Addition to last commit.
This commit is contained in:
Marcel Kronfeld
parent
3a18cedcc6
commit
9bae041840
@ -0,0 +1,52 @@
|
||||
package javaeva.server.go.operators.terminators;
|
||||
|
||||
import javaeva.gui.BeanInspector;
|
||||
import javaeva.server.go.IndividualInterface;
|
||||
import javaeva.server.go.InterfaceTerminator;
|
||||
import javaeva.server.go.PopulationInterface;
|
||||
import javaeva.server.go.individuals.AbstractEAIndividual;
|
||||
import javaeva.server.go.operators.distancemetric.PhenotypeMetric;
|
||||
|
||||
public class PhenotypeConvergenceTerminator extends FitnessConvergenceTerminator implements InterfaceTerminator {
|
||||
AbstractEAIndividual oldIndy = null;
|
||||
double oldPhenNorm = 0;
|
||||
|
||||
public PhenotypeConvergenceTerminator() {
|
||||
super();
|
||||
}
|
||||
|
||||
public PhenotypeConvergenceTerminator(double thresh, int stagnTime, boolean bFitCallBased, boolean bAbsolute) {
|
||||
super(thresh, stagnTime, bFitCallBased, bAbsolute);
|
||||
}
|
||||
/**
|
||||
* Return true if |oldPhen - curPhen| < |oldPhen| * thresh% (relative case)
|
||||
* and if |oldFit - curFit| < thresh (absolute case).
|
||||
*
|
||||
* @param curFit
|
||||
* @return
|
||||
*/
|
||||
protected boolean isStillConverged(IndividualInterface indy) {
|
||||
double dist = pMetric.distance(oldIndy, (AbstractEAIndividual)indy);
|
||||
boolean ret;
|
||||
if (getConvergenceCondition().isSelectedString("Relative")) {
|
||||
ret = (dist < (oldPhenNorm * convThresh));
|
||||
} else {
|
||||
ret = (dist < convThresh);
|
||||
}
|
||||
if (TRACE) System.out.println("isStillConverged returns " + ret + ", dist " + dist + ", old indy " + BeanInspector.toString(oldIndy) + ", cur indy" + BeanInspector.toString(indy));
|
||||
return ret;
|
||||
}
|
||||
|
||||
public String terminatedBecause(PopulationInterface pop) {
|
||||
if (isTerminated(pop)) {
|
||||
return getTerminationMessage("Phenotype converged");
|
||||
} else return "Not yet terminated.";
|
||||
}
|
||||
|
||||
|
||||
protected void saveState(PopulationInterface Pop) {
|
||||
super.saveState(Pop);
|
||||
oldIndy = (AbstractEAIndividual)((AbstractEAIndividual)Pop.getBestIndividual()).clone();
|
||||
oldPhenNorm = PhenotypeMetric.norm(oldIndy);
|
||||
}
|
||||
}
|
||||
222
src/javaeva/server/go/problems/SimpleProblemWrapper.java
Normal file
222
src/javaeva/server/go/problems/SimpleProblemWrapper.java
Normal file
@ -0,0 +1,222 @@
|
||||
package javaeva.server.go.problems;
|
||||
|
||||
import java.lang.reflect.Method;
|
||||
import java.util.BitSet;
|
||||
|
||||
import javaeva.gui.BeanInspector;
|
||||
import javaeva.gui.GenericObjectEditor;
|
||||
import javaeva.server.go.individuals.AbstractEAIndividual;
|
||||
import javaeva.server.go.individuals.ESIndividualDoubleData;
|
||||
import javaeva.server.go.individuals.GAIndividualBinaryData;
|
||||
import javaeva.server.go.individuals.InterfaceDataTypeBinary;
|
||||
import javaeva.server.go.individuals.InterfaceDataTypeDouble;
|
||||
import javaeva.server.go.populations.Population;
|
||||
import javaeva.server.go.strategies.InterfaceOptimizer;
|
||||
import javaeva.server.go.tools.RandomNumberGenerator;
|
||||
import simpleprobs.InterfaceSimpleProblem;
|
||||
import simpleprobs.SimpleF1;
|
||||
import simpleprobs.SimpleProblemBinary;
|
||||
import simpleprobs.SimpleProblemDouble;
|
||||
|
||||
public class SimpleProblemWrapper extends AbstractOptimizationProblem {
|
||||
InterfaceSimpleProblem simProb = new SimpleF1();
|
||||
protected double m_DefaultRange = 10;
|
||||
protected double m_Noise = 0;
|
||||
|
||||
public SimpleProblemWrapper() {
|
||||
initTemplate();
|
||||
}
|
||||
|
||||
public SimpleProblemWrapper(SimpleProblemWrapper other) {
|
||||
other.m_DefaultRange = m_DefaultRange;
|
||||
other.m_Noise = m_Noise;
|
||||
// warning! this does no deep copy!
|
||||
other.simProb = simProb;
|
||||
}
|
||||
|
||||
@Override
|
||||
public Object clone() {
|
||||
return new SimpleProblemWrapper(this);
|
||||
}
|
||||
|
||||
@Override
|
||||
public void evaluate(AbstractEAIndividual individual) {
|
||||
if (simProb instanceof SimpleProblemDouble) {
|
||||
double[] x;
|
||||
double[] fitness;
|
||||
|
||||
x = new double[((InterfaceDataTypeDouble) individual).getDoubleData().length];
|
||||
System.arraycopy(((InterfaceDataTypeDouble) individual).getDoubleData(), 0, x, 0, x.length);
|
||||
// evaluate the vector
|
||||
fitness = ((SimpleProblemDouble)simProb).eval(x);
|
||||
// if indicated, add Gaussian noise
|
||||
if (m_Noise != 0) RandomNumberGenerator.addNoise(fitness, m_Noise);
|
||||
// set the fitness
|
||||
individual.SetFitness(fitness);
|
||||
} else if (simProb instanceof SimpleProblemBinary) {
|
||||
BitSet tmpBitSet;
|
||||
double[] result;
|
||||
|
||||
tmpBitSet = ((InterfaceDataTypeBinary) individual).getBinaryData();
|
||||
// evaluate the fitness
|
||||
result = ((SimpleProblemBinary)simProb).eval(tmpBitSet);
|
||||
// set the fitness
|
||||
individual.SetFitness(result);
|
||||
} else {
|
||||
System.err.println("Error in SimpleProblemWrapper: " + simProb.getClass().getName() + " is unknown type!");
|
||||
}
|
||||
}
|
||||
|
||||
@Override
|
||||
public void initPopulation(Population population) {
|
||||
AbstractEAIndividual tmpIndy;
|
||||
population.clear();
|
||||
|
||||
initTemplate();
|
||||
|
||||
for (int i = 0; i < population.getPopulationSize(); i++) {
|
||||
tmpIndy = (AbstractEAIndividual)((AbstractEAIndividual)this.m_Template).clone();
|
||||
tmpIndy.init(this);
|
||||
population.add(tmpIndy);
|
||||
}
|
||||
// population init must be last
|
||||
// it set's fitcalls and generation to zero
|
||||
population.init();
|
||||
|
||||
}
|
||||
|
||||
@Override
|
||||
public void initProblem() {
|
||||
initTemplate();
|
||||
}
|
||||
|
||||
protected void initTemplate() {
|
||||
if (simProb instanceof SimpleProblemDouble) {
|
||||
this.m_Template = new ESIndividualDoubleData();
|
||||
((ESIndividualDoubleData)this.m_Template).setDoubleDataLength(simProb.getProblemDimension());
|
||||
((ESIndividualDoubleData)this.m_Template).SetDoubleRange(makeRange());
|
||||
} else if (simProb instanceof SimpleProblemBinary) {
|
||||
this.m_Template = new GAIndividualBinaryData();
|
||||
((InterfaceDataTypeBinary)this.m_Template).setBinaryDataLength(simProb.getProblemDimension());
|
||||
}
|
||||
}
|
||||
|
||||
protected double[][] makeRange() {
|
||||
double[][] range = new double[simProb.getProblemDimension()][2];
|
||||
for (int i = 0; i < range.length; i++) {
|
||||
range[i][0] = getRangeLowerBound(i);
|
||||
range[i][1] = getRangeUpperBound(i);
|
||||
}
|
||||
return range;
|
||||
}
|
||||
|
||||
protected double getRangeLowerBound(int dim) {
|
||||
return -m_DefaultRange;
|
||||
}
|
||||
|
||||
protected double getRangeUpperBound(int dim) {
|
||||
return m_DefaultRange;
|
||||
}
|
||||
|
||||
/**
|
||||
* @return the simProb
|
||||
*/
|
||||
public InterfaceSimpleProblem getSimpleProblem() {
|
||||
return simProb;
|
||||
}
|
||||
|
||||
/**
|
||||
* @param simProb the simProb to set
|
||||
*/
|
||||
public void setSimpleProblem(InterfaceSimpleProblem simProb) {
|
||||
this.simProb = simProb;
|
||||
initTemplate();
|
||||
GenericObjectEditor.setShowProperty(getClass(), "noise", (simProb instanceof SimpleProblemDouble));
|
||||
GenericObjectEditor.setShowProperty(getClass(), "defaultRange", (simProb instanceof SimpleProblemDouble));
|
||||
}
|
||||
|
||||
/**
|
||||
*
|
||||
*/
|
||||
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.
|
||||
*/
|
||||
public void setNoise(double noise) {
|
||||
if (noise < 0) noise = 0;
|
||||
this.m_Noise = noise;
|
||||
}
|
||||
public double getNoise() {
|
||||
return this.m_Noise;
|
||||
}
|
||||
public String noiseTipText() {
|
||||
return "Gaussian noise level on the fitness value.";
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* A (symmetric) absolute range limit.
|
||||
*
|
||||
* @return value of the absolute range limit
|
||||
*/
|
||||
public double getDefaultRange() {
|
||||
return m_DefaultRange;
|
||||
}
|
||||
/**
|
||||
* Set a (symmetric) absolute range limit.
|
||||
*
|
||||
* @param defaultRange
|
||||
*/
|
||||
public void setDefaultRange(double defaultRange) {
|
||||
this.m_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.
|
||||
*/
|
||||
public void hideHideable() {
|
||||
setSimpleProblem(getSimpleProblem());
|
||||
}
|
||||
|
||||
/////////// for GUI
|
||||
|
||||
/** This method returns a string describing the optimization problem.
|
||||
* @param opt The Optimizer that is used or had been used.
|
||||
* @return The description.
|
||||
*/
|
||||
public String getStringRepresentationForProblem(InterfaceOptimizer opt) {
|
||||
StringBuffer sb = new StringBuffer(200);
|
||||
sb.append("A wrapped simple problem based on ");
|
||||
sb.append(simProb.getClass().getName());
|
||||
sb.append(", Dimension : ");
|
||||
sb.append(simProb.getProblemDimension());
|
||||
return sb.toString();
|
||||
}
|
||||
|
||||
/** This method allows the CommonJavaObjectEditorPanel to read the
|
||||
* name to the current object.
|
||||
* @return The name.
|
||||
*/
|
||||
public String getName() {
|
||||
return "SimpleProblemWrapper";
|
||||
}
|
||||
|
||||
/** This method returns a global info string
|
||||
* @return description
|
||||
*/
|
||||
public String globalInfo() {
|
||||
Object maybeAdditionalString = BeanInspector.callIfAvailable(simProb, "globalInfo", null);
|
||||
if (maybeAdditionalString != null) {
|
||||
return "Wrapping a simple problem: " + (String)maybeAdditionalString;
|
||||
} else return "Wrapping a simple problem.";
|
||||
}
|
||||
}
|
||||
Loading…
x
Reference in New Issue
Block a user