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Hide several elements from the UI

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This commit is contained in:
Fabian Becker 2014-11-02 13:40:31 +01:00
parent 29a1bb64e3
commit 89402e0b05
19 changed files with 44 additions and 77 deletions
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2
src/eva2/optimization/individuals/AbstractEAIndividual.java
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@ -275,7 +275,7 @@ public abstract class AbstractEAIndividual implements IndividualInterface, java.
*
* @param opt The optimization problem that is to be solved.
*/
public void init(InterfaceOptimizationProblem opt) {
public void initialize(InterfaceOptimizationProblem opt) {
initializationOperator.initialize(this, opt);
this.mutationOperator.initialize(this, opt);
this.crossoverOperator.init(this, opt);

13
src/eva2/optimization/individuals/ESIndividualDoubleData.java
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@ -105,9 +105,6 @@ public class ESIndividualDoubleData extends AbstractEAIndividual implements Inte
}
}
/************************************************************************************
* InterfaceDataTypeDouble methods
*/
/**
* This method allows you to request a certain amount of double data
*
@ -235,17 +232,14 @@ public class ESIndividualDoubleData extends AbstractEAIndividual implements Inte
System.arraycopy(doubleData, 0, this.genotype, 0, doubleData.length);
}
/************************************************************************************
* AbstractEAIndividual methods
*/
/**
* This method will allow a default initialisation of the individual
*
* @param opt The optimization problem that is to be solved.
*/
@Override
public void init(InterfaceOptimizationProblem opt) {
super.init(opt);
public void initialize(InterfaceOptimizationProblem opt) {
super.initialize(opt);
// evil operators may not respect the range, so at least give some hint
if (!Mathematics.isInRange(genotype, range)) {
EVAERROR.errorMsgOnce("Warning: Individual out of range after initialization (and potential initial crossover/mutation)!");
@ -304,9 +298,6 @@ public class ESIndividualDoubleData extends AbstractEAIndividual implements Inte
return strB.toString();
}
/************************************************************************************
* InterfaceESIndividual methods
*/
/**
* This method will allow the user to read the ES 'genotype'
*

10
src/eva2/optimization/individuals/GAESIndividualBinaryDoubleData.java
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@ -76,9 +76,9 @@ public class GAESIndividualBinaryDoubleData extends AbstractEAIndividual impleme
* @param opt The optimization problem that is to be solved.
*/
@Override
public void init(InterfaceOptimizationProblem opt) {
((AbstractEAIndividual) this.doubleIndividual).init(opt);
((AbstractEAIndividual) this.binaryIndividual).init(opt);
public void initialize(InterfaceOptimizationProblem opt) {
((AbstractEAIndividual) this.doubleIndividual).initialize(opt);
((AbstractEAIndividual) this.binaryIndividual).initialize(opt);
}
@Override
@ -105,8 +105,8 @@ public class GAESIndividualBinaryDoubleData extends AbstractEAIndividual impleme
((AbstractEAIndividual) this.binaryIndividual).initByValue(((Object[]) obj)[0], opt);
}
} else {
((AbstractEAIndividual) this.doubleIndividual).init(opt);
((AbstractEAIndividual) this.binaryIndividual).init(opt);
((AbstractEAIndividual) this.doubleIndividual).initialize(opt);
((AbstractEAIndividual) this.binaryIndividual).initialize(opt);
System.out.println("Initial value for GAESIndividualDoubleData is not suitable!");
}
}

15
src/eva2/optimization/individuals/GAIndividualDoubleData.java
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@ -10,6 +10,7 @@ import eva2.optimization.operator.mutation.MutateGAUniform;
import eva2.problems.InterfaceOptimizationProblem;
import eva2.tools.math.RNG;
import eva2.util.annotation.Description;
import eva2.util.annotation.Parameter;
import java.util.BitSet;
@ -229,10 +230,6 @@ public class GAIndividualDoubleData extends AbstractEAIndividual implements Inte
}
}
/************************************************************************************
* AbstractEAIndividual methods
*/
/**
* This method will initialize the individual with a given value for the
* phenotype.
@ -373,6 +370,7 @@ public class GAIndividualDoubleData extends AbstractEAIndividual implements Inte
*
* @param coding The used genotype coding method
*/
@Parameter(name = "coding", description = "Choose the coding to use.")
public void setGACoding(InterfaceGADoubleCoding coding) {
this.doubleCoding = coding;
}
@ -381,16 +379,13 @@ public class GAIndividualDoubleData extends AbstractEAIndividual implements Inte
return this.doubleCoding;
}
public String gADoubleCodingTipText() {
return "Choose the coding to use.";
}
/**
* This method allows you to set the number of mulitruns that are to be performed,
* necessary for stochastic optimizers to ensure reliable results.
*
* @param precision The number of multiruns that are to be performed
*/
@Parameter(description = "Gives the number of bits to be used to code a double.")
public void setPrecision(int precision) {
this.precision = precision;
}
@ -398,8 +393,4 @@ public class GAIndividualDoubleData extends AbstractEAIndividual implements Inte
public int getPrecision() {
return this.precision;
}
public String precisionTipText() {
return "Gives the number of bits to be used to code a double.";
}
}

10
src/eva2/optimization/individuals/GAPIndividualProgramData.java
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@ -72,9 +72,9 @@ public class GAPIndividualProgramData extends AbstractEAIndividual implements In
* @param opt The optimization problem that is to be solved.
*/
@Override
public void init(InterfaceOptimizationProblem opt) {
((AbstractEAIndividual) this.numberData).init(opt);
((AbstractEAIndividual) this.programData).init(opt);
public void initialize(InterfaceOptimizationProblem opt) {
((AbstractEAIndividual) this.numberData).initialize(opt);
((AbstractEAIndividual) this.programData).initialize(opt);
}
@Override
@ -101,8 +101,8 @@ public class GAPIndividualProgramData extends AbstractEAIndividual implements In
((AbstractEAIndividual) this.programData).initByValue(((Object[]) obj)[0], opt);
}
} else {
((AbstractEAIndividual) this.numberData).init(opt);
((AbstractEAIndividual) this.programData).init(opt);
((AbstractEAIndividual) this.numberData).initialize(opt);
((AbstractEAIndividual) this.programData).initialize(opt);
System.out.println("Initial value for GAPIndividualDoubleData is not suitable!");
}
}

10
src/eva2/optimization/individuals/GIOBGAIndividualIntegerPermutationData.java
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@ -72,9 +72,9 @@ public class GIOBGAIndividualIntegerPermutationData extends AbstractEAIndividual
* @param opt The optimization problem that is to be solved.
*/
@Override
public void init(InterfaceOptimizationProblem opt) {
((AbstractEAIndividual) this.integerData).init(opt);
((AbstractEAIndividual) this.permutationData).init(opt);
public void initialize(InterfaceOptimizationProblem opt) {
((AbstractEAIndividual) this.integerData).initialize(opt);
((AbstractEAIndividual) this.permutationData).initialize(opt);
}
@Override
@ -101,8 +101,8 @@ public class GIOBGAIndividualIntegerPermutationData extends AbstractEAIndividual
((AbstractEAIndividual) this.permutationData).initByValue(((Object[]) obj)[0], opt);
}
} else {
((AbstractEAIndividual) this.integerData).init(opt);
((AbstractEAIndividual) this.permutationData).init(opt);
((AbstractEAIndividual) this.integerData).initialize(opt);
((AbstractEAIndividual) this.permutationData).initialize(opt);
System.out.println("Initial value for GIOBGAIndividualIntegerPermutationData is not suitable!");
}
}

4
src/eva2/optimization/operator/crossover/TestESCrossover.java
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@ -110,12 +110,12 @@ public class TestESCrossover implements java.io.Serializable {
tmpIndyD.setDoubleRange(newRange);
for (int i = 0; i < partners.getTargetSize(); i++) {
tmpIndyEA = (AbstractEAIndividual) ((AbstractEAIndividual) tmpIndyD).clone();
tmpIndyEA.init(optimizationProblem);
tmpIndyEA.initialize(optimizationProblem);
partners.add(tmpIndyEA);
}
partners.init();
daddy = (AbstractEAIndividual) ((AbstractEAIndividual) tmpIndyD).clone();
daddy.init(optimizationProblem);
daddy.initialize(optimizationProblem);
plot.clearAll();
plot.setUnconnectedPoint(-2, -2, 0);
plot.setUnconnectedPoint(2, 2, 0);

9
src/eva2/optimization/population/Population.java
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@ -15,6 +15,7 @@ import eva2.tools.math.Mathematics;
import eva2.tools.math.RNG;
import eva2.tools.math.StatisticUtils;
import eva2.util.annotation.Description;
import eva2.util.annotation.Hidden;
import eva2.util.annotation.Parameter;
import java.util.*;
@ -602,6 +603,7 @@ public class Population extends ArrayList implements PopulationInterface, Clonea
return historyList;
}
@Hidden
public void setHistory(LinkedList<AbstractEAIndividual> theHist) {
historyList = theHist;
}
@ -684,6 +686,7 @@ public class Population extends ArrayList implements PopulationInterface, Clonea
*
* @param d The new number of functioncalls.
*/
@Hidden
public void setFunctionCalls(int d) {
this.functionCallCount = d;
}
@ -738,6 +741,7 @@ public class Population extends ArrayList implements PopulationInterface, Clonea
*
* @param gen the value to set as new generation index
*/
@Hidden
public void setGeneration(int gen) {
this.generationCount = gen;
}
@ -2519,11 +2523,8 @@ public class Population extends ArrayList implements PopulationInterface, Clonea
return seedCardinality;
}
@Parameter(description = "The initial cardinality for binary genotype individuals, given as pair of mean and std.dev.")
public void setSeedCardinality(Pair<Integer, Integer> seedCardinality) {
this.seedCardinality = seedCardinality;
}
public String seedCardinalityTipText() {
return "The initial cardinality for binary genotype individuals, given as pair of mean and std.dev.";
}
}

2
src/eva2/optimization/strategies/ANPSO.java
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@ -541,7 +541,7 @@ public class ANPSO extends NichePSO implements InterfaceAdditionalPopulationInfo
if (reinitSuperfl) {
for (int i = 0; i < tmpPop.size(); i++) {
AbstractEAIndividual indy = tmpPop.getEAIndividual(i);
indy.init(optimizationProblem);
indy.initialize(optimizationProblem);
indy.resetFitness(Double.MAX_VALUE); // TODO this is not so nice... they should be collected in a reinit-list and inserted at the beginning of the next optimize step
ParticleSwarmOptimization.initIndividualDefaults(indy, 0.2);
ParticleSwarmOptimization.initIndividualMemory(indy);

2
src/eva2/optimization/strategies/ArtificialBeeColony.java
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@ -194,7 +194,7 @@ public class ArtificialBeeColony extends AbstractOptimizer implements Serializab
*/
AbstractEAIndividual oldestIndy = getOldestIndividual();
if (oldestIndy.getAge() > this.maxTrials) {
oldestIndy.init(this.optimizationProblem);
oldestIndy.initialize(this.optimizationProblem);
this.optimizationProblem.evaluate(oldestIndy);
this.population.incrFunctionCalls();
}

2
src/eva2/optimization/strategies/MultiObjectiveCMAES.java
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@ -100,7 +100,7 @@ public class MultiObjectiveCMAES extends AbstractOptimizer implements Serializab
/*
* (non-Javadoc)
*
* @see eva2.optimization.strategies.InterfaceOptimizer#init()
* @see eva2.optimization.strategies.InterfaceOptimizer#initialize()
*/
@Override
public void initialize() {

2
src/eva2/optimization/strategies/ParticleFilterOptimization.java
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@ -146,7 +146,7 @@ public class ParticleFilterOptimization extends AbstractOptimizer implements jav
int i;
for (i = 0; (i + parents.getTargetSize()) < pop.getTargetSize(); i++) {
immi = (AbstractEAIndividual) pop.getEAIndividual(0).clone();
immi.init(getProblem());
immi.initialize(getProblem());
parents.add(immi);
}
parents.synchSize();

2
src/eva2/optimization/strategies/ParticleSubSwarmOptimization.java
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@ -481,7 +481,7 @@ public class ParticleSubSwarmOptimization extends ParticleSwarmOptimizationGCPSO
for (int i = 0; i < tmp.getTargetSize(); i++) {
tmpIndy = (AbstractEAIndividual) template.clone();
tmpIndy.init(prob);
tmpIndy.initialize(prob);
tmp.add(tmpIndy);
}
tmp.init();

4
src/eva2/optimization/strategies/tribes/TribesExplorer.java
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@ -954,7 +954,7 @@ v[d] = cmin * v[d];
}
@Override
public void init(InterfaceOptimizationProblem opt) {
public void initialize(InterfaceOptimizationProblem opt) {
// TODO whats this for?
for (int i = 0; i < this.position.x.length; i++) {
this.position.x[0] = 0.;
@ -983,7 +983,7 @@ v[d] = cmin * v[d];
}
this.setDoubleGenotype(x);
} else {
this.init(opt);
this.initialize(opt);
System.err.println("Initial value for ESIndividualDoubleData is not double[]!");
}
}

2
src/eva2/optimization/tools/ImpactOfDimensionOnMOEAs.java
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@ -104,7 +104,7 @@ public class ImpactOfDimensionOnMOEAs {
((InterfaceDataTypeDouble) template).setDoubleDataLength(numberOfVariables);
for (int i = 0; i < popSize; i++) {
tmpIndy = (AbstractEAIndividual) template.clone();
tmpIndy.init(null);
tmpIndy.initialize(null);
pop.add(tmpIndy);
}
}

2
src/eva2/problems/AbstractMultiModalProblemKnown.java
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@ -57,7 +57,7 @@ public abstract class AbstractMultiModalProblemKnown extends AbstractProblemDoub
((InterfaceDataTypeDouble) this.template).setDoubleRange(makeRange());
for (int i = 0; i < population.getTargetSize(); i++) {
tmpIndy = (AbstractEAIndividual) this.template.clone();
tmpIndy.init(this);
tmpIndy.initialize(this);
population.add(tmpIndy);
}
// population initialize must be last

2
src/eva2/problems/AbstractOptimizationProblem.java
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@ -189,7 +189,7 @@ public abstract class AbstractOptimizationProblem implements InterfaceOptimizati
for (int i = 0; i < population.getTargetSize(); i++) {
tmpIndy = (AbstractEAIndividual) template.clone();
tmpIndy.init(prob);
tmpIndy.initialize(prob);
population.add(tmpIndy);
}
// population initialize must be last

2
src/eva2/problems/BKnapsackProblem.java
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@ -160,7 +160,7 @@ public class BKnapsackProblem extends AbstractProblemBinary implements java.io.S
}
protected void initIndy(int k, AbstractEAIndividual indy) {
indy.init(this);
indy.initialize(this);
if (RNG.flipCoin(this.problemSpecificInit)) {
BitSet tmpSet = new BitSet();
tmpSet.clear();

26
src/eva2/problems/SimpleProblemWrapper.java
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@ -12,6 +12,7 @@ import eva2.problems.simple.InterfaceSimpleProblem;
import eva2.problems.simple.SimpleF1;
import eva2.problems.simple.SimpleProblemBinary;
import eva2.problems.simple.SimpleProblemDouble;
import eva2.util.annotation.Parameter;
import java.util.BitSet;
@ -164,6 +165,7 @@ public class SimpleProblemWrapper extends AbstractOptimizationProblem {
/**
* @param simProb the simProb to set
*/
@Parameter(description = "Set the simple problem class which is to be optimized")
public void setSimpleProblem(InterfaceSimpleProblem<?> simProb) {
this.simProb = simProb;
initTemplate();
@ -186,19 +188,13 @@ public class SimpleProblemWrapper extends AbstractOptimizationProblem {
}
}
/**
*
*/
public String simpleProblemTipText() {
return "Set the simple problem class which is to be optimized";
}
/**
* This method allows you to choose how much noise is to be added to the
* fitness. This can be used to make the optimization problem more difficult.
*
* @param noise The sigma for a gaussian random number.
*/
@Parameter(description = "Gaussian noise level on the fitness value.")
public void setNoise(double noise) {
if (noise < 0) {
noise = 0;
@ -210,11 +206,6 @@ public class SimpleProblemWrapper extends AbstractOptimizationProblem {
return this.noise;
}
public String noiseTipText() {
return "Gaussian noise level on the fitness value.";
}
/**
* A (symmetric) absolute range limit.
*
@ -229,15 +220,12 @@ public class SimpleProblemWrapper extends AbstractOptimizationProblem {
*
* @param defaultRange
*/
@Parameter(name = "range", description = "Absolute limit for the symmetric range in any dimension")
public void setDefaultRange(double defaultRange) {
this.defaultRange = defaultRange;
initTemplate();
}
public String defaultRangeTipText() {
return "Absolute limit for the symmetric range in any dimension";
}
/**
* Take care that all properties which may be hidden (and currently are) send a "hide" message to the Java Bean properties.
* This is called by PropertySheetPanel in use with the GenericObjectEditor.
@ -246,16 +234,12 @@ public class SimpleProblemWrapper extends AbstractOptimizationProblem {
setSimpleProblem(getSimpleProblem());
}
@Parameter(name = "individual", description = "Set the individual properties for the optimization")
public void setIndividualTemplate(AbstractEAIndividual indy) {
resetTemplate = false;
template = indy;
}
@Override
public String individualTemplateTipText() {
return "Set the individual properties for the optimization";
}
/**
* This method returns a string describing the optimization problem.
*