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Random refactoring to make EvA2Problems work again.

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This commit is contained in:
Fabian Becker 2014-10-31 18:36:15 +01:00
parent 3ac628e85f
commit c8de290e4c
17 changed files with 33 additions and 32 deletions
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1
src/eva2/optimization/tools/GeneralOptimizationEditorProperty.java
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@ -13,6 +13,7 @@ public class GeneralOptimizationEditorProperty {
public PropertyEditor editor;
public Object value;
public JComponent view;
public JComponent viewWrapper;
public JLabel label;
public Class propertyType;
public String name;

4
src/eva2/optimization/tools/ImpactOfDimensionOnMOEAs.java
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@ -52,7 +52,7 @@ public class ImpactOfDimensionOnMOEAs {
mean = 0;
for (int j = 0; j < multiRuns; j++) {
pop = new Population();
ikel.initPopulation(pop, popSize, numberofVariables);
ikel.initializePopulation(pop, popSize, numberofVariables);
ikel.evaluatePopulation(pop, i);
mean += ikel.numberOfParetoOptimalSolutions(pop) / (double) pop.size();
}
@ -97,7 +97,7 @@ public class ImpactOfDimensionOnMOEAs {
}
}
public void initPopulation(Population pop, int popSize, int numberOfVariables) {
public void initializePopulation(Population pop, int popSize, int numberOfVariables) {
AbstractEAIndividual tmpIndy, template;
pop.clear();
template = new ESIndividualDoubleData();

2
src/eva2/problems/AbstractDynTransProblem.java
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@ -129,7 +129,7 @@ public abstract class AbstractDynTransProblem extends AbstractSynchronousOptimiz
*
*/
@Override
public void initPopulationAt(Population population, double time) {
public void initializePopulationAt(Population population, double time) {
getProblem().initializePopulation(population);
for (Object individuum : population) {
((AbstractEAIndividual) individuum).setAge(0);

4
src/eva2/problems/AbstractDynamicOptimizationProblem.java
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@ -101,7 +101,7 @@ public abstract class AbstractDynamicOptimizationProblem extends AbstractOptimiz
*/
@Override
public void initializePopulation(Population population) {
this.initPopulationAt(population, getCurrentProblemTime());
this.initializePopulationAt(population, getCurrentProblemTime());
}
/**
@ -110,7 +110,7 @@ public abstract class AbstractDynamicOptimizationProblem extends AbstractOptimiz
* @param population The populations that is to be inited
* @param time current time stamp to be used
*/
public abstract void initPopulationAt(Population population, double time);
public abstract void initializePopulationAt(Population population, double time);
/**
* @return the startTime

10
src/eva2/problems/AbstractMultiObjectiveOptimizationProblem.java
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@ -96,7 +96,7 @@ public abstract class AbstractMultiObjectiveOptimizationProblem extends Abstract
this.template = new ESIndividualDoubleData();
makeBorder();
if (this.show) {
this.initProblemFrame();
this.initializeProblemFrame();
}
}
@ -112,7 +112,7 @@ public abstract class AbstractMultiObjectiveOptimizationProblem extends Abstract
public void setShowParetoFront(boolean b) {
this.show = b;
if (this.show) {
this.initProblemFrame();
this.initializeProblemFrame();
} else if (this.plot != null) {
this.plot.dispose();
this.plot = null;
@ -146,7 +146,7 @@ public abstract class AbstractMultiObjectiveOptimizationProblem extends Abstract
makeBorder();
this.paretoFront = new Population();
if (this.show) {
this.initProblemFrame();
this.initializeProblemFrame();
}
}
@ -206,7 +206,7 @@ public abstract class AbstractMultiObjectiveOptimizationProblem extends Abstract
public void evaluatePopulationStart(Population population) {
super.evaluatePopulationStart(population);
if (this.show && (this.plot == null)) {
this.initProblemFrame();
this.initializeProblemFrame();
}
}
@ -283,7 +283,7 @@ public abstract class AbstractMultiObjectiveOptimizationProblem extends Abstract
/**
* This method will initialize the problem specific visualisation of the problem
*/
public void initProblemFrame() {
public void initializeProblemFrame() {
double[] tmpD = new double[2];
tmpD[0] = 0;
tmpD[1] = 0;

2
src/eva2/problems/AbstractOptimizationProblem.java
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@ -188,7 +188,7 @@ public abstract class AbstractOptimizationProblem implements InterfaceOptimizati
* @param template
* @param prob
*/
public static void defaultInitPopulation(Population population, AbstractEAIndividual template, InterfaceOptimizationProblem prob) {
public static void defaultInitializePopulation(Population population, AbstractEAIndividual template, InterfaceOptimizationProblem prob) {
AbstractEAIndividual tmpIndy;
population.clear();

6
src/eva2/problems/AbstractProblemBinary.java
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@ -40,7 +40,7 @@ public abstract class AbstractProblemBinary extends AbstractOptimizationProblem
tmpBitSet = ((InterfaceDataTypeBinary) individual).getBinaryData();
// evaluate the fitness
result = eval(tmpBitSet);
result = evaluate(tmpBitSet);
// set the fitness
individual.setFitness(result);
}
@ -52,12 +52,12 @@ public abstract class AbstractProblemBinary extends AbstractOptimizationProblem
* @param x a BitSet representing a possible
* @return
*/
public abstract double[] eval(BitSet bs);
public abstract double[] evaluate(BitSet bs);
@Override
public void initializePopulation(Population population) {
((InterfaceDataTypeBinary) this.template).setBinaryDataLength(this.getProblemDimension());
AbstractOptimizationProblem.defaultInitPopulation(population, template, this);
AbstractOptimizationProblem.defaultInitializePopulation(population, template, this);
}
@Override

2
src/eva2/problems/AbstractProblemDouble.java
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@ -205,7 +205,7 @@ public abstract class AbstractProblemDouble extends AbstractOptimizationProblem
@Override
public void initializePopulation(Population population) {
initTemplate();
AbstractOptimizationProblem.defaultInitPopulation(population, template, this);
AbstractOptimizationProblem.defaultInitializePopulation(population, template, this);
}
/**

2
src/eva2/problems/AbstractProblemInteger.java
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@ -47,7 +47,7 @@ public abstract class AbstractProblemInteger extends AbstractOptimizationProblem
public void initializePopulation(Population population) {
this.bestIndividuum = null;
((InterfaceDataTypeInteger) this.template).setIntegerDataLength(this.problemDimension);
AbstractOptimizationProblem.defaultInitPopulation(population, template, this);
AbstractOptimizationProblem.defaultInitializePopulation(population, template, this);
}
@Override

2
src/eva2/problems/B1Problem.java
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@ -48,7 +48,7 @@ public class B1Problem extends AbstractProblemBinary implements java.io.Serializ
* @return Double[]
*/
@Override
public double[] eval(BitSet b) {
public double[] evaluate(BitSet b) {
double[] result = new double[1];
int fitness = 0;

14
src/eva2/problems/BKnapsackProblem.java
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@ -165,7 +165,7 @@ public class BKnapsackProblem extends AbstractProblemBinary implements java.io.S
BitSet tmpSet = new BitSet();
tmpSet.clear();
while (eval(tmpSet)[1] > 0) {
while (evaluate(tmpSet)[1] > 0) {
tmpSet.set(RNG.randomInt(0, items.length - 1));
}
((InterfaceDataTypeBinary) indy).setBinaryGenotype(tmpSet);
@ -183,7 +183,7 @@ public class BKnapsackProblem extends AbstractProblemBinary implements java.io.S
double[] result;
tmpBitSet = ((InterfaceDataTypeBinary) individual).getBinaryData();
result = this.eval(tmpBitSet);
result = this.evaluate(tmpBitSet);
if (RNG.flipCoin(this.localSearch)) {
// first remove surplus assets
while (result[1] > 0) {
@ -203,7 +203,7 @@ public class BKnapsackProblem extends AbstractProblemBinary implements java.io.S
}
// remove the weakest
tmpBitSet.clear(weakest);
result = this.eval(tmpBitSet);
result = this.evaluate(tmpBitSet);
}
// now lets see if we can replace some guy with a more efficient one
int weakest = tmpBitSet.nextSetBit(0);
@ -223,7 +223,7 @@ public class BKnapsackProblem extends AbstractProblemBinary implements java.io.S
}
tmpBitSet.clear(weakest);
result = this.eval(tmpBitSet);
result = this.evaluate(tmpBitSet);
int weight = 0;
for (int i = 0; i < items.length; i++) {
if (tmpBitSet.get(i)) {
@ -246,7 +246,7 @@ public class BKnapsackProblem extends AbstractProblemBinary implements java.io.S
if (stronger >= 0) {
tmpBitSet.set(stronger);
}
result = this.eval(tmpBitSet);
result = this.evaluate(tmpBitSet);
}
if (this.lamarckism) {
@ -266,7 +266,7 @@ public class BKnapsackProblem extends AbstractProblemBinary implements java.io.S
* @return Double[]
*/
@Override
public double[] eval(BitSet b) {
public double[] evaluate(BitSet b) {
double[] result = new double[3];
int l = items.length;
@ -306,7 +306,7 @@ public class BKnapsackProblem extends AbstractProblemBinary implements java.io.S
tmpIndy = (InterfaceDataTypeBinary) individual;
tmpBitSet = tmpIndy.getBinaryData();
report = this.eval(tmpBitSet);
report = this.evaluate(tmpBitSet);
result += individual.getStringRepresentation() + "\n";
result += "Is worth: " + Math.abs(report[2]) + " and ";
if (report[1] == 0) {

2
src/eva2/problems/ExternalRuntimeProblem.java
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@ -149,7 +149,7 @@ public class ExternalRuntimeProblem extends AbstractOptimizationProblem
((InterfaceDataTypeDouble) this.template).setDoubleDataLength(this.problemDimension);
((InterfaceDataTypeDouble) this.template).setDoubleRange(makeRange());
AbstractOptimizationProblem.defaultInitPopulation(population, template, this);
AbstractOptimizationProblem.defaultInitializePopulation(population, template, this);
}
@Override

2
src/eva2/problems/FLensProblem.java
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@ -285,7 +285,7 @@ public class FLensProblem extends AbstractOptimizationProblem
}
((InterfaceDataTypeDouble) this.template).setDoubleRange(range);
AbstractOptimizationProblem.defaultInitPopulation(population, template, this);
AbstractOptimizationProblem.defaultInitializePopulation(population, template, this);
if (this.show) {
this.initProblemFrame();
}

2
src/eva2/problems/MatlabProblem.java
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@ -561,7 +561,7 @@ public class MatlabProblem extends AbstractOptimizationProblem implements Interf
@Override
public void initializePopulation(Population population) {
initTemplate();
AbstractOptimizationProblem.defaultInitPopulation(population, template, this);
AbstractOptimizationProblem.defaultInitializePopulation(population, template, this);
}
@Override

6
src/eva2/problems/PSymbolicRegression.java
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@ -144,7 +144,7 @@ public class PSymbolicRegression extends AbstractOptimizationProblem implements
*/
@Override
public void initializePopulation(Population population) {
initPopulation(population, this, useInnerConst, numberOfConstants);
initializePopulation(population, this, useInnerConst, numberOfConstants);
}
/**
@ -155,7 +155,7 @@ public class PSymbolicRegression extends AbstractOptimizationProblem implements
* @param useInnerConsts
* @param numConsts
*/
public static void initPopulation(Population pop, InterfaceProgramProblem prob, boolean useInnerConsts, int numConsts) {
public static void initializePopulation(Population pop, InterfaceProgramProblem prob, boolean useInnerConsts, int numConsts) {
AbstractEAIndividual template;
template = ((AbstractOptimizationProblem) prob).getIndividualTemplate();
@ -166,7 +166,7 @@ public class PSymbolicRegression extends AbstractOptimizationProblem implements
if ((template instanceof GAPIndividualProgramData) && useInnerConsts) {
((GAPIndividualProgramData) template).setDoubleDataLength(numConsts);
}
AbstractOptimizationProblem.defaultInitPopulation(pop, template, prob);
AbstractOptimizationProblem.defaultInitializePopulation(pop, template, prob);
}
/**

2
src/eva2/problems/SimpleProblemWrapper.java
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@ -104,7 +104,7 @@ public class SimpleProblemWrapper extends AbstractOptimizationProblem {
@Override
public void initializePopulation(Population population) {
initTemplate();
AbstractOptimizationProblem.defaultInitPopulation(population, template, this);
AbstractOptimizationProblem.defaultInitializePopulation(population, template, this);
}
@Override

2
src/eva2/problems/TF1Problem.java
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@ -95,7 +95,7 @@ public class TF1Problem extends AbstractMultiObjectiveOptimizationProblem implem
((InterfaceDataTypeDouble) this.template).setDoubleDataLength(this.problemDimension);
((InterfaceDataTypeDouble) this.template).setDoubleRange(newRange);
AbstractOptimizationProblem.defaultInitPopulation(population, template, this);
AbstractOptimizationProblem.defaultInitializePopulation(population, template, this);
}
protected double[][] makeRange() {