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FunctionArea may now plot circles easily. The FLensProblemViewer seems to be cured.

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This commit is contained in:
Marcel Kronfeld
2008-06-19 11:03:38 +00:00
parent 113f119b29
commit 5acff4aec6
14 changed files with 472 additions and 377 deletions
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3
src/eva2/EvAInfo.java
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@@ -3,6 +3,7 @@ package eva2;
/**
* Main product and version information strings.
*
* 2.025: FunctionArea may now plot circles easily. The FLensProblemViewer seems to be cured.
* 2.024: Cleaned up AbstractGOParams, deactivated parent logging (saving memory)
* 2.023: Cleaned up the PF strategy
* 2.022: Some changes to the SimpleProblemWrapper, not of great interest. However,
@@ -14,7 +15,7 @@ package eva2;
public class EvAInfo {
public static final String productName = "EvA 2";
public static final String productLongName = "Evolutionary Algorithms Workbench 2";
public static final String versionNum = new String ("2.024");
public static final String versionNum = new String ("2.025");
public static final String url = "http://www.ra.cs.uni-tuebingen.de/software/EvA2";
public static final String propertyFile = "resources/EvA2.props";

11
src/eva2/gui/Chart2DDPointIconText.java
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@@ -16,6 +16,7 @@ public class Chart2DDPointIconText implements DPointIcon {
private DPointIcon m_Icon = new Chart2DDPointIconCross();
private String m_Text = " ";
private Color m_Color;
public Chart2DDPointIconText(String s) {
m_Text = s;
@@ -34,6 +35,7 @@ public class Chart2DDPointIconText implements DPointIcon {
*/
public void paint( Graphics g ){
this.m_Icon.paint(g);
g.setColor(m_Color);
g.drawString(this.m_Text, 4, 4);
}
@@ -46,4 +48,13 @@ public class Chart2DDPointIconText implements DPointIcon {
public DBorder getDBorder() {
return new DBorder(4, 4, 4, 4);
}
/**
* Set the color for the text.
*
* @param col
*/
public void setColor(Color col) {
m_Color = col;
}
}

46
src/eva2/gui/FunctionArea.java
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@@ -88,7 +88,51 @@ public class FunctionArea extends DArea implements Serializable {
repaint();
notifyNegLog = true;
}
/**
* Plot a circle icon to the function area which is annotated with a char and
* a double value.
*
* @param c
* @param val
* @param position
*/
public void drawCircle(double val, double[] position, int graphID) {
drawCircle(""+val, position, graphID);
}
/**
* Plot a circle icon to the function area which is annotated with a char and
* a double value.
*
* @param c
* @param val
* @param position
* @param graphID
*/
public void drawCircle(char c, double val, double[] position, int graphID) {
drawCircle(c+""+val, position, graphID);
}
/**
* Plot a circle icon to the function area which is annotated with a char and
* a double value. The color corresponds to the color of the graph with given ID
*
* @param label
* @param position
* @param graphID
*/
public void drawCircle(String label, double[] position, int graphID) {
DPointSet popRep;
popRep = new DPointSet();
popRep.addDPoint(new DPoint(position[0], position[1]));
DPointIcon icon = new Chart2DDPointIconText(label);
((Chart2DDPointIconText)icon).setIcon(new Chart2DDPointIconCircle());
((Chart2DDPointIconText)icon).setColor(getGraphPointSet(graphID).getColor());
popRep.setIcon(icon);
addDElement(popRep);
}
/**
*
*/

2
src/eva2/gui/GraphPointSet.java
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@@ -40,7 +40,7 @@ public class GraphPointSet {
private Color m_Color;
private DPointIcon m_Icon;
private int m_CacheIndex = 0;
private int m_CacheSize = 1;
private int m_CacheSize = 0;
private double [] m_cachex;
private double [] m_cachey;
/**

8
src/eva2/gui/Plot.java
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@@ -13,6 +13,7 @@ package eva2.gui;
* IMPORTS
*==========================================================================*/
import java.awt.AWTException;
import java.awt.Dimension;
import java.awt.FlowLayout;
import java.awt.Rectangle;
import java.awt.Robot;
@@ -276,6 +277,13 @@ public class Plot implements PlotInterface, Serializable {
m_Frame.setVisible(true);
}
public void setPreferredSize(Dimension prefSize) {
if (m_Frame != null) {
m_Frame.setPreferredSize(prefSize);
m_Frame.pack();
}
}
/**
* Return true if the Plot object is valid.
*

8
src/eva2/server/go/individuals/AbstractEAIndividual.java
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@@ -21,9 +21,9 @@ import eva2.tools.EVAERROR;
/** This is the abstract EA individual implementing the most important methods giving
* access to mutation and crossover rates and operators, fitness values and selection
* probabilities. All EA individuals should typically extend this abstract EA individual.
* In that case the EA individuals only implement the genotpye and phenotype interfaces.
* In that case the EA individuals only implement the genotype and phenotype interfaces.
* The names of the implementation should be build like this:
* (Genotpye)Individual(Phenotype)
* (Genotype)Individual(Phenotype)
* Thus a binary individual coding double values is named GAIndividualDoubleData and a
* real-valued individual coding binary values is named ESIndividualBinaryData.
* Created by IntelliJ IDEA.
@@ -911,6 +911,10 @@ public abstract class AbstractEAIndividual implements IndividualInterface, java.
else return this.getFitness();
}
public boolean isDominantNotEqual(double[] otherFitness) {
return isDominatingFitnessNotEqual(m_Fitness, otherFitness);
}
public boolean isDominant(double[] otherFitness) {
return isDominatingFitness(m_Fitness, otherFitness);
}

5
src/eva2/server/go/individuals/ESIndividualDoubleData.java
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@@ -1,14 +1,11 @@
package eva2.server.go.individuals;
import java.util.Arrays;
import eva2.server.go.IndividualInterface;
import wsi.ra.math.RNG;
import eva2.server.go.operators.crossover.CrossoverESDefault;
import eva2.server.go.operators.mutation.InterfaceMutation;
import eva2.server.go.operators.mutation.MutateESGlobal;
import eva2.server.go.problems.InterfaceOptimizationProblem;
import wsi.ra.math.RNG;
/** This individual uses a real-valued genotype to code for double values.
* Created by IntelliJ IDEA.

634
src/eva2/server/go/individuals/ESIndividualPermutationData.java
View File

@@ -17,363 +17,363 @@ import wsi.ra.math.RNG;
*/
public class ESIndividualPermutationData extends AbstractEAIndividual implements InterfaceESIndividual, InterfaceDataTypePermutation, java.io.Serializable {
private double[][] m_Genotype;
private int[][] m_Phenotype;
private double[][][] m_Range;
private int[] firstindex;
private double[][] m_Genotype;
private int[][] m_Phenotype;
private double[][][] m_Range;
private int[] firstindex;
public ESIndividualPermutationData() {
this.m_MutationProbability = 1.0;
this.m_MutationOperator = new MutateESGlobal();
this.m_CrossoverProbability = 0.5;
this.m_CrossoverOperator = new CrossoverESDefault();
this.m_Genotype = new double[1][1];
this.m_Range = new double[1][1][2];
this.m_Range[0][0][0] = 0;
this.m_Range[0][0][1] = 1;
this.firstindex = new int[]{0};
}
public ESIndividualPermutationData() {
this.m_MutationProbability = 1.0;
this.m_MutationOperator = new MutateESGlobal();
this.m_CrossoverProbability = 0.5;
this.m_CrossoverOperator = new CrossoverESDefault();
this.m_Genotype = new double[1][1];
this.m_Range = new double[1][1][2];
this.m_Range[0][0][0] = 0;
this.m_Range[0][0][1] = 1;
this.firstindex = new int[]{0};
}
public ESIndividualPermutationData(ESIndividualPermutationData individual) {
if (individual.m_Phenotype != null) {
this.m_Phenotype = new int[individual.m_Phenotype.length][];
for (int i = 0; i < m_Phenotype.length; i++) {
this.m_Phenotype[i] =new int[ individual.m_Phenotype[i].length];
System.arraycopy(individual.m_Phenotype[i], 0, this.m_Phenotype[i], 0, this.m_Phenotype[i].length);
}
}
public ESIndividualPermutationData(ESIndividualPermutationData individual) {
if (individual.m_Phenotype != null) {
this.m_Phenotype = new int[individual.m_Phenotype.length][];
for (int i = 0; i < m_Phenotype.length; i++) {
this.m_Phenotype[i] =new int[ individual.m_Phenotype[i].length];
System.arraycopy(individual.m_Phenotype[i], 0, this.m_Phenotype[i], 0, this.m_Phenotype[i].length);
}
}
this.firstindex = individual.firstindex;
this.m_Genotype = new double[individual.m_Genotype.length][];
this.m_Range = new double[individual.m_Genotype.length][][];
for (int i = 0; i < this.m_Genotype.length; i++) {
// if (individual.m_Phenotype != null) {
this.firstindex = individual.firstindex;
this.m_Genotype = new double[individual.m_Genotype.length][];
this.m_Range = new double[individual.m_Genotype.length][][];
for (int i = 0; i < this.m_Genotype.length; i++) {
// if (individual.m_Phenotype != null) {
this.m_Genotype[i] = new double[individual.m_Genotype[i].length];
this.m_Range[i] = new double[individual.m_Genotype[i].length][2];
for (int j = 0; j < this.m_Genotype[i].length; j++) {
this.m_Genotype[i][j] = individual.m_Genotype[i][j];
this.m_Range[i][j][0] = individual.m_Range[i][j][0];
this.m_Range[i][j][1] = individual.m_Range[i][j][1];
// }
}
}
this.m_Genotype[i] = new double[individual.m_Genotype[i].length];
this.m_Range[i] = new double[individual.m_Genotype[i].length][2];
for (int j = 0; j < this.m_Genotype[i].length; j++) {
this.m_Genotype[i][j] = individual.m_Genotype[i][j];
this.m_Range[i][j][0] = individual.m_Range[i][j][0];
this.m_Range[i][j][1] = individual.m_Range[i][j][1];
// }
}
}
// cloning the members of AbstractEAIndividual
this.m_Age = individual.m_Age;
this.m_CrossoverOperator = individual.m_CrossoverOperator;
this.m_CrossoverProbability = individual.m_CrossoverProbability;
this.m_MutationOperator = (InterfaceMutation)individual.m_MutationOperator.clone();
this.m_MutationProbability = individual.m_MutationProbability;
this.m_SelectionProbability = new double[individual.m_SelectionProbability.length];
for (int i = 0; i < this.m_SelectionProbability.length; i++) {
this.m_SelectionProbability[i] = individual.m_SelectionProbability[i];
}
this.m_Fitness = new double[individual.m_Fitness.length];
for (int i = 0; i < this.m_Fitness.length; i++) {
this.m_Fitness[i] = individual.m_Fitness[i];
}
cloneAEAObjects((AbstractEAIndividual) individual);
// cloning the members of AbstractEAIndividual
this.m_Age = individual.m_Age;
this.m_CrossoverOperator = individual.m_CrossoverOperator;
this.m_CrossoverProbability = individual.m_CrossoverProbability;
this.m_MutationOperator = (InterfaceMutation)individual.m_MutationOperator.clone();
this.m_MutationProbability = individual.m_MutationProbability;
this.m_SelectionProbability = new double[individual.m_SelectionProbability.length];
for (int i = 0; i < this.m_SelectionProbability.length; i++) {
this.m_SelectionProbability[i] = individual.m_SelectionProbability[i];
}
this.m_Fitness = new double[individual.m_Fitness.length];
for (int i = 0; i < this.m_Fitness.length; i++) {
this.m_Fitness[i] = individual.m_Fitness[i];
}
cloneAEAObjects((AbstractEAIndividual) individual);
}
}
public Object clone() {
return (Object) new ESIndividualPermutationData(this);
}
public Object clone() {
return (Object) new ESIndividualPermutationData(this);
}
/** This method checks on equality regarding genotypic equality
* @param individual The individual to compare to.
* @return boolean if equal true else false.
*/
public boolean equalGenotypes(AbstractEAIndividual individual) {
if (individual instanceof ESIndividualPermutationData) {
ESIndividualPermutationData indy = (ESIndividualPermutationData) individual;
if ((this.m_Genotype == null) || (indy.m_Genotype == null)) return false;
if ((this.m_Range == null) || (indy.m_Range == null)) return false;
if (this.m_Range.length != indy.m_Range.length) return false;
for (int i = 0; i < this.m_Range.length; i++) {
if (this.m_Genotype[i] != indy.m_Genotype[i]) return false;
if (this.m_Range[i][0] != indy.m_Range[i][0]) return false;
if (this.m_Range[i][1] != indy.m_Range[i][1]) return false;
}
return true;
} else {
return false;
}
}
/** This method checks on equality regarding genotypic equality
* @param individual The individual to compare to.
* @return boolean if equal true else false.
*/
public boolean equalGenotypes(AbstractEAIndividual individual) {
if (individual instanceof ESIndividualPermutationData) {
ESIndividualPermutationData indy = (ESIndividualPermutationData) individual;
if ((this.m_Genotype == null) || (indy.m_Genotype == null)) return false;
if ((this.m_Range == null) || (indy.m_Range == null)) return false;
if (this.m_Range.length != indy.m_Range.length) return false;
for (int i = 0; i < this.m_Range.length; i++) {
if (this.m_Genotype[i] != indy.m_Genotype[i]) return false;
if (this.m_Range[i][0] != indy.m_Range[i][0]) return false;
if (this.m_Range[i][1] != indy.m_Range[i][1]) return false;
}
return true;
} else {
return false;
}
}
/************************************************************************************
* InterfaceDataTypePermutation methods
*/
/************************************************************************************
* InterfaceDataTypePermutation methods
*/
public void setPermutationDataLength(int[] length){
public void setPermutationDataLength(int[] length){
this.m_Genotype = new double[length.length][];
this.m_Range = new double[length.length][][];
for (int i = 0; i < this.m_Range.length; i++) {
this.m_Genotype[i] = new double[length[i]];
}
this.m_Genotype = new double[length.length][];
this.m_Range = new double[length.length][][];
for (int i = 0; i < this.m_Range.length; i++) {
this.m_Genotype[i] = new double[length[i]];
}
for (int i = 0; i < this.m_Range.length; i++) {
for (int i = 0; i < this.m_Range.length; i++) {
this.m_Range[i] = new double[length[i]][2];
for (int j = 0; j < this.m_Range[i].length; j++) {
this.m_Range[i][j][0] = 0;
this.m_Range[i][j][1] = 1;
}
}
}
this.m_Range[i] = new double[length[i]][2];
for (int j = 0; j < this.m_Range[i].length; j++) {
this.m_Range[i][j][0] = 0;
this.m_Range[i][j][1] = 1;
}
}
}
public int[] sizePermutation() {
int[] res = new int[m_Genotype.length];
for (int i = 0; i < m_Genotype.length; i++) {
res[i] = m_Genotype[i].length;
}
return res;
}
public int[] sizePermutation() {
int[] res = new int[m_Genotype.length];
for (int i = 0; i < m_Genotype.length; i++) {
res[i] = m_Genotype[i].length;
}
return res;
}
public void SetPermutationData(int[][] perm){
this.m_Phenotype = perm;
this.m_Range = new double[perm.length][][];
for (int i = 0; i < perm.length; i++) {
this.m_Range[i] = new double[perm[i].length][2];
for (int j = 0; j < this.m_Range[i].length; j++) {
this.m_Range[i][j][0] = 0;
this.m_Range[i][j][1] = 1;
}
}
public void SetPermutationData(int[][] perm){
this.m_Phenotype = perm;
this.m_Range = new double[perm.length][][];
for (int i = 0; i < perm.length; i++) {
this.m_Range[i] = new double[perm[i].length][2];
for (int j = 0; j < this.m_Range[i].length; j++) {
this.m_Range[i][j][0] = 0;
this.m_Range[i][j][1] = 1;
}
}
}
}
public void SetPermutationDataLamarckian(int[][] perm){
this.SetPermutationData(perm);
public void SetPermutationDataLamarckian(int[][] perm){
this.SetPermutationData(perm);
this.m_Genotype = new double[perm.length][];
this.m_Range = new double[perm.length][][];
for (int p = 0; p < perm.length; p++) {
int biggest = Integer.MIN_VALUE;
int smallest = Integer.MAX_VALUE;
this.m_Range[p] = new double[perm[p].length][2];
for (int i = 0; i < perm[p].length; i++) {
if (perm[p][i] > biggest) biggest = perm[p][i];
if (perm[p][i] < smallest) smallest = perm[p][i];
this.m_Range[p][i][0] = 0;
this.m_Range[p][i][1] = 1;
}
for (int i = 0; i < this.m_Genotype[p].length; i++) {
this.m_Genotype[p][i] = (perm[p][i] - smallest)/(double)biggest;
}
}
this.m_Genotype = new double[perm.length][];
this.m_Range = new double[perm.length][][];
for (int p = 0; p < perm.length; p++) {
int biggest = Integer.MIN_VALUE;
int smallest = Integer.MAX_VALUE;
this.m_Range[p] = new double[perm[p].length][2];
for (int i = 0; i < perm[p].length; i++) {
if (perm[p][i] > biggest) biggest = perm[p][i];
if (perm[p][i] < smallest) smallest = perm[p][i];
this.m_Range[p][i][0] = 0;
this.m_Range[p][i][1] = 1;
}
for (int i = 0; i < this.m_Genotype[p].length; i++) {
this.m_Genotype[p][i] = (perm[p][i] - smallest)/(double)biggest;
}
}
}
}
public int[][] getPermutationData() {
this.m_Phenotype = new int[this.m_Genotype.length][];
for (int p = 0; p < m_Genotype.length; p++) {
this.m_Phenotype[p] = new int[m_Genotype[p].length];
boolean notValid = true;
while (notValid) {
notValid = false;
for (int i = 0; i < this.m_Genotype[p].length; i++) {
for (int j = 0; j < this.m_Genotype[p].length; j++) {
if ((i != j) && (this.m_Genotype[p][i] == this.m_Genotype[p][j])) {
notValid = true;
this.m_Genotype[p][j] = RNG.randomDouble(0, 1);
}
}
}
public int[][] getPermutationData() {
this.m_Phenotype = new int[this.m_Genotype.length][];
for (int p = 0; p < m_Genotype.length; p++) {
this.m_Phenotype[p] = new int[m_Genotype[p].length];
boolean notValid = true;
while (notValid) {
notValid = false;
for (int i = 0; i < this.m_Genotype[p].length; i++) {
for (int j = 0; j < this.m_Genotype[p].length; j++) {
if ((i != j) && (this.m_Genotype[p][i] == this.m_Genotype[p][j])) {
notValid = true;
this.m_Genotype[p][j] = RNG.randomDouble(0, 1);
}
}
}
}
for (int i = 0; i < this.m_Genotype[p].length; i++) {
for (int j = 0; j < this.m_Genotype[p].length; j++) {
if (this.m_Genotype[p][i] > this.m_Genotype[p][j]) this.m_Phenotype[p][i]++;
}
}
}
return this.m_Phenotype;
}
}
for (int i = 0; i < this.m_Genotype[p].length; i++) {
for (int j = 0; j < this.m_Genotype[p].length; j++) {
if (this.m_Genotype[p][i] > this.m_Genotype[p][j]) this.m_Phenotype[p][i]++;
}
}
}
return this.m_Phenotype;
}
/** This method allows you to read the permutation data without
* an update from the genotype
* @return int[] representing the permutation.
*/
public int[][] getPermutationDataWithoutUpdate() {
return this.m_Phenotype;
}
/** This method allows you to read the permutation data without
* an update from the genotype
* @return int[] representing the permutation.
*/
public int[][] getPermutationDataWithoutUpdate() {
return this.m_Phenotype;
}
public int[] getFirstindex() {
return firstindex;
}
public void setFirstindex(int[] firstindex) {
this.firstindex = firstindex;
}
public int[] getFirstindex() {
return firstindex;
}
public void setFirstindex(int[] firstindex) {
this.firstindex = firstindex;
}
/************************************************************************************
* AbstractEAIndividual methods
*/
/** This method will allow a default initialisation of the individual
* @param opt The optimization problem that is to be solved.
*/
public void init(InterfaceOptimizationProblem opt) {
this.defaultInit();
this.m_MutationOperator.init(this, opt);
this.m_CrossoverOperator.init(this, opt);
}
/************************************************************************************
* AbstractEAIndividual methods
*/
/** This method will allow a default initialisation of the individual
* @param opt The optimization problem that is to be solved.
*/
public void init(InterfaceOptimizationProblem opt) {
this.defaultInit();
this.m_MutationOperator.init(this, opt);
this.m_CrossoverOperator.init(this, opt);
}
/** This method will init the individual with a given value for the
* phenotype.
* @param obj The initial value for the phenotype
* @param opt The optimization problem that is to be solved.
*/
public void initByValue(Object obj, InterfaceOptimizationProblem opt) {
if (obj instanceof int[][]) {
int[][] bs = (int[][]) obj;
if (bs.length != this.m_Genotype.length) System.out.println("Init value and requested length doesn't match!");
this.SetPermutationDataLamarckian(bs);
} else {
this.defaultInit();
System.out.println("Initial value for ESIndividualPermutationData is not int[]!");
}
this.m_MutationOperator.init(this, opt);
this.m_CrossoverOperator.init(this, opt);
}
/** This method will init the individual with a given value for the
* phenotype.
* @param obj The initial value for the phenotype
* @param opt The optimization problem that is to be solved.
*/
public void initByValue(Object obj, InterfaceOptimizationProblem opt) {
if (obj instanceof int[][]) {
int[][] bs = (int[][]) obj;
if (bs.length != this.m_Genotype.length) System.out.println("Init value and requested length doesn't match!");
this.SetPermutationDataLamarckian(bs);
} else {
this.defaultInit();
System.out.println("Initial value for ESIndividualPermutationData is not int[]!");
}
this.m_MutationOperator.init(this, opt);
this.m_CrossoverOperator.init(this, opt);
}
/** This method will return a string description of the GAIndividal
* noteably the Genotype.
* @return A descriptive string
*/
public String getStringRepresentation() {
String result = "";
result += "ESIndividual coding permutation: (";
result += "Fitness {";
for (int i = 0; i < this.m_Fitness.length; i++) result += this.m_Fitness[i] + ";";
result += "}/SelProb{";
for (int i = 0; i < this.m_SelectionProbability.length; i++) result += this.m_SelectionProbability[i] + ";";
result += "})\n Value: ";
result += "[";
for (int i = 0; i < this.m_Genotype.length; i++) {
result += this.m_Genotype[i] + "; ";
}
result += "]";
return result;
}
/** This method will return a string description of the GAIndividal
* noteably the Genotype.
* @return A descriptive string
*/
public String getStringRepresentation() {
String result = "";
result += "ESIndividual coding permutation: (";
result += "Fitness {";
for (int i = 0; i < this.m_Fitness.length; i++) result += this.m_Fitness[i] + ";";
result += "}/SelProb{";
for (int i = 0; i < this.m_SelectionProbability.length; i++) result += this.m_SelectionProbability[i] + ";";
result += "})\n Value: ";
result += "[";
for (int i = 0; i < this.m_Genotype.length; i++) {
result += this.m_Genotype[i] + "; ";
}
result += "]";
return result;
}
/************************************************************************************
* InterfaceESIndividual methods
*/
/** This method will allow the user to read the ES 'genotype'
* @return BitSet
*/
public double[] getDGenotype() {
return mapMatrixToVector(m_Genotype);
}
/************************************************************************************
* InterfaceESIndividual methods
*/
/** This method will allow the user to read the ES 'genotype'
* @return BitSet
*/
public double[] getDGenotype() {
return mapMatrixToVector(m_Genotype);
}
public double[] mapMatrixToVector(double[][] matrix) {
int sumentries = 0;
for (int i = 0; i < matrix.length; i++) {
sumentries += matrix[i].length;
}
double[] res = new double[sumentries];
int counter = 0;
for (int i = 0; i < matrix.length; i++) {
for (int j = 0; j < matrix[i].length; j++) {
res[counter] = matrix[i][j];
counter++;
}
}
return res;
}
public double[] mapMatrixToVector(double[][] matrix) {
int sumentries = 0;
for (int i = 0; i < matrix.length; i++) {
sumentries += matrix[i].length;
}
double[] res = new double[sumentries];
int counter = 0;
for (int i = 0; i < matrix.length; i++) {
for (int j = 0; j < matrix[i].length; j++) {
res[counter] = matrix[i][j];
counter++;
}
}
return res;
}
public double[][] mapVectorToMatrix(double[] vector, int[] sizes) {
double[][] matrix = new double[sizes.length][];
int counter = 0;
for (int i = 0; i < sizes.length; i++) {
matrix[i] = new double[sizes[i]];
for (int j = 0; j < matrix[i].length; j++) {
matrix[i][j] = vector[counter];
counter++;
}
}
public double[][] mapVectorToMatrix(double[] vector, int[] sizes) {
double[][] matrix = new double[sizes.length][];
int counter = 0;
for (int i = 0; i < sizes.length; i++) {
matrix[i] = new double[sizes[i]];
for (int j = 0; j < matrix[i].length; j++) {
matrix[i][j] = vector[counter];
counter++;
}
}
return matrix;
}
return matrix;
}
/** This method will allow the user to set the current ES 'genotype'.
* @param b The new genotype of the Individual
*/
public void SetDGenotype(double[] b) {
this.m_Genotype = mapVectorToMatrix(b, this.sizePermutation());
for (int i = 0; i < this.m_Genotype.length; i++) {
for (int j = 0; j < this.m_Genotype[i].length; j++) {
if (this.m_Genotype[i][j] < this.m_Range[i][j][0]) this.m_Genotype[i][j] = this.m_Range[i][j][0];
if (this.m_Genotype[i][j] > this.m_Range[i][j][1]) this.m_Genotype[i][j] = this.m_Range[i][j][1];
}
}
/** This method will allow the user to set the current ES 'genotype'.
* @param b The new genotype of the Individual
*/
public void SetDGenotype(double[] b) {
this.m_Genotype = mapVectorToMatrix(b, this.sizePermutation());
for (int i = 0; i < this.m_Genotype.length; i++) {
for (int j = 0; j < this.m_Genotype[i].length; j++) {
if (this.m_Genotype[i][j] < this.m_Range[i][j][0]) this.m_Genotype[i][j] = this.m_Range[i][j][0];
if (this.m_Genotype[i][j] > this.m_Range[i][j][1]) this.m_Genotype[i][j] = this.m_Range[i][j][1];
}
}
}
}
/** This method performs a simple one element mutation on the double vector
*/
public void defaultMutate() {
for (int i = 0; i < m_Genotype.length; i++) {
int mutationIndex = RNG.randomInt(0, this.m_Genotype[i].length-1);
this.m_Genotype[i][mutationIndex] += ((this.m_Range[i][mutationIndex][1] - this.m_Range[i][mutationIndex][0])/2)*RNG.gaussianDouble(0.05f);
if (this.m_Genotype[i][mutationIndex] < this.m_Range[i][mutationIndex][0]) this.m_Genotype[i][mutationIndex] = this.m_Range[i][mutationIndex][0];
if (this.m_Genotype[i][mutationIndex] > this.m_Range[i][mutationIndex][1]) this.m_Genotype[i][mutationIndex] = this.m_Range[i][mutationIndex][1];
}
/** This method performs a simple one element mutation on the double vector
*/
public void defaultMutate() {
for (int i = 0; i < m_Genotype.length; i++) {
int mutationIndex = RNG.randomInt(0, this.m_Genotype[i].length-1);
this.m_Genotype[i][mutationIndex] += ((this.m_Range[i][mutationIndex][1] - this.m_Range[i][mutationIndex][0])/2)*RNG.gaussianDouble(0.05f);
if (this.m_Genotype[i][mutationIndex] < this.m_Range[i][mutationIndex][0]) this.m_Genotype[i][mutationIndex] = this.m_Range[i][mutationIndex][0];
if (this.m_Genotype[i][mutationIndex] > this.m_Range[i][mutationIndex][1]) this.m_Genotype[i][mutationIndex] = this.m_Range[i][mutationIndex][1];
}
}
}
/** This method initializes the double vector
*/
public void defaultInit() {
for (int i = 0; i < this.m_Genotype.length; i++) {
for (int j = 0; j < this.m_Genotype[i].length; j++) {
this.m_Genotype[i][j] = RNG.randomDouble(this.m_Range[i][j][0], this.m_Range[i][j][1]);
}
}
}
/** This method initializes the double vector
*/
public void defaultInit() {
for (int i = 0; i < this.m_Genotype.length; i++) {
for (int j = 0; j < this.m_Genotype[i].length; j++) {
this.m_Genotype[i][j] = RNG.randomDouble(this.m_Range[i][j][0], this.m_Range[i][j][1]);
}
}
}
/** This method will return the range for all double attributes.
* @return The range array.
*/
public double[][] getDoubleRange() {
int sumentries = 0;
for (int i = 0; i < this.m_Range.length; i++) {
sumentries += this.m_Range[i].length;
}
double[][] res = new double[sumentries][2];
int counter = 0;
for (int i = 0; i < this.m_Range.length; i++) {
for (int j = 0; j < this.m_Range[i].length; j++) {
res[counter][0] = this.m_Range[i][j][0];
res[counter][1] = this.m_Range[i][j][1];
counter++;
}
}
return res;
}
/**********************************************************************************************************************
* These are for GUI
*/
/** This method allows the CommonJavaObjectEditorPanel to read the
* name to the current object.
* @return The name.
*/
public String getName() {
return "ES individual";
}
/** This method will return the range for all double attributes.
* @return The range array.
*/
public double[][] getDoubleRange() {
int sumentries = 0;
for (int i = 0; i < this.m_Range.length; i++) {
sumentries += this.m_Range[i].length;
}
double[][] res = new double[sumentries][2];
int counter = 0;
for (int i = 0; i < this.m_Range.length; i++) {
for (int j = 0; j < this.m_Range[i].length; j++) {
res[counter][0] = this.m_Range[i][j][0];
res[counter][1] = this.m_Range[i][j][1];
counter++;
}
}
return res;
}
/** This method returns a global info string
* @return description
*/
public String globalInfo() {
return "This is an ES individual suited to optimize permutations.";
}
/**********************************************************************************************************************
* These are for GUI
*/
/** This method allows the CommonJavaObjectEditorPanel to read the
* name to the current object.
* @return The name.
*/
public String getName() {
return "ES individual";
}
/** This method returns a global info string
* @return description
*/
public String globalInfo() {
return "This is an ES individual suited to optimize permutations.";
}
}

92
src/eva2/server/go/problems/FLensProblem.java
View File

@@ -1,31 +1,46 @@
package eva2.server.go.problems;
import javax.swing.*;
import java.awt.BasicStroke;
import java.awt.BorderLayout;
import java.awt.Color;
import java.awt.Dimension;
import java.awt.Graphics;
import java.awt.Graphics2D;
import java.awt.Rectangle;
import java.awt.Shape;
import java.awt.Stroke;
import java.awt.image.BufferedImage;
import javax.swing.JComponent;
import javax.swing.JFrame;
import javax.swing.JPanel;
import javax.swing.JScrollPane;
import javax.swing.JTextArea;
import wsi.ra.math.RNG;
import eva2.server.go.GOStandaloneVersion;
import eva2.server.go.individuals.AbstractEAIndividual;
import eva2.server.go.individuals.ESIndividualDoubleData;
import eva2.server.go.individuals.GAIndividualDoubleData;
import eva2.server.go.individuals.InterfaceDataTypeDouble;
import eva2.server.go.populations.Population;
import eva2.server.go.strategies.InterfaceOptimizer;
import wsi.ra.math.RNG;
import eva2.server.modules.GOParameters;
import java.awt.*;
import java.awt.image.BufferedImage;
class MyLensViewer extends JPanel {
private double[] m_BestVariables;
/**
*
*/
private static final long serialVersionUID = 7945150208043416139L;
private double[] m_BestVariables;
private double m_BestFitness;
private int m_Height, m_Width, m_CenterX, m_CenterY;
private int m_Height, m_Width;
FLensProblem m_LensProblem;
public MyLensViewer (FLensProblem f) {
this.m_LensProblem = f;
Dimension d = new Dimension (450, 350);
Dimension d = new Dimension (280, 220);
this.setPreferredSize(d);
this.setMinimumSize(d);
resetBest();
@@ -40,12 +55,12 @@ class MyLensViewer extends JPanel {
Shape tmpShape;
BufferedImage bufferedImage;
BasicStroke ds = new BasicStroke();
Stroke dashStroke, lineStroke, pointStroke;
int currentPos, width, mag = 10;
Stroke dashStroke;
int mag = 10;
int centerLens, centerScreen, segment;
lineStroke = ds;
pointStroke = new BasicStroke(ds.getLineWidth(), ds.getEndCap(), ds.getLineJoin(), ds.getMiterLimit() , new float[] {1, 4}, 0);
// lineStroke = ds;
// pointStroke = new BasicStroke(ds.getLineWidth(), ds.getEndCap(), ds.getLineJoin(), ds.getMiterLimit() , new float[] {1, 4}, 0);
dashStroke = new BasicStroke(ds.getLineWidth(), ds.getEndCap(), ds.getLineJoin(), ds.getMiterLimit() , new float[] {8, 8}, 0);
super.paint(g);
@@ -54,16 +69,24 @@ class MyLensViewer extends JPanel {
return;
}
// Create a buffered image in which to draw
try {
this.m_Height = (int)g.getClipBounds().getHeight();
this.m_Width = (int)g.getClipBounds().getWidth();
this.m_CenterX = (int)g.getClipBounds().getCenterX();
this.m_CenterY = (int)g.getClipBounds().getCenterY();
} catch (java.lang.NullPointerException npe) {
//System.out.println("Try fail...");
}
if (this.m_Height == 0) this.m_Height = 250;
if (this.m_Width == 0) this.m_Width = 350;
// try {
// this.m_Height = (int)g.getClipBounds().getHeight();
// this.m_Width = (int)g.getClipBounds().getWidth();
// this.m_CenterX = (int)g.getClipBounds().getCenterX();
// this.m_CenterY = (int)g.getClipBounds().getCenterY();
// } catch (java.lang.NullPointerException npe) {
// //System.out.println("Try fail...");
// }
// This might cure the eternal display problems: just ignore clipping and leave it up to swing
Dimension winDim = getSize();
m_Height = winDim.height;
m_Width = winDim.width;
// m_CenterX = m_Width/2;
// m_CenterY = m_Height/2;
// if (this.m_Height == 0) this.m_Height = 250;
// if (this.m_Width == 0) this.m_Width = 350;
// System.out.println(" h w cx cy " + m_Height + " " + m_Width + " " + m_CenterX + " " + m_CenterY );
bufferedImage = new BufferedImage(this.m_Width, this.m_Height, BufferedImage.TYPE_INT_RGB);
// Create a graphics contents on the buffered image
Graphics2D g2D = bufferedImage.createGraphics();
@@ -139,6 +162,10 @@ class MyLensViewer extends JPanel {
*/
public class FLensProblem extends AbstractOptimizationProblem implements InterfaceOptimizationProblem, java.io.Serializable {
/**
*
*/
private static final long serialVersionUID = 4694920294291719310L;
protected AbstractEAIndividual m_OverallBest = null;
protected int m_ProblemDimension = 10;
protected double m_Noise = 0.0;
@@ -244,25 +271,6 @@ public class FLensProblem extends AbstractOptimizationProblem implements Interfa
population.init();
}
// /** This method evaluates a given population and set the fitness values
// * accordingly
// * @param population The population that is to be evaluated.
// */
// public void evaluate(Population population) {
// evaluatePopulationStart(population);
// AbstractEAIndividual tmpIndy;
//
// for (int i = 0; i < population.size(); i++) {
// tmpIndy = (AbstractEAIndividual) population.get(i);
// tmpIndy.resetConstraintViolation();
// this.evaluate(tmpIndy);
// population.incrFunctionCalls();
// }
// evaluatePopulationEnd(population);
// //if (sleepTime > 0 ) try { Thread.sleep(sleepTime); } catch(Exception e) {}
//// if (this.m_Show) this.updateProblemFrame(population);
// }
public void evaluatePopulationEnd(Population pop) {
if (this.m_Show) this.updateProblemFrame(pop);
}

4
src/eva2/tools/Mathematics.java
View File

@@ -588,8 +588,8 @@ public class Mathematics {
}
/**
* Normalizes the doubles in the array by their sum.
*
* Normalizes the doubles in the array by their sum,
* so that they add up to one.
* @param doubles the array of double
* @exception IllegalArgumentException if sum is Zero or NaN
*/

6
src/wsi/ra/chart2d/DLine.java
View File

@@ -57,7 +57,11 @@ public class DLine extends DComponent
if( color != null ) g.setColor( color );
Point p1 = m.getPoint( start ),
p2 = m.getPoint( end ) ;
g.drawLine( p1.x, p1.y, p2.x, p2.y );
if ((p1!=null) && (p2!=null)) {
g.drawLine( p1.x, p1.y, p2.x, p2.y );
} else {
System.err.println("Couldnt paint rect!");
}
}
public String toString(){

10
src/wsi/ra/chart2d/DMeasures.java
View File

@@ -87,6 +87,9 @@ private boolean under_construction = false;
*/
public Point getPoint( double x, double y ){
DRectangle rect = getSourceOf( getDRectangle() );
if (rect == null) {
return null;
}
try{
if( x_scale != null ) x = x_scale.getSourceOf( x );
if( y_scale != null ) y = y_scale.getSourceOf( y );
@@ -214,8 +217,11 @@ private boolean under_construction = false;
*/
DRectangle getSourceOf( DRectangle rect ){
if( under_construction ) System.out.println("DMeasures.getSourceOf: "+rect);
if( !getDRectangle().contains( rect ) ) throw
new IllegalArgumentException("The rectangle lies not in the currently painted rectangle");
if( !getDRectangle().contains( rect ) ) {
return null;
//throw new IllegalArgumentException("The rectangle lies not in the currently painted rectangle");
}
if( x_scale == null && y_scale == null ) return rect;
if( rect.isEmpty() ) return (DRectangle)rect.clone();
DPoint p1 = new DPoint( rect.x, rect.y ),

5
src/wsi/ra/math/RNG.java
View File

@@ -191,7 +191,10 @@ public class RNG extends Random {
return (float)random.nextGaussian()*dev;
}
/**
*
* Return a Gaussian double with mean 0 and deviation dev.
*
* @param dev the deviation of the distribution.
* @return a Gaussian double with mean 0 and given deviation.
*/
public static double gaussianDouble(double dev) {
//counter++;

15
src/wsi/ra/tool/BasicResourceLoader.java
View File

@@ -188,6 +188,7 @@ public class BasicResourceLoader implements ResourceLoader
* @param rawData Strings containing an array with double data columns
* @param colSplit String regexp for the splitting of a line
* @param selectedCols indices of the columns to retrieve, null for all.
* @see java.util.regex.Pattern
* @return
*/
public static double[][] parseDoubleArray(ArrayList<String> rawData, String colSplit, int[] selectedCols) {
@@ -199,7 +200,7 @@ public class BasicResourceLoader implements ResourceLoader
entries = rawData.get(i).split(colSplit);
if (i == 0) { // at the first pass
dat = new double[rawData.size()][(selectedCols == null) ? entries.length : selectedCols.length];
}
}
fillLine(dat, i, entries, selectedCols);
}
} catch (Exception e) {
@@ -270,11 +271,19 @@ public class BasicResourceLoader implements ResourceLoader
}
if (cols == null) {
for (int i=0; i<entries.length; i++) {
dest[lineCnt][i] = Double.valueOf(entries[i]);
try {
dest[lineCnt][i] = Double.valueOf(entries[i]);
} catch(NumberFormatException ex) {
System.err.println("Invalid Double format in line " + lineCnt + ", data was " + entries[i]);
}
}
} else {
for (int i=0; i<cols.length; i++) {
dest[lineCnt][i] = Double.valueOf(entries[cols[i]]);
try {
dest[lineCnt][i] = Double.valueOf(entries[cols[i]]);
} catch(NumberFormatException ex) {
System.err.println("Invalid Double format in line " + lineCnt + ", data was " + entries[cols[i]]);
}
}
}
}