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Refactored "SetFitness" function to "setFitness". Coding Standards for the win.

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This commit is contained in:
Fabian Becker 2013-01-16 12:52:11 +00:00
parent 0f553039e4
commit cb357417a2
38 changed files with 50 additions and 50 deletions
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2
src/eva2/server/go/IndividualInterface.java
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@ -36,7 +36,7 @@ public interface IndividualInterface {
*
* @param fit new fitness of the individual
*/
void SetFitness (double[] fit);
void setFitness (double[] fit);
/**
* Check whether the instance is dominating the given other individual and return

2
src/eva2/server/go/individuals/AbstractEAIndividual.java
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@ -618,7 +618,7 @@ public abstract class AbstractEAIndividual implements IndividualInterface, java.
* @param fitness The new fitness array
* @deprecated
*/
public void SetFitness(double[] fitness) {
public void setFitness(double[] fitness) {
this.m_Fitness = fitness;
}

2
src/eva2/server/go/operators/archiving/ArchivingMaxiMin.java
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@ -62,7 +62,7 @@ public class ArchivingMaxiMin implements InterfaceArchiving, java.io.Serializabl
// now unconvert from SO to MO
for (int i = 0; i < archive.size(); i++) {
tmpD = (double[])((AbstractEAIndividual)archive.get(i)).getData("MOFitness");
((AbstractEAIndividual)archive.get(i)).SetFitness(tmpD);
((AbstractEAIndividual)archive.get(i)).setFitness(tmpD);
}
pop.SetArchive(archive);

2
src/eva2/server/go/operators/cluster/ClusteringKMeans.java
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@ -280,7 +280,7 @@ public class ClusteringKMeans implements InterfaceClustering, java.io.Serializab
*/
private double distance(AbstractEAIndividual indy, double[] p) {
if (m_UseSearchSpace) ((InterfaceDataTypeDouble)tmpIndy).SetDoubleGenotype(p);
else tmpIndy.SetFitness(p);
else tmpIndy.setFitness(p);
return metric.distance(indy, tmpIndy);
}

2
src/eva2/server/go/operators/moso/MOSODynamicallyWeightedFitness.java
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@ -59,7 +59,7 @@ public class MOSODynamicallyWeightedFitness implements InterfaceMOSOConverter, j
for (int i = 0; (i <2) && (i < tmpFit.length); i++)
resultFit[0] += tmpFit[i]*weights[i];
indy.SetFitness(resultFit);
indy.setFitness(resultFit);
}
/** This method allows the problem to set the current output size of

2
src/eva2/server/go/operators/moso/MOSOEpsilonConstraint.java
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@ -59,7 +59,7 @@ public class MOSOEpsilonConstraint implements InterfaceMOSOConverter, java.io.Se
indy.addConstraintViolation(Math.max(0, tmpFit[i] - this.m_EpsilonConstraint.m_TargetValue[i]));
}
}
indy.SetFitness(resultFit);
indy.setFitness(resultFit);
}
/** This method allows the problem to set the current output size of

2
src/eva2/server/go/operators/moso/MOSOEpsilonThreshold.java
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@ -78,7 +78,7 @@ public class MOSOEpsilonThreshold implements InterfaceMOSOConverter, java.io.Ser
if (new Double(tmpFit[i]).isNaN()) System.out.println("-Fitness is NaN");
if (new Double(tmpFit[i]).isInfinite()) System.out.println("-Fitness is Infinite");
}
indy.SetFitness(resultFit);
indy.setFitness(resultFit);
}
/** This method allows the problem to set the current output size of

2
src/eva2/server/go/operators/moso/MOSOGoalProgramming.java
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@ -54,7 +54,7 @@ public class MOSOGoalProgramming implements InterfaceMOSOConverter, java.io.Seri
resultFit[0] = 0;
for (int i = 0; (i < this.m_Goals.getNumRows()) && (i < tmpFit.length) ; i++)
resultFit[0] += tmpFit[i]-this.m_Goals.getValue(i, 0);
indy.SetFitness(resultFit);
indy.setFitness(resultFit);
}
/** This method allows the problem to set the current output size of

2
src/eva2/server/go/operators/moso/MOSOLpMetric.java
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@ -68,7 +68,7 @@ public class MOSOLpMetric implements InterfaceMOSOConverter, java.io.Serializabl
}
}
indy.SetFitness(resultFit);
indy.setFitness(resultFit);
}
/** This method allows the problem to set the current output size of

2
src/eva2/server/go/operators/moso/MOSOMOGARankBased.java
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@ -57,7 +57,7 @@ public class MOSOMOGARankBased implements InterfaceMOSOConverter, java.io.Serial
tmpFit = indy.getFitness();
indy.putData("MOFitness", tmpFit);
resultFit[0] = ((Integer)indy.getData("MOGARank")).doubleValue();
indy.SetFitness(resultFit);
indy.setFitness(resultFit);
}
/** This method allows the problem to set the current output size of

4
src/eva2/server/go/operators/moso/MOSOMaxiMin.java
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@ -65,7 +65,7 @@ public class MOSOMaxiMin implements InterfaceMOSOConverter, java.io.Serializable
tmpIndy.putData("MOFitness", tmpFit);
resultFit = new double[1];
resultFit[0] = result[i];
tmpIndy.SetFitness(resultFit);
tmpIndy.setFitness(resultFit);
}
////////////////////////////////////////////////////////////////////////////////////
// if (false) {
@ -106,7 +106,7 @@ public class MOSOMaxiMin implements InterfaceMOSOConverter, java.io.Serializable
indy.putData("MOFitness", tmpFit);
System.err.println("The MaxiMin MOSO can not be applied to single individuals! I default to random criterion.");
resultFit[0] = tmpFit[RNG.randomInt(0, tmpFit.length)];
indy.SetFitness(resultFit);
indy.setFitness(resultFit);
}
/** This method allows the problem to set the current output size of

2
src/eva2/server/go/operators/moso/MOSORandomChoice.java
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@ -47,7 +47,7 @@ public class MOSORandomChoice implements InterfaceMOSOConverter, java.io.Serial
tmpFit = indy.getFitness();
indy.putData("MOFitness", tmpFit);
resultFit[0] = tmpFit[RNG.randomInt(0, tmpFit.length-1)];
indy.SetFitness(resultFit);
indy.setFitness(resultFit);
}
/** This method allows the problem to set the current output size of

2
src/eva2/server/go/operators/moso/MOSORandomWeight.java
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@ -57,7 +57,7 @@ public class MOSORandomWeight implements InterfaceMOSOConverter, java.io.Seriali
}
for (int i = 0; (i < tmpWeight.length) && (i < tmpFit.length) ; i++)
resultFit[0] += tmpFit[i]*tmpWeight[i];
indy.SetFitness(resultFit);
indy.setFitness(resultFit);
}
/** This method allows the problem to set the current output size of

2
src/eva2/server/go/operators/moso/MOSORankbased.java
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@ -46,7 +46,7 @@ public class MOSORankbased implements InterfaceMOSOConverter, java.io.Serializab
tmpFit = indy.getFitness();
indy.putData("MOFitness", tmpFit);
resultFit[0] = ((Integer)indy.getData("ParetoLevel")).doubleValue();
indy.SetFitness(resultFit);
indy.setFitness(resultFit);
}
/** This method allows the problem to set the current output size of

2
src/eva2/server/go/operators/moso/MOSOUtilityFunction.java
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@ -59,7 +59,7 @@ public class MOSOUtilityFunction implements InterfaceMOSOConverter, java.io.Seri
/**********************************************************************************************
* and don't forget to set the reduced fitness to the individual
*/
indy.SetFitness(resultFit);
indy.setFitness(resultFit);
}
/** This method allows the problem to set the current output size of

2
src/eva2/server/go/operators/moso/MOSOWeightedFitness.java
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@ -61,7 +61,7 @@ public class MOSOWeightedFitness implements InterfaceMOSOConverter, java.io.Seri
indy.putData("MOFitness", tmpFit);
for (int i = 0; (i < this.m_Weights.getNumRows()) && (i < tmpFit.length) ; i++)
resultFit[0] += tmpFit[i]*this.m_Weights.getValue(i,0);
indy.SetFitness(resultFit);
indy.setFitness(resultFit);
}
private void checkingWeights() {

2
src/eva2/server/go/operators/moso/MOSOWeightedLPTchebycheff.java
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@ -65,7 +65,7 @@ public class MOSOWeightedLPTchebycheff implements InterfaceMOSOConverter, java.i
}
}
if (this.m_WLPT.m_P > 0) resultFit[0] = Math.pow(resultFit[0], 1/((double)this.m_WLPT.m_P));
indy.SetFitness(resultFit);
indy.setFitness(resultFit);
}
/** This method allows the problem to set the current output size of

2
src/eva2/server/go/operators/paretofrontmetrics/MetricS.java
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@ -115,7 +115,7 @@ public class MetricS implements InterfaceParetoFrontMetric, java.io.Serializable
redF = new double[tmpF.length -1];
for (int j = 0; j < redF.length; j++) redF[j] = tmpF[j];
tmpIndy = new ESIndividualDoubleData();
tmpIndy.SetFitness(redF);
tmpIndy.setFitness(redF);
smPop.add(i, tmpIndy);
}
}

4
src/eva2/server/go/operators/paretofrontmetrics/MetricSWithReference.java
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@ -109,7 +109,7 @@ public class MetricSWithReference implements InterfaceParetoFrontMetric, java.io
tmpPop.clear();
for (int i = 0; i < this.m_Reference.length; i++) {
tmpIndy = new ESIndividualDoubleData();
tmpIndy.SetFitness(this.m_Reference[i]);
tmpIndy.setFitness(this.m_Reference[i]);
tmpPop.addIndividual(tmpIndy);
}
this.m_ReferenceSMetric = this.calculateSMetric(tmpPop, this.m_ObjectiveSpaceRange, this.m_ObjectiveSpaceRange.length);
@ -149,7 +149,7 @@ public class MetricSWithReference implements InterfaceParetoFrontMetric, java.io
redF = new double[tmpF.length -1];
for (int j = 0; j < redF.length; j++) redF[j] = tmpF[j];
tmpIndy = new ESIndividualDoubleData();
tmpIndy.SetFitness(redF);
tmpIndy.setFitness(redF);
smPop.add(i, tmpIndy);
}
}

4
src/eva2/server/go/operators/selection/SelectMOMAIIDominanceCounter.java
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@ -77,11 +77,11 @@ public class SelectMOMAIIDominanceCounter implements InterfaceSelection, java.io
malta.m_SizeDominantSolutions = domCount;
double[] fitness = new double[1];
fitness[0] = 1/((double)(domCount+1));
tmpIndy1.SetFitness(fitness);
tmpIndy1.setFitness(fitness);
} else {
double[] fitness = new double[1];
fitness[0] = 2;
tmpIndy1.SetFitness(fitness);
tmpIndy1.setFitness(fitness);
}
}
}

2
src/eva2/server/go/operators/selection/SelectMOMaxiMin.java
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@ -61,7 +61,7 @@ public class SelectMOMaxiMin implements InterfaceSelection, java.io.Serializable
// now unconvert from SO to MO
for (int i = 0; i < result.size(); i++) {
tmpD = (double[])((AbstractEAIndividual)result.get(i)).getData("MOFitness");
((AbstractEAIndividual)result.get(i)).SetFitness(tmpD);
((AbstractEAIndividual)result.get(i)).setFitness(tmpD);
}
return result;
}

4
src/eva2/server/go/operators/selection/SelectMOSPEAII.java
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@ -64,7 +64,7 @@ public class SelectMOSPEAII implements InterfaceSelection, java.io.Serializable
orgFit[i] = ((AbstractEAIndividual)population.get(i)).getFitness();
newFit = new double[1];
newFit[0] = this.m_SPEAFitness[i];
((AbstractEAIndividual)population.get(i)).SetFitness(newFit);
((AbstractEAIndividual)population.get(i)).setFitness(newFit);
}
// then select
@ -72,7 +72,7 @@ public class SelectMOSPEAII implements InterfaceSelection, java.io.Serializable
// finally replace the fitness with the original
for (int i = 0; i < population.size(); i++) {
((AbstractEAIndividual)population.get(i)).SetFitness(orgFit[i]);
((AbstractEAIndividual)population.get(i)).setFitness(orgFit[i]);
}
if (false) {

6
src/eva2/server/go/populations/Population.java
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@ -680,7 +680,7 @@ public class Population extends ArrayList implements PopulationInterface, Clonea
AbstractEAIndividual indy;
for (int i = 0; i < size(); i++) {
indy = getEAIndividual(i);
indy.SetFitness(f.clone());
indy.setFitness(f.clone());
}
}
@ -882,7 +882,7 @@ public class Population extends ArrayList implements PopulationInterface, Clonea
public void resetFitness(IndividualInterface indy) {
double[] tmpFit = indy.getFitness();
java.util.Arrays.fill(tmpFit, Double.MAX_VALUE);
indy.SetFitness(tmpFit);
indy.setFitness(tmpFit);
}
/**
@ -2150,7 +2150,7 @@ public class Population extends ArrayList implements PopulationInterface, Clonea
AbstractEAIndividual indy = (AbstractEAIndividual) getEAIndividual(0).clone();
double[] center = getCenter();
AbstractEAIndividual.setDoublePosition(indy, center);
indy.SetFitness(null);
indy.setFitness(null);
return indy;
}

2
src/eva2/server/go/problems/AbstractDynTransProblem.java
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@ -48,7 +48,7 @@ public abstract class AbstractDynTransProblem extends AbstractSynchronousOptimiz
AbstractEAIndividual tussy = (AbstractEAIndividual)individual.clone();
transform(tussy, time);
getProblem().evaluate(tussy);
individual.SetFitness(tussy.getFitness());
individual.setFitness(tussy.getFitness());
}
/**

2
src/eva2/server/go/problems/AbstractMultiModalProblemKnown.java
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@ -180,7 +180,7 @@ implements Interface2DBorderProblem, InterfaceMultimodalProblemKnown {
InterfaceDataTypeDouble tmpIndy;
tmpIndy = (InterfaceDataTypeDouble)((AbstractEAIndividual)this.m_Template).clone();
tmpIndy.SetDoubleGenotype(point);
((AbstractEAIndividual)tmpIndy).SetFitness(evalUnnormalized(point));
((AbstractEAIndividual)tmpIndy).setFitness(evalUnnormalized(point));
if (((AbstractEAIndividual)tmpIndy).getFitness(0)>=m_GlobalOpt) {
m_GlobalOpt = ((AbstractEAIndividual)tmpIndy).getFitness(0);
if (makeGlobalOptUnreachable) {

2
src/eva2/server/go/problems/AbstractProblemBinary.java
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@ -41,7 +41,7 @@ public abstract class AbstractProblemBinary extends AbstractOptimizationProblem
// evaluate the fitness
result = eval(tmpBitSet);
// set the fitness
individual.SetFitness(result);
individual.setFitness(result);
}
/**

6
src/eva2/server/go/problems/AbstractProblemDouble.java
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@ -204,7 +204,7 @@ public abstract class AbstractProblemDouble extends AbstractOptimizationProblem
*/
protected void setEvalFitness(AbstractEAIndividual individual, double[] x,
double[] fit) {
individual.SetFitness(fit);
individual.setFitness(fit);
}
/**
@ -441,7 +441,7 @@ public abstract class AbstractProblemDouble extends AbstractOptimizationProblem
// required
tmpIndy.SetDoubleGenotype(pos);
}
((AbstractEAIndividual) tmpIndy).SetFitness(prob.eval(pos));
((AbstractEAIndividual) tmpIndy).setFitness(prob.eval(pos));
if (!Mathematics.isInRange(pos, prob.makeRange())) {
System.err.println("Warning, add optimum which is out of range!");
}
@ -462,7 +462,7 @@ public abstract class AbstractProblemDouble extends AbstractOptimizationProblem
tmpIndy = (InterfaceDataTypeDouble) prob.getIndividualTemplate()
.clone();
tmpIndy.SetDoubleGenotype(pos);
((AbstractEAIndividual) tmpIndy).SetFitness(prob.eval(pos));
((AbstractEAIndividual) tmpIndy).setFitness(prob.eval(pos));
pop.add(tmpIndy);
FitnessConvergenceTerminator convTerm = new FitnessConvergenceTerminator(
1e-25, 10, StagnationTypeEnum.generationBased,

2
src/eva2/server/go/problems/ExternalRuntimeProblem.java
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@ -180,7 +180,7 @@ implements Interface2DBorderProblem, InterfaceProblemDouble, InterfaceHasInitRan
x = getXVector(individual);
double[] fit = eval(x);
individual.SetFitness(fit);
individual.setFitness(fit);
// if (this.m_UseTestConstraint) {
// if (x[0] < 1) individual.addConstraintViolation(1-x[0]);

2
src/eva2/server/go/problems/FLensProblem.java
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@ -56,7 +56,7 @@ class MyLensViewer extends JPanel implements InterfaceSolutionViewer {
// this.m_BestFitness = Double.POSITIVE_INFINITY;
// this.m_BestVariables = new double[10];
ESIndividualDoubleData dummy = new ESIndividualDoubleData();
dummy.SetFitness(new double[]{Double.POSITIVE_INFINITY});
dummy.setFitness(new double[]{Double.POSITIVE_INFINITY});
indiesToPaint = new Population();
}

4
src/eva2/server/go/problems/MatlabProblem.java
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@ -329,7 +329,7 @@ public class MatlabProblem extends AbstractOptimizationProblem implements Interf
for (int i=0; i<seedData.length; i++) {
AbstractEAIndividual indy = (AbstractEAIndividual)m_Template.clone();
setIndyGenotype(indy, seedData[i]);
indy.SetFitness(seedDataFit[i]);
indy.setFitness(seedDataFit[i]);
seedPopulation.add(indy);
}
}
@ -620,7 +620,7 @@ public class MatlabProblem extends AbstractOptimizationProblem implements Interf
double[] res = handler.requestEval(this, AbstractEAIndividual.getIndyData(indy));
log("evaluated to " + BeanInspector.toString(res) + "\n");
log("Free mem is " + Runtime.getRuntime().freeMemory() + ", time is " + System.currentTimeMillis() + "\n");
indy.SetFitness(res);
indy.setFitness(res);
}
@Override

4
src/eva2/server/go/problems/SimpleProblemWrapper.java
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@ -60,7 +60,7 @@ public class SimpleProblemWrapper extends AbstractOptimizationProblem {
// if indicated, add Gaussian noise
if (m_Noise != 0) RNG.addNoise(fitness, m_Noise);
// set the fitness
individual.SetFitness(fitness);
individual.setFitness(fitness);
} else if (simProb instanceof SimpleProblemBinary) {
BitSet tmpBitSet;
double[] result;
@ -69,7 +69,7 @@ public class SimpleProblemWrapper extends AbstractOptimizationProblem {
// evaluate the fitness
result = ((SimpleProblemBinary)simProb).eval(tmpBitSet);
// set the fitness
individual.SetFitness(result);
individual.setFitness(result);
} else {
System.err.println("Error in SimpleProblemWrapper: " + simProb.getClass().getName() + " is unknown type!");
}

2
src/eva2/server/go/strategies/DifferentialEvolution.java
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@ -405,7 +405,7 @@ public class DifferentialEvolution implements InterfaceOptimizer, java.io.Serial
indy.resetConstraintViolation();
double[] fit = new double[1];
fit[0] = 0;
indy.SetFitness(fit);
indy.setFitness(fit);
if (parents != null) indy.setParents(parents);
return indy;
}

2
src/eva2/server/go/strategies/MemeticAlgorithm.java
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@ -172,7 +172,7 @@ public class MemeticAlgorithm implements InterfaceOptimizer,
try {
AbstractEAIndividual newindy = (AbstractEAIndividual) antilamarckismcache
.get(indy);
indy.SetFitness(newindy.getFitness());
indy.setFitness(newindy.getFitness());
} catch (Exception ex) {
System.err.println("individual not found in antilamarckismcache");
}

2
src/eva2/server/go/strategies/ParticleSwarmOptimization.java
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@ -2228,7 +2228,7 @@ public class ParticleSwarmOptimization implements InterfaceOptimizer, java.io.Se
throw new RuntimeException("Mismatching best fitness!! " + personalBestfit[0] + " vs. " + ((InterfaceProblemDouble) m_Problem).eval(personalBestPos)[0]);
}
((InterfaceDataTypeDouble) indy).SetDoubleGenotype(personalBestPos);
indy.SetFitness(personalBestfit);
indy.setFitness(personalBestfit);
bests.add((AbstractEAIndividual) indy.clone());
}
return bests;

4
src/eva2/server/go/strategies/Tribes.java
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@ -253,7 +253,7 @@ public class Tribes implements InterfaceOptimizer, java.io.Serializable {
AbstractEAIndividual bestExp = population.getBestEAIndividual();
if (bestMemPos.firstIsBetter(bestMemPos.getFitness(), bestExp.getFitness())) {
AbstractEAIndividual indy = (AbstractEAIndividual)bestExp.clone();
indy.SetFitness(bestMemPos.getFitness());
indy.setFitness(bestMemPos.getFitness());
((InterfaceDataTypeDouble)indy).SetDoubleGenotype(bestMemPos.getPos());
return indy;
} else return bestExp;
@ -688,7 +688,7 @@ public class Tribes implements InterfaceOptimizer, java.io.Serializable {
TribesExplorer indy = tmp.clone();
indy.clearPosVel();
indy.SetDoubleGenotype(pos.getPos());
indy.SetFitness(pos.getFitness());
indy.setFitness(pos.getFitness());
return indy;
}

4
src/eva2/server/go/strategies/tribes/TribesExplorer.java
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@ -94,9 +94,9 @@ public class TribesExplorer extends AbstractEAIndividual implements InterfaceDat
* Be aware that for a TribesExplorer, an objective value might be taken into account
* by reducing the fitness (in the first dimension).
*/
public void SetFitness(double[] fitness) {
public void setFitness(double[] fitness) {
position.fitness = fitness;
super.SetFitness(fitness);
super.setFitness(fitness);
fitness[0] -= objectiveValueFirstDim;
position.setTotalError();
}

2
src/eva2/server/go/tools/DeNovofilter.java
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@ -63,7 +63,7 @@ public class DeNovofilter {
tmpD[i-2] = new Double(tmpS[i]).doubleValue();
}
indy = new ESIndividualDoubleData();
indy.SetFitness(tmpD);
indy.setFitness(tmpD);
pop.add(indy);
}
reader.close();

2
src/eva2/server/go/tools/ImpactOfDimensionOnMOEAs.java
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@ -124,7 +124,7 @@ public class ImpactOfDimensionOnMOEAs {
if (j < x.length) fitness[j] =1/((double)fitness[j]) + x[j];
else fitness[j] =1/((double)fitness[j]) + x[j%objectives] + x[(j+1)%objectives];
}
((AbstractEAIndividual)pop.get(i)).SetFitness(fitness);
((AbstractEAIndividual)pop.get(i)).setFitness(fitness);
}
}