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Remove last traces of the TRACE variable.

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This commit is contained in:
Fabian Becker 2014-10-19 14:19:54 +02:00
parent d9cc88e60d
commit 7d6a9faf66
45 changed files with 127 additions and 1211 deletions
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14
src/eva2/gui/EvATreeSelectionListener.java
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@ -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));

4
src/eva2/gui/PropertySheetPanelStat.java
View File

@ -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];

1
src/eva2/gui/plot/FunctionArea.java
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@ -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);
}

7
src/eva2/gui/plot/TopoPlot.java
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@ -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;
}

7
src/eva2/optimization/individuals/codings/gp/AbstractGPNode.java
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@ -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);
}
}

2
src/eva2/optimization/mocco/paretofrontviewer/ParetoFrontView2D.java
View File

@ -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]);

3
src/eva2/optimization/modules/Processor.java
View File

@ -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 (Error error) {
} catch (Exception | Error ex) {
}
//statistics.stopOptimizationPerformed(false);
setOptimizationRunning(false); // normal finish

25
src/eva2/optimization/operator/cluster/ClusteringNearestBetter.java
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@ -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 {

4
src/eva2/optimization/operator/constraint/AbstractConstraint.java
View File

@ -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;

7
src/eva2/optimization/operator/constraint/ConstraintCollection.java
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@ -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;
}

9
src/eva2/optimization/operator/constraint/GenericConstraint.java
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@ -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() {

16
src/eva2/optimization/operator/crossover/CrossoverGAGINPoint.java
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@ -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
* selected points. Therefore, far-away allels (larger GA schemas) are more likely to be split
* parent individuals are recombined by exchanging sub-segments within randomly
* 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;
}

28
src/eva2/optimization/operator/crossover/CrossoverGPDefault.java
View File

@ -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++) {
((GPIndividualProgramData) result[i]).checkDepth();
result[i].getMutationOperator().crossoverOnStrategyParameters(indy1, partners);
}
if (TRACE) {
for (int i = 0; i < result.length; i++) {
System.out.println("After Crossover: " + result[i].getStringRepresentation());
}
for (AbstractEAIndividual aResult : result) {
((GPIndividualProgramData) aResult).checkDepth();
aResult.getMutationOperator().crossoverOnStrategyParameters(indy1, partners);
}
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

6
src/eva2/optimization/operator/mutation/CMAParamSet.java
View File

@ -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)) {

24
src/eva2/optimization/operator/mutation/MutateESCorrVector.java
View File

@ -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++) {
if (((AbstractEAIndividual) partners.get(i)).getMutationOperator() instanceof MutateESCorrVector) {
tmpList.add(new Double(((MutateESCorrVector) ((AbstractEAIndividual) partners.get(i)).getMutationOperator()).scalingDev));
for (Object partner : partners) {
if (((AbstractEAIndividual) partner).getMutationOperator() instanceof MutateESCorrVector) {
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)];
}

5
src/eva2/optimization/operator/mutation/MutateESCovarianceMatrixAdaption.java
View File

@ -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 {

109
src/eva2/optimization/operator/mutation/MutateESRankMuCMA.java
View File

@ -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,
// so we take the parameter set from the last adpation step.
// for GA and ES we can expect that selection occurred directly before the mutation cycle,
// 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)) {
if (TRACE_TEST) {
System.out.println("testCCondition hit");
}
return true;
} else {
return false;
}
return (minMax.head <= 0) || (minMax.tail >= d);
}
/**

5
src/eva2/optimization/operator/paramcontrol/AbstractParameterControl.java
View File

@ -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);
}
}
}
}

19
src/eva2/optimization/operator/paramcontrol/ConstraintBasedAdaption.java
View File

@ -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;
}

5
src/eva2/optimization/operator/paramcontrol/PSOActivityFeedbackControl.java
View File

@ -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

12
src/eva2/optimization/operator/paramcontrol/ParameterControlManager.java
View File

@ -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++) {
String prm = singleAdapters[i].getControlledParam();
for (ParamAdaption singleAdapter : singleAdapters) {
String prm = singleAdapter.getControlledParam();
if (prm != null) {
names.add(prm);
}

25
src/eva2/optimization/operator/paretofrontmetrics/MetricS.java
View File

@ -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++) {
reference *= (this.objectiveSpaceRange[i][1] - this.objectiveSpaceRange[i][0]);
for (double[] anObjectiveSpaceRange : this.objectiveSpaceRange) {
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

33
src/eva2/optimization/operator/postprocess/PostProcess.java
View File

@ -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));
}
}

30
src/eva2/optimization/operator/terminators/PopulationMeasureTerminator.java
View File

@ -22,15 +22,13 @@ import java.io.Serializable;
*
* @author mkron
*/
public abstract class PopulationMeasureTerminator implements InterfaceTerminator,
Serializable {
public abstract class PopulationMeasureTerminator implements InterfaceTerminator, 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;
}

18
src/eva2/optimization/population/Population.java
View File

@ -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;
}

23
src/eva2/optimization/stat/EvAStatisticalEvaluation.java
View File

@ -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,

89
src/eva2/optimization/strategies/ANPSO.java
View File

@ -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++) {
setOfSubswarms.get(i).synchSize();
for (Population setOfSubswarm : setOfSubswarms) {
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>();
//reinitedSwarm = new Vector<ParticleSubSwarmOptimization>();
deactivatedSwarm = new Vector<>();
// merging
mergingOccurd = false;
borg = new Vector<ParticleSubSwarmOptimization>();
others = new Vector<ParticleSubSwarmOptimization>();
borgbest = new Vector<AbstractEAIndividual>();
othersbest = new Vector<AbstractEAIndividual>();
borg = new Vector<>();
others = new Vector<>();
borgbest = new Vector<>();
othersbest = new Vector<>();
// absorbtion
absorbtionOccurd = false;
indytoabsorb = new Vector<AbstractEAIndividual>();
indytoabsorb = new Vector<>();
// subswarmcreation
creationOccurd = false;
indyconverged = new Vector<AbstractEAIndividual>();
convergedneighbor = new Vector<AbstractEAIndividual>();
indyconverged = new Vector<>();
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
currentsubswarm = (Population) inactiveSubSwarms.get(i).getPopulation().clone();
for (ParticleSubSwarmOptimization inactiveSubSwarm : inactiveSubSwarms) { // in the case of ANPSO
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) {
elitePop.addIndividual((AbstractEAIndividual) inactiveSubSwarms.get(i).bestIndividual.clone());
for (ParticleSubSwarmOptimization inactiveSubSwarm : inactiveSubSwarms) {
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;
}

20
src/eva2/optimization/strategies/BinaryScatterSearch.java
View File

@ -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
* @return the new Population
* @param targetSize The size of 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++) {
Population s = newSubsets.get(i);
for (Population s : newSubsets) {
AbstractEAIndividual x = combineSolution(s);
if (!contains((InterfaceDataTypeBinary) x, this.pool) && this.pool.size() <= this.poolSize) {
this.pool.add(x);

222
src/eva2/optimization/strategies/ClusterBasedNichingEA.java
View File

@ -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++) {
countIndies += species.get(i).size();
}
if (TRACE) {
System.out.println("NumIndies: " + countIndies);
for (Population specy1 : species) {
countIndies += specy1.size();
}
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++) {
this.population.addPopulation(this.species.get(i));
for (Population specy : this.species) {
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++) {
Population curSpec = species.get(i);
for (Population curSpec : species) {
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++) {
this.population.addPopulation(this.species.get(i));
for (Population specy : this.species) {
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 pop2
* @param spec1
* @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());
}

25
src/eva2/optimization/strategies/ClusteringHillClimbing.java
View File

@ -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);
}
/**

128
src/eva2/optimization/strategies/EsDpiNiching.java
View File

@ -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.");
}
}
/**

18
src/eva2/optimization/strategies/GradientDescentAlgorithm.java
View File

@ -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);

7
src/eva2/optimization/strategies/IslandModelEA.java
View File

@ -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) {

23
src/eva2/optimization/strategies/MemeticAlgorithm.java
View File

@ -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);
}
}

9
src/eva2/optimization/strategies/ParticleFilterOptimization.java
View File

@ -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);
}

15
src/eva2/optimization/strategies/ParticleSwarmOptimization.java
View File

@ -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));
}
}
}
}

57
src/eva2/optimization/strategies/ScatterSearch.java
View File

@ -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;
}

10
src/eva2/optimization/strategies/Tribes.java
View File

@ -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) {

24
src/eva2/optimization/strategies/tribes/TribesPosition.java
View File

@ -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();
}

16
src/eva2/optimization/strategies/tribes/TribesSwarm.java
View File

@ -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();

1
src/eva2/problems/MatlabEvalMediator.java
View File

@ -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;

6
src/eva2/problems/MatlabProblem.java
View File

@ -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();

18
src/eva2/tools/KMEANSJAVA.java
View File

@ -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);
if (indices[j] == indexofc) {
for (int indice : indices) { //System.out.println("j="+j);
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 (int j = 0; j < test[i].length; j++) {
System.out.print(test[i][j] + " ");
for (double[] aTest : test) {
for (int j = 0; j < aTest.length; j++) {
System.out.print(aTest[j] + " ");
}
System.out.println("");
}

179
src/eva2/tools/ReflectPackage.java
View File

@ -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++) {
if (reqSuperCls.isAssignableFrom(classes.get(i))) {
if (TRACE) {
System.out.println(" taking over " + classes.get(i));
}
assClasses.add(classes.get(i));
for (Class aClass : classes) {
if (reqSuperCls.isAssignableFrom(aClass)) {
assClasses.add(aClass);
}
}
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) {
System.err.println("ReflectPackage: Couldnt get Class from jar for " + clsName + ": " + e.getMessage());
} catch (Error e) {
System.err.println("ReflectPackage: Couldnt get Class from jar for " + clsName + ": " + e.getMessage());
} catch (Exception | Error e) {
System.err.println("ReflectPackage: Couldn't 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 includeSubs
* @param bSort sort alphanumerically by class name
* @param pkg Package name
* @param includeSubs Whether to include sub packages
* @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) {
return getClassesInPackageFltr(new HashSet<Class>(), pckg, includeSubs, bSort, null);
public static Class[] getAllClassesInPackage(String pkg, boolean includeSubs, boolean bSort) {
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) {
String classPath = null;
public static Class[] getClassesInPackageFltr(HashSet<Class> set, String pkg, boolean includeSubs, boolean bSort, Class reqSuperCls) {
if (!useFilteredClassPath || (dynCP == null)) {
classPath = System.getProperty("java.class.path", ".");
if (useFilteredClassPath) {
try {
dynCP = getValidCPArray();
@ -263,20 +226,11 @@ public class ReflectPackage {
}
}
if (TRACE) {
System.out.println("classpath is " + classPath);
}
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);
for (String aDynCP : dynCP) {
if (aDynCP.endsWith(".jar")) {
getClassesFromJarFltr(set, aDynCP, pkg, includeSubs, reqSuperCls);
} else {
if (TRACE) {
System.out.println("reading from files: " + dynCP[i] + " " + pckg);
}
getClassesFromFilesFltr(set, dynCP[i], pckg, includeSubs, reqSuperCls);
getClassesFromFilesFltr(set, aDynCP, pkg, 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++) {
if (!cpEntries[i].endsWith(".jar")) { // its a fs directory (hopefully)
if (TRACE) {
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]);
}
for (String cpEntry : cpEntries) {
if (!cpEntry.endsWith(".jar")) { // its a fs directory (hopefully)
f = new File(cpEntry + fNameSep);
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++) {
if (!cpEntries[i].endsWith(".jar")) { // its a fs directory (hopefully)
if (TRACE) {
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]);
}
for (String cpEntry : cpEntries) {
if (!cpEntry.endsWith(".jar")) { // its a fs directory (hopefully)
f = new File(cpEntry + fNameSep);
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++) {
// System.err.println(pathElements[i]);
f = new File(pathElements[i]);
// if (f.canRead()) {valids.add(pathElements[i]);}
for (String pathElement : pathElements) {
f = new File(pathElement);
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 reqSuperCls
* @param pckgClassName String denoting the package
* @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("2: " + cld.getResource("eva2/server"));
// 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());
System.out.println("1: " + cld.getResource("/eva2/optimization"));
System.out.println("2: " + cld.getResource("eva2/optimization"));
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);
}
}
}

30
src/eva2/tools/chart2d/DArea.java
View File

@ -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,
2);
public static final DRectangle DEFAULT_MIN_RECT = new DRectangle(-1, -1, 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"