From e9af3216aff9ca3aab9404eae7820f8e59467dbe Mon Sep 17 00:00:00 2001 From: Fabian Becker Date: Sat, 26 Dec 2015 19:02:38 +0100 Subject: [PATCH] Rename SetFitness to setFitnessAt --- .../optimization/individuals/AbstractEAIndividual.java | 2 +- .../operator/constraint/AbstractConstraint.java | 4 ++-- .../fitnessmodifier/FitnessAdaptiveClustering.java | 2 +- .../operator/fitnessmodifier/FitnessSharing.java | 2 +- .../java/eva2/optimization/strategies/SteadyStateGA.java | 2 +- .../optimization/strategies/tribes/TribesExplorer.java | 6 +++--- src/main/java/eva2/problems/AbstractProblemInteger.java | 2 +- src/main/java/eva2/problems/BKnapsackProblem.java | 2 +- src/main/java/eva2/problems/FLensProblem.java | 3 +-- src/main/java/eva2/problems/PSymbolicRegression.java | 8 ++++---- src/main/java/eva2/problems/TF1Problem.java | 2 +- 11 files changed, 17 insertions(+), 18 deletions(-) diff --git a/src/main/java/eva2/optimization/individuals/AbstractEAIndividual.java b/src/main/java/eva2/optimization/individuals/AbstractEAIndividual.java index bd166c3f..ec4cee80 100644 --- a/src/main/java/eva2/optimization/individuals/AbstractEAIndividual.java +++ b/src/main/java/eva2/optimization/individuals/AbstractEAIndividual.java @@ -546,7 +546,7 @@ public abstract class AbstractEAIndividual implements IndividualInterface, java. * @param index The index of the fitness value to set. * @param fitness The new fitness value. */ - public void SetFitness(int index, double fitness) { + public void setFitnessAt(int index, double fitness) { if (this.fitness.length > index) { this.fitness[index] = fitness; } else { diff --git a/src/main/java/eva2/optimization/operator/constraint/AbstractConstraint.java b/src/main/java/eva2/optimization/operator/constraint/AbstractConstraint.java index c40d35cc..73faaf31 100644 --- a/src/main/java/eva2/optimization/operator/constraint/AbstractConstraint.java +++ b/src/main/java/eva2/optimization/operator/constraint/AbstractConstraint.java @@ -81,7 +81,7 @@ public abstract class AbstractConstraint implements InterfaceDoubleConstraint, S if (v > 0) { indy.setMarkPenalized(true); for (int i = 0; i < indy.getFitness().length; i++) { - indy.SetFitness(i, indy.getFitness(i) + v + penaltyFactor); + indy.setFitnessAt(i, indy.getFitness(i) + v + penaltyFactor); } } break; @@ -89,7 +89,7 @@ public abstract class AbstractConstraint implements InterfaceDoubleConstraint, S if (v > 0) { indy.setMarkPenalized(true); for (int i = 0; i < indy.getFitness().length; i++) { - indy.SetFitness(i, indy.getFitness(i) * (v + penaltyFactor)); + indy.setFitnessAt(i, indy.getFitness(i) * (v + penaltyFactor)); } } case specificTag: diff --git a/src/main/java/eva2/optimization/operator/fitnessmodifier/FitnessAdaptiveClustering.java b/src/main/java/eva2/optimization/operator/fitnessmodifier/FitnessAdaptiveClustering.java index 747e3322..02cdb547 100644 --- a/src/main/java/eva2/optimization/operator/fitnessmodifier/FitnessAdaptiveClustering.java +++ b/src/main/java/eva2/optimization/operator/fitnessmodifier/FitnessAdaptiveClustering.java @@ -57,7 +57,7 @@ public class FitnessAdaptiveClustering implements java.io.Serializable, Interfac } for (int i = 0; i < population.size(); i++) { - population.get(i).SetFitness(x, result[i]); + population.get(i).setFitnessAt(x, result[i]); } } } diff --git a/src/main/java/eva2/optimization/operator/fitnessmodifier/FitnessSharing.java b/src/main/java/eva2/optimization/operator/fitnessmodifier/FitnessSharing.java index 5628f9ff..ba904d91 100644 --- a/src/main/java/eva2/optimization/operator/fitnessmodifier/FitnessSharing.java +++ b/src/main/java/eva2/optimization/operator/fitnessmodifier/FitnessSharing.java @@ -62,7 +62,7 @@ public class FitnessSharing implements java.io.Serializable, InterfaceFitnessMod } for (int i = 0; i < population.size(); i++) { - population.get(i).SetFitness(x, result[i]); + population.get(i).setFitnessAt(x, result[i]); } } } diff --git a/src/main/java/eva2/optimization/strategies/SteadyStateGA.java b/src/main/java/eva2/optimization/strategies/SteadyStateGA.java index a48e35b8..4fcc12c8 100644 --- a/src/main/java/eva2/optimization/strategies/SteadyStateGA.java +++ b/src/main/java/eva2/optimization/strategies/SteadyStateGA.java @@ -86,7 +86,7 @@ public class SteadyStateGA extends AbstractOptimizer implements java.io.Serializ GAIndividualBinaryData tmpIndy; for (int i = 0; i < population.size(); i++) { tmpIndy = (GAIndividualBinaryData) population.get(i); - tmpIndy.SetFitness(0, tmpIndy.defaultEvaulateAsMiniBits()); + tmpIndy.setFitnessAt(0, tmpIndy.defaultEvaulateAsMiniBits()); population.incrFunctionCalls(); } population.incrGeneration(); diff --git a/src/main/java/eva2/optimization/strategies/tribes/TribesExplorer.java b/src/main/java/eva2/optimization/strategies/tribes/TribesExplorer.java index f4a3991a..26163007 100644 --- a/src/main/java/eva2/optimization/strategies/tribes/TribesExplorer.java +++ b/src/main/java/eva2/optimization/strategies/tribes/TribesExplorer.java @@ -108,8 +108,8 @@ public class TribesExplorer extends AbstractEAIndividual implements InterfaceDat * by reducing the fitness (in the first dimension). */ @Override - public void SetFitness(int index, double fitness) { - super.SetFitness(index, fitness); + public void setFitnessAt(int index, double fitness) { + super.setFitnessAt(index, fitness); if (index > position.fitness.length) { double[] newFit = new double[index + 1]; System.arraycopy(position.fitness, 0, newFit, 0, position.fitness.length); @@ -447,7 +447,7 @@ public class TribesExplorer extends AbstractEAIndividual implements InterfaceDat // pb.fitnessSize, evaluate); } else { // Artificial fitness by using penalties for (n = 0; n < position.fitness.length; n++) { - SetFitness(n, swarm.tribes[fromTribe].memory[ + setFitnessAt(n, swarm.tribes[fromTribe].memory[ contact]. getPos(). fitness[n] + diff --git a/src/main/java/eva2/problems/AbstractProblemInteger.java b/src/main/java/eva2/problems/AbstractProblemInteger.java index dd1fd754..206135a7 100644 --- a/src/main/java/eva2/problems/AbstractProblemInteger.java +++ b/src/main/java/eva2/problems/AbstractProblemInteger.java @@ -62,7 +62,7 @@ public abstract class AbstractProblemInteger extends AbstractOptimizationProblem fitness = this.evaluate(x); for (int i = 0; i < fitness.length; i++) { // set the fitness of the individual - individual.SetFitness(i, fitness[i]); + individual.setFitnessAt(i, fitness[i]); } if ((this.bestIndividuum == null) || (this.bestIndividuum.getFitness(0) > individual.getFitness(0))) { this.bestIndividuum = (AbstractEAIndividual) individual.clone(); diff --git a/src/main/java/eva2/problems/BKnapsackProblem.java b/src/main/java/eva2/problems/BKnapsackProblem.java index bdddde91..2df4a6e7 100644 --- a/src/main/java/eva2/problems/BKnapsackProblem.java +++ b/src/main/java/eva2/problems/BKnapsackProblem.java @@ -254,7 +254,7 @@ public class BKnapsackProblem extends AbstractProblemBinary implements java.io.S } } result[0] += 5100; - individual.SetFitness(0, result[0]); + individual.setFitnessAt(0, result[0]); } /** diff --git a/src/main/java/eva2/problems/FLensProblem.java b/src/main/java/eva2/problems/FLensProblem.java index c766a150..942cacc5 100644 --- a/src/main/java/eva2/problems/FLensProblem.java +++ b/src/main/java/eva2/problems/FLensProblem.java @@ -13,7 +13,6 @@ import eva2.tools.math.RNG; import javax.swing.*; import java.awt.*; -import java.awt.image.BufferStrategy; import java.awt.image.BufferedImage; class MyLensViewer extends JPanel implements InterfaceSolutionViewer { @@ -317,7 +316,7 @@ public class FLensProblem extends AbstractOptimizationProblem fitness[i] += RNG.gaussianDouble(this.noise); fitness[i] += this.yOffset; // set the fitness of the individual - individual.SetFitness(i, fitness[i]); + individual.setFitnessAt(i, fitness[i]); } if ((this.overallBest == null) || (this.overallBest.getFitness(0) > individual.getFitness(0))) { this.overallBest = (AbstractEAIndividual) individual.clone(); diff --git a/src/main/java/eva2/problems/PSymbolicRegression.java b/src/main/java/eva2/problems/PSymbolicRegression.java index 1e59d36e..e9a98b3d 100644 --- a/src/main/java/eva2/problems/PSymbolicRegression.java +++ b/src/main/java/eva2/problems/PSymbolicRegression.java @@ -196,21 +196,21 @@ public class PSymbolicRegression extends AbstractOptimizationProblem implements AbstractEAIndividual tmpBestConst = (AbstractEAIndividual) ((GAPIndividualProgramData) tmpIndy).getNumbers(); AbstractEAIndividual tmpConst; this.evaluate(tmpIndy); - tmpBestConst.SetFitness(0, tmpIndy.getFitness(0)); + tmpBestConst.setFitnessAt(0, tmpIndy.getFitness(0)); population.incrFunctionCalls(); for (int j = 0; j < 10; j++) { tmpConst = (AbstractEAIndividual) tmpBestConst.clone(); tmpConst.mutate(); ((GAPIndividualProgramData) tmpIndy).setNumbers((InterfaceDataTypeDouble) tmpConst); this.evaluate(tmpIndy); - tmpConst.SetFitness(0, tmpIndy.getFitness(0)); + tmpConst.setFitnessAt(0, tmpIndy.getFitness(0)); population.incrFunctionCalls(); if (tmpBestConst.getFitness(0) > tmpConst.getFitness(0)) { tmpBestConst = (AbstractEAIndividual) tmpConst.clone(); } } ((GAPIndividualProgramData) tmpIndy).setNumbers((InterfaceDataTypeDouble) tmpBestConst); - tmpIndy.SetFitness(0, tmpBestConst.getFitness(0)); + tmpIndy.setFitnessAt(0, tmpBestConst.getFitness(0)); } else { if (useLocalHillClimbing) { EVAERROR.errorMsgOnce("Error: local hill climbing only works on GAPIndividualProgramData individuals!"); @@ -251,7 +251,7 @@ public class PSymbolicRegression extends AbstractOptimizationProblem implements // add noise to the fitness fitness += RNG.gaussianDouble(this.noise); // set the fitness of the individual - individual.SetFitness(0, fitness); + individual.setFitnessAt(0, fitness); if ((this.plot != null) && (this.plot.getFunctionArea().getContainerSize() == 0)) { this.overallBestIndividuum = null; } diff --git a/src/main/java/eva2/problems/TF1Problem.java b/src/main/java/eva2/problems/TF1Problem.java index 8f2c47e3..bc5c42fb 100644 --- a/src/main/java/eva2/problems/TF1Problem.java +++ b/src/main/java/eva2/problems/TF1Problem.java @@ -132,7 +132,7 @@ public class TF1Problem extends AbstractMultiObjectiveOptimizationProblem implem fitness[i] += RNG.gaussianDouble(this.noise); fitness[i] += this.yOffset; // set the fitness of the individual - individual.SetFitness(i, fitness[i]); + individual.setFitnessAt(i, fitness[i]); } if (this.applyConstraints) { if (fitness[0] > 0.5) {