator.init(this, opt);
@@ -814,6 +815,7 @@ public abstract class AbstractEAIndividual implements IndividualInterface, java.
      *
      * @param mutator The mutation operator.
      */
+    @Parameter(name = "mutator", description = "The mutation operator to use.")
     public void setMutationOperator(InterfaceMutation mutator) {
         this.mutationOperator = mutator;
     }
@@ -822,16 +824,13 @@ public abstract class AbstractEAIndividual implements IndividualInterface, java.
         return this.mutationOperator;
     }
 
-    public String mutationOperatorTipText() {
-        return "Choose the mutation operator to use.";
-    }
-
     /**
      * This method allows you to set the mutation probability, e.g. the chance
      * that mutation occurs at all.
      *
      * @param mutprob The mutation probability.
      */
+    @Parameter(name = "pm", description = "The chance that mutation occurs.")
     public void setMutationProbability(double mutprob) {
         if (mutprob < 0) {
             mutprob = 0;
@@ -846,16 +845,13 @@ public abstract class AbstractEAIndividual implements IndividualInterface, java.
         return mutationProbability;
     }
 
-    public String mutationProbabilityTipText() {
-        return "The chance that mutation occurs.";
-    }
-
     /**
      * This method allows you to choose from multiple crossover operators. Note:
-     * If the operator doeesn't suite the data nothing will happen.
+     * If the operator doesn't suite the data nothing will happen.
      *
      * @param crossover The crossover operator.
      */
+    @Parameter(name = "crossover", description = "The crossover operator.")
     public void setCrossoverOperator(InterfaceCrossover crossover) {
         this.crossoverOperator = crossover;
     }
@@ -864,15 +860,12 @@ public abstract class AbstractEAIndividual implements IndividualInterface, java.
         return this.crossoverOperator;
     }
 
-    public String crossoverOperatorTipText() {
-        return "Choose the crossover operator to use.";
-    }
-
     /**
      * This method allows to set the crossover probability
      *
      * @param prob
      */
+    @Parameter(name = "pc", description = "The crossover rate")
     public void setCrossoverProbability(double prob) {
         this.crossoverProbability = prob;
         if (this.crossoverProbability > 1) {
@@ -887,22 +880,15 @@ public abstract class AbstractEAIndividual implements IndividualInterface, java.
         return this.crossoverProbability;
     }
 
-    public String crossoverProbabilityTipText() {
-        return "The chance that crossover occurs.";
-    }
-
     public InterfaceInitialization getInitOperator() {
         return initializationOperator;
     }
 
+    @Parameter(name = "initop", description = "The initialization method for the individual")
     public void setInitOperator(InterfaceInitialization mInitOperator) {
         initializationOperator = mInitOperator;
     }
 
-    public String initOperatorTipText() {
-        return "An initialization method for the individual";
-    }
-
     /**
      * This method allows you to store an arbitrary value under an arbitrary
      * name.

src/eva2/optimization/individuals/ESIndividualDoubleData.java

@@ -244,8 +244,8 @@ public class ESIndividualDoubleData extends AbstractEAIndividual implements Inte
      * @param opt The optimization problem that is to be solved.
      */
     @Override
-    public void init(InterfaceOptimizationProblem opt) {
+    public void initialize(InterfaceOptimizationProblem opt) {
-        super.init(opt);
+        super.initialize(opt);
         // evil operators may not respect the range, so at least give some hint
         if (!Mathematics.isInRange(genotype, range)) {
             EVAERROR.errorMsgOnce("Warning: Individual out of range after initialization (and potential initial crossover/mutation)!");

src/eva2/optimization/individuals/GAESIndividualBinaryDoubleData.java

@@ -76,9 +76,9 @@ public class GAESIndividualBinaryDoubleData extends AbstractEAIndividual impleme
      * @param opt The optimization problem that is to be solved.
      */
     @Override
-    public void init(InterfaceOptimizationProblem opt) {
+    public void initialize(InterfaceOptimizationProblem opt) {
-        ((AbstractEAIndividual) this.doubleIndividual).init(opt);
+        ((AbstractEAIndividual) this.doubleIndividual).initialize(opt);
-        ((AbstractEAIndividual) this.binaryIndividual).init(opt);
+        ((AbstractEAIndividual) this.binaryIndividual).initialize(opt);
     }
 
     @Override
@@ -105,8 +105,8 @@ public class GAESIndividualBinaryDoubleData extends AbstractEAIndividual impleme
                 ((AbstractEAIndividual) this.binaryIndividual).initByValue(((Object[]) obj)[0], opt);
             }
         } else {
-            ((AbstractEAIndividual) this.doubleIndividual).init(opt);
+            ((AbstractEAIndividual) this.doubleIndividual).initialize(opt);
-            ((AbstractEAIndividual) this.binaryIndividual).init(opt);
+            ((AbstractEAIndividual) this.binaryIndividual).initialize(opt);
             System.out.println("Initial value for GAESIndividualDoubleData is not suitable!");
         }
     }

src/eva2/optimization/individuals/GAPIndividualProgramData.java

@@ -72,9 +72,9 @@ public class GAPIndividualProgramData extends AbstractEAIndividual implements In
      * @param opt The optimization problem that is to be solved.
      */
     @Override
-    public void init(InterfaceOptimizationProblem opt) {
+    public void initialize(InterfaceOptimizationProblem opt) {
-        ((AbstractEAIndividual) this.numberData).init(opt);
+        ((AbstractEAIndividual) this.numberData).initialize(opt);
-        ((AbstractEAIndividual) this.programData).init(opt);
+        ((AbstractEAIndividual) this.programData).initialize(opt);
     }
 
     @Override
@@ -101,8 +101,8 @@ public class GAPIndividualProgramData extends AbstractEAIndividual implements In
                 ((AbstractEAIndividual) this.programData).initByValue(((Object[]) obj)[0], opt);
             }
         } else {
-            ((AbstractEAIndividual) this.numberData).init(opt);
+            ((AbstractEAIndividual) this.numberData).initialize(opt);
-            ((AbstractEAIndividual) this.programData).init(opt);
+            ((AbstractEAIndividual) this.programData).initialize(opt);
             System.out.println("Initial value for GAPIndividualDoubleData is not suitable!");
         }
     }

src/eva2/optimization/individuals/GIOBGAIndividualIntegerPermutationData.java

@@ -72,9 +72,9 @@ public class GIOBGAIndividualIntegerPermutationData extends AbstractEAIndividual
      * @param opt The optimization problem that is to be solved.
      */
     @Override
-    public void init(InterfaceOptimizationProblem opt) {
+    public void initialize(InterfaceOptimizationProblem opt) {
-        ((AbstractEAIndividual) this.integerData).init(opt);
+        ((AbstractEAIndividual) this.integerData).initialize(opt);
-        ((AbstractEAIndividual) this.permutationData).init(opt);
+        ((AbstractEAIndividual) this.permutationData).initialize(opt);
     }
 
     @Override
@@ -101,8 +101,8 @@ public class GIOBGAIndividualIntegerPermutationData extends AbstractEAIndividual
                 ((AbstractEAIndividual) this.permutationData).initByValue(((Object[]) obj)[0], opt);
             }
         } else {
-            ((AbstractEAIndividual) this.integerData).init(opt);
+            ((AbstractEAIndividual) this.integerData).initialize(opt);
-            ((AbstractEAIndividual) this.permutationData).init(opt);
+            ((AbstractEAIndividual) this.permutationData).initialize(opt);
             System.out.println("Initial value for GIOBGAIndividualIntegerPermutationData is not suitable!");
         }
     }

src/eva2/optimization/operator/crossover/TestESCrossover.java

@@ -110,12 +110,12 @@ public class TestESCrossover implements java.io.Serializable {
             tmpIndyD.setDoubleRange(newRange);
             for (int i = 0; i < partners.getTargetSize(); i++) {
                 tmpIndyEA = (AbstractEAIndividual) ((AbstractEAIndividual) tmpIndyD).clone();
-                tmpIndyEA.init(optimizationProblem);
+                tmpIndyEA.initialize(optimizationProblem);
                 partners.add(tmpIndyEA);
             }
             partners.init();
             daddy = (AbstractEAIndividual) ((AbstractEAIndividual) tmpIndyD).clone();
-            daddy.init(optimizationProblem);
+            daddy.initialize(optimizationProblem);
             plot.clearAll();
             plot.setUnconnectedPoint(-2, -2, 0);
             plot.setUnconnectedPoint(2, 2, 0);

src/eva2/optimization/strategies/ANPSO.java

@@ -541,7 +541,7 @@ public class ANPSO extends NichePSO implements InterfaceAdditionalPopulationInfo
                     if (reinitSuperfl) {
                         for (int i = 0; i < tmpPop.size(); i++) {
                             AbstractEAIndividual indy = tmpPop.getEAIndividual(i);
-                            indy.init(optimizationProblem);
+                            indy.initialize(optimizationProblem);
                             indy.resetFitness(Double.MAX_VALUE); // TODO this is not so nice... they should be collected in a reinit-list and inserted at the beginning of the next optimize step
                             ParticleSwarmOptimization.initIndividualDefaults(indy, 0.2);
                             ParticleSwarmOptimization.initIndividualMemory(indy);

src/eva2/optimization/strategies/ArtificialBeeColony.java

@@ -194,7 +194,7 @@ public class ArtificialBeeColony extends AbstractOptimizer implements Serializab
          */
         AbstractEAIndividual oldestIndy = getOldestIndividual();
         if (oldestIndy.getAge() > this.maxTrials) {
-            oldestIndy.init(this.optimizationProblem);
+            oldestIndy.initialize(this.optimizationProblem);
             this.optimizationProblem.evaluate(oldestIndy);
             this.population.incrFunctionCalls();
         }

src/eva2/optimization/strategies/GeneticAlgorithm.java

@@ -1,6 +1,5 @@
 package eva2.optimization.strategies;
 
-import eva2.optimization.population.InterfacePopulationChangedEventListener;
 import eva2.optimization.individuals.AbstractEAIndividual;
 import eva2.optimization.operator.mutation.InterfaceAdaptOperatorGenerational;
 import eva2.optimization.operator.selection.InterfaceSelection;
@@ -12,8 +11,6 @@ import eva2.optimization.population.SolutionSet;
 import eva2.problems.InterfaceOptimizationProblem;
 import eva2.util.annotation.Description;
 
-import java.util.Vector;
-
 /**
  * The traditional genetic algorithms as devised by Holland. To only special
  * here it the plague factor which reduces the population size to tune from a
@@ -28,7 +25,6 @@ public class GeneticAlgorithm extends AbstractOptimizer implements java.io.Seria
     private boolean useElitism = true;
     private int plague = 0;
     private int numberOfPartners = 1;
-    transient private Vector<InterfacePopulationChangedEventListener> changeListener;
 
     public GeneticAlgorithm() {
     }
@@ -153,38 +149,6 @@ public class GeneticAlgorithm extends AbstractOptimizer implements java.io.Seria
         this.firePropertyChangedEvent(Population.NEXT_GENERATION_PERFORMED);
     }
 
-    /**
-     * This method allows you to add the LectureGUI as listener to the Optimizer
-     *
-     * @param ea
-     */
-    @Override
-    public void addPopulationChangedEventListener(InterfacePopulationChangedEventListener ea) {
-        if (this.changeListener == null) {
-            this.changeListener = new Vector<>();
-        }
-        this.changeListener.add(ea);
-    }
-
-    @Override
-    public boolean removePopulationChangedEventListener(
-            InterfacePopulationChangedEventListener ea) {
-        return changeListener != null && changeListener.removeElement(ea);
-    }
-
-    /**
-     * Something has changed
-     *
-     * @param name
-     */
-    protected void firePropertyChangedEvent(String name) {
-        if (this.changeListener != null) {
-            for (int i = 0; i < this.changeListener.size(); i++) {
-                this.changeListener.get(i).registerPopulationStateChanged(this, name);
-            }
-        }
-    }
-
     @Override
     public InterfaceOptimizationProblem getProblem() {
         return this.optimizationProblem;

src/eva2/optimization/strategies/ParticleFilterOptimization.java

@@ -146,7 +146,7 @@ public class ParticleFilterOptimization extends AbstractOptimizer implements jav
             int i;
             for (i = 0; (i + parents.getTargetSize()) < pop.getTargetSize(); i++) {
                 immi = (AbstractEAIndividual) pop.getEAIndividual(0).clone();
-                immi.init(getProblem());
+                immi.initialize(getProblem());
                 parents.add(immi);
             }
             parents.synchSize();

src/eva2/optimization/strategies/ParticleSubSwarmOptimization.java

@@ -481,7 +481,7 @@ public class ParticleSubSwarmOptimization extends ParticleSwarmOptimizationGCPSO
 
         for (int i = 0; i < tmp.getTargetSize(); i++) {
             tmpIndy = (AbstractEAIndividual) template.clone();
-            tmpIndy.init(prob);
+            tmpIndy.initialize(prob);
             tmp.add(tmpIndy);
         }
         tmp.init();

src/eva2/optimization/strategies/tribes/TribesExplorer.java

@@ -954,7 +954,7 @@ v[d] = cmin * v[d];
     }
 
     @Override
-    public void init(InterfaceOptimizationProblem opt) {
+    public void initialize(InterfaceOptimizationProblem opt) {
         // TODO whats this for?
         for (int i = 0; i < this.position.x.length; i++) {
             this.position.x[0] = 0.;
@@ -983,7 +983,7 @@ v[d] = cmin * v[d];
             }
             this.setDoubleGenotype(x);
         } else {
-            this.init(opt);
+            this.initialize(opt);
             System.err.println("Initial value for ESIndividualDoubleData is not double[]!");
         }
     }

src/eva2/optimization/tools/ImpactOfDimensionOnMOEAs.java

@@ -104,7 +104,7 @@ public class ImpactOfDimensionOnMOEAs {
         ((InterfaceDataTypeDouble) template).setDoubleDataLength(numberOfVariables);
         for (int i = 0; i < popSize; i++) {
             tmpIndy = (AbstractEAIndividual) template.clone();
-            tmpIndy.init(null);
+            tmpIndy.initialize(null);
             pop.add(tmpIndy);
         }
     }

src/eva2/problems/AbstractMultiModalProblemKnown.java

@@ -57,7 +57,7 @@ public abstract class AbstractMultiModalProblemKnown extends AbstractProblemDoub
         ((InterfaceDataTypeDouble) this.template).setDoubleRange(makeRange());
         for (int i = 0; i < population.getTargetSize(); i++) {
             tmpIndy = (AbstractEAIndividual) this.template.clone();
-            tmpIndy.init(this);
+            tmpIndy.initialize(this);
             population.add(tmpIndy);
         }
         // population initialize must be last

src/eva2/problems/AbstractOptimizationProblem.java

@@ -191,7 +191,7 @@ public abstract class AbstractOptimizationProblem implements InterfaceOptimizati
 
         for (int i = 0; i < population.getTargetSize(); i++) {
             tmpIndy = (AbstractEAIndividual) template.clone();
-            tmpIndy.init(prob);
+            tmpIndy.initialize(prob);
             population.add(tmpIndy);
         }
         // population initialize must be last

src/eva2/problems/BKnapsackProblem.java

@@ -160,7 +160,7 @@ public class BKnapsackProblem extends AbstractProblemBinary implements java.io.S
     }
 
     protected void initIndy(int k, AbstractEAIndividual indy) {
-        indy.init(this);
+        indy.initialize(this);
         if (RNG.flipCoin(this.problemSpecificInit)) {
             BitSet tmpSet = new BitSet();
             tmpSet.clear();