Remove last traces of the TRACE variable.

src/eva2/gui/EvATreeSelectionListener.java

@@ -22,7 +22,6 @@ public class EvATreeSelectionListener implements TreeSelectionListener, Property
     private PropertyEditor goe = null;
     private EvATreeNode root = null;
     private JTree jtree = null;
-    public static final boolean TRACE = true;
 
     /**
      * Create a tree listener and hook it up in the editor to listen to parameter changes
@@ -47,17 +46,9 @@ public class EvATreeSelectionListener implements TreeSelectionListener, Property
 
     @Override
     public void valueChanged(TreeSelectionEvent e) {
-        if (TRACE) {
-            System.out.println("valueChanged to " + BeanInspector.toString(e.getPath()));
-        }
         TreePath tp = e.getPath();
-        if (TRACE) {
+
-            for (int i = tp.getPathCount() - 1; i >= 0; i--) {
-                System.out.println("* " + i + " " + tp.getPathComponent(i));
-            }
-        }
         EvATreeNode leafNode = (EvATreeNode) tp.getLastPathComponent();
-//		goe.setValue(leafNode.getUserObject());
         Component editComp = goe.getCustomEditor();
         if (editComp instanceof OptimizationEditorPanel) {
             // update the object in the main OptimizationEditorPanel
@@ -69,9 +60,6 @@ public class EvATreeSelectionListener implements TreeSelectionListener, Property
 
     @Override
     public void propertyChange(PropertyChangeEvent evt) {
-        if (TRACE) {
-            System.out.println("EvATreeNode received change event " + evt);
-        }
         root.setObject(evt.getNewValue(), true);
         if (jtree != null) {
             jtree.setModel(new DefaultTreeModel(root));

src/eva2/gui/PropertySheetPanelStat.java

@@ -11,8 +11,6 @@ import java.io.Serializable;
  *
  */
 public class PropertySheetPanelStat extends JPanel implements Serializable {
-
-    public final static boolean TRACE = false;
     private Object[] values;
     private JCheckBoxFlag[] views;
     private JLabel[] labels;
@@ -38,8 +36,6 @@ public class PropertySheetPanelStat extends JPanel implements Serializable {
         setLayout(gbLayout);
         setVisible(false);
 
-        int rowHeight = 12;
-
         values = new Object[flag.length];
         views = new JCheckBoxFlag[flag.length];
         labels = new JLabel[names.length];

src/eva2/gui/plot/FunctionArea.java

@@ -426,7 +426,6 @@ public class FunctionArea extends DArea implements Serializable {
                 minY = Math.min(minY, pSet.getMinYVal());
             }
         }
-        // if (TRACE) System.out.println("min is " + minY);
         return (minY > 0);
     }
 

src/eva2/gui/plot/TopoPlot.java

@@ -25,12 +25,10 @@ public class TopoPlot extends Plot {
      */
     public TopoPlot(String PlotName, String xname, String yname) {
         super(PlotName, xname, yname, true);
-        //if (TRACE) System.out.println("Constructor TopoPlot "+PlotName);
     }
 
     public TopoPlot(String PlotName, String xname, String yname, double[] a, double[] b) {
         super(PlotName, xname, yname, a, b);
-        //if (TRACE) System.out.println("Constructor TopoPlot "+PlotName);
     }
 
     /**
@@ -98,17 +96,12 @@ public class TopoPlot extends Plot {
         double deltaY = sizeXY[1] / gridy;
         double maxDeriv = 0;
         double[] pos = new double[2];
-        boolean TRACEMETH = false;
-        //double fitRange = java.lang.Math.abs(problem.getMinFitness()-problem.getMaxFitness() );
         double fitRange = 0, max = -Double.MAX_VALUE, min = Double.MAX_VALUE, tmp;
         for (int x = 0; x < gridx; x++) {
             for (int y = 0; y < gridy; y++) {
                 pos[0] = border[0][0] + x * deltaX;
                 pos[1] = border[1][0] + y * deltaY;
                 tmp = (float) (problem.functionValue(pos));
-                if (TRACEMETH) {
-                    System.out.println(pos[0] + " " + pos[1] + " " + tmp);
-                }
                 if (tmp < min) {
                     min = tmp;
                 }

src/eva2/optimization/individuals/codings/gp/AbstractGPNode.java

@@ -22,7 +22,6 @@ public abstract class AbstractGPNode implements InterfaceProgram, java.io.Serial
     protected AbstractGPNode parentNode;
     protected AbstractGPNode[] nodes = new AbstractGPNode[0];
     protected int depth = 0;
-    private static final boolean TRACE = false;
 
     /**
      * This method allows you to clone the Nodes
@@ -132,9 +131,6 @@ public abstract class AbstractGPNode implements InterfaceProgram, java.io.Serial
                 System.err.println("String has ambiguous prefix: " + str + " -- " + BeanInspector.toString(matchSet));
             } else { // exactly one match:
                 AbstractGPNode currentNode = (AbstractGPNode) matchSet.get(0).clone();
-                if (TRACE) {
-                    System.out.println("Found match: " + currentNode.getOpIdentifier() + "/" + currentNode.getArity());
-                }
                 int cutFront = currentNode.getOpIdentifier().length();
                 String restStr;
                 if (currentNode.getArity() == 0) {
@@ -163,9 +159,6 @@ public abstract class AbstractGPNode implements InterfaceProgram, java.io.Serial
                             e.printStackTrace();
                         }
                     }
-                    if (TRACE) {
-                        System.out.println("read " + currentNode.getName() + ", rest: " + restStr);
-                    }
                     return new Pair<AbstractGPNode, String>(currentNode, restStr);
                 }
             }

src/eva2/optimization/mocco/paretofrontviewer/ParetoFrontView2D.java

@@ -261,7 +261,7 @@ public class ParetoFrontView2D extends JPanel implements InterfaceParetoFrontVie
                     InterfaceOptimizationObjective[] tmpObj = ((InterfaceMultiObjectiveDeNovoProblem) this.moccoViewer.moccoStandalone.state.currentProblem).getProblemObjectives();
                     fitness = new double[tmpObj.length];
                     for (int k = 0; k < tmpObj.length; k++) {
-                        fitness[k] = ((Double) ((AbstractEAIndividual) pf.get(i)).getData(tmpObj[k].getIdentName())).doubleValue();
+                        fitness[k] = (Double) ((AbstractEAIndividual) pf.get(i)).getData(tmpObj[k].getIdentName());
                     }
                 }
                 point = new DPoint(fitness[indexX], fitness[indexY]);

src/eva2/optimization/modules/Processor.java

@@ -192,8 +192,7 @@ public class Processor extends Thread implements InterfaceProcessor, InterfacePo
             LOGGER.log(Level.SEVERE, errMsg, e);
             try {
                 JOptionPane.showMessageDialog(null, StringTools.wrapLine(errMsg, 60, 0.2), "Error in Optimization", JOptionPane.ERROR_MESSAGE);
-            } catch (Exception ex) {
+            } catch (Exception | Error ex) {
-            } catch (Error error) {
             }
             //statistics.stopOptimizationPerformed(false);
             setOptimizationRunning(false); // normal finish

src/eva2/optimization/operator/cluster/ClusteringNearestBetter.java

@@ -43,8 +43,6 @@ public class ClusteringNearestBetter implements InterfaceClustering, Serializabl
     private static final String initializedForKey = "initializedClustNearestBetterOnHash";
     private static final String initializedRefData = "initializedClustNearestBetterData";
 
-    private static boolean TRACE = false;
-
     public ClusteringNearestBetter() {
     }
 
@@ -216,9 +214,7 @@ public class ClusteringNearestBetter implements InterfaceClustering, Serializabl
                 }
             }
             currentMeanDistance = createClusterTreeFromSortedPop(sorted);
-            if (TRACE) {
+
-                pop.putData(initializedForKey, pop.hashCode());
-            }
             pop.putData(initializedRefData, currentMeanDistance);
             return initializedRefData;
         } else {
@@ -247,10 +243,6 @@ public class ClusteringNearestBetter implements InterfaceClustering, Serializabl
             }
         }
 
-        if (TRACE) {
-            System.out.println("Current pop measures: " + BeanInspector.toString(pop.getPopulationMeasures(metric)[0]));
-            System.out.println("Current threshold: " + currentDistThreshold());
-        }
         if (isAdaptiveThreshold()) { // test if there was a valid initialization step
             if (!getRefData(referenceSet, pop)) {
                 currentMeanDistance = createClusterTreeFromSortedPop(sorted);
@@ -304,13 +296,7 @@ public class ClusteringNearestBetter implements InterfaceClustering, Serializabl
         }
         Double refDat = (Double) referenceSet.getData(initializedRefData);
         if (refDat != null) {
-            if (TRACE) { // check hash
+
-                Integer hash = (Integer) referenceSet.getData(initializedForKey);
-                if ((hash == null) || (hash != referenceSet.hashCode())) {
-                    System.err.println("Warning, missing initialization before clustering for ClusteringNearestBetter!");
-                    return false;
-                }
-            }
             currentMeanDistance = refDat.doubleValue();
             return true;
         } else {
@@ -362,14 +348,7 @@ public class ClusteringNearestBetter implements InterfaceClustering, Serializabl
                     // so add it to the cluster, mark it, and proceed recursively.
                     currentClust.add(sorted.get(children[current].get(i)));
                     clustered[children[current].get(i)] = true;
-                    if (TRACE) {
-                        System.out.println("Assigned " + current);
-                    }
                     addChildren(children[current].get(i), clustered, sorted, currentClust);
-                } else {
-                    if (TRACE) {
-                        System.out.println("Not assigned " + current);
-                    }
                 }
             }
         } else {

src/eva2/optimization/operator/constraint/AbstractConstraint.java

@@ -18,7 +18,7 @@ public abstract class AbstractConstraint implements InterfaceDoubleConstraint, S
     //	private transient GPFunctionProblem func = null;
     protected ConstraintRelationEnum relation = ConstraintRelationEnum.lessEqZero;
     protected ConstraintHandlingEnum handling = ConstraintHandlingEnum.specificTag;
-    protected static boolean TRACE = false;
+
     protected double equalityEpsilon = 0.0001; // threshold below which equality constraints are seen as satisfied
     private AbstractEAIndividual currentIndy = null;
 
@@ -31,11 +31,9 @@ public abstract class AbstractConstraint implements InterfaceDoubleConstraint, S
         relation = ConstraintRelationEnum.lessEqZero;
         penaltyFactor = 1.;
         paramCtrl = new ParameterControlManager(new NoParamAdaption());
-//		penaltyFactAdaption = new NoParamAdaption();		
     }
 
     public AbstractConstraint(AbstractConstraint o) {
-//		penaltyFactAdaption = (ParamAdaption)o.penaltyFactAdaption.clone();
         paramCtrl = new ParameterControlManager(o.paramCtrl);
         penaltyFactor = o.penaltyFactor;
         relation = o.relation;

src/eva2/optimization/operator/constraint/ConstraintCollection.java

@@ -41,15 +41,10 @@ public class ConstraintCollection extends AbstractConstraint {
     @Override
     protected double getRawViolationValue(double[] indyX) {
         double v, sum = 0;
-        if (TRACE) {
+
-            System.out.println("Viol (pen " + getPenaltyFactor() + ")");
-        }
         for (AbstractConstraint constr : constraintArray) {
             v = constr.getViolation(indyX);
             sum += v;
-            if (TRACE) {
-                System.out.println(constr.getClass().getSimpleName() + " " + v);
-            }
         }
         return sum;
     }

src/eva2/optimization/operator/constraint/GenericConstraint.java

@@ -62,10 +62,6 @@ public class GenericConstraint extends AbstractConstraint implements InterfaceDo
         if (constraintProgram == null) {
             System.err.println("Error: invalid expression: " + constraintString);
         }
-        if (TRACE) {
-            System.out.println("Compiled constraint " + constraintString);
-            System.out.println("Program: " + constraintProgram.getStringRepresentation());
-        }
     }
 
     /**
@@ -97,8 +93,6 @@ public class GenericConstraint extends AbstractConstraint implements InterfaceDo
                 } else {
                     return 0.;
                 }
-//		case linearLessEqZero:
-//			return getViolation(evalLinearConstr(indy));
         }
         EVAERROR.errorMsgOnce("Error: unknown relation for GenericConstraint!");
         return 0.;
@@ -111,9 +105,6 @@ public class GenericConstraint extends AbstractConstraint implements InterfaceDo
     public void setConstraintString(String constraintString) {
         this.constraintString = constraintString;
         constraintProgram = null;
-        if (TRACE) {
-            System.out.println(" NEW CONSTRAINT STRING SET! in " + this);
-        }
     }
 
     public String getName() {

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

@@ -13,15 +13,14 @@ import java.util.BitSet;
 
 /**
  * The famous n-point crossover operator on a binary and integer genotype. Genotypes of
- * parent individuals are recombined by exchanging subsegments within randomly
+ * parent individuals are recombined by exchanging sub-segments within randomly
- * selected points. Therefore, far-away allels (larger GA schemas) are more likely to be split
+ * selected points. Therefore, far-away alleles (larger GA schemas) are more likely to be split
  * between individuals.
  *
  * @author mkron, streiche
  */
 public class CrossoverGAGINPoint implements InterfaceCrossover, java.io.Serializable {
     private int numberOfCrossovers = 3;
-    private static boolean TRACE = false;
 
     public CrossoverGAGINPoint() {
 
@@ -71,7 +70,6 @@ public class CrossoverGAGINPoint implements InterfaceCrossover, java.io.Serializ
 
         if (individual instanceof InterfaceGAIndividual || (individual instanceof InterfaceGIIndividual)) {
             int length = getGenotypeLength(individual);
-//            Object[][]  tmpGenotypes       = new Object[2][partners.size()+1];
             Object[] origGenotypes = new Object[partners.size() + 1];
             Object[] newGenotypes = new Object[partners.size() + 1];
 
@@ -83,14 +81,9 @@ public class CrossoverGAGINPoint implements InterfaceCrossover, java.io.Serializ
                 newGenotypes[i + 1] = getGenotype(result[i + 1]);
                 length = Math.max(length, getGenotypeLength(partners.getEAIndividual(i)));
             }
-            if (TRACE) {
+
-                System.out.println("Before CO: " + BeanInspector.toString(newGenotypes));
-            }
             int mixer = RNG.randomInt(0, partners.size()); // partner index with which to exchange genes
             int[] crossoverPoints = getCrossoverPoints(length, numberOfCrossovers);
-            if (TRACE) {
-                System.out.println("CO points: " + BeanInspector.toString(crossoverPoints));
-            }
             for (int i = 0; i < length; i++) { // loop positions
                 for (int j = 0; j < this.numberOfCrossovers; j++) {
                     if (i == crossoverPoints[j]) {
@@ -106,9 +99,6 @@ public class CrossoverGAGINPoint implements InterfaceCrossover, java.io.Serializ
             for (int i = 0; i < result.length; i++) {
                 writeBack(result[i], newGenotypes[i]);
             }
-            if (TRACE) {
-                System.out.println("After CO: " + BeanInspector.toString(newGenotypes));
-            }
         }
         return result;
     }

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

@@ -10,11 +10,6 @@ import eva2.problems.InterfaceOptimizationProblem;
 import eva2.tools.math.RNG;
 
 /**
- * Created by IntelliJ IDEA.
- * User: streiche
- * Date: 04.04.2003
- * Time: 16:37:05
- * To change this template use Options | File Templates.
  */
 public class CrossoverGPDefault implements InterfaceCrossover, java.io.Serializable {
     /**
@@ -23,7 +18,6 @@ public class CrossoverGPDefault implements InterfaceCrossover, java.io.Serializa
     private static final long serialVersionUID = 8900427365914281930L;
     private InterfaceOptimizationProblem optimizationProblem;
     private boolean maintainMaxDepth = true;
-    private static final boolean TRACE = false;
 
     public CrossoverGPDefault() {
     }
@@ -60,11 +54,6 @@ public class CrossoverGPDefault implements InterfaceCrossover, java.io.Serializa
         for (int i = 0; i < partners.size(); i++) {
             result[i + 1] = (AbstractEAIndividual) ((AbstractEAIndividual) partners.get(i)).clone();
         }
-        if (TRACE) {
-            for (int i = 0; i < result.length; i++) {
-                System.out.println("Before Crossover: " + result[i].getStringRepresentation());
-            }
-        }
         if (partners.size() == 0) {
             return result;
         }
@@ -94,10 +83,6 @@ public class CrossoverGPDefault implements InterfaceCrossover, java.io.Serializa
                         selNodeOther = ((InterfaceGPIndividual) result[1]).getPGenotype()[t].getRandomLeaf();
                     }
                 }
-                if (TRACE) {
-                    System.out.println("Selected t " + selNodeThis.getStringRepresentation());
-                    System.out.println("Selected o " + selNodeOther.getStringRepresentation());
-                }
 
                 AbstractGPNode selNodeThisParent, selNodeOtherParent;
                 selNodeThisParent = selNodeThis.getParent();
@@ -119,20 +104,15 @@ public class CrossoverGPDefault implements InterfaceCrossover, java.io.Serializa
             }
         }
         //in case the crossover was successfull lets give the mutation operators a chance to mate the strategy parameters
-        for (int i = 0; i < result.length; i++) {
+        for (AbstractEAIndividual aResult : result) {
-            ((GPIndividualProgramData) result[i]).checkDepth();
+            ((GPIndividualProgramData) aResult).checkDepth();
-            result[i].getMutationOperator().crossoverOnStrategyParameters(indy1, partners);
+            aResult.getMutationOperator().crossoverOnStrategyParameters(indy1, partners);
-        }
-        if (TRACE) {
-            for (int i = 0; i < result.length; i++) {
-                System.out.println("After Crossover: " + result[i].getStringRepresentation());
-            }
         }
         return result;
     }
 
     /**
-     * This method allows you to evaluate wether two crossover operators
+     * This method allows you to evaluate whether two crossover operators
      * are actually the same.
      *
      * @param crossover The other crossover operator

src/eva2/optimization/operator/mutation/CMAParamSet.java

@@ -116,8 +116,6 @@ class CMAParamSet implements InterfacePopulationChangedEventListener, Serializab
         params.range = range;
 
         int dim = params.range.length;
-//		if (TRACE_1) System.out.println("WCMA initialize " + dim);
-//		if (TRACE_1) System.out.println("WCMA static initialize " + dim);
         params.eigenvalues = new double[dim];
         Arrays.fill(params.eigenvalues, 1.);
         params.meanX = new double[dim];
@@ -219,9 +217,7 @@ class CMAParamSet implements InterfacePopulationChangedEventListener, Serializab
     public void registerPopulationStateChanged(Object source, String name) {
         if (name.equals(Population.POPULATION_INITIALIZED)) {
             Population pop = (Population) source;
-            if (MutateESRankMuCMA.TRACE_1) {
+
-                System.out.println("Event " + name + " arrived in CMAParamSet!!!");
-            }
             CMAParamSet params = (CMAParamSet) (pop.getData(MutateESRankMuCMA.cmaParamsKey));
             int mu;
             if (pop.hasData(EvolutionStrategies.esMuParam)) {

src/eva2/optimization/operator/mutation/MutateESCorrVector.java

@@ -30,7 +30,6 @@ public class MutateESCorrVector implements InterfaceMutation, java.io.Serializab
     protected double rotationDev = 15.;
     protected boolean checkConstraints = true;
     public static final String vectorKey = "MutateESCorrVectorVector";
-    public static final boolean TRACE = false;
 
     public MutateESCorrVector() {
     }
@@ -128,7 +127,6 @@ public class MutateESCorrVector implements InterfaceMutation, java.io.Serializab
      */
     @Override
     public void mutate(AbstractEAIndividual individual) {
-//        if (TRACE) System.out.println("Before Mutate: " + AbstractEAIndividual.getDefaultDataString(individual));
         if (individual instanceof InterfaceESIndividual) {
             double[] genes = ((InterfaceESIndividual) individual).getDGenotype();
             double[][] range = ((InterfaceESIndividual) individual).getDoubleRange();
@@ -137,9 +135,6 @@ public class MutateESCorrVector implements InterfaceMutation, java.io.Serializab
 
             // mutate the velocity vector and write it back
             if ((scalingDev > 0) || (rotationDev > 0)) {
-//            	for (int i = 0; i < vel.length; i++) {
-//            		vel[i] += ((range[i][1] -range[i][0])/2)*RNG.gaussianDouble(this.mutationStepSize);
-//            	}
                 double rotateRad = rotationDev * (Math.PI / 360.) * RNG.gaussianDouble(1.);
                 // rotate with a gaussian distribution of deviation rotationDeg
                 Mathematics.rotateAllAxes(vel, rotateRad, false); // rotate
@@ -158,12 +153,6 @@ public class MutateESCorrVector implements InterfaceMutation, java.io.Serializab
                 Mathematics.svMult(rScale, vel, vel); // mutate speed
 
                 individual.putData(vectorKey, vel);
-                if (TRACE) {
-                    System.out.println("rotated by " + rotateRad + ", scaled by " + rScale);
-                }
-                if (TRACE) {
-                    System.out.println("-- dir is  " + BeanInspector.toString(vel));
-                }
             }
 
             // add velocity to the individual
@@ -178,7 +167,6 @@ public class MutateESCorrVector implements InterfaceMutation, java.io.Serializab
             ((InterfaceESIndividual) individual).setDGenotype(genes);
 
         }
-//        if (TRACE) System.out.println("After Mutate:  " + AbstractEAIndividual.getDefaultDataString(individual));
     }
 
     /**
@@ -192,21 +180,21 @@ public class MutateESCorrVector implements InterfaceMutation, java.io.Serializab
     public void crossoverOnStrategyParameters(AbstractEAIndividual indy1, Population partners) {
         ArrayList<Double> tmpList = new ArrayList<Double>();
         if (indy1.getMutationOperator() instanceof MutateESCorrVector) {
-            tmpList.add(new Double(((MutateESCorrVector) indy1.getMutationOperator()).scalingDev));
+            tmpList.add(((MutateESCorrVector) indy1.getMutationOperator()).scalingDev);
         }
-        for (int i = 0; i < partners.size(); i++) {
+        for (Object partner : partners) {
-            if (((AbstractEAIndividual) partners.get(i)).getMutationOperator() instanceof MutateESCorrVector) {
+            if (((AbstractEAIndividual) partner).getMutationOperator() instanceof MutateESCorrVector) {
-                tmpList.add(new Double(((MutateESCorrVector) ((AbstractEAIndividual) partners.get(i)).getMutationOperator()).scalingDev));
+                tmpList.add(((MutateESCorrVector) ((AbstractEAIndividual) partner).getMutationOperator()).scalingDev);
             }
         }
         double[] list = new double[tmpList.size()];
         for (int i = 0; i < tmpList.size(); i++) {
-            list[i] = tmpList.get(i).doubleValue();
+            list[i] = tmpList.get(i);
         }
         if (list.length <= 1) {
             return;
         }
-        // discreete mutation for step size
+        // discrete mutation for step size
         this.scalingDev = list[RNG.randomInt(0, list.length - 1)];
     }
 

src/eva2/optimization/operator/mutation/MutateESCovarianceMatrixAdaption.java

@@ -10,11 +10,6 @@ import eva2.tools.math.Mathematics;
 import eva2.tools.math.RNG;
 
 /**
- * Created by IntelliJ IDEA.
- * User: streiche
- * Date: 27.05.2003
- * Time: 17:47:45
- * To change this template use Options | File Templates.
  */
 
 public class MutateESCovarianceMatrixAdaption implements InterfaceMutation, java.io.Serializable {

src/eva2/optimization/operator/mutation/MutateESRankMuCMA.java

@@ -49,9 +49,6 @@ public class MutateESRankMuCMA implements InterfaceAdaptOperatorGenerational, In
     private boolean checkRange = true;
     public static final String cmaParamsKey = "RankMuCMAParameters";
 
-    public static boolean TRACE_1 = false; // true for plotting CMA
-    public static boolean TRACE_2 = false; // true for plotting CMA
-    public static boolean TRACE_TEST = false;
 
     public MutateESRankMuCMA() {
     }
@@ -67,7 +64,6 @@ public class MutateESRankMuCMA implements InterfaceAdaptOperatorGenerational, In
 
     @Override
     public Object clone() {
-//		if (TRACE) System.out.println("WCMA clone");
         return new MutateESRankMuCMA(this);
     }
 
@@ -162,26 +158,13 @@ public class MutateESRankMuCMA implements InterfaceAdaptOperatorGenerational, In
             return;
         }
 
-        if (TRACE_1) {
-            System.out.println("WCMA adaptGenerational **********");
-//			System.out.println("newPop measures: " + BeanInspector.toString(newPop.getPopulationMeasures()));
-            System.out.println("mu_eff: " + CMAParamSet.getMuEff(params.weights, mu));
-            System.out.println(params.toString());
-            System.out.println("*********************************");
-        }
-
         double[] newMeanX = calcMeanX(params.weights, selectedSorted);
-        if (TRACE_1) {
-            System.out.println("newMeanX:  " + BeanInspector.toString(newMeanX));
-        }
-
         int dim = params.meanX.length;
         double[] BDz = new double[dim];
         for (int i = 0; i < dim; i++) { /* calculate xmean and BDz~N(0,C) */
             // Eq. 4 from HK04, most right term
             BDz[i] = Math.sqrt(CMAParamSet.getMuEff(params.weights, mu)) * (newMeanX[i] - params.meanX[i]) / getSigma(params, i);
         }
-//        if (TRACE_2) System.out.println("BDz is " + BeanInspector.toString(BDz));
 
         double[] newPathS = params.pathS.clone();
         double[] newPathC = params.pathC.clone();
@@ -233,16 +216,6 @@ public class MutateESRankMuCMA implements InterfaceAdaptOperatorGenerational, In
             checkValidDouble(newPathC[i]);
         }
 
-        // TODO missing: "remove momentum in ps"
-
-        if (TRACE_1) {
-            System.out.println("newPathC: " + BeanInspector.toString(newPathC));
-            System.out.println("newPathS: " + BeanInspector.toString(newPathS));
-        }
-
-        if (TRACE_1) {
-            System.out.println("Bef: C is \n" + params.mC.toString());
-        }
         if (params.meanX == null) {
             params.meanX = newMeanX;
         }
@@ -250,10 +223,6 @@ public class MutateESRankMuCMA implements InterfaceAdaptOperatorGenerational, In
         updateCov(params, newPathC, newMeanX, hsig, mu, selectedSorted);
         updateBD(params);
 
-        if (TRACE_2) {
-            System.out.println("Aft: C is " + params.mC.toString());
-        }
-
         /* update of sigma */
         double sigFact = Math.exp(((psNorm / expRandStepLen) - 1) * params.c_sig
                 / params.d_sig);
@@ -269,12 +238,6 @@ public class MutateESRankMuCMA implements InterfaceAdaptOperatorGenerational, In
             params = CMAParamSet.initCMAParams(params, mu, lambda, params.meanX, ((InterfaceDataTypeDouble) oldGen.getEAIndividual(0)).getDoubleRange(), params.firstSigma);
         }
 
-        if (TRACE_1) {
-            System.out.println("sigma=" + params.sigma);
-            System.out.print("psLen=" + (psNorm) + " ");
-            outputParams(params, mu);
-        }
-
         // take over data
         params.meanX = newMeanX;
         params.pathC = newPathC;
@@ -284,7 +247,6 @@ public class MutateESRankMuCMA implements InterfaceAdaptOperatorGenerational, In
         lastParams = (CMAParamSet) params.clone();
         oldGen.putData(cmaParamsKey, params);
         selectedP.putData(cmaParamsKey, params);
-//		if (TRACE_2) System.out.println("sampling around " + BeanInspector.toString(meanX));
     }
 
     /**
@@ -319,19 +281,13 @@ public class MutateESRankMuCMA implements InterfaceAdaptOperatorGenerational, In
         if (iterations > 1 && (selected.size() > 1)) {
             // selected pop is sorted
             if (nearlySame(selected.getEAIndividual(0).getFitness(), selected.getEAIndividual(selected.size() - 1).getFitness())) {
-                if (TRACE_1) {
-                    System.err.println("flat fitness landscape, consider reformulation of fitness, step-size increased");
-                }
                 params.sigma *= Math.exp(0.2 + params.c_sig / params.d_sig);
-//    			sigma=0.1;
             }
         }
 
         if (!checkValidDouble(params.sigma)) {
             System.err.println("Error, unstable sigma!");
             corrected = false;
-//        	params.sigma=params.firstSigma; // MK TODO
-//        	System.err.println(
         }
 
     	/* Align (renormalize) scale C (and consequently sigma) */
@@ -347,7 +303,6 @@ public class MutateESRankMuCMA implements InterfaceAdaptOperatorGenerational, In
         }
 
         if (fac != 1.) {
-//    		System.err.println("Scaling by " + fac);
             params.sigma /= fac;
             for (int i = 0; i < params.meanX.length; ++i) {
                 params.pathC[i] *= fac;
@@ -571,26 +526,6 @@ public class MutateESRankMuCMA implements InterfaceAdaptOperatorGenerational, In
     @Override
     public void init(AbstractEAIndividual individual,
                      InterfaceOptimizationProblem opt) {
-//		firstAdaptionDone = false;
-//		range = ((InterfaceDataTypeDouble)individual).getDoubleRange();
-//		dim = range.length;
-//		if (TRACE_1) System.out.println("WCMA initialize " + dim);
-//		c_c = (4./(dim+4));
-//		c_sig = Double.NaN; // mark as not yet initialized
-////		c_u_sig = Double.NaN;
-//		d_sig = Double.NaN; // initialize in first adaption step!
-//		if (TRACE_1) System.out.println("WCMA static initialize " + dim);
-//		eigenvalues = new double[dim];
-//		Arrays.fill(eigenvalues, 1.);
-//		
-//		meanX = new double[dim];
-//		pathC = new double[dim];
-//		pathS = new double[dim];
-////		mBD = new double[dim];
-//		mC = Matrix.identity(dim, dim);
-//		mB = Matrix.identity(dim, dim);
-//		sigma = 0.2;
-        // ^^^ moved to CMAParamSet initialization
         double[][] range = ((InterfaceDataTypeDouble) individual).getDoubleRange();
         int dim = range.length;
         c_c = (4. / (dim + 4));
@@ -600,21 +535,15 @@ public class MutateESRankMuCMA implements InterfaceAdaptOperatorGenerational, In
 
     @Override
     public void mutate(AbstractEAIndividual individual) {
-//		if (!firstAdaptionDone) {
-//			if (TRACE) System.out.println("No mutation before first adaptions step");
-//			return;
-//		}
         if (individual instanceof InterfaceDataTypeDouble) {
             double[] x = ((InterfaceDataTypeDouble) individual).getDoubleData();
-//			if (TRACE) System.out.println("WCMA mutate, bef: " + BeanInspector.toString(x));
             double[][] range = ((InterfaceDataTypeDouble) individual).getDoubleRange();
 
             // this is a critical point: where do the CMA parameters for this individual's mutation come from?
-            // for GA and ES we can expect that selection occured directly before the mutation cycle,
+            // for GA and ES we can expect that selection occurred directly before the mutation cycle,
-            // so we take the parameter set from the last adpation step.
+            // so we take the parameter set from the last adaption step.
             ((InterfaceDataTypeDouble) individual).setDoubleGenotype(mutate(lastParams, x, range, 0));
 
-//			if (TRACE) System.out.println("WCMA mutate, aft: " + BeanInspector.toString(x));
         } else {
             System.err.println("Error, expecting InterfaceDataTypeDouble");
         }
@@ -626,7 +555,6 @@ public class MutateESRankMuCMA implements InterfaceAdaptOperatorGenerational, In
             System.err.println("Error in MutateESRankMuCMA.mutate !");
             Mathematics.projectToRange(params.meanX, range);
         }
-//		System.out.println("--- In mutate!");
         if (params != null && (params.firstAdaptionDone)) {
             double[] sampl = new double[dim]; // generate scaled random vector (D * z)
             for (int i = 0; i < dim; ++i) {
@@ -677,9 +605,6 @@ public class MutateESRankMuCMA implements InterfaceAdaptOperatorGenerational, In
         if (!Mathematics.isInRange(params.meanX, range)) {
             System.err.println("Error B in MutateESRankMuCMA.mutate !");
         }
-        if (TRACE_1) {
-            System.out.println("mutated indy: " + BeanInspector.toString(x));
-        }
         return x;
     }
 
@@ -788,7 +713,6 @@ public class MutateESRankMuCMA implements InterfaceAdaptOperatorGenerational, In
      * @return
      */
     public boolean testAllDistBelow(Population pop, double tolX) {
-//		if all(sigma*(max(abs(pc), sqrt(diag(C)))) < stopTolX) 
         boolean res = true;
         CMAParamSet params = (CMAParamSet) pop.getData(cmaParamsKey);
         int i = 0;
@@ -796,11 +720,7 @@ public class MutateESRankMuCMA implements InterfaceAdaptOperatorGenerational, In
             res = res && (getSigma(params, i) * Math.max(Math.abs(params.pathC[i]), Math.sqrt(params.mC.get(i, i))) < tolX);
             i++;
         }
-        if (TRACE_TEST) {
+
-            if (res) {
-                System.out.println("testAllDistBelow hit");
-            }
-        }
         return res;
     }
 
@@ -827,11 +747,6 @@ public class MutateESRankMuCMA implements InterfaceAdaptOperatorGenerational, In
             res = res && (params.meanX[i] == (params.meanX[i] + d * getSigma(params, i) * ev_k[i]));
             i++;
         }
-        if (TRACE_TEST) {
-            if (res) {
-                System.out.println("testNoChangeAddingDevAxis hit");
-            }
-        }
         return res;
     }
 
@@ -842,8 +757,6 @@ public class MutateESRankMuCMA implements InterfaceAdaptOperatorGenerational, In
      * @return
      */
     public boolean testNoEffectCoord(Population pop, double d) {
-//		if any(xmean == xmean + 0.2*sigma*sqrt(diag(C))) 
-//		stopflag(end+1) = {'warnnoeffectcoord'};
         boolean ret = false;
         CMAParamSet params = (CMAParamSet) pop.getData(cmaParamsKey);
         int i = 0;
@@ -851,11 +764,6 @@ public class MutateESRankMuCMA implements InterfaceAdaptOperatorGenerational, In
             ret = ret || (params.meanX[i] == (params.meanX[i] + d * getSigma(params, i) * Math.sqrt(params.mC.get(i, i))));
             i++;
         }
-        if (TRACE_TEST) {
-            if (ret) {
-                System.out.println("testNoEffectCoord hit");
-            }
-        }
         return ret;
     }
 
@@ -867,18 +775,9 @@ public class MutateESRankMuCMA implements InterfaceAdaptOperatorGenerational, In
      * @return true, if a diagonal entry is <= 0 or >= d, else false
      */
     public boolean testCCondition(Population pop, double d) {
-//	    if (min(diag(D)) <= 0) || (max(diag(D)) > 1e14*min(diag(D))) 
-//		  stopflag(end+1) = {'warnconditioncov'};
         CMAParamSet params = (CMAParamSet) pop.getData(cmaParamsKey);
         Pair<Double, Double> minMax = params.mC.getMinMaxDiag();
-        if ((minMax.head <= 0) || (minMax.tail >= d)) {
+        return (minMax.head <= 0) || (minMax.tail >= d);
-            if (TRACE_TEST) {
-                System.out.println("testCCondition hit");
-            }
-            return true;
-        } else {
-            return false;
-        }
     }
 
     /**

src/eva2/optimization/operator/paramcontrol/AbstractParameterControl.java

@@ -16,7 +16,6 @@ import eva2.optimization.population.Population;
  */
 public abstract class AbstractParameterControl implements InterfaceParameterControl {
     public Object[] initialValues = null;
-    protected static boolean TRACE = false;
 
     public AbstractParameterControl() {
     }
@@ -57,10 +56,6 @@ public abstract class AbstractParameterControl implements InterfaceParameterCont
             if (!BeanInspector.setMem(obj, params[i], vals[i])) {
                 System.err.println("Error: failed to set parameter from parameter control " + this.getClass().getName());
                 System.err.println("  Tried to set name/val: " + params[i] + " / " + BeanInspector.toString(vals[i]));
-            } else {
-                if (TRACE) {
-                    System.out.println("Successfully set " + params[i] + " / " + BeanInspector.toString(vals[i]) + " at " + iteration);
-                }
             }
         }
     }

src/eva2/optimization/operator/paramcontrol/ConstraintBasedAdaption.java

@@ -30,9 +30,6 @@ public class ConstraintBasedAdaption implements ParamAdaption, Serializable {
 
     LinkedList<Boolean> lastBestSatisfactionState = new LinkedList<Boolean>();
 
-    //	private double endAct=0;
-//	private double deltaInertness = 0.1;
-    private static boolean TRACE = false;
 
     private static String target = "penaltyFactor";
 
@@ -44,8 +41,6 @@ public class ConstraintBasedAdaption implements ParamAdaption, Serializable {
         betaInc = o.betaInc;
         betaDec = o.betaDec;
         genGap = o.genGap;
-//		endAct = o.endAct;
-//		deltaInertness = o.deltaInertness;
     }
 
     @Override
@@ -59,9 +54,6 @@ public class ConstraintBasedAdaption implements ParamAdaption, Serializable {
         if (!(obj instanceof AbstractConstraint)) {
             System.err.println(this.getClass().getSimpleName() + " cant control " + obj.getClass().getSimpleName() + " ! ");
         } else {
-            if (TRACE) {
-                System.out.println("calc value at it " + iteration + " of " + maxIteration);
-            }
             if (lastBestSatisfactionState.size() == genGap) {
                 lastBestSatisfactionState.poll();
             }
@@ -80,9 +72,6 @@ public class ConstraintBasedAdaption implements ParamAdaption, Serializable {
             currentFactor = maxPenalty / initialPenalty;
             curPen = maxPenalty;
         }
-        if (TRACE && changed) {
-            System.out.println("NEW penalty: " + curPen);
-        }
         return curPen;
     }
 
@@ -101,18 +90,10 @@ public class ConstraintBasedAdaption implements ParamAdaption, Serializable {
             if (allValid) {
                 currentFactor *= betaDec;
                 changed = true;
-                if (TRACE) {
-                    System.out.println("all valid, new fact is " + currentFactor + " times " + initialPenalty);
-                }
             } else if (allInvalid) {
                 changed = true;
                 currentFactor *= betaInc;
-                if (TRACE) {
-                    System.out.println("all invalid, new fact is " + currentFactor + " times " + initialPenalty);
-                }
             }
-        } else if (TRACE) {
-            System.out.println("not yet looking at " + genGap + " individuals...");
         }
         return changed;
     }

src/eva2/optimization/operator/paramcontrol/PSOActivityFeedbackControl.java

@@ -27,7 +27,6 @@ public class PSOActivityFeedbackControl implements ParamAdaption, Serializable {
     private double startAct = 0.17;
     private double endAct = 0.01;
     private double deltaInertness = 0.1;
-    private static boolean TRACE = false;
     private boolean exponentialSchedule = true;
 
     private static String target = "inertnessOrChi";
@@ -71,9 +70,7 @@ public class PSOActivityFeedbackControl implements ParamAdaption, Serializable {
 
     private double calcNewInertness(double currentInertness, double currentAct,
                                     double desiredActivity) {
-        if (TRACE) {
+
-            System.out.println("Activity was " + currentAct + ", desired: " + desiredActivity);
-        }
         if (currentAct < desiredActivity) { // increase inertness
             return Math.min(maxInert, currentInertness + deltaInertness);
         } else if (currentAct > desiredActivity) { // too high act, so decrease inertness

src/eva2/optimization/operator/paramcontrol/ParameterControlManager.java

@@ -27,7 +27,6 @@ import java.util.Vector;
 public class ParameterControlManager implements InterfaceParameterControl, Serializable {
     public Object[] initialValues = null;
     private ParamAdaption[] singleAdapters = new ParamAdaption[]{};
-    protected static boolean TRACE = false;
 
     public ParameterControlManager() {
     }
@@ -111,13 +110,6 @@ public class ParameterControlManager implements InterfaceParameterControl, Seria
             if (!BeanInspector.setMem(obj, params[i], vals[i])) {
                 System.err.println("Error: failed to set parameter from parameter control " + this.getClass().getName());
                 System.err.println("  Tried to set name/val: " + params[i] + " / " + BeanInspector.toString(vals[i]));
-            } else {
-                if (TRACE) {
-                    System.out.println("Successfully set " + params[i] + " / " + BeanInspector.toString(vals[i]) + " at " + iteration);
-                }
-//				if (!oldVal.equals(vals[i])) {
-//					if (obj instanceof InterfaceParamControllable) ((InterfaceParamControllable)obj).notifyParamChanged(params[i], oldVal, vals[i]);
-//				}
             }
         }
         Object[] args = new Object[]{null, pop, iteration, maxIteration};
@@ -140,8 +132,8 @@ public class ParameterControlManager implements InterfaceParameterControl, Seria
     public String[] getControlledParameters() {
         if (singleAdapters != null) {
             Vector<String> names = new Vector<String>(singleAdapters.length);
-            for (int i = 0; i < singleAdapters.length; i++) {
+            for (ParamAdaption singleAdapter : singleAdapters) {
-                String prm = singleAdapters[i].getControlledParam();
+                String prm = singleAdapter.getControlledParam();
                 if (prm != null) {
                     names.add(prm);
                 }

src/eva2/optimization/operator/paretofrontmetrics/MetricS.java

@@ -13,7 +13,6 @@ import eva2.problems.AbstractMultiObjectiveOptimizationProblem;
 public class MetricS implements InterfaceParetoFrontMetric, java.io.Serializable {
 
     private double[][] objectiveSpaceRange;
-    private static boolean TRACE = false;
 
     public MetricS() {
 
@@ -57,35 +56,17 @@ public class MetricS implements InterfaceParetoFrontMetric, java.io.Serializable
     @Override
     public double calculateMetricOn(Population pop, AbstractMultiObjectiveOptimizationProblem problem) {
         this.objectiveSpaceRange = problem.getObjectiveSpaceRange();
-        if (TRACE) {
+
-            System.out.println("Border: " + BeanInspector.toString(objectiveSpaceRange));
-        }
         double smetric = this.calculateSMetric(pop, this.objectiveSpaceRange, this.objectiveSpaceRange.length);
         double reference = 1;
-        for (int i = 0; i < this.objectiveSpaceRange.length; i++) {
+        for (double[] anObjectiveSpaceRange : this.objectiveSpaceRange) {
-            reference *= (this.objectiveSpaceRange[i][1] - this.objectiveSpaceRange[i][0]);
+            reference *= (anObjectiveSpaceRange[1] - anObjectiveSpaceRange[0]);
         }
         //System.out.println("SMetric: "+smetric +" Reference: " + reference);
         double res = ((Math.abs(smetric) / Math.abs(reference)) * 100);
-        if (TRACE) {
-            System.out.println("Res is " + res);
-        }
         return res;
     }
 
-//    /** This method gives a metric how to evaluate
-//     * an achieved Pareto-Front
-//     */
-//    public double calculateMetricOn(Population pop) {
-//        double smetric = this.calculateSMetric(pop, this.objectiveSpaceRange, this.objectiveSpaceRange.length);
-//        double reference = 1;
-//        for (int i = 0; i < this.objectiveSpaceRange.length; i++) {
-//            reference *= (this.objectiveSpaceRange[i][1] - this.objectiveSpaceRange[i][0]);
-//        }
-//        //System.out.println("SMetric: "+smetric +" Reference: " + reference);
-//        return ((Math.abs(smetric)/Math.abs(reference))*100);
-//    }
-
     /**
      * This method will calculate the s-metric from a double array of
      * fitness cases

src/eva2/optimization/operator/postprocess/PostProcess.java

@@ -46,7 +46,6 @@ import java.util.Vector;
  */
 public class PostProcess {
     protected static InterfaceDistanceMetric metric = new PhenotypeMetric();
-    private static final boolean TRACE = false;
 
     // the default mutation step size for HC post processing
     private static double defaultMutationStepSize = 0.01;
@@ -175,17 +174,7 @@ public class PostProcess {
         result.setSameParams(pop);
         clustering.initClustering(pop);
         Population[] clusters = clustering.cluster(pop, null);
-        if (TRACE) {
+
-            System.out.println("found " + clusters.length + " clusters!");
-            int sum = 0;
-            for (int j = 0; j < clusters.length; j++) {
-                sum += clusters[j].size();
-                if (TRACE) {
-                    System.out.print(j + " w " + clusters[j].size() + ", ");
-                }
-            }
-            System.out.println("\nsum was " + sum);
-        }
         for (int j = 0; j < clusters.length; j++) {
             if (j == 0) { // cluster 0 contains non-assigned individuals
                 if (lonerMode == DISCARD_LONERS) {
@@ -580,9 +569,7 @@ public class PostProcess {
             case nelderMead:
                 double[][] range = ((InterfaceDataTypeDouble) candidates.getEAIndividual(index)).getDoubleRange();
                 double perturb = findNMSPerturb(candidates, index, relToAbsPerturb(maxRelativePerturbation, range));
-                if (TRACE) {
+
-                    System.out.println("perturb " + index + " is " + perturb);
-                }
                 subPop = NelderMeadSimplex.createNMSPopulation(candidates.getEAIndividual(index), absToRelPerturb(perturb, range), range, false);
         }
         return subPop;
@@ -636,9 +623,7 @@ public class PostProcess {
             return evalsDone;
         } else {
             int stepsPerCand = (steps - (candCnt * (dim - 1))) / candCnt;
-            if (TRACE) {
+
-                System.out.println("employing " + stepsPerCand + " steps per cand.");
-            }
             if (stepsPerCand < dim) {
                 System.err.println("Too few steps allowed in processSingleCandidates!");
                 System.err.println("Method: " + method + ", cands: " + candidates.size() + ", steps: " + steps);
@@ -689,9 +674,7 @@ public class PostProcess {
 
         if (term == null) {
             int stepsPerCand = 10 * (nmPops.get(0).size() - 1); // == 10*dim for NM
-            if (TRACE) {
+
-                System.out.println("employing " + stepsPerCand + " per candidate.");
-            }
             if (stepsPerCand < 1) {
                 System.err.println("Too few steps allowed!");
                 return 0;
@@ -959,18 +942,11 @@ public class PostProcess {
 
         double[] meanFit = clust.getMeanFitness();
 
-        if (TRACE) {
-            System.out.println("BEF: funcalls done: " + pop.getFunctionCalls() + ", now allowed: " + funCalls);
-        }
-
         int evalsDone = processSingleCandidates(method, clust, funCalls, sigmaCluster / 2., problem, mute);
 
         clust.setFunctionCalls(evalsBefore + evalsDone);
 
         double improvement = EuclideanMetric.euclideanDistance(meanFit, clust.getMeanFitness());
-        if (TRACE) {
-            System.out.println("improvement by " + improvement + " funcalls done: " + evalsDone);
-        }
         return new Pair<Population, Double>(clust, improvement);
     }
 
@@ -990,7 +966,6 @@ public class PostProcess {
             listener.println("max peak ratio is " + mmkProb.getMaximumPeakRatio(getFoundOptima(solutions, mmkProb.getRealOptima(), mmkProb.getDefaultAccuracy(), true)));
             if (mmkProb.fullListAvailable()) {
                 for (double epsilon = 0.1; epsilon > 0.00000001; epsilon /= 10.) {
-//	out.println("no optima found: " + ((InterfaceMultimodalProblemKnown)mmProb).getNumberOfFoundOptima(pop));
                     listener.println("found " + getFoundOptima(solutions, mmkProb.getRealOptima(), epsilon, true).size() + " for epsilon = " + epsilon + ", maxPeakRatio: " + mmkProb.getMaximumPeakRatio(solutions));
                 }
             }

src/eva2/optimization/operator/terminators/PopulationMeasureTerminator.java

@@ -22,15 +22,13 @@ import java.io.Serializable;
  *
  * @author mkron
  */
-public abstract class PopulationMeasureTerminator implements InterfaceTerminator,
+public abstract class PopulationMeasureTerminator implements InterfaceTerminator, Serializable {
-        Serializable {
     public enum ChangeTypeEnum {relativeChange, absoluteChange, absoluteValue}
 
     public enum DirectionTypeEnum {decrease, bidirectional}
 
     public enum StagnationTypeEnum {fitnessCallBased, generationBased}
 
-    protected static boolean TRACE = false;
     private double convThresh = 0.01; //, convThreshLower=0.02;
     private double oldMeasure = -1;
     private int stagTime = 1000;
@@ -96,9 +94,7 @@ public abstract class PopulationMeasureTerminator implements InterfaceTerminator
     @Override
     public boolean isTerminated(PopulationInterface pop) {
         if (!firstTime && isStillConverged(pop)) {
-            if (TRACE) {
+
-                System.out.println("Converged at " + pop.getGeneration() + "/" + pop.getFunctionCalls() + ", measure " + calcPopulationMeasure(pop));
-            }
             if (stagnationTimeHasPassed(pop)) {
                 // population hasnt changed much for max time, criterion is met
                 msg = getTerminationMessage();
@@ -226,18 +222,6 @@ public abstract class PopulationMeasureTerminator implements InterfaceTerminator
                 break;
         }
         ret = (measure <= allowedUpper) && (measure >= allowedLower);
-        // Old Version:
-//		if (isRelativeConvergence()) {
-//			double delta = oldMeasure*convThresh;
-//			if (doCheckImprovement()) ret = (measure >= (oldMeasure - delta));
-//			else ret = ((measure >= (oldMeasure-delta)) && (measure <= (oldMeasure+delta))); // check for rel. change which must be within +/- thresh
-//		} else { // check absolute values
-//			if (doCheckImprovement()) ret = (measure < oldMeasure+convThresh); // absolute improvement below fixed number
-//			else ret = ((measure < oldMeasure+convThresh) && (measure > oldMeasure-convThresh)); // absolute change within fixed range
-//		}
-        if (TRACE) {
-            System.out.println("isStillConverged returns " + ret + ", measure " + measure + ", old measure " + BeanInspector.toString(oldMeasure) + ", bounds: [" + allowedLower + " , " + allowedUpper + "]");
-        }
         return ret;
     }
 
@@ -277,16 +261,6 @@ public abstract class PopulationMeasureTerminator implements InterfaceTerminator
         return "Ratio of improvement/change or absolute value of improvement/change to determine convergence.";
     }
 
-//	public void setConvergenceThresholdLower(double x) {
-//		convThreshLower = x;
-//	}
-//	public double getConvergenceThresholdLower() {
-//		return convThreshLower;
-//	}
-//	public String convergenceThresholdUpperTipText() {
-//		return "Lower threshold value in case of detecting absolute change, meaning the bounds [measure-convThresh,measure+convThresh] must be kept to assume convergence.";
-//	}
-
     public void setStagnationTime(int k) {
         stagTime = k;
     }

src/eva2/optimization/population/Population.java

@@ -1853,24 +1853,8 @@ public class Population extends ArrayList implements PopulationInterface, Clonea
      *         an array of three
      */
     public double[] getPopulationMeasures(InterfaceDistanceMetric metric) {
-//    	Integer lastMeasuresModCount = (Integer)getData(lastPopMeasuresFlagKey);
+
-//    	if (lastMeasuresModCount!=null && (lastMeasuresModCount==modCount)) {
-//    		double[] measures = (double[])getData(lastPopMeasuresDatKey);
-//            if (TRACE ) {
-//            	double[] verify = calcPopulationMeasures(metric);
-//            	if (Mathematics.dist(measures, verify, 2)>1e-10) {
-//            		System.out.println(getStringRepresentation());
-//            		System.err.println("Warning, invalid measures!!!");
-//            		
-//            	}
-//            }
-//    		return measures;
-//    	} 
         double[] res = getPopulationMeasures(this, metric);
-//        putData(lastPopMeasuresFlagKey, new Integer(modCount));
-//        putData(lastPopMeasuresDatKey, res);
-//        System.out.println(getStringRepresentation());
-//        System.out.println("0-1-dist: " + BeanInspector.toString(metric.distance((AbstractEAIndividual)this.get(0), (AbstractEAIndividual)this.get(1))));
         return res;
     }
 

src/eva2/optimization/stat/EvAStatisticalEvaluation.java

@@ -19,29 +19,6 @@ public class EvAStatisticalEvaluation {
 
     public static EvAStatisticalEvaluationParams statsParams = new EvAStatisticalEvaluationParams();
 
-//	public static void evaluate(OptimizationJob[] jobList, int[] selectedIndices) {
-//		if (TRACE) System.out.println("Job list: " + BeanInspector.toString(jobList));
-//		JTextoutputFrame textout = new JTextoutputFrame("Statistics");
-//		textout.setShow(true);
-//		ArrayList<OptimizationJob> jobsToWorkWith = new ArrayList<OptimizationJob>();
-//		for (int i=0; i<jobList.length; i++) {
-//			// remove jobs which are not finished or not selected
-//			if (jobList[i]!=null && (Mathematics.contains(selectedIndices, i)) && (jobList[i].isFinishedAndComplete())) jobsToWorkWith.add(jobList[i]);
-//		}
-//		List<String> commonFields = getCommonFields(jobsToWorkWith);
-//		if (commonFields!=null && !commonFields.isEmpty()) for (String field : commonFields) {
-//			textout.println("Checking field " + field);
-//
-//			for (int i=0; i<jobsToWorkWith.size(); i++) {
-//				textout.print(jobsToWorkWith.get(i).getParams().getOptimizer().getName() + "\t");
-//				for (int j=0; j<jobsToWorkWith.size(); j++) {
-////					System.out.println("Comparing " + i + " with " + j);
-//					textout.print("\t" + compare(field, jobsToWorkWith.get(i), jobsToWorkWith.get(j)));
-//				}
-//				textout.println("");
-//			}
-//		}
-//	}
 
     public static void evaluate(InterfaceTextListener textout, OptimizationJob[] jobList, int[] selectedIndices,
                                 StatsOnSingleDataSetEnum[] singleStats,

src/eva2/optimization/strategies/ANPSO.java

@@ -523,12 +523,7 @@ public class ANPSO extends NichePSO implements InterfaceOptimizer, InterfaceAddi
         Population tmpPop = new Population(), newMainPop = new Population();
         Vector<Population> setOfSubswarms = new Vector<Population>();
         boolean reinitSuperfl = true;
-        boolean TRACEMTHD = false;
 
-        // ... and use the corresponding particles to create the subswarms
-        if (TRACEMTHD) {
-            System.out.println("---------");
-        }
         for (Set<String> connSet : connectedComps) {
             if (connSet.size() > 1) {// create niche
                 Population pop = new Population(connSet.size());
@@ -540,16 +535,9 @@ public class ANPSO extends NichePSO implements InterfaceOptimizer, InterfaceAddi
                     }
                     pop.add(indy);
                 }
-                if (TRACEMTHD) {
-                    System.out.print(" subswarm size ssize " + pop.size());
-                }
                 if (maxInitialSubSwarmSize > 0 && (pop.size() > maxInitialSubSwarmSize)) {
-                    if (TRACEMTHD) {
-                        System.out.print(" removing " + (pop.size() - maxInitialSubSwarmSize));
-                    }
                     tmpPop = pop.getWorstNIndividuals(pop.size() - maxInitialSubSwarmSize, -1);
                     tmpPop.synchSize();
-//					Population testPop=(Population)pop.clone();
                     pop.removeMembers(tmpPop, true);
                     if (reinitSuperfl) {
                         for (int i = 0; i < tmpPop.size(); i++) {
@@ -565,9 +553,6 @@ public class ANPSO extends NichePSO implements InterfaceOptimizer, InterfaceAddi
                     pop.synchSize();
                 }
                 setOfSubswarms.add(pop);
-                if (TRACEMTHD) {
-                    System.out.print("\nNew subswarm of size: " + pop.size());
-                }
             } else { // move particles corresponding to unconnected vertices to the mainswarm
                 Iterator<String> it = connSet.iterator();
                 Integer index = Integer.valueOf(it.next());
@@ -575,17 +560,10 @@ public class ANPSO extends NichePSO implements InterfaceOptimizer, InterfaceAddi
                 newMainPop.add(indy);
             }
         }
-//		for (int i=0; i<setOfSubswarms.size(); i++) {
+
-//			if (!getMainSwarm().getPopulation().assertMembers(setOfSubswarms.get(i))) {
-//				System.err.println("Wrong subswarm " + i);
-//			}
-//		}
-        if (TRACEMTHD) {
-            System.out.println();
-        }
         newMainPop.synchSize();
-        for (int i = 0; i < setOfSubswarms.size(); i++) {
+        for (Population setOfSubswarm : setOfSubswarms) {
-            setOfSubswarms.get(i).synchSize();
+            setOfSubswarm.synchSize();
         }
         useAsSubSwarms(setOfSubswarms);
         useAsMainSwarm(newMainPop);
@@ -599,7 +577,6 @@ public class ANPSO extends NichePSO implements InterfaceOptimizer, InterfaceAddi
      */
     @Override
     public void optimize() {
-//		System.out.println(BeanInspector.toString(getMainSwarm()));
         // main swarm:
         if (getMainSwarm().getPopulation().size() == 0) {// || mainSwarm.getPopulation().size() == 1){
             if (isVerbose()) {
@@ -656,27 +633,24 @@ public class ANPSO extends NichePSO implements InterfaceOptimizer, InterfaceAddi
         if (isPlot()) {
             doPlot();
         }
-//		System.out.println();
-        /** end plotting *******************************************************************************/
 
         // reset flags etc for:
         // deactivation
         deactivationOccured = false;
-        deactivatedSwarm = new Vector<ParticleSubSwarmOptimization>();
+        deactivatedSwarm = new Vector<>();
-        //reinitedSwarm = new Vector<ParticleSubSwarmOptimization>();
         // merging
         mergingOccurd = false;
-        borg = new Vector<ParticleSubSwarmOptimization>();
+        borg = new Vector<>();
-        others = new Vector<ParticleSubSwarmOptimization>();
+        others = new Vector<>();
-        borgbest = new Vector<AbstractEAIndividual>();
+        borgbest = new Vector<>();
-        othersbest = new Vector<AbstractEAIndividual>();
+        othersbest = new Vector<>();
         // absorbtion
         absorbtionOccurd = false;
-        indytoabsorb = new Vector<AbstractEAIndividual>();
+        indytoabsorb = new Vector<>();
         // subswarmcreation
         creationOccurd = false;
-        indyconverged = new Vector<AbstractEAIndividual>();
+        indyconverged = new Vector<>();
-        convergedneighbor = new Vector<AbstractEAIndividual>();
+        convergedneighbor = new Vector<>();
         //clearing - deprecated
         //reinitoccurd = false;
 
@@ -751,21 +725,10 @@ public class ANPSO extends NichePSO implements InterfaceOptimizer, InterfaceAddi
             currentsubswarm = (Population) getSubSwarms().get(i).getPopulation().clone();
             metapop.addPopulation(currentsubswarm);
         }
-        for (int i = 0; i < inactiveSubSwarms.size(); ++i) { // in the case of ANPSO
+        for (ParticleSubSwarmOptimization inactiveSubSwarm : inactiveSubSwarms) { // in the case of ANPSO
-            currentsubswarm = (Population) inactiveSubSwarms.get(i).getPopulation().clone();
+            currentsubswarm = (Population) inactiveSubSwarm.getPopulation().clone();
             metapop.addPopulation(currentsubswarm);
         }
-        // add the best pbest particle to the population
-//		if (metapop.size() != 0){
-//			AbstractEAIndividual hero = (AbstractEAIndividual)metapop.getEAIndividual(0).getData("PersonalBestKey");
-//			for (int i = 0; i < metapop.size(); ++i){
-//				AbstractEAIndividual currentPBest = (AbstractEAIndividual)metapop.getEAIndividual(i).getData("PersonalBestKey");
-//				if (currentPBest.isDominating(hero)){
-//					hero = currentPBest;
-//				}
-//			}
-//			metapop.add(hero);
-//		}
 
         // set correct number of generations
         metapop.setGeneration(getMainSwarm().getPopulation().getGeneration());
@@ -774,9 +737,7 @@ public class ANPSO extends NichePSO implements InterfaceOptimizer, InterfaceAddi
         int calls = getMainSwarm().getPopulation().getFunctionCalls();
         for (int i = 0; i < getSubSwarms().size(); ++i) {
             ParticleSubSwarmOptimization subswarm = getSubSwarms().get(i);
-            //	if (subswarm.isActive()){
             calls += subswarm.getPopulation().getFunctionCalls();
-            //	}
         }
         // calls from inactivated subswarms were transfered to the mainswarm, see useAsSubSwarms method
 
@@ -795,17 +756,13 @@ public class ANPSO extends NichePSO implements InterfaceOptimizer, InterfaceAddi
         int mainSize = 0;
         //if (includeMainSwarm) mainSize = getMainSwarm().getPopulation().size();
         Population elitePop = new Population(getSubSwarms().size() + inactiveSubSwarms.size() + mainSize);
-//		if (includeMainSwarm){
+
-//			for (int i = 0; i < mainSize; ++i){
-//				elite[i] = getMainSwarm().getPopulation().getEAIndividual(i);
-//			}
-//		}
         for (int i = 0; i < getSubSwarms().size(); ++i) {
             AbstractEAIndividual bestSS = getSubSwarms().get(i).getBestIndividual();
             elitePop.addIndividual((AbstractEAIndividual) getSubSwarms().get(i).bestIndividual.clone());
         }
-        for (int i = 0; i < inactiveSubSwarms.size(); ++i) {
+        for (ParticleSubSwarmOptimization inactiveSubSwarm : inactiveSubSwarms) {
-            elitePop.addIndividual((AbstractEAIndividual) inactiveSubSwarms.get(i).bestIndividual.clone());
+            elitePop.addIndividual((AbstractEAIndividual) inactiveSubSwarm.bestIndividual.clone());
         }
         return elitePop;
     }
@@ -821,7 +778,6 @@ public class ANPSO extends NichePSO implements InterfaceOptimizer, InterfaceAddi
         for (int i = 0; i < getSubSwarms().size() + inactiveSubSwarms.size(); ++i) {
             result += elite.getEAIndividual(i).getStringRepresentation() + "\n";
         }
-        //result += "\n";
         return result;
     }
 
@@ -863,15 +819,8 @@ public class ANPSO extends NichePSO implements InterfaceOptimizer, InterfaceAddi
                 if (!currentsubswarm.isActive()) {
                     plotCircleForIndy((AbstractEAIndividual) best, "[I]");
                 } else {
-                    if (!getSubswarmOptimizerTemplate().isGcpso()) {
-                        //plotCircleForIndy((AbstractEAIndividual)best,getMaxStdDevFromSwarmAsString(currentsubswarm));
-                    }
                     if (getSubswarmOptimizerTemplate().isGcpso()) {
                         String rhoAsString = String.format("%6.3f", currentsubswarm.getRho());
-                        //plotCircleForIndy((AbstractEAIndividual)best,rhoAsString);
-                        if (currentsubswarm.gbestParticle != null) {
-                            //plotCircleForIndy((AbstractEAIndividual)currentsubswarm.gbestParticle,"gbest");
-                        }
                     }
                 }
 
@@ -921,12 +870,6 @@ public class ANPSO extends NichePSO implements InterfaceOptimizer, InterfaceAddi
         return "ANPSO-" + getMainSwarmSize();
     }
 
-//
-//	public double getMinimalR() {
-//		return minimalR;
-//	}
-
-
     public void SetMinimalR(double minimalR) {
         this.minimalR = minimalR;
     }

src/eva2/optimization/strategies/BinaryScatterSearch.java

@@ -30,8 +30,6 @@ import java.util.BitSet;
  */
 @Description("A basic implementation of a Binary ScatterSearch")
 public class BinaryScatterSearch implements InterfaceOptimizer, java.io.Serializable, InterfacePopulationChangedEventListener {
-
-    private static boolean TRACE = false;
     transient private InterfacePopulationChangedEventListener populationChangedEventListener = null;
     private String identifier = "BinaryScatterSearch";
     private int MaxImpIter = 5;
@@ -236,17 +234,9 @@ public class BinaryScatterSearch implements InterfaceOptimizer, java.io.Serializ
         int numToInit = this.poolSize - pop.size();
         if (numToInit > 0) {
             pop.addAll(generateG1((int) (numToInit * this.g1)));
-            if (TRACE) {
+
-                System.out.println("s1: " + pop.size());
-            }
             generateG2(pop, (int) (numToInit * this.g2));
-            if (TRACE) {
-                System.out.println("s2: " + pop.size());
-            }
             generateG3(pop, poolSize - pop.size());
-            if (TRACE) {
-                System.out.println("s3: " + pop.size());
-            }
         }
         return pop;
     }
@@ -272,8 +262,9 @@ public class BinaryScatterSearch implements InterfaceOptimizer, java.io.Serializ
      * 000...000, then 010101...01, 101010...10, 001001001...001,
      * 110110110...110 and so on
      *
-     * @param pop the initial Population
+     * @param targetSize The size of the new Population
-     * @return the new Population
+     * @param template The template individual to use
+     * @return a new Population
      */
     public static Population generateG1Pop(int targetSize, AbstractEAIndividual template) {
         boolean method1 = true;
@@ -716,8 +707,7 @@ public class BinaryScatterSearch implements InterfaceOptimizer, java.io.Serializ
             // generate a new Pool
             this.pool = new Population();
             ArrayList<Population> newSubsets = generateSubsets();
-            for (int i = 0; i < newSubsets.size(); i++) {
+            for (Population s : newSubsets) {
-                Population s = newSubsets.get(i);
                 AbstractEAIndividual x = combineSolution(s);
                 if (!contains((InterfaceDataTypeBinary) x, this.pool) && this.pool.size() <= this.poolSize) {
                     this.pool.add(x);

src/eva2/optimization/strategies/ClusterBasedNichingEA.java

@@ -69,7 +69,6 @@ public class ClusterBasedNichingEA implements InterfacePopulationChangedEventLis
     private int populationSize = 50;
     private int convergedCnt = 0;
     private int collisions = 0;
-    private static boolean TRACE = false, TRACE_STATE = false, TRACE_EVTS = false;
     private int showCycle = 0;
     transient private TopoPlot topologyPlot;
     private int haltingWindow = 15;
@@ -450,88 +449,43 @@ public class ClusterBasedNichingEA implements InterfacePopulationChangedEventLis
             return ret;
         } else {
             return (histComparator.compare(firstIndy, secIndy) > 0);
-//    		return (secIndy.isDominatingDebConstraints(firstIndy));
         }
     }
 
     private Population optimizeSpecies(Population species, boolean minorPlot) {
         optimizer.setPopulation(species);
-//    	optimizer.initializeByPopulation(species, false);
         if (optimizer instanceof EvolutionStrategies) {
             EvolutionStrategies es = (EvolutionStrategies) optimizer;
             int mu = Math.max(1, (int) (muLambdaRatio * species.size()));
             if (mu >= species.size()) {
-                if (TRACE) {
-                    System.err.println("warning, muLambdaRatio produced mu >= lambda.. reducing to mu=lambda-1");
-                }
                 mu = Math.max(1, species.size() - 1);
             }
             es.setMu(mu);
             es.setLambda(species.size());
-            if (TRACE) {
-                System.out.println("mu: " + es.getMu() + " / lambda: " + es.getLambda());
-            }
-        }
-        if (TRACE) {
-            System.out.println("Bef: spec size: " + species.size() + ", target size " + species.getTargetSize());
-            System.out.println("Best bef: " + BeanInspector.toString(optimizer.getPopulation().getBestFitness()));
         }
 
         if (BeanInspector.hasMethod(optimizer, "getLastModelPopulation", null) != null) {
             Object pc = BeanInspector.callIfAvailable(optimizer, "getLastTrainingPatterns", null);
-//   			System.out.println("MAPSO train set bef optSpec: " + BeanInspector.callIfAvailable(pc, "getStringRepresentation", null));
         }
 
         this.optimizer.optimize();
         Population retPop = optimizer.getPopulation();
-
-        if (TRACE) {
-            System.out.println("Aft: spec size: " + retPop.size() + ", target size " + retPop.getTargetSize());
-            System.out.println("Best aft: " + BeanInspector.toString(retPop.getBestFitness()));
-        }
         if (retPop.size() != retPop.getTargetSize()) {
-            if (TRACE) {
-                System.out.println("correcting popsize after opt: " + retPop.getTargetSize() + " to " + retPop.size());
-            }
             retPop.synchSize();
         }
-
-//    	if (useDistraction) { // distraction step
-//    		if ((distraction != null) && (!distraction.isEmpty())) {
-//    			System.out.println("Distraction step!!!");
-//    			boolean distrHappened = false;
-//    			for (int i=0; i<retPop.size(); i++) {
-//    				distrHappened |= distraction.applyDistractionTo(retPop.getEAIndividual(i));
-//    			}
-//    			if (distrHappened) {
-////    				Object distrList = species.getData("distraction");
-////    				if (distr)
-////    				species.addData("distr", value)
-//    			}
-//    		}
-//    	}
         return retPop;
     }
 
     @Override
     public void optimize() {
         Population reinitPop = null;
-        if (TRACE_STATE) {
-            printState("---- CBN Optimizing", doomedPopulation);
-            //            System.out.println("-Funcalls: "+undifferentiatedPopulation.getFunctionCalls());
-        }
         if (doomedPopulation.size() > 0) {
             reinitPop = this.initializeIndividuals(doomedPopulation.size()); // do not add these to undifferentiated yet, that would mess up the evaluation count
             doomedPopulation.clear();
-//    		if (TRACE) 
-//    			System.out.println("At " + undifferentiatedPopulation.getFunctionCalls() + " reinited " + reinitPop.size() + " indies... ");
         }
         int countIndies = (reinitPop != null ? reinitPop.size() : 0) + undifferentiatedPopulation.size();
-        for (int i = 0; i < species.size(); i++) {
+        for (Population specy1 : species) {
-            countIndies += species.get(i).size();
+            countIndies += specy1.size();
-        }
-        if (TRACE) {
-            System.out.println("NumIndies: " + countIndies);
         }
         if (this.showCycle > 0) {
             if (undifferentiatedPopulation.getGeneration() <= 1) {
@@ -550,7 +504,6 @@ public class ClusterBasedNichingEA implements InterfacePopulationChangedEventLis
         // optimize D_0
         this.undifferentiatedPopulation.synchSize();
         if (undifferentiatedPopulation.size() > 0) {
-//            this.capMutationRate(this.undifferentiatedPopulation, 0); // MK this sets mutation rate to 0! why? possibly to guarantee contraction of the species?
             undifferentiatedPopulation.putData(InterfaceSpeciesAware.populationTagKey, InterfaceSpeciesAware.explorerPopTag);
             undifferentiatedPopulation = optimizeSpecies(undifferentiatedPopulation, false);
         } else {
@@ -560,40 +513,17 @@ public class ClusterBasedNichingEA implements InterfacePopulationChangedEventLis
         Population curSpecies;
         // optimize the clustered species
         for (int i = this.species.size() - 1; i >= 0; i--) {
-            if (TRACE) {
-                System.out.println("-Deme " + i + " size: " + this.species.get(i).size());
-            }
             curSpecies = this.species.get(i);
             curSpecies.setFunctionCalls(0);
             curSpecies.synchSize();
-//            if (isActive(curSpecies)) { // Lets have only active species...
             if ((haltingWindow > 0) && (this.testSpeciesForConvergence(curSpecies))) {
-///////////////////////////////////////////// Halting Window /////////////////////////////////////////////////
-//                    if (this.debug) {
-//                        System.out.println("Undiff.Size: " + this.undifferentiatedPopulation.size() +"/"+this.undifferentiatedPopulation.getPopulationSize());
-//                        System.out.println("Diff.Size  : " + ((Population)this.species.get(i)).size() +"/"+((Population)this.species.get(i)).getPopulationSize());
-//                    }
                 convergedCnt++;
-                if (TRACE_EVTS) {
-                    System.out.println("!!!! Converged Spec!");
-                }
-                if (TRACE) {
-                    testSpeciesForConvergence(curSpecies);
-                    System.out.print("--Converged: " + convergedCnt + " - " + testSpeciesForConvergence(curSpecies));
-                }
-                if (TRACE) {
-                    System.out.println(curSpecies.getBestEAIndividual());
-                }
-
-                // memorize the best one....
-//                    AbstractEAIndividual best = (AbstractEAIndividual)curSpecies.getBestEAIndividual().getClone();
                 AbstractEAIndividual best = curSpecies.getBestHistoric(); // usually we want the best alltogether
                 if (best == null) {
                     best = (AbstractEAIndividual) curSpecies.getBestEAIndividual().getClone();
                 }
                 int toReinit = 0;
                 populationArchive.add(best);
-//                    	System.out.println((""+ population.getFunctionCalls() + " " + (BeanInspector.toString(best.getDoublePosition())).replaceAll(";|\\[|\\]", "")));
                 species.remove(i);  // remove the converged Species
                 toReinit = curSpecies.size();
                 // those will not be optimized anymore, so we dont need to doom them, but can directly add them to undiff!
@@ -609,17 +539,13 @@ public class ClusterBasedNichingEA implements InterfacePopulationChangedEventLis
 //            }
             // This is necessary to keep track of the function calls needed
             undifferentiatedPopulation.incrFunctionCallsBy(curSpecies.getFunctionCalls());
-            if (TRACE) {
-                System.out.println("### funcalls: " + undifferentiatedPopulation.getFunctionCalls());
-            }
         }
 
-        //////////////////////
         synchronized (population) { // fill the population instance with the current individuals from undiff, spec, etc.
             this.population = (Population) this.undifferentiatedPopulation.clone();
             population.setUseHistory(true);
-            for (int i = 0; i < this.species.size(); i++) {
+            for (Population specy : this.species) {
-                this.population.addPopulation(this.species.get(i));
+                this.population.addPopulation(specy);
             }
             if (doomedPopulation.size() > 0) {
                 population.addPopulation(reinitPop);
@@ -627,34 +553,15 @@ public class ClusterBasedNichingEA implements InterfacePopulationChangedEventLis
             population.synchSize();
         }
 
-        //////////////////////
-        if ((this.undifferentiatedPopulation.getFunctionCalls() + (reinitPop == null ? 0 : (reinitPop.size()))) % this.populationSize != 0) {
-            if (TRACE) {
-                System.out.println("### mismatching number of funcalls, inactive species?");
-            }// Correcting by " + (populationSize - (undifferentiatedPopulation.getFunctionCalls() % populationSize)));
-//        	if (TRACE) System.out.println("### undiff " + ((isActive(undifferentiatedPopulation)) ? "active!" : "inactive!"));
-//        	undifferentiatedPopulation.incrFunctionCallsBy(populationSize - (undifferentiatedPopulation.getFunctionCalls() % populationSize));
-        } //else if (TRACE) System.out.println("### undiff active: " + isActive(undifferentiatedPopulation));
-
         // possible species differentiation and convergence
         if (this.undifferentiatedPopulation.getGeneration() % this.speciesCycle == 0) {
-            if (TRACE) {
-                System.out.println("Species cycle:");
-            }
             initClustering();
 
             if (this.useSpeciesDifferentiation) {
-///////////////////////////// species differentiation phase
-                if (TRACE) {
-                    printState("---Species Differentation", reinitPop);
-                }
                 Population[] clusters;
                 ArrayList<Population> newSpecies = new ArrayList<Population>();
                 //cluster the undifferentiated population
                 clusters = this.caForSpeciesDifferentation.cluster(this.undifferentiatedPopulation, population);
-                if (TRACE) {
-                    System.out.println("clustered undiff to " + clusters.length);
-                }
                 for (int j = 1; j < clusters.length; j++) { // loop new clusters
                     splitFromFirst(undifferentiatedPopulation, clusters[j], false);
                     newSpecies.add(clusters[j]);
@@ -662,12 +569,8 @@ public class ClusterBasedNichingEA implements InterfacePopulationChangedEventLis
                 replaceUndifferentiated(clusters[0]);
                 for (int i = 0; i < this.species.size(); i++) { // loop old species
                     curSpecies = this.species.get(i);
-//                    if (curSpecies.size()>minGroupSize) { // only active populations are clustered
                     // check if a species has differentiated any further
                     clusters = this.caForSpeciesDifferentation.cluster(curSpecies, population);
-                    if (TRACE) {
-                        System.out.println("clustered " + i + " to " + clusters.length);
-                    }
                     if (clusters[0].size() > 0) {
                         mergeToFirst(undifferentiatedPopulation, clusters[0], false);
                     }
@@ -683,17 +586,8 @@ public class ClusterBasedNichingEA implements InterfacePopulationChangedEventLis
                         newSpecies.add(clusters[j]);
 
                     }
-//                    } else {
-//                        // small populations are kept directly
-//                        newSpecies.add(curSpecies);
-//                    }
                 }
                 this.species = newSpecies;
-                if (TRACE) {
-                    printState("---After differentiation", reinitPop);
-                }
-
-                //if (this.show) this.plot();
             } // end of species differentiation
 
             // plot the populations
@@ -704,17 +598,10 @@ public class ClusterBasedNichingEA implements InterfacePopulationChangedEventLis
             }
 
             if (this.mergeSpecies && (species.size() > 0)) {
-///////////////////////////// species merging phase
-                if (TRACE) {
-                    System.out.println("-Species merge:");
-                }
                 // first test if loners belong to any species
                 int[] assocSpec = caForSpeciesMerging.associateLoners(undifferentiatedPopulation, species.toArray(new Population[species.size()]), population);
                 for (int i = undifferentiatedPopulation.size() - 1; i >= 0; i--) { // backwards or die!
                     if (assocSpec[i] >= 0) {
-                        if (TRACE_EVTS) {
-                            System.out.println("!!! Loner merge to " + i);
-                        }
                         // loner i should be merged to species assocSpec[i]
                         AbstractEAIndividual tmpIndy = (AbstractEAIndividual) this.undifferentiatedPopulation.get(i);
                         if (topologyPlot != null) {
@@ -724,9 +611,6 @@ public class ClusterBasedNichingEA implements InterfacePopulationChangedEventLis
                         species.get(assocSpec[i]).add(tmpIndy); // TODO merge information from loners?
                     }
                 }
-                if (TRACE) {
-                    printState("---After loner-merges", reinitPop);
-                }
                 Population spec1, spec2;
                 // test if species are close to already archived solutions - deactivate them if so
                 assocSpec = caForSpeciesMerging.associateLoners(populationArchive, species.toArray(new Population[species.size()]), population);
@@ -740,16 +624,6 @@ public class ClusterBasedNichingEA implements InterfacePopulationChangedEventLis
                             // the species has not yet been deactivated
                             specToRemove.add(assocSpec[i]);
                             collisions++;
-                            if (TRACE) {
-                                System.out.println("Inactive merge - resetting " + spec1.size() + " surplus indies");
-                            }
-                            if (spec1.getBestEAIndividual().isDominating(aIndy)) {
-                                // update the archived one with the better one? No rather not - it may happen that a large species is assoctiated which is quite large and spans over several optima - in that case an earlier found may get lost
-//                				populationArchive.set(i, spec1.getBestEAIndividual());
-                            }
-                            if (TRACE_EVTS) {
-                                System.out.println("!!! Reinit Spec " + assocSpec[i] + ", fit " + spec1.getBestEAIndividual());
-                            }
                             doomedPopulation.addPopulation(spec1);
                         }
                     }
@@ -760,15 +634,9 @@ public class ClusterBasedNichingEA implements InterfacePopulationChangedEventLis
                     if (specIndex > lastRemoved) {
                         System.err.println("Stupid queue!!!");
                     }
-                    if (TRACE) {
-                        System.out.println("Removing species at index " + specIndex);
-                    }
                     species.remove(specIndex); // warning, dont try to remove Integer object but index i!
                     lastRemoved = specIndex;
                 }
-                if (TRACE) {
-                    printState("---After archive-merges", reinitPop);
-                }
                 // Now test if species should be merged among each other
                 for (int i1 = 0; i1 < this.species.size(); i1++) {
                     spec1 = this.species.get(i1);
@@ -776,39 +644,24 @@ public class ClusterBasedNichingEA implements InterfacePopulationChangedEventLis
                         spec2 = this.species.get(i2);
                         if (this.caForSpeciesMerging.mergingSpecies(spec1, spec2, population)) {
 
-                            if (TRACE_EVTS || TRACE) {
-                                System.out.println("!!! -Merging species (" + i1 + ", " + i2 + ") [" + spec1.size() + "/" + spec2.size() + "]");
-                            }
                             mergeToFirst(spec1, spec2, true);
                             this.species.remove(i2);
                             i2--;
                         }
                     }
                 }
-                if (TRACE) {
-                    printState("---After merging", reinitPop);
-                }
             } /// end of species merging
 
             if (maxSpeciesSize >= minGroupSize) {
                 // reinit worst n individuals from all species which are too large
-                for (int i = 0; i < species.size(); i++) {
+                for (Population curSpec : species) {
-                    Population curSpec = species.get(i);
                     if (curSpec.size() > maxSpeciesSize) {
-                        if (TRACE_EVTS) {
-                            System.out.println("!!! Reinit indies " + (maxSpeciesSize - curSpec.size()));
-                        }
                         ArrayList<AbstractEAIndividual> sorted = curSpec.getSorted(reduceSizeComparator);
                         for (int k = maxSpeciesSize; k < sorted.size(); k++) {
                             if (curSpec.remove(sorted.get(k))) {
                                 doomedPopulation.add(sorted.get(k));
                             }
                         }
-//            			reinitCount = sorted.size()-maxSpeciesSize;
-//            			curSpec.setPopulationSize(maxSpeciesSize);
-//            			if (TRACE) System.out.println("Reduced spec " + i + " to size " + curSpec.size() + ", reinit of " + reinitCount + " indies immanent...");
-//                        this.undifferentiatedPopulation.addPopulation(this.initializeIndividuals(reinitCount));
-//                        this.undifferentiatedPopulation.setPopulationSize(this.undifferentiatedPopulation.getPopulationSize()+reinitCount);
                     }
                 }
             }
@@ -821,40 +674,21 @@ public class ClusterBasedNichingEA implements InterfacePopulationChangedEventLis
         }
         undifferentiatedPopulation.setTargetSize(undifferentiatedPopulation.size());
         // output the result
-        if (TRACE) {
-            System.out.println("-Funcalls: " + this.undifferentiatedPopulation.getFunctionCalls());
-        }
 
         synchronized (population) { // fill the population instance with the current individuals from undiff, spec, etc.
             this.population = (Population) this.undifferentiatedPopulation.clone();
             population.setUseHistory(true);
-            for (int i = 0; i < this.species.size(); i++) {
+            for (Population specy : this.species) {
-                this.population.addPopulation(this.species.get(i));
+                this.population.addPopulation(specy);
             }
             if (doomedPopulation.size() > 0) {
                 population.addPopulation(doomedPopulation);
             } // this is just so that the numbers match up...
             population.synchSize();
-            if (TRACE) {
-                System.out.println("Doomed size: " + doomedPopulation.size());
-                System.out.println("Population size: " + this.population.size());
-            }
             if (population.size() != populationSize) {
                 System.err.println("Warning: Invalid population size in CBNEA! " + population.size());
             }
-            if (TRACE_STATE) {
-                printState("---- EoCBN", doomedPopulation);
-                System.out.println("Archive: " + populationArchive.getStringRepresentation());
-            }
         }
-//        if (TRACE) {
-//        	// this is just a test adding all species centers as distractors with high strength
-//        	Distraction distr = new Distraction(5., 0, species);
-//        	if (!distr.isEmpty()) {
-//        		double[] distVect = distr.calcDistractionFor(undifferentiatedPopulation.getBestEAIndividual());
-//        		System.out.println("species distract best towards " + BeanInspector.toString(distVect));
-//        	}
-//        }
 
         this.firePropertyChangedEvent(Population.NEXT_GENERATION_PERFORMED);
     }
@@ -866,9 +700,6 @@ public class ClusterBasedNichingEA implements InterfacePopulationChangedEventLis
         if (getClusterDiffDist() > 0) { // assume that it should be set
             if (this.caForSpeciesDifferentation instanceof InterfaceClusteringDistanceParam) {
                 ((InterfaceClusteringDistanceParam) caForSpeciesDifferentation).setClustDistParam(getClusterDiffDist());
-                if (TRACE) {
-                    System.out.println("### Clustering distance parameter set to " + getClusterDiffDist());
-                }
             } else {
                 EVAERROR.errorMsgOnce("Warning: cluster distance is defined in CBN  but the clustering method " + caForSpeciesDifferentation.getClass() + " cant interpret it!");
             }
@@ -876,49 +707,16 @@ public class ClusterBasedNichingEA implements InterfacePopulationChangedEventLis
         this.caForSpeciesDifferentation.initClustering(population);
     }
 
-//
-//    /**
-//     * Unite all current species and the undiff. pop and return
-//     * the merged set. Note that data such as generation, evaluations etc
-//     * are not copied!
-//     * 
-//     * @return
-//     */
-//	private Population getCurrentPop() {
-//		Population pop = new Population(getPopulationSize());
-//		pop.addPopulation(undifferentiatedPopulation);
-//		for (int i=0; i<species.size(); i++) pop.addPopulation(species.get(i));
-//		pop.synchSize();
-//		return pop;
-//	}
-
     /**
      * Replace the undifferentiated population with the given one.
      *
      * @param pop
      */
     private void replaceUndifferentiated(Population pop) {
-//        System.out.println("Adding " + pop.size() + " as undiff.");
         undifferentiatedPopulation.clear();
         undifferentiatedPopulation.addPopulation(pop);
     }
 
-    private void printState(String headline, Population reinit) {
-        System.out.print(headline + ", Gen. " + this.undifferentiatedPopulation.getGeneration());
-        System.out.print(" - Undiff.: " + specTag(undifferentiatedPopulation));
-        System.out.print(", Demes: ");
-        int sum = undifferentiatedPopulation.size() + (reinit == null ? 0 : reinit.size());
-        if (species.size() > 0) {
-            sum += species.get(0).size();
-            System.out.print(specTag(species.get(0)));
-            for (int i = 1; i < species.size(); i++) {
-                System.out.print(", " + specTag(species.get(i)));
-                sum += species.get(i).size();
-            }
-        }
-        System.out.println(", reinit: " + (reinit == null ? 0 : reinit.size()) + ", sum: " + sum);
-    }
-
     private String specTag(Population spec) {
         return spec.size() + "(" + spec.getGeneration() + ((spec.hasData("MAPSOModelInformation")) ? "/" + (BeanInspector.callIfAvailable(spec.getData("MAPSOModelInformation"), "getStringRepresentation", null)) : "") + ")";
     }
@@ -927,11 +725,11 @@ public class ClusterBasedNichingEA implements InterfacePopulationChangedEventLis
      * Merge two species by adding the second to the first. Keep the longer
      * history. The second species should be deactivated after merging.
      *
-     * @param pop1
+     * @param spec1
-     * @param pop2
+     * @param spec2
+     * @param plot
      */
     protected void mergeToFirst(Population spec1, Population spec2, boolean plot) {
-//    	System.out.println("Merging " + spec2.size() + " to " + spec1.size());
         if (plot && (topologyPlot != null)) {
             plotLine(topologyPlot, spec1.getBestEAIndividual(), spec2.getBestEAIndividual());
         }

src/eva2/optimization/strategies/ClusteringHillClimbing.java

@@ -40,7 +40,6 @@ public class ClusteringHillClimbing implements InterfacePopulationChangedEventLi
         InterfaceOptimizer, Serializable, InterfaceAdditionalPopulationInformer {
 
     transient private InterfacePopulationChangedEventListener populationChangedEventListener;
-    public static final boolean TRACE = false;
     transient private String identifier = "";
     private Population population = new Population();
     private transient Population archive = new Population();
@@ -48,7 +47,6 @@ public class ClusteringHillClimbing implements InterfacePopulationChangedEventLi
     private int hcEvalCycle = 1000;
     private int initialPopSize = 100;
     private int loopCnt = 0;
-    //   	private int								baseEvalCnt = 0;
     private int notifyGuiEvery = 50;
     private double sigmaClust = 0.01;
     private double minImprovement = 0.000001;
@@ -198,9 +196,6 @@ public class ClusteringHillClimbing implements InterfacePopulationChangedEventLi
             evalsNow = hcEvalCycle;
         }
         do {
-            if (TRACE) {
-                System.out.println("evalCycle: " + hcEvalCycle + ", evals now: " + evalsNow);
-            }
             popD = PostProcess.clusterLocalSearch(localSearchMethod, population, (AbstractOptimizationProblem) optimizationProblem, sigmaClust, evalsNow, 0.5, mutator);
             //		(population, (AbstractOptimizationProblem)problem, sigmaClust, hcEvalCycle - (population.getFunctionCalls() % hcEvalCycle), 0.5);
             if (popD.head().getFunctionCalls() == funCallsBefore) {
@@ -210,21 +205,12 @@ public class ClusteringHillClimbing implements InterfacePopulationChangedEventLi
         } while (popD.head().getFunctionCalls() == funCallsBefore);
         improvement = popD.tail();
         population = popD.head();
-        if (TRACE) {
-            System.out.println("num inds after clusterLS: " + population.size());
-        }
 
         popD.head().setGeneration(population.getGeneration() + 1);
 
         if (doReinitialization && (improvement < minImprovement)) {
-            if (TRACE) {
-                System.out.println("improvement below " + minImprovement);
-            }
             if ((localSearchMethod != PostProcessMethod.hillClimber) || (mutator.getSigma() < stepSizeThreshold)) { // reinit!
                 // is performed for nm and cma, and if hc has too low sigma
-                if (TRACE) {
-                    System.out.println("REINIT!!");
-                }
 
                 if (localSearchMethod == PostProcessMethod.hillClimber) {
                     mutator.setSigma(initialStepSize);
@@ -252,12 +238,8 @@ public class ClusteringHillClimbing implements InterfacePopulationChangedEventLi
                     System.err.println("Invalid case in ClusteringHillClimbing!");
                 }
                 mutator.setSigma(mutator.getSigma() * reduceFactor);
-                if (TRACE) {
-                    System.out.println("mutation stepsize reduced to " + mutator.getSigma());
-                }
             }
         }
-//		System.out.println("funcalls: " + evalCnt);
         this.firePropertyChangedEvent(Population.NEXT_GENERATION_PERFORMED);
 
     }
@@ -266,17 +248,10 @@ public class ClusteringHillClimbing implements InterfacePopulationChangedEventLi
     public void registerPopulationStateChanged(Object source, String name) {
         // The events of the interim hill climbing population will be caught here 
         if (name.compareTo(Population.FUN_CALL_INTERVAL_REACHED) == 0) {
-//			if ((((Population)source).size() % 50) > 0) {
-//				System.out.println("bla");
-//			}
             // set funcalls to real value
             population.setFunctionCalls(((Population) source).getFunctionCalls());
-//			System.out.println("FunCallIntervalReached at " + (((Population)source).getFunctionCalls()));
             this.firePropertyChangedEvent(Population.NEXT_GENERATION_PERFORMED);
         }
-        // do not react to NextGenerationPerformed
-        //else System.err.println("ERROR, event was " + name);
-
     }
 
     /**

src/eva2/optimization/strategies/EsDpiNiching.java

@@ -91,7 +91,6 @@ import java.util.Formatter;
         + "in parallel, which are reclustered in each iteration based on the dynamic peak set.")
 public class EsDpiNiching implements InterfaceOptimizer, Serializable, InterfaceAdditionalPopulationInformer, InterfacePopulationChangedEventListener {
 
-    private static final boolean TRACE = false, TRACE_DEMES = false;
     private double nicheRadius = 0.3;
     private int expectedPeaks = 5;
     private int explorerPeaks = 0;
@@ -250,7 +249,6 @@ public class EsDpiNiching implements InterfaceOptimizer, Serializable, Interface
             population.incrFunctionCallsBy(peakOpts[i].getPopulation().getFunctionCalls());
         }
         // possibly reduce immigrants to produce a conforming number of initial evaluations (same number as in later iterations: numPeaks*muLambda+immigrants)
-//		int initialImmigrants = (fullNumPeaks()*lambdaPerPeak+getNumRndImmigrants())-(fullNumPeaks()*muPerPeak+getNumRndImmigrants());
         if (getNumRndImmigrants() > 0) {
             generateEvalImmigrants(getNumRndImmigrants());
         }
@@ -319,7 +317,6 @@ public class EsDpiNiching implements InterfaceOptimizer, Serializable, Interface
             }
             r = 0.5 * Math.sqrt(dim);
         }
-//		setNicheRadius(r*Math.pow(numExpectedPeaks, -1./(double)dim));
         return r * Math.pow(numExpectedOptima, -1. / (double) dim);
     }
 
@@ -347,8 +344,6 @@ public class EsDpiNiching implements InterfaceOptimizer, Serializable, Interface
     }
 
     private int increaseExpectedPeaksCriterion() {
-//		if ((getPopulation().getGeneration() % 5) == 0) return 1;
-//		else return 0;
         if (isDoNumPeakAdaption() && (archive.size() >= getExpectedPeaks())) {
             return (int) Math.max(((double) getExpectedPeaks()) * 1.2, 2.);
         } else {
@@ -374,9 +369,6 @@ public class EsDpiNiching implements InterfaceOptimizer, Serializable, Interface
         if (increaseExpectedPeaksCriterion() > 0) {
             addExpectedPeaks(increaseExpectedPeaksCriterion());
         }
-        if (TRACE) {
-            System.out.println("--- FULL POP SIZE: " + population.size() + " , funcalls: " + population.getFunctionCalls() + ", gen " + population.getGeneration());
-        }
         ClusteringDynPeakIdent dpiClustering = new ClusteringDynPeakIdent(getExpectedPeaks(), getLambdaPerPeak(), nicheRadius, true, metric);
         // perform dynamic peak identification resulting in the dynamic peak set dps
         dpiClustering.initClustering(population);
@@ -386,20 +378,12 @@ public class EsDpiNiching implements InterfaceOptimizer, Serializable, Interface
             peakPopSet[i].removePopulationChangedEventListener(this);
         }
         setGeneration(population.getGeneration(), peakPopSet);
-        if (TRACE_DEMES) {
-            printDemes("After clustering: ", peakPopSet);
-        }
 
         int curNumPeaks = peakPopSet.length - 1;
 
-//		boolean copyHashFromParents=true;
         // transfer population hash data along the peaks -> for each peak chose the original last population
         // and transfer the data to the new cluster
-//		if (copyHashFromParents) {
         copyDataFromParents(peakPopSet);
-//		} else {
-//			copyDataFromClosest(clusteredPeakPops);
-//		}
 
         int reqNewPeaks = 0;
         if (curNumPeaks < getExpectedPeaks()) {
@@ -427,10 +411,6 @@ public class EsDpiNiching implements InterfaceOptimizer, Serializable, Interface
         // add missing and explorer peaks as new random individuals (or old unclustered ones)
         peakPopSet = generateMissingSpecies(peakPopSet, getMuPerPeak(), reqNewPeaks, false);
 
-        if (TRACE_DEMES) {
-            printDemes("After expansion: ", peakPopSet);
-        }
-
         if (archive != null && (archive.size() > 0) && isReinitOnCollision()) {
             double origNicheRad = dpiClustering.getNicheRadius();
             dpiClustering.setNicheRadius(collisionDetNicheRadius);
@@ -443,28 +423,12 @@ public class EsDpiNiching implements InterfaceOptimizer, Serializable, Interface
                         // the new found species is actually better than the archived solution
                         archive.set(i, peakPopSet[assoc[i]].getBestEAIndividual().clone()); // replace archived indy
                     }
-                    if (TRACE) {
-                        System.out.println(" Converged on archived solution.. resetting peak pop " + assoc[i]);
-                    }
                     peakPopSet[assoc[i]] = initRandomPeakPop(getMuPerPeak());
                 }
             }
             dpiClustering.setNicheRadius(origNicheRad);
-            if (TRACE_DEMES) {
-                printDemes("After archivie-merge: ", peakPopSet);
-            }
         }
 
-        if (TRACE) {
-            for (int k = 0; k < peakPopSet.length - 1; k++) {
-                for (int j = k + 1; j < peakPopSet.length; j++) {
-                    Population cut = peakPopSet[k].setCut(peakPopSet[j]);
-                    if (cut.size() > 0) {
-                        System.err.println("duplicate inherited in EsDpiNiching! OK if explorer peaks exist that are not always reinited and " + j + ">" + getExpectedPeaks() + " and " + k + "==0.");
-                    }
-                }
-            }
-        }
         plot = null;
         // now generate the lambda offsprings
 //		nextGeneration = this.generateEvalChildren(dps); // create lambda new ones from mu parents
@@ -475,9 +439,6 @@ public class EsDpiNiching implements InterfaceOptimizer, Serializable, Interface
             if (curSpecies.size() == 1 && (!isAllowSingularPeakPops())) {
                 // Quoting SB05: "In case that the niche only contains one individual, the second parent will be the best indidivual of another niche."
                 AbstractEAIndividual bestOther = (AbstractEAIndividual) selectBestFromOtherSpecies(clustIndex, peakPopSet).clone();
-                if (TRACE) {
-                    System.out.println("Adding best from other species: " + bestOther);
-                }
                 curSpecies.add(bestOther);
             } else if (curSpecies.size() == 0) {
                 System.err.println("Warning, empty niche population in EsDpiNiching!");
@@ -497,19 +458,10 @@ public class EsDpiNiching implements InterfaceOptimizer, Serializable, Interface
             if (doDraw(population.getGeneration())) {
                 drawPeakPop("" + clustIndex, curSpecies);
             }
-            if (TRACE) {
-                System.out.println("Optimizing cluster index " + (clustIndex) + ", size " + curSpecies.size());
-            }
             peakOpts[clustIndex - 1].optimize(); // !!!!!!!! Actual optimization step
             optimizedSpecies = peakOpts[clustIndex - 1].getPopulation();
             optimizedSpecies.putData(origPeakIndyKey, curPeak);
             population.incrFunctionCallsBy(optimizedSpecies.size());
-//        	optimizedSpecies.incrGeneration(); // is already done in the .optimize() call above
-//        	optimizedSpecies.incrFunctionCallsBy(optimizedSpecies.size());
-            if (TRACE) {
-                System.out.println("  ..." + optimizedSpecies.size() + " more funcalls... ");
-            }
-
         }
 
         // we may have a problem if, by chance, all species have been deactivated simultaneously AND there are no unclustered !
@@ -518,21 +470,6 @@ public class EsDpiNiching implements InterfaceOptimizer, Serializable, Interface
             peakOpts[0].getPopulation().addPopulation(initRandomPeakPop(getMuPerPeak()));
         }
 
-        if (TRACE) {
-            for (int k = 0; k < peakPopSet.length - 1; k++) {
-                for (int j = k + 1; j < peakPopSet.length; j++) {
-                    Population cut = peakPopSet[k].setCut(peakPopSet[j]);
-                    if (cut.size() > 1) {
-                        // one may happen after a cluster had a size of one, since then another leader is added
-                        if (cut.size() == 2 && (peakPopSet[k].size() == 2) && (peakPopSet[j].size() == 2)) {
-                            // two may happen since they can be added reciprocally to each other
-                        } else {
-                            System.err.println("duplicate indy in EsDpiNiching. OK if explorer peaks exist that are not always reinited and " + j + ">" + getExpectedPeaks() + " and " + k + "==0.");
-                        }
-                    }
-                }
-            }
-        }
         if (doEtaPreselection) { // this basically replaces ES-environment selection
             // select the eta best from the offspring per peak population
             // fill up to muPerPeak by adding from the old peak population
@@ -545,9 +482,6 @@ public class EsDpiNiching implements InterfaceOptimizer, Serializable, Interface
                     System.err.println("Warning: fewer clusters than expected peaks in EsDpiNiching!");
                     offspring.clear(); // empty set to avoid duplicates!
                 } else {
-                    if (TRACE) {
-                        System.out.println("EtaPresel: from " + offspring.size() + " offspring selecting " + eta);
-                    }
                     Population selected = selBest.selectFrom(offspring, eta);
                     if (!selected.isSubSet(offspring)) {
                         System.err.println("fatal problem in EsDpiNiching!!!");
@@ -558,33 +492,16 @@ public class EsDpiNiching implements InterfaceOptimizer, Serializable, Interface
                     int delta = muPerPeak - eta;
                     if (delta > 0) {
                         Population filterPeakPop = peakPopSet[i + 1].filter(selected);
-                        if (TRACE) {
-                            System.out.println("Adding " + Math.min(delta, filterPeakPop.size()) + " from peak population.");
-                        }
                         // (few) duplicates may happen because parents are copied to another peak population
                         // if a cluster had a size of 1 AND parents may survive due to elitism.
                         selected.addPopulation(selBest.selectFrom(filterPeakPop, Math.min(delta, filterPeakPop.size())), false);
                         if (selected.size() < muPerPeak && (addLonersToPeaks)) {
                             delta = Math.min(muPerPeak - selected.size(), loners.size());
-                            if (TRACE) {
-                                System.out.println("filling up with lucky loners: " + delta);
-                            }
                             // fill up with loner indies
                             SelectRandom selRnd = new SelectRandom(false); // no duplicates wanted!
                             Population luckyLosers = selRnd.selectFrom(loners, delta);
                             selected.addPopulation(luckyLosers, true);
                             loners.removeMembers(luckyLosers, true);
-                            // fill up with random indies
-                            //        				Population randomNewIndies = new Population(lambdaPerPeak - selected.size());
-                            //        				problem.initializePopulation(randomNewIndies); // function calls??
-                            //        				selected.addAll(randomNewIndies);
-                        }
-                    }
-                    if (TRACE) {
-                        for (int k = 0; k < i; k++) {
-                            if (selected.setCut(peakOpts[k].getPopulation()).size() > 2) { //one may happen after a cluster had size one (see above) 
-                                System.err.println("Warning, nonempty set cut between " + k + " and " + i + " !");
-                            }
                         }
                     }
                     peakOpts[i].population.clear();
@@ -595,7 +512,7 @@ public class EsDpiNiching implements InterfaceOptimizer, Serializable, Interface
                 }
             }
         }
-//        System.out.println("Best of second peak: " + clusteredPeakPops[2].getBestEAIndividual());
+
         if (doDraw(population.getGeneration()) && archive != null) {
             for (int i = 0; i < this.archive.size(); i++) {
                 ClusterBasedNichingEA.plotIndy(plot, 'x', (InterfaceDataTypeDouble) archive.get(i));
@@ -605,7 +522,6 @@ public class EsDpiNiching implements InterfaceOptimizer, Serializable, Interface
             generateEvalImmigrants(getNumRndImmigrants());
         }
         collectPopulationIncGen(population, peakOpts, randomNewIndies);
-        //this.firePropertyChangedEvent(Population.NEXT_GENERATION_PERFORMED); // moved this to registerPopulationStateChanged which is called from the population
     }
 
     private Population deactivateSpecies(int clustIndex, boolean resetRandomly) {
@@ -634,7 +550,6 @@ public class EsDpiNiching implements InterfaceOptimizer, Serializable, Interface
                 Population origPop = peakOpts[origEsPop].getPopulation();
                 clusteredPeakPops[i].copyHashData(origPop);
                 clusteredPeakPops[i].SetHistory(origPop.getHistory()); // copy the history for deactivation!
-//				System.out.println("Copied hash for peak " + clusteredPeakPops[i].getBestEAIndividual() + ", cluster " + i + " from " + origEsPop);
             } else { // ok in the first iteration of if the indy was a random immigrant
                 if (population.getGeneration() > 1 && (getNumRndImmigrants() == 0)) {
                     System.err.println("Error, empty original es pop ID!");
@@ -643,30 +558,6 @@ public class EsDpiNiching implements InterfaceOptimizer, Serializable, Interface
         }
     }
 
-    //	/**
-//	 * For each new cluster copy the additional data from the closest parent population.
-//	 *  
-//	 * @param clusteredPeakPops
-//	 */
-//	private void copyDataFromClosest(Population[] clusteredPeakPops) {
-//		Population centers = new Population(clusteredPeakPops.length);
-//		AbstractEAIndividual indy;
-//		// collect leaders
-//		for (int i=0; i<peakOpts.length; i++) {
-//			Population peakPop = peakOpts[i].getPopulation();
-//			indy = (AbstractEAIndividual) peakPop.getData(origPeakIndyKey);
-//			if (indy!=null) centers.add(indy);
-//			else centers.add(peakOpts[i].getPopulation().getCenterIndy());
-//		}
-//		for (int i=1; i<clusteredPeakPops.length; i++) {
-//			indy = clusteredPeakPops[i].getBestEAIndividual();
-//			Pair<Integer,Double> closestIdDist = Population.getClosestFarthestIndy(clusteredPeakPops[i].getBestEAIndividual(), centers, metric, true);
-//			Population closestPop = peakOpts[closestIdDist.head()].getPopulation();
-//			System.out.println("Closest to new peak " + indy.toString() + " is old pop " + closestPop.getData(origPeakIndyKey));
-//			System.out.println("   meanX was " + (MutateESRankMuCMA.getMeanXOfPop(closestPop)));
-//			clusteredPeakPops[i].copyHashData(closestPop);
-//		}
-//	}
     private void printDemes(String prefix, Population[] peakPops) {
         System.out.print(prefix + " demes: ");
         for (int i = 0; i < peakPops.length; i++) {
@@ -743,9 +634,6 @@ public class EsDpiNiching implements InterfaceOptimizer, Serializable, Interface
             for (int i = 0; i < origClusters.length; i++) {
                 newClusters[i] = origClusters[i];
             }
-            if (TRACE) {
-                System.out.println("Generated missing peak species...");
-            }
             return newClusters;
         }
     }
@@ -776,9 +664,6 @@ public class EsDpiNiching implements InterfaceOptimizer, Serializable, Interface
             problem.initializePopulation(randomNewIndies);
             problem.evaluate(randomNewIndies);
             population.incrFunctionCallsBy(cnt);
-            if (TRACE) {
-                System.out.println("evaluated immigrants: " + randomNewIndies.size());
-            }
         } else {
             randomNewIndies = null;
         }
@@ -802,9 +687,6 @@ public class EsDpiNiching implements InterfaceOptimizer, Serializable, Interface
         if (rndIndex == i) {
             rndIndex++;
         }
-        if (TRACE) {
-            System.out.println("selected spec index " + rndIndex);
-        }
         return clusteredSpecies[rndIndex].getBestEAIndividual();
     }
 
@@ -828,7 +710,6 @@ public class EsDpiNiching implements InterfaceOptimizer, Serializable, Interface
                 }
                 ClusterBasedNichingEA.plotPopConnected(plot, npop);
                 plot.drawIndividual(1, 0, "", npop.getBestEAIndividual());
-//		plot.drawPopulation(prefix, npop);
             } catch (Exception e) {
                 plot = null;
             }
@@ -926,18 +807,13 @@ public class EsDpiNiching implements InterfaceOptimizer, Serializable, Interface
             // (few) duplicates may happen because parents are copied to another peak population
             // if a cluster had a size of 1 AND parents may survive due to elitism.
             pop.addPopulation(pi, false);
-//			if (i==0) pop.setGeneration(pi.getGeneration());
-//			else if (pop.getGeneration()!=pi.getGeneration()) System.err.println("Error, mismatching generation in collectPopulation");
         }
         if (immigrants != null) {
-            immigrants.putDataAllIndies(originalPeakPop, new Integer(-2));
+            immigrants.putDataAllIndies(originalPeakPop, -2);
             pop.addPopulation(immigrants, true);
         }
         pop.incrGeneration();
         pop.synchSize();
-        if (TRACE) {
-            System.out.println("Collected " + pop.size() + " indies in pop.");
-        }
     }
 
     /**

src/eva2/optimization/strategies/GradientDescentAlgorithm.java

@@ -1,6 +1,5 @@
 package eva2.optimization.strategies;
 
-import eva2.gui.BeanInspector;
 import eva2.optimization.go.InterfacePopulationChangedEventListener;
 import eva2.optimization.individuals.AbstractEAIndividual;
 import eva2.optimization.individuals.InterfaceDataTypeDouble;
@@ -47,7 +46,6 @@ public class GradientDescentAlgorithm implements InterfaceOptimizer, java.io.Ser
     // These variables are necessary for the more complex LectureGUI enviroment
     transient private String identifier = "";
     private Population population;
-    private static boolean TRACE = false;
     private static final String lockKey = "gdaLockDataKey";
     private static final String lastFitnessKey = "gdaLastFitDataKey";
     private static final String stepSizeKey = "gdaStepSizeDataKey";
@@ -155,10 +153,8 @@ public class GradientDescentAlgorithm implements InterfaceOptimizer, java.io.Ser
 
             int[] lock = (int[]) indy.getData(lockKey);
             double indystepsize = ((Double) indy.getData(stepSizeKey)).doubleValue();
-            //   System.out.println("indystepsize" + indystepsize);
 
             if ((this.optimizationProblem instanceof InterfaceFirstOrderDerivableProblem) && (indy instanceof InterfaceDataTypeDouble)) {
-//        Hashtable history = (Hashtable) indyhash.get(indy);
                 for (int iterations = 0; iterations < this.iterations; iterations++) {
 
                     double[] oldgradient = indy.hasData(gradientKey) ? (double[]) indy.getData(gradientKey) : null;
@@ -166,9 +162,6 @@ public class GradientDescentAlgorithm implements InterfaceOptimizer, java.io.Ser
                     double[] oldchange = null;
 
                     double[] gradient = ((InterfaceFirstOrderDerivableProblem) optimizationProblem).getFirstOrderGradients(params);
-                    if (TRACE) {
-                        System.out.println("GDA: " + BeanInspector.toString(params) + ", grad: " + BeanInspector.toString(gradient));
-                    }
                     if ((oldgradient != null) && (wstepsize != null)) { // LOCAL adaption
                         for (int li = 0; li < wstepsize.length; li++) {
                             double prod = gradient[li] * oldgradient[li];
@@ -180,7 +173,6 @@ public class GradientDescentAlgorithm implements InterfaceOptimizer, java.io.Ser
                             wstepsize[li] = (wstepsize[li] < localminstepsize) ? localminstepsize : wstepsize[li];
                             wstepsize[li] = (wstepsize[li] > localmaxstepsize) ? localmaxstepsize : wstepsize[li];
 
-//              System.out.println("wstepsize "+ li + " " + wstepsize[li]);
                         }
 
                     }
@@ -251,11 +243,8 @@ public class GradientDescentAlgorithm implements InterfaceOptimizer, java.io.Ser
         if (this.recovery) {
             for (int i = 0; i < this.population.size(); i++) {
                 indy = ((AbstractEAIndividual) this.population.get(i));
-//        Hashtable history = (Hashtable) indyhash.get(indy);
                 if (indy.getFitness()[0] > recoverythreshold) {
-                    if (TRACE) {
+
-                        System.out.println("Gradient Descent: Fitness critical:" + indy.getFitness()[0]);
-                    }
                     ((InterfaceDataTypeDouble) indy).setDoublePhenotype((double[]) indy.getData(oldParamsKey));
                     double[] changes = (double[]) indy.getData(changesKey);
                     int[] lock = (int[]) indy.getData(lockKey);
@@ -282,8 +271,7 @@ public class GradientDescentAlgorithm implements InterfaceOptimizer, java.io.Ser
             //System.out.println("gsa main");
             for (int i = 0; i < this.population.size(); i++) {
                 indy = ((AbstractEAIndividual) this.population.get(i));
-//        Hashtable history = (Hashtable) indyhash.get(indy);
+
-//        if (history == null) break;
                 if (indy.getData(lastFitnessKey) != null) {
                     double lastfit = ((Double) indy.getData(lastFitnessKey)).doubleValue();
                     double indystepsize = ((Double) indy.getData(stepSizeKey)).doubleValue();
@@ -296,7 +284,7 @@ public class GradientDescentAlgorithm implements InterfaceOptimizer, java.io.Ser
 //System.out.println("newstepsize" + indystepsize);
                     indystepsize = (indystepsize > globalmaxstepsize) ? globalmaxstepsize : indystepsize;
                     indystepsize = (indystepsize < globalminstepsize) ? globalminstepsize : indystepsize;
-                    indy.putData(stepSizeKey, new Double(indystepsize));
+                    indy.putData(stepSizeKey, indystepsize);
                 }
 
 //System.out.println("newstepsize in bounds" + indystepsize);

src/eva2/optimization/strategies/IslandModelEA.java

@@ -50,7 +50,6 @@ public class IslandModelEA implements InterfacePopulationChangedEventListener, I
     transient private Plot plot = null;
     transient private String identifier = "";
     transient private InterfacePopulationChangedEventListener populationChangedEventListener;
-    transient private final boolean TRACE = false;
 
     public IslandModelEA() {
     }
@@ -203,15 +202,9 @@ public class IslandModelEA implements InterfacePopulationChangedEventListener, I
         for (int i = 0; i < this.islands.length; i++) {
             if (this.islands[i].getPopulation().size() > 0) {
                 this.islands[i].optimize();
-                if (TRACE) {
-                    System.out.println(BeanInspector.toString(islands[i].getPopulation()));
-                }
             } else {
                 this.islands[i].getPopulation().incrGeneration();
             }
-            if (TRACE) {
-                System.out.println("----");
-            }
         }
         this.population.incrGeneration();
         if ((this.population.getGeneration() % this.migrationRate) == 0) {

src/eva2/optimization/strategies/MemeticAlgorithm.java

@@ -34,9 +34,6 @@ public class MemeticAlgorithm implements InterfaceOptimizer,
     private int subsetsize = 5;
     private int globalSearchIterations = 1;
     private boolean lamarckism = true;
-    // int counter = 0; !?
-    // int maxfunctioncalls = 1000; !?
-    private boolean TRACE = false;
     private String identifier = "";
     private InterfaceOptimizationProblem optimizationProblem = new F1Problem();
     private InterfaceOptimizer globalOptimizer = new GeneticAlgorithm();
@@ -94,20 +91,13 @@ public class MemeticAlgorithm implements InterfaceOptimizer,
 
     @Override
     public void optimize() {
-
-        if (TRACE) {
-            System.out.println("global search");
-        }
         this.globalOptimizer.optimize();
 
         if ((globalSearchIterations > 0) && (((this.globalOptimizer.getPopulation().getGeneration() % this.globalSearchIterations) == 0))
                 && (this.localSearchSteps > 0)
                 && (this.optimizationProblem instanceof InterfaceLocalSearchable)) {
             // here the local search is performed
-            if (TRACE) {
+
-                System.out.println("Performing local search on " + subsetsize
-                        + " individuals.");
-            }
             Population gop = this.globalOptimizer.getPopulation();
             Population subset = selectorPlug.selectFrom(gop, subsetsize);
             Population subsetclone = new Population();
@@ -164,17 +154,9 @@ public class MemeticAlgorithm implements InterfaceOptimizer,
             gop.setFunctionCalls(gop.getFunctionCalls()
                     + (int) Math.round(localSearchSteps * cost * subset.size()));
 
-            if (TRACE) {
-                System.out.println("Population size after local search:" + gop.size());
-            }
-
             this.setPopulation(gop);
         }
 
-        if (TRACE) {
-            System.out.println("function calls"
-                    + this.globalOptimizer.getPopulation().getFunctionCalls());
-        }
         this.firePropertyChangedEvent(Population.NEXT_GENERATION_PERFORMED);
     }
 
@@ -205,9 +187,6 @@ public class MemeticAlgorithm implements InterfaceOptimizer,
      */
     protected void firePropertyChangedEvent(String name) {
         if (this.populationChangedEventListener != null) {
-            if (TRACE) {
-                System.out.println("firePropertyChangedEvent MA");
-            }
             this.populationChangedEventListener.registerPopulationStateChanged(this, name);
         }
     }

src/eva2/optimization/strategies/ParticleFilterOptimization.java

@@ -47,7 +47,6 @@ public class ParticleFilterOptimization implements InterfaceOptimizer, java.io.S
     transient private int indCount = 0;
     transient private InterfacePopulationChangedEventListener populationChangedEventListener;
     transient Plot myPlot = null;
-    public static final boolean TRACE = false;
 
     public ParticleFilterOptimization() {
         if (withShow) {
@@ -167,9 +166,6 @@ public class ParticleFilterOptimization implements InterfaceOptimizer, java.io.S
                 parents.add(immi);
             }
             parents.synchSize();
-            if (TRACE) {
-                System.out.println("Added " + i + " random individuals");
-            }
         }
 
         parents.setFunctionCalls(pop.getFunctionCalls());
@@ -249,14 +245,9 @@ public class ParticleFilterOptimization implements InterfaceOptimizer, java.io.S
 
         // predict step
         predict(nextGeneration);
-        if (TRACE) {
-            System.out.println("Speed is  " + BeanInspector.toString(ParticleSwarmOptimization.getPopulationVelSpeed(population, 3, MutateESCorrVector.vectorKey, null, null)) + " popM " + BeanInspector.toString(population.getPopulationMeasures(new EuclideanMetric())));
-        }
 
         population = evaluatePopulation(nextGeneration);
 
-//        collectStatistics(population);
-
         this.firePropertyChangedEvent(Population.NEXT_GENERATION_PERFORMED);
 
     }

src/eva2/optimization/strategies/ParticleSwarmOptimization.java

@@ -103,7 +103,6 @@ public class ParticleSwarmOptimization implements InterfaceOptimizer, java.io.Se
     // parameter for exponential moving average
     private int emaPeriods = 0;
     // for debugging only
-    transient private static boolean TRACE = false;
     transient protected boolean show = false;
     transient protected Plot plot;
     private boolean externalInitialPop = false;
@@ -778,7 +777,7 @@ public class ParticleSwarmOptimization implements InterfaceOptimizer, java.io.Se
             for (int i = 0; i < this.population.size(); i++) {
                 double[] succVel = (double[]) population.getEAIndividual(i).getData(lastSuccessKey);
                 if (succVel != null) {
-                    successes.add(new Integer(i));
+                    successes.add(i);
                 }
             }
             if (successes.size() > 0) {
@@ -1250,15 +1249,6 @@ public class ParticleSwarmOptimization implements InterfaceOptimizer, java.io.Se
      * Do some preparations in the beginning of the loop.
      */
     protected void startOptimize() {
-        if (TRACE) {
-            for (int i = 0; i < population.size(); i++) {
-                AbstractEAIndividual indy = population.getEAIndividual(i);
-                System.out.println(BeanInspector.toString(indy.getData(partTypeKey)));
-                System.out.println(BeanInspector.toString(indy.getData(partBestPosKey)));
-                System.out.println(BeanInspector.toString(indy.getData(partBestFitKey)));
-                System.out.println(BeanInspector.toString(indy.getData(partVelKey)));
-            }
-        }
         if (this.show) {
             this.show();
         }
@@ -1580,9 +1570,6 @@ public class ParticleSwarmOptimization implements InterfaceOptimizer, java.io.Se
                     initIndividualMemory(indy);
                     indy.putData(indexKey, i);
                     indy.setIndividualIndex(i);
-                    if (TRACE) {
-                        System.err.println("initialize indy " + i + " " + AbstractEAIndividual.getDefaultDataString(indy));
-                    }
                 }
             }
         }

src/eva2/optimization/strategies/ScatterSearch.java

@@ -70,7 +70,6 @@ public class ScatterSearch implements InterfaceOptimizer, java.io.Serializable,
     private double nelderMeadInitPerturbation = 0.01;
     private double improvementEpsilon = 0.1; // minimal relative fitness improvement for a candidate to be taken over into the refset
     private double minDiversityEpsilon = 0.0001; // minimal phenotypic distance for a candidate to be taken over into the refset
-    private static boolean TRACE = false;
 
     public ScatterSearch() {
         GenericObjectEditor.setHideProperty(this.getClass(), "population", true);
@@ -137,14 +136,9 @@ public class ScatterSearch implements InterfaceOptimizer, java.io.Serializable,
      */
     private void initRefSet(Population pop) {
         optimizationProblem.evaluate(pop);
-        if (TRACE) {
-            System.out.println("building ref set from pop with avg dist " + pop.getPopulationMeasures()[0]);
-        }
         refSet = getRefSetFitBased(new Population(refSetSize), pop);
         refSet.incrFunctionCallsBy(pop.size());
-        if (TRACE) {
+
-            System.out.println("ref set size " + refSet.size() + " avg dist " + refSet.getPopulationMeasures()[0]);
-        }
         refSet.addPopulationChangedEventListener(this);
         refSet.setNotifyEvalInterval(generationCycle);
     }
@@ -166,9 +160,6 @@ public class ScatterSearch implements InterfaceOptimizer, java.io.Serializable,
             }
             probDim = (Integer) dim;
             range = ((InterfaceDataTypeDouble) template).getDoubleRange();
-            if (TRACE) {
-                System.out.println("Range is " + BeanInspector.toString(range));
-            }
         }
     }
 
@@ -228,27 +219,15 @@ public class ScatterSearch implements InterfaceOptimizer, java.io.Serializable,
         int funCallsStart = refSet.getFunctionCalls();
         do {
             if (combinations == null || combinations.size() == 0) {
-                if (TRACE) {
-                    System.out.println("Improvements: " + lastImprovementCount);
-                    System.out.println("---------- best: " + refSet.getBestEAIndividual().getFitness(0));
-                }
                 combinations = generateCombinations(refSet);
                 oldRefSet = (Population) refSet.clone();
                 lastImprovementCount = 0;
             }
-            if (TRACE) {
-                System.out.println("No combinations: " + combinations.size());
-            }
             if (combinations.size() > 0) {
                 updateRefSet(refSet, combinations, oldRefSet);
             }
         } while (refSet.getFunctionCalls() - funCallsStart < generationCycle);
         optimizationProblem.evaluatePopulationEnd(refSet);
-
-        if (TRACE) {
-            System.out.println("Improvements: " + lastImprovementCount);
-        }
-
     }
 
     private boolean isDoLocalSolver(AbstractEAIndividual cand, Population refSet) {
@@ -271,15 +250,9 @@ public class ScatterSearch implements InterfaceOptimizer, java.io.Serializable,
         Population diversifiedPop = diversify();
         int keep = refSetSize / 2;
         Population newRefSet = refSet.cloneWithoutInds();
-        if (TRACE) {
-            System.out.println("regen after " + refSet.getFunctionCalls() + ", best is " + refSet.getBestEAIndividual().getFitness(0));
-        }
 
         newRefSet.addAll(refSet.getBestNIndividuals(keep, fitCrit));
 
-        if (TRACE) {
-            System.out.println("keeping " + keep + " indies from former ref set, best is " + newRefSet.getBestEAIndividual().getFitness(0));
-        }
 
         int h = newRefSet.size();
         ArrayList<double[]> distVects = new ArrayList<double[]>();
@@ -364,10 +337,6 @@ public class ScatterSearch implements InterfaceOptimizer, java.io.Serializable,
         AbstractEAIndividual bestCand = candidates.getEAIndividual(bestIndex);
         AbstractEAIndividual worstRef = refSet.getWorstEAIndividual();
 
-        if (TRACE) {
-            System.out.println("best cand: " + bestCand.getFitness(0));
-        }
-
         if (isDoLocalSolver(bestCand, refSet)) {
             Pair<AbstractEAIndividual, Integer> lsRet = localSolver(bestCand, localSearchSteps);
             if ((Math.abs(lsRet.tail() - localSearchSteps) / localSearchSteps) > 0.05) {
@@ -375,33 +344,21 @@ public class ScatterSearch implements InterfaceOptimizer, java.io.Serializable,
             }
             bestCand = lsRet.head();
             refSet.incrFunctionCallsBy(lsRet.tail());
-            if (TRACE) {
-                System.out.println("best cand after: " + bestCand.getFitness(0));
-            }
         }
 
         if (bestCand.isDominatingEqual(worstRef)) {
-            if (TRACE) {
-                System.out.println("cand is dominating worst ref!");
-            }
             if (diversityCriterionFulfilled(bestCand, refSet, oldRefSet)) {
-//				System.out.println("diversity criterion is fulfilled! replacing fit " + worstRef.getFitness(0));
                 int replIndex = refSet.indexOf(worstRef);
                 refSet.set(replIndex, bestCand);
                 lastImprovementCount++;
             } else if (bestCand.isDominating(refSet.getBestEAIndividual())) {
                 // exception: always accept best solution found so far
                 int closestIndex = getClosestIndy(bestCand, refSet);
-//				if (TRACE) System.out.println("replacing due to best fit");
                 refSet.set(closestIndex, bestCand);
                 lastImprovementCount++;
             }
-//			System.out.println("Improvements: " + lastImprovementCount);
             candidates.remove(bestIndex);
         } else {
-            if (TRACE) {
-                System.out.println("cand is too bad!");
-            }
             // if the best candidate is worse and no local search is performed, all following will be worse - at least in the uni-criterial case
             // so we can just clear the rest of the candidates
             if (!doLocalSearch && (bestCand.getFitness().length == 1)) {
@@ -422,7 +379,6 @@ public class ScatterSearch implements InterfaceOptimizer, java.io.Serializable,
 
     private Pair<AbstractEAIndividual, Integer> localSolverHC(AbstractEAIndividual cand, int hcSteps) {
         // use HC for a start...
-//		double[] fitBefore = cand.getFitness();
         Population hcPop = new Population(1);
         hcPop.add(cand);
         int stepsDone = PostProcess.processWithHC(hcPop, optimizationProblem, hcSteps);
@@ -481,7 +437,6 @@ public class ScatterSearch implements InterfaceOptimizer, java.io.Serializable,
         for (int i = 0; i < half - 1; i++) { // better-better
             AbstractEAIndividual indy1 = refSorted.getEAIndividual(i);
             for (int j = i + 1; j < half; j++) {
-//				if (TRACE) System.out.println("combi T bb, " + i+ "/" + j);
                 AbstractEAIndividual indy2 = refSorted.getEAIndividual(j);
                 combs.add(combineTypeOne(indy1, indy2));
                 combs.add(combineTypeTwo(indy1, indy2));
@@ -493,7 +448,6 @@ public class ScatterSearch implements InterfaceOptimizer, java.io.Serializable,
         for (int i = 0; i < half; i++) { // better-worse
             AbstractEAIndividual indy1 = refSorted.getEAIndividual(i);
             for (int j = half; j < refSet.size(); j++) {
-//				if (TRACE) System.out.println("combi T bw, " + i+ "/" + j);
                 AbstractEAIndividual indy2 = refSorted.getEAIndividual(j);
                 combs.add(combineTypeOne(indy1, indy2));
                 combs.add(combineTypeTwo(indy1, indy2));
@@ -504,7 +458,6 @@ public class ScatterSearch implements InterfaceOptimizer, java.io.Serializable,
         for (int i = half; i < refSet.size() - 1; i++) { // worse-worse
             AbstractEAIndividual indy1 = refSorted.getEAIndividual(i);
             for (int j = i + 1; j < refSet.size(); j++) {
-//				if (TRACE) System.out.println("combi T ww, " + i+ "/" + j);
                 AbstractEAIndividual indy2 = refSorted.getEAIndividual(j);
                 combs.add(combineTypeTwo(indy1, indy2));
                 if (RNG.flipCoin(0.5)) {
@@ -514,10 +467,6 @@ public class ScatterSearch implements InterfaceOptimizer, java.io.Serializable,
                 }
             }
         }
-
-        if (TRACE) {
-            System.out.println("created combinations " + combs.size() + " best is " + combs.getBestEAIndividual().getFitness(0));
-        }
         return combs;
     }
 
@@ -649,9 +598,7 @@ public class ScatterSearch implements InterfaceOptimizer, java.io.Serializable,
             pop.add(createDiverseIndy(freq));
         }
         pop.setTargetSize(poolSize);
-        if (TRACE) {
+
-            System.out.println("created diverse pop size " + pop.size());
-        }
         return pop;
     }
 

src/eva2/optimization/strategies/Tribes.java

@@ -134,7 +134,6 @@ import java.util.List;
 @Description("TRIBES: a parameter free PSO implementation by Maurice Clerc.")
 public class Tribes implements InterfaceOptimizer, java.io.Serializable {
 
-    public static final boolean TRACE = false;
     protected String identifier = "TRIBES";
     transient private InterfacePopulationChangedEventListener listener = null;
     protected AbstractOptimizationProblem optimizationProblem;
@@ -322,16 +321,7 @@ public class Tribes implements InterfaceOptimizer, java.io.Serializable {
         }
         optimizationProblem.evaluatePopulationEnd(population);
 
-//		this.population.incrFunctionCallsby(evals);
         this.population.incrGeneration();
-        //this.firePropertyChangedEvent("NextGenerationPerformed");	// This is now done implicitely, as after every evaluation, addEvals is called
-
-        if (TRACE) {
-            System.out.println("loop finished after " + population.getFunctionCalls() + " evaluations");
-            //for (int i=0; i<population.size(); i++) System.out.println(" * "+((TribesExplorer)population.get(i)).getStringRepresentation());
-            System.out.println(" best: " + population.getBestEAIndividual().getStringRepresentation() + " - " + population.getBestEAIndividual().getFitness(0));
-            System.out.println("swarm contains " + swarm.numParticles() + " particles in iteration " + iter);
-        }
     }
 
     private void plotAll(Population pop) {

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

@@ -11,7 +11,6 @@ public class TribesPosition implements java.io.Serializable {
      *
      */
     private static final long serialVersionUID = 1L;
-    private boolean TRACE = false;
     double x[];
     int[][] maxIsoLink = null;
     double[] fitness;
@@ -23,22 +22,6 @@ public class TribesPosition implements java.io.Serializable {
         fitness = new double[1];// new double[maxFunctionNb]; // TODO
     }
 
-//    public TribesPosition clone(TribesPosition position, int fitnessSize) {
-//    	// TODO this method might better vanish
-//        int n;
-//        // Pour remplacer "implements Cloneable"
-//        TribesPosition Clone = new TribesPosition(x.length, fitness.length);
-//        Clone.Dimension = position.Dimension;
-//        System.arraycopy(position.x, 0, Clone.x, 0, position.Dimension);
-//        for (n = 0; n < fitnessSize; n++) {
-//            Clone.fitness[n] = position.fitness[n];
-//        }
-//
-//        Clone.totalError = position.totalError;
-//        Clone.isolation=position.isolation;
-//        return Clone;
-//    }
-
     @Override
     public TribesPosition clone() {
         // Pour remplacer "implements Cloneable"
@@ -695,9 +678,6 @@ public class TribesPosition implements java.io.Serializable {
                  No need of a very precise solution
          */
 
-        if (TRACE) {
-            System.out.println("sunny start");
-        }
         // INITIALISATION
 
         for (n = 0; n < swarm.size; n++) {
@@ -835,9 +815,7 @@ public class TribesPosition implements java.io.Serializable {
              System.out.print(swarm.Best.position.x[d]+" ");
          */
         swarm.bestMem.getPos().isolation = swarm.bestMem.getPos().fitness[0];
-        if (TRACE) {
+
-            System.out.println("sunny end, ret " + swarm.bestMem.getPos().toString());
-        }
         return swarm.bestMem.getPos();
     }
 

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

@@ -612,14 +612,8 @@ public class TribesSwarm implements java.io.Serializable {
         TribesPosition posTemp = new TribesPosition(range.length);
         double[] rand_i;
 
-        if (Tribes.TRACE) {
-            System.out.println("+ generateExplorer option " + option);
-        }
         switch (option) {
             case 3: // around a "center"
-                if (Tribes.TRACE) {
-                    System.out.println("+ around center ");
-                }
                 if (radius < 0) {
                     // Choose at random a memory
                     m = RNG.randomInt(this.tribes[fromTribe].memoryNb);
@@ -648,9 +642,6 @@ public class TribesSwarm implements java.io.Serializable {
              In order to do that all memorizez positions are used, including de "dead" ones
                See SunnySpell
     	 */
-                if (Tribes.TRACE) {
-                    System.out.println("+ sunny spell ");
-                }
 
                 // if only initRange should be used for initialization, give that one to the sspell
                 expl.position = expl.position.maxIsolated((initRange == null) ? range : initRange, this);
@@ -666,9 +657,7 @@ public class TribesSwarm implements java.io.Serializable {
             default:
                 // For pure random (0) method, or option 1 (on the bounds)
                 if (initType == 1) {    // use initRange
-                    if (Tribes.TRACE) {
+
-                        System.out.println("+ in initRange ");
-                    }
                     if (initRange == null) {
                         System.err.println("unexpected null initRange!");
                     }
@@ -677,9 +666,6 @@ public class TribesSwarm implements java.io.Serializable {
                     posTemp = expl.position.clone();
                     expl.initExplorerSpace(initRange);
                 } else {    // use default range
-                    if (Tribes.TRACE) {
-                        System.out.println("+ in whole range ");
-                    }
                     //default: // In the whole search space
                     expl.initExplorerSpace(range);
                     posTemp = expl.position.clone();

src/eva2/problems/MatlabEvalMediator.java

@@ -26,7 +26,6 @@ import java.util.concurrent.Semaphore;
  */
 public class MatlabEvalMediator {
     volatile Boolean requesting = false;
-    //	final static boolean TRACE = false;
     volatile private Boolean fin = false;
     volatile Object question = null;
     volatile double[] answer = null;

src/eva2/problems/MatlabProblem.java

@@ -33,7 +33,6 @@ import java.util.BitSet;
 @Description("Interface problem class for optimization in Matlab, only usable from within Matlab")
 public class MatlabProblem extends AbstractOptimizationProblem implements InterfaceHasInitRange, InterfaceTextListener, Serializable {
     private static final long serialVersionUID = 4913310869887420815L;
-    public static boolean TRACE = false;
     transient OptimizerRunnable runnable = null;
     protected boolean allowSingleRunnable = true;
     private transient Population seedPopulation = null;
@@ -219,8 +218,6 @@ public class MatlabProblem extends AbstractOptimizationProblem implements Interf
         log("### Data type is " + dataType);
 
         initTemplate();
-
-        setDebugOut(TRACE, defTestOut);
         log("Initial range is " + BeanInspector.toString(initialRange) + "\n");
     }
 
@@ -233,8 +230,6 @@ public class MatlabProblem extends AbstractOptimizationProblem implements Interf
      * @param fname
      */
     public void setDebugOut(boolean swtch, String fname) {
-        TRACE = swtch;
-//		System.err.println("setDebugOut: " +  swtch +" " + fname);
         if (!swtch && (dos != null)) {
             dos.close();
             dos = null;
@@ -243,7 +238,6 @@ public class MatlabProblem extends AbstractOptimizationProblem implements Interf
                 if (fname == null || (fname.length() == 0)) {
                     fname = defTestOut;
                 }
-//				System.err.println("Opening "+fname);
                 dos = new PrintStream(new FileOutputStream(fname));
             } catch (FileNotFoundException e) {
                 e.printStackTrace();

src/eva2/tools/KMEANSJAVA.java

@@ -8,7 +8,6 @@ import java.util.Comparator;
  *
  */
 public class KMEANSJAVA {
-    static public boolean TRACE = false;
     protected double[][] c;
     protected int[] indices;
 
@@ -41,10 +40,6 @@ public class KMEANSJAVA {
      *
      */
     public KMEANSJAVA(double[][] samples, int K, int iterations) {
-        //System.out.print("in");
-        if (TRACE) {
-            System.out.println("K" + K);
-        }
         if (K > samples.length) {
             K = samples.length;
         }
@@ -72,11 +67,11 @@ public class KMEANSJAVA {
             for (int indexofc = 0; indexofc < c.length; indexofc++) {
                 double[] newcenter = new double[samples[0].length];
                 int treffer = 0;
-                for (int j = 0; j < indices.length; j++) { //System.out.println("j="+j);
+                for (int indice : indices) { //System.out.println("j="+j);
-                    if (indices[j] == indexofc) {
+                    if (indice == indexofc) {
                         treffer++;
                         for (int d = 0; d < newcenter.length; d++) {
-                            newcenter[d] += c[indices[j]][d];
+                            newcenter[d] += c[indice][d];
                             //newcenter[d] = newcenter[d] + samples[j][d];
                         }
                     }
@@ -88,7 +83,6 @@ public class KMEANSJAVA {
             }
             // determine the new centers
         }
-        //System.out.println("out");
     }
 
     /**
@@ -115,9 +109,9 @@ public class KMEANSJAVA {
             System.out.println("");
         }
         System.out.println("test");
-        for (int i = 0; i < test.length; i++) {
+        for (double[] aTest : test) {
-            for (int j = 0; j < test[i].length; j++) {
+            for (int j = 0; j < aTest.length; j++) {
-                System.out.print(test[i][j] + " ");
+                System.out.print(aTest[j] + " ");
             }
             System.out.println("");
         }

src/eva2/tools/ReflectPackage.java

@@ -25,13 +25,9 @@ import java.util.jar.JarInputStream;
  * @author mkron
  */
 public class ReflectPackage {
-
-    final static boolean TRACE = false;
     static int missedJarsOnClassPath = 0;
     static boolean useFilteredClassPath = true;
-    //	static boolean usePathMap = true;
     static String[] dynCP = null;
-//	static HashMap<String, ArrayList<String>> pathMap = new HashMap<String, ArrayList<String>>();
 
     static class ClassComparator<T> implements Comparator<T> {
         @Override
@@ -59,26 +55,15 @@ public class ReflectPackage {
                 }
                 dir = path + "/" + pckgname.replace(".", "/");
 
-                if (TRACE) {
-                    System.out.println(".. opening " + path);
-                }
-
                 directory = new File(dir);
 
             } catch (NullPointerException x) {
-                if (TRACE) {
-                    System.err.println(directory.getPath() + " not found in " + path);
-                    System.err.println("directory " + (directory.exists() ? "exists" : "doesnt exist"));
-                }
                 return 0;
             }
             if (directory.exists()) {
                 // Get the list of the files contained in the package
                 return getClassesFromDirFltr(set, directory, pckgname, includeSubs, reqSuperCls);
             } else {
-                if (TRACE) {
-                    System.err.println(directory.getPath() + " doesnt exist in " + path + ", dir was " + dir);
-                }
                 return 0;
             }
         } catch (ClassNotFoundException e) {
@@ -88,21 +73,17 @@ public class ReflectPackage {
         }
     }
 
-//	public static ArrayList<Class> getClassesFromDir(File directory, String pckgname, boolean includeSubs) {
-//		return getClassesFromDirFltr(directory, pckgname, includeSubs, null);
-//	}
-
     public static int getClassesFromDirFltr(HashSet<Class> set, File directory, String pckgname, boolean includeSubs, Class<?> reqSuperCls) {
         int cntAdded = 0;
         if (directory.exists()) {
             // Get the list of the files contained in the package
             String[] files = directory.list();
-            for (int i = 0; i < files.length; i++) {
+            for (String file : files) {
                 // we are only interested in .class files
-                if (files[i].endsWith(".class")) {
+                if (file.endsWith(".class")) {
                     // removes the .class extension
                     try {
-                        Class<?> cls = Class.forName(pckgname + '.' + files[i].substring(0, files[i].length() - 6));
+                        Class<?> cls = Class.forName(pckgname + '.' + file.substring(0, file.length() - 6));
                         if (reqSuperCls != null) {
                             if (reqSuperCls.isAssignableFrom(cls)) {
                                 cntAdded += addClass(set, cls);
@@ -111,15 +92,15 @@ public class ReflectPackage {
                             cntAdded += addClass(set, cls);
                         }
                     } catch (Exception e) {
-                        System.err.println("ReflectPackage: Couldnt get Class from jar for " + pckgname + '.' + files[i] + ": " + e.getMessage());
+                        System.err.println("ReflectPackage: Couldnt get Class from jar for " + pckgname + '.' + file + ": " + e.getMessage());
                     } catch (Error e) {
-                        System.err.println("ReflectPackage: Couldnt get Class from jar for " + pckgname + '.' + files[i] + ": " + e.getMessage());
+                        System.err.println("ReflectPackage: Couldnt get Class from jar for " + pckgname + '.' + file + ": " + e.getMessage());
                     }
                 } else if (includeSubs) {
                     // do a recursive search over subdirs
-                    File subDir = new File(directory.getAbsolutePath() + File.separatorChar + files[i]);
+                    File subDir = new File(directory.getAbsolutePath() + File.separatorChar + file);
                     if (subDir.exists() && subDir.isDirectory()) {
-                        cntAdded += getClassesFromDirFltr(set, subDir, pckgname + "." + files[i], includeSubs, reqSuperCls);
+                        cntAdded += getClassesFromDirFltr(set, subDir, pckgname + "." + file, includeSubs, reqSuperCls);
                     }
                 }
             }
@@ -136,9 +117,6 @@ public class ReflectPackage {
     }
 
     private static int addClass(HashSet<Class> set, Class cls) {
-        if (TRACE) {
-            System.out.println("adding class " + cls.getName());
-        }
         if (set.contains(cls)) {
             System.err.println("warning, Class " + cls.getName() + " not added twice!");
             return 0;
@@ -150,12 +128,9 @@ public class ReflectPackage {
 
     public static ArrayList<Class> filterAssignableClasses(ArrayList<Class> classes, Class<?> reqSuperCls) {
         ArrayList<Class> assClasses = new ArrayList<Class>();
-        for (int i = 0; i < classes.size(); i++) {
+        for (Class aClass : classes) {
-            if (reqSuperCls.isAssignableFrom(classes.get(i))) {
+            if (reqSuperCls.isAssignableFrom(aClass)) {
-                if (TRACE) {
+                assClasses.add(aClass);
-                    System.out.println(" taking over " + classes.get(i));
-                }
-                assClasses.add(classes.get(i));
             }
         }
         return assClasses;
@@ -173,9 +148,6 @@ public class ReflectPackage {
         int cntAdded = 0;
 
         packageName = packageName.replaceAll("\\.", "/");
-        if (TRACE) {
-            System.out.println("Jar " + jarName + " looking for " + packageName);
-        }
         try {
             JarInputStream jarFile = new JarInputStream
                     (new FileInputStream(jarName));
@@ -183,7 +155,6 @@ public class ReflectPackage {
 
             while ((jarEntry = jarFile.getNextJarEntry()) != null) {
                 String jarEntryName = jarEntry.getName();
-//				if (TRACE) System.out.println("- " + jarEntry.getName());
                 if ((jarEntryName.startsWith(packageName)) &&
                         (jarEntryName.endsWith(".class"))) {
 //					subpackages are hit here as well!
@@ -203,25 +174,20 @@ public class ReflectPackage {
                             } else {
                                 cntAdded += addClass(set, cls);
                             }
-                        } catch (Exception e) {
+                        } catch (Exception | Error e) {
-                            System.err.println("ReflectPackage: Couldnt get Class from jar for " + clsName + ": " + e.getMessage());
+                            System.err.println("ReflectPackage: Couldn't get Class from jar for " + clsName + ": " + e.getMessage());
-                        } catch (Error e) {
-                            System.err.println("ReflectPackage: Couldnt get Class from jar for " + clsName + ": " + e.getMessage());
                         }
                     }
-
-//					classes.add (jarEntry.getName().replaceAll("/", "\\."));
                 }
             }
         } catch (IOException e) {
             missedJarsOnClassPath++;
             if (missedJarsOnClassPath == 0) {
-                System.err.println("Couldnt open jar from class path: " + e.getMessage());
+                System.err.println("Couldn't open jar from class path: " + e.getMessage());
                 System.err.println("Dirty class path?");
             } else if (missedJarsOnClassPath == 2) {
-                System.err.println("Couldnt open jar from class path more than once...");
+                System.err.println("Couldn't open jar from class path more than once...");
             }
-            //e.printStackTrace();
         }
         return cntAdded;
     }
@@ -230,13 +196,13 @@ public class ReflectPackage {
      * Collect all classes from a given package on the classpath. If includeSubs is true,
      * the sub-packages are listed as well.
      *
-     * @param pckg
+     * @param pkg           Package name
-     * @param includeSubs
+     * @param includeSubs   Whether to include sub packages
-     * @param bSort       sort alphanumerically by class name
+     * @param bSort         sort alphanumerically by class name
      * @return An ArrayList of Class objects contained in the package which may be empty if an error occurs.
      */
-    public static Class[] getAllClassesInPackage(String pckg, boolean includeSubs, boolean bSort) {
+    public static Class[] getAllClassesInPackage(String pkg, boolean includeSubs, boolean bSort) {
-        return getClassesInPackageFltr(new HashSet<Class>(), pckg, includeSubs, bSort, null);
+        return getClassesInPackageFltr(new HashSet<Class>(), pkg, includeSubs, bSort, null);
     }
 
     /**
@@ -244,14 +210,11 @@ public class ReflectPackage {
      * as superclass or superinterface. If includeSubs is true,
      * the sub-packages are listed as well.
      *
-     * @param pckg
+     * @param pkg
      * @return
-     * @see Class.assignableFromClass(Class cls)
      */
-    public static Class[] getClassesInPackageFltr(HashSet<Class> set, String pckg, boolean includeSubs, boolean bSort, Class reqSuperCls) {
+    public static Class[] getClassesInPackageFltr(HashSet<Class> set, String pkg, boolean includeSubs, boolean bSort, Class reqSuperCls) {
-        String classPath = null;
         if (!useFilteredClassPath || (dynCP == null)) {
-            classPath = System.getProperty("java.class.path", ".");
             if (useFilteredClassPath) {
                 try {
                     dynCP = getValidCPArray();
@@ -263,20 +226,11 @@ public class ReflectPackage {
             }
         }
 
-        if (TRACE) {
+        for (String aDynCP : dynCP) {
-            System.out.println("classpath is " + classPath);
+            if (aDynCP.endsWith(".jar")) {
-        }
+                getClassesFromJarFltr(set, aDynCP, pkg, includeSubs, reqSuperCls);
-        for (int i = 0; i < dynCP.length; i++) {
-            if (TRACE) {
-                System.out.println("reading element " + dynCP[i]);
-            }
-            if (dynCP[i].endsWith(".jar")) {
-                getClassesFromJarFltr(set, dynCP[i], pckg, includeSubs, reqSuperCls);
             } else {
-                if (TRACE) {
+                getClassesFromFilesFltr(set, aDynCP, pkg, includeSubs, reqSuperCls);
-                    System.out.println("reading from files: " + dynCP[i] + " " + pckg);
-                }
-                getClassesFromFilesFltr(set, dynCP[i], pckg, includeSubs, reqSuperCls);
             }
         }
         Object[] clsArr = set.toArray();
@@ -298,9 +252,6 @@ public class ReflectPackage {
     public static String getResourcePathFromCP(String res) {
         String[] cpEntries = getClassPathElements();
         URL url = ClassLoader.getSystemResource(res);
-        if (TRACE) {
-            System.out.println(res + ((url == null) ? " not" : " was") + " found by classloader.");
-        }
         if (url != null) {
             File f;
             try {
@@ -319,15 +270,9 @@ public class ReflectPackage {
             fNameSep = System.getProperty("file.separator") + res;
         }
 
-        for (int i = 0; i < cpEntries.length; i++) {
+        for (String cpEntry : cpEntries) {
-            if (!cpEntries[i].endsWith(".jar")) { // its a fs directory (hopefully)
+            if (!cpEntry.endsWith(".jar")) { // its a fs directory (hopefully)
-                if (TRACE) {
+                f = new File(cpEntry + fNameSep);
-                    System.out.println("reading element " + cpEntries[i]);
-                }
-                f = new File(cpEntries[i] + fNameSep);
-                if (TRACE) {
-                    System.out.println(res + ((!f.exists()) ? " not" : " was") + " found in " + cpEntries[i]);
-                }
                 if (f.exists()) {
                     return f.getAbsolutePath();
                 }
@@ -345,9 +290,6 @@ public class ReflectPackage {
     public static InputStream getResourceStreamFromCP(String res) {
 
         InputStream in = BasicResourceLoader.instance().getStreamFromResourceLocation(res);
-        if (TRACE) {
-            System.out.println(res + ((in == null) ? " not" : " was") + " found by classloader.");
-        }
         if (in != null) {
             return in;
         }
@@ -362,15 +304,9 @@ public class ReflectPackage {
             fNameSep = System.getProperty("file.separator") + res;
         }
 
-        for (int i = 0; i < cpEntries.length; i++) {
+        for (String cpEntry : cpEntries) {
-            if (!cpEntries[i].endsWith(".jar")) { // its a fs directory (hopefully)
+            if (!cpEntry.endsWith(".jar")) { // its a fs directory (hopefully)
-                if (TRACE) {
+                f = new File(cpEntry + fNameSep);
-                    System.out.println("reading element " + cpEntries[i]);
-                }
-                f = new File(cpEntries[i] + fNameSep);
-                if (TRACE) {
-                    System.out.println(res + ((!f.exists()) ? " not" : " was") + " found in " + cpEntries[i]);
-                }
                 if (f.exists()) {
                     try {
                         return new FileInputStream(f);
@@ -387,12 +323,10 @@ public class ReflectPackage {
         String[] pathElements = getClassPathElements();
         File f;
         ArrayList<String> valids = new ArrayList<String>(pathElements.length);
-        for (int i = 0; i < pathElements.length; i++) {
+        for (String pathElement : pathElements) {
-//						System.err.println(pathElements[i]);
+            f = new File(pathElement);
-            f = new File(pathElements[i]);
-//						if (f.canRead()) {valids.add(pathElements[i]);}
             if (f.exists() && f.canRead()) {
-                valids.add(pathElements[i]);
+                valids.add(pathElement);
             }
         }
         return valids;
@@ -400,7 +334,6 @@ public class ReflectPackage {
 
     public static String[] getValidCPArray() {
         ArrayList<String> valids = getValidCPEntries();
-//		vp = valids.toArray(dynCP); // this causes Matlab to crash meanly.
         String[] vp = new String[valids.size()];
         for (int i = 0; i < valids.size(); i++) {
             vp[i] = valids.get(i);
@@ -416,9 +349,6 @@ public class ReflectPackage {
      * @return
      */
     public static Class<?>[] getAssignableClassesInPackage(String pckg, Class reqSuperCls, boolean includeSubs, boolean bSort) {
-        if (TRACE) {
-            System.out.println("requesting classes assignable from " + reqSuperCls.getName());
-        }
         return getClassesInPackageFltr(new HashSet<Class>(), pckg, includeSubs, bSort, reqSuperCls);
     }
 
@@ -426,8 +356,9 @@ public class ReflectPackage {
      * Retrieve assignable classes of the given package from classpath given by full class and package String,
      * such as eva2.problems.AbstractOptimizationProblem.
      *
-     * @param pckg        String denoting the package
+     * @param pckgClassName        String denoting the package
-     * @param reqSuperCls
+     * @param includeSubs
+     * @param bSort
      * @return
      */
     public static Class<?>[] getAssignableClasses(String pckgClassName, boolean includeSubs, boolean bSort) {
@@ -450,13 +381,8 @@ public class ReflectPackage {
 
     public static void main(String[] args) {
         ClassLoader cld = Thread.currentThread().getContextClassLoader();
-        System.out.println("1: " + cld.getResource("/eva2/server"));
+        System.out.println("1: " + cld.getResource("/eva2/optimization"));
-        System.out.println("2: " + cld.getResource("eva2/server"));
+        System.out.println("2: " + cld.getResource("eva2/optimization"));
-//		BasicResourceLoader rld = BasicResourceLoader.instance();
-//		byte[] b = rld.getBytesFromResourceLocation("images/Sub24.gif");
-//		System.out.println((b == null) ? "null" : b.toString());
-//		b = rld.getBytesFromResourceLocation("src/eva2/client/SplashScreen.java");
-//		System.out.println((b == null) ? "null" : b.toString());
 
         HashSet<String> h = new HashSet<String>(20);
 
@@ -466,27 +392,10 @@ public class ReflectPackage {
         for (String string : h) {
             System.out.println("+ " + string);
         }
-
-//		String[] pathElements = getClassPathElements();
-//		for (int i=0; i<pathElements.length; i++) {
-//			System.out.print(i+" " + pathElements[i]);
-//			System.out.println(pathElements[i].endsWith(".jar") ? " is a jar" : " is a path");
-//			if (pathElements[i].endsWith(".jar")) {
-//				ArrayList al = getClassesFromJarFltr(pathElements[i], "eva2.server.model", false, null);
-//				for (int k=0; k<al.size(); k++) {
-//					//if (Class.forName("eva2.server.modules.ModuleAdapter").isAssignableFrom((Class)al.get(i))) 
-//						System.out.println((Class)al.get(k));
-//				}
-//			} else {
-//				
-//			}
-//		}
-
     }
 
     public static String[] getClassPathElements() {
         String classPath = System.getProperty("java.class.path", ".");
-//		System.out.println("classpath: " + classPath);
         return classPath.split(File.pathSeparator);
     }
 
@@ -495,7 +404,6 @@ public class ReflectPackage {
         Object bean = null;
         try {
             bean = server.getObjectInstance(new ObjectName("com.sun.management:type=HotSpotDiagnostic"));
-            //bean = server.queryMBeans(null, null);
         } catch (Exception e) {
             // TODO Auto-generated catch block
             e.printStackTrace();
@@ -507,12 +415,6 @@ public class ReflectPackage {
         MBeanServer server = ManagementFactory.getPlatformMBeanServer();
         Object ret = null;
         try {
-//        	void setVMOption(String name, String value)
-            //-Xrunhprof:heap=dump,format=b
-//        	ret = server.invoke(new ObjectName("com.sun.management:type=HotSpotDiagnostic"), 
-//        			"setVMOption", new Object[]{"agentlib", "hprof=heap=dump,format=a"}, 
-//        			new String[] {"java.lang.String","java.lang.String"});
-//        	ret = server.invoke(new ObjectName("com.sun.management:type=HotSpotDiagnostic"), "getDiagnosticOptions", new Object[] {}, new String[] {});
             server.invoke(new ObjectName("com.sun.management:type=HotSpotDiagnostic"), "dumpHeap", new Object[]{file, live}, new String[]{"java.lang.String", "boolean"});
             //bean = server.queryMBeans(null, null);
         } catch (Exception e) {
@@ -544,7 +446,6 @@ public class ReflectPackage {
      * @param args            constructor arguments
      * @param paramValuePairs pairs of values to set using generic setter methods
      * @return
-     * @see BeanInspector.setMem(Object,String,Object)
      */
     public static Object instantiateWithParams(String clsName, Object[] args, List<Pair<String, Object>> paramValuePairs) {
         Object o = getInstance(clsName, args);
@@ -555,8 +456,6 @@ public class ReflectPackage {
                     if (!succ) {
                         System.err.println("Error, unable to set " + nameVal.head + " to " + nameVal.tail + " in object " + o);
                         return null;
-                    } else if (TRACE) {
-                        System.out.println("Successfully set " + nameVal.head + " to " + nameVal.tail + " in object " + o);
                     }
                 }
             }

src/eva2/tools/chart2d/DArea.java

@@ -29,16 +29,13 @@ public class DArea extends JComponent implements DParent, Printable {
     /**
      * the default minimal rectangle which is shown
      */
-    public static final DRectangle DEFAULT_MIN_RECT = new DRectangle(-1, -1, 2,
+    public static final DRectangle DEFAULT_MIN_RECT = new DRectangle(-1, -1, 2, 2);
-            2);
 
     /**
      *
      */
     private static final long serialVersionUID = 1461387400381365146L;
 
-    private static final boolean TRACE = false;
-
     private boolean auto_focus = false, auto_grid = false,
             grid_to_front = false;
 
@@ -358,9 +355,6 @@ public class DArea extends JComponent implements DParent, Printable {
      */
     @Override
     public void paint(Graphics g) {
-        if (TRACE) {
-            System.out.println("DArea.paint(Graphics)");
-        }
         if (auto_focus) {
             container.restore();
             visible_rect = (DRectangle) container.getRectangle().clone();
@@ -388,9 +382,6 @@ public class DArea extends JComponent implements DParent, Printable {
      * auto_grid option
      */
     private void paintGrid(DMeasures m) {
-        if (TRACE) {
-            System.out.println("DArea.paintGrid(DMeasures)");
-        }
         grid.rectangle = getDRectangle();
         if (auto_grid) {
             Border b = getBorder();
@@ -417,9 +408,6 @@ public class DArea extends JComponent implements DParent, Printable {
      * @param m  the measures of the area
      */
     private void paintGrid(ScaledBorder sb, DMeasures m) {
-        if (TRACE) {
-            System.out.println("DArea.paintGrid(ScaledBorder, DMeasures)");
-        }
         Dimension d = getSize();
         FontMetrics fm = m.getGraphics().getFontMetrics();
         grid.setDistances(sb.getSrcdX(fm, d), sb.getSrcdY(fm, d));
@@ -479,9 +467,6 @@ public class DArea extends JComponent implements DParent, Printable {
      */
     @Override
     public int print(Graphics g, PageFormat pf, int pi) {
-        if (TRACE) {
-            System.out.println("DArea.print(...)");
-        }
         if (pi > 0) {
             return Printable.NO_SUCH_PAGE;
         }
@@ -553,9 +538,6 @@ public class DArea extends JComponent implements DParent, Printable {
      */
     @Override
     public void repaint(DRectangle r) {
-        if (TRACE) {
-            System.out.println("DArea.repaint(DRectangle)" + r);
-        }
         if (r == null) {
             throw new IllegalArgumentException(
                     "Cannot repaint a null DRectangle");
@@ -580,9 +562,6 @@ public class DArea extends JComponent implements DParent, Printable {
     @Override
     public void restoreBorder() {
         dborder = container.getDBorder();
-        if (TRACE) {
-            System.out.println("DArea.restoreBorder -> " + dborder);
-        }
     }
 
     /**
@@ -659,9 +638,7 @@ public class DArea extends JComponent implements DParent, Printable {
      * @param aFlag visible or not
      */
     public void setGridVisible(boolean aFlag) {
-        if (TRACE) {
+
-            System.out.println("DArea.setGridVisisble: " + aFlag);
-        }
         grid.rectangle = getDRectangle();
         grid.setVisible(aFlag);
     }
@@ -784,9 +761,6 @@ public class DArea extends JComponent implements DParent, Printable {
      * @param rect the visible <code>DRectangle</code> in DArea coordinates
      */
     public void setVisibleRectangle(DRectangle rect) {
-        if (TRACE) {
-            System.out.println("DArea.setVisibleRectangle(DRectangle)");
-        }
         if (rect.isEmpty()) {
             throw new IllegalArgumentException(
                     "You should never try to set an empty rectangle\n"