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Merging MK branch revs. 332:338; constraint handling; GP nodes; minor stuff;

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This commit is contained in:
Marcel Kronfeld
2009-07-17 13:04:27 +00:00
parent 5cb5915907
commit 29f2a0d771
36 changed files with 1761 additions and 253 deletions
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26
src/eva2/OptimizerFactory.java
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@@ -649,6 +649,18 @@ public class OptimizerFactory {
return opt;
}
/**
* Produce a runnable optimizer from a GOParameters instance. Output is written to a file if the
* prefix String is given.
*
* @param params
* @param outputFilePrefix
* @return a runnable optimizer
*/
public static OptimizerRunnable getOptRunnable(GOParameters params, String outputFilePrefix) {
return new OptimizerRunnable(params, outputFilePrefix);
}
// /////////////////////////// constructing a default OptimizerRunnable
/**
* Produce a runnable optimizer from a strategy identifier, a problem instance and with the current
@@ -708,7 +720,19 @@ public class OptimizerFactory {
public static GOParameters makeParams(InterfaceOptimizer opt, int popSize, AbstractOptimizationProblem problem) {
return makeParams(opt, popSize, problem, randSeed, makeDefaultTerminator());
}
/**
* Use default random seed and the population size of the optimizer.
*
* @see #makeParams(InterfaceOptimizer, int, AbstractOptimizationProblem, long, InterfaceTerminator)
* @param opt
* @param popSize
* @param problem
* @return
*/
public static GOParameters makeParams(InterfaceOptimizer opt, AbstractOptimizationProblem problem, InterfaceTerminator term) {
return makeParams(opt, opt.getPopulation().getPopulationSize(), problem, randSeed, term);
}
/**
* Set the population size, initialize the population and return a parameter structure containing all
* given parts.

25
src/eva2/OptimizerRunnable.java
View File

@@ -57,9 +57,7 @@ public class OptimizerRunnable implements Runnable {
* @param restart
*/
public OptimizerRunnable(GOParameters params, boolean restart) {
proc = new Processor(new StatisticsDummy(), null, params);
if (proc.getStatistics() instanceof AbstractStatistics) ((AbstractStatistics)proc.getStatistics()).setSaveParams(false);
doRestart = restart;
this(params, new StatisticsDummy(), restart);
}
/**
@@ -72,7 +70,19 @@ public class OptimizerRunnable implements Runnable {
* @param restart
*/
public OptimizerRunnable(GOParameters params, String outputFilePrefix, boolean restart) {
proc = new Processor(new StatisticsStandalone(outputFilePrefix), null, params);
this(params, new StatisticsStandalone(outputFilePrefix), restart);
}
/**
* Construct an OptimizerRunnable with given parameters and statistics instance with optional restart.
* If restart is true, the processor will not reinitialize the population allowing search on predefined populations.
*
* @param params
* @param outputFilePrefix
* @param restart
*/
public OptimizerRunnable(GOParameters params, InterfaceStatistics stats, boolean restart) {
proc = new Processor(stats, null, params);
if (proc.getStatistics() instanceof AbstractStatistics) ((AbstractStatistics)proc.getStatistics()).setSaveParams(false);
doRestart = restart;
}
@@ -85,6 +95,13 @@ public class OptimizerRunnable implements Runnable {
return proc.getStatistics();
}
public void setStats(InterfaceStatistics stats) {
if (proc.isOptRunning()) throw new RuntimeException("Error - cannot change statistics instance during optimization.");
InterfaceGOParameters params = proc.getGOParams();
proc = new Processor(stats, null, params);
if (proc.getStatistics() instanceof AbstractStatistics) ((AbstractStatistics)proc.getStatistics()).setSaveParams(false);
}
public void setTextListener(InterfaceTextListener lsnr) {
proc.getStatistics().removeTextListener(listener);
this.listener = lsnr;

2
src/eva2/gui/GOEPanel.java
View File

@@ -373,7 +373,7 @@ public class GOEPanel extends JPanel implements ItemListener {
JOptionPane.showMessageDialog(this,
"Could not create an example of\n"
+ className + "\n"
+ "from the current classpath. Is it abstract? Is the default constructor missing?",
+ "from the current classpath. Is the resource folder at the right place?\nIs the class abstract or the default constructor missing?",
"GenericObjectEditor",
JOptionPane.ERROR_MESSAGE);
EVAHELP.getSystemPropertyString();

18
src/eva2/server/go/individuals/AbstractEAIndividual.java
View File

@@ -160,6 +160,7 @@ public abstract class AbstractEAIndividual implements IndividualInterface, java.
* @return boolean if equal true else false
*/
public boolean equals(Object obj) {
if (this==obj) return true;
if (obj instanceof AbstractEAIndividual) {
AbstractEAIndividual indy = (AbstractEAIndividual) obj;
@@ -607,13 +608,18 @@ public abstract class AbstractEAIndividual implements IndividualInterface, java.
boolean result = true;
int i=0;
while (result && (i < fit1.length) && (i < fit2.length)) {
if (fit1[i] > fit2[i]) result = false;
if (firstIsFiniteAndLarger(fit1[i], fit2[i])) result = false;
i++;
}
return result;
}
/**
private static boolean firstIsFiniteAndLarger(double a, double b) {
if (Double.isNaN(a) || Double.isInfinite(a)) return false;
else return (a > b);
}
/**
* Returns true if the first fitness vector truly dominates the second one in every component.
*
* @param fit1 first fitness vector to look at
@@ -863,6 +869,8 @@ public abstract class AbstractEAIndividual implements IndividualInterface, java.
sb.append(", fitness: ");
sb.append(BeanInspector.toString(individual.getFitness()));
if (individual.isMarkedPenalized() || individual.violatesConstraint())
sb.append(", X");
sb.append(", ID: ");
sb.append(individual.getIndyID());
if (individual.getParentIDs()!=null) {
@@ -882,7 +890,7 @@ public abstract class AbstractEAIndividual implements IndividualInterface, java.
public static String getDefaultDataString(IndividualInterface individual) {
// Note that changing this method might change the hashcode of an individual
// which might interfere with some functionality.
return getDefaultDataString(individual, "; ");
return getDefaultDataString(individual, ", ");
}
/**
@@ -897,8 +905,8 @@ public abstract class AbstractEAIndividual implements IndividualInterface, java.
// which might interfere with some functionality.
if (individual == null) return "null";
StringBuffer sb = new StringBuffer("");
char left = '[';
char right = ']';
char left = '{';
char right = '}';
sb.append(left);
if (individual instanceof InterfaceDataTypeBinary) {
BitSet b = ((InterfaceDataTypeBinary)individual).getBinaryData();

9
src/eva2/server/go/individuals/ESIndividualDoubleData.java
View File

@@ -6,6 +6,8 @@ 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 eva2.tools.EVAERROR;
import eva2.tools.Mathematics;
/** This individual uses a real-valued genotype to code for double values.
* Created by IntelliJ IDEA.
@@ -162,8 +164,9 @@ public class ESIndividualDoubleData extends AbstractEAIndividual implements Inte
return this.m_Phenotype;
}
/** This method allows you to read the double data without
* an update from the genotype
/**
* This method allows you to read the double data without
* an update from the genotype.
* @return double[] representing the double data.
*/
public double[] getDoubleDataWithoutUpdate() {
@@ -198,6 +201,8 @@ public class ESIndividualDoubleData extends AbstractEAIndividual implements Inte
this.defaultInit();
this.m_MutationOperator.init(this, opt);
this.m_CrossoverOperator.init(this, opt);
// evil operators may not respect the range, so at least give some hint
if (!Mathematics.isInRange(m_Genotype, m_Range)) EVAERROR.errorMsgOnce("Warning: Individual out of range after initialization (and potential initial crossover/mutation)!");
}
/** This method will init the individual with a given value for the

91
src/eva2/server/go/individuals/codings/gp/AbstractGPNode.java
View File

@@ -6,7 +6,9 @@ import java.util.Vector;
import eva2.gui.BeanInspector;
import eva2.gui.GenericObjectEditor;
import eva2.server.go.problems.GPFunctionProblem;
import eva2.server.go.problems.InterfaceProgramProblem;
import eva2.tools.Mathematics;
import eva2.tools.Pair;
@@ -73,7 +75,8 @@ public abstract class AbstractGPNode implements InterfaceProgram, java.io.Serial
public abstract String getOpIdentifier();
/**
* Small parser for GP nodes from a String. Format must be (nearly) equivalent to what makeStringRepresentation produces.
* Small parser for GP nodes from a String. Format must be (nearly) equivalent to what
* makeStringRepresentation produces.
* This mainly means prefix notation with braces and commata, such as in:
* AbstractGPNode node = AbstractGPNode.parseFromString("+(2.0,cos(*(pi,pi)))");
* System.out.println("Parsed GPNode: " + node.getStringRepresentation());
@@ -84,15 +87,7 @@ public abstract class AbstractGPNode implements InterfaceProgram, java.io.Serial
*/
public static Pair<AbstractGPNode,String> parseFromString(String str, Vector<AbstractGPNode> nodeTypes) {
if (nodeTypes == null) {
ArrayList<String>cls = GenericObjectEditor.getClassesFromClassPath(AbstractGPNode.class.getCanonicalName());
nodeTypes = new Vector<AbstractGPNode>(cls.size());
for (int i=0; i<cls.size(); i++) {
try {
AbstractGPNode node = (AbstractGPNode)Class.forName((String)cls.get(i)).newInstance();
nodeTypes.add(node);
} catch(Exception e) {}
}
nodeTypes.add(new GPNodeInput("X"));
nodeTypes = getNodeTypes();
}
if (nodeTypes.size()>0) {
Vector<AbstractGPNode> matchSet=AbstractGPNode.match(nodeTypes, str, true, true);
@@ -116,10 +111,10 @@ public abstract class AbstractGPNode implements InterfaceProgram, java.io.Serial
if (currentNode instanceof GPNodeInput) {
Pair<Double, String> nextState=readDouble(restStr, false);
if (nextState!=null) {
((GPNodeInput)currentNode).setIdentifier("X"+((int)nextState.head().doubleValue()));
((GPNodeInput)currentNode).setIdentifier(currentNode.getOpIdentifier()+((int)nextState.head().doubleValue()));
restStr = nextState.tail();
} else {
((GPNodeInput)currentNode).setIdentifier("X");
((GPNodeInput)currentNode).setIdentifier(currentNode.getOpIdentifier());
}
}
return new Pair<AbstractGPNode,String>(currentNode,restStr);
@@ -129,7 +124,13 @@ public abstract class AbstractGPNode implements InterfaceProgram, java.io.Serial
for (int i=0; i<currentNode.getArity(); i++) {
Pair<AbstractGPNode,String> nextState = parseFromString(restStr, nodeTypes);
currentNode.m_Nodes[i]=nextState.head();
restStr=nextState.tail().substring(1).trim(); // cut comma or brace
try {
restStr=nextState.tail().substring(1).trim(); // cut comma or brace
} catch (StringIndexOutOfBoundsException e) {
System.err.println("Error: parsing failed for node " + currentNode.getOpIdentifier() + "/" + currentNode.getArity() + ", depth " + currentNode.getDepth());
System.err.println("String was " + str);
e.printStackTrace();
}
}
if (TRACE) System.out.println("read " + currentNode.getName() + ", rest: " + restStr);
return new Pair<AbstractGPNode,String>(currentNode, restStr);
@@ -137,6 +138,27 @@ public abstract class AbstractGPNode implements InterfaceProgram, java.io.Serial
}
} return null;
}
/**
* Return all available node types as AbstractGPNode list.
* Using getOpIdentifier on all elements gives an overview of the operators
* that can be used.
*
* @return a list of available AbstractGPNode implementations
*/
public static Vector<AbstractGPNode> getNodeTypes() {
ArrayList<String>cls = GenericObjectEditor.getClassesFromClassPath(AbstractGPNode.class.getCanonicalName());
Vector<AbstractGPNode> nodeTypes = new Vector<AbstractGPNode>(cls.size());
for (int i=0; i<cls.size(); i++) {
try {
AbstractGPNode node = (AbstractGPNode)Class.forName((String)cls.get(i)).newInstance();
nodeTypes.add(node);
} catch(Exception e) {}
}
// nodeTypes.add(new GPNodeInput("X"));
nodeTypes.add(new GPNodeInput("N"));
return nodeTypes;
}
private static Pair<Double, String> readDouble(String str, boolean expect) {
String firstArg;
@@ -193,14 +215,19 @@ public abstract class AbstractGPNode implements InterfaceProgram, java.io.Serial
if (matching.size()>1 && firstLongestOnly) { // allow only the longest match (or first longest)
int maxLen = matching.get(0).getOpIdentifier().length();
AbstractGPNode longest=matching.get(0);
Vector<AbstractGPNode> longestList = new Vector<AbstractGPNode>();
longestList.add(longest);
for (int i=1; i<matching.size(); i++) {
if (matching.get(i).getOpIdentifier().length()>maxLen) {
longest = matching.get(i);
maxLen = longest.getOpIdentifier().length();
}
longestList.clear();
longestList.add(longest);
} else if (matching.get(i).getOpIdentifier().length()==maxLen) longestList.add(matching.get(i));
}
matching.clear();
matching.add(longest);
matching.addAll(longestList);
// TODO test if arities are different!
}
return matching;
}
@@ -214,14 +241,46 @@ public abstract class AbstractGPNode implements InterfaceProgram, java.io.Serial
public static void main(String[] args) {
// Double d = Double.parseDouble("2.58923 + 3");
// AbstractGPNode node = AbstractGPNode.parseFromString("-23421");
AbstractGPNode node = AbstractGPNode.parseFromString("+(-23421,cOs(*(pI,x1)))");
AbstractGPNode node = AbstractGPNode.parseFromString("+(-23421,cOs(*(pI,x)))");
AbstractGPNode.parseFromString("+(+(85.334407,*(0.0056858,*(x1,x4))), +(*(0.00026,*(x0,x3)),*(-0.0022053,*(x2,x4))))");
AbstractGPNode.parseFromString("+(+(80.51249,*(0.0071317,*(x1,x4))), +(*(0.0029955,*(x0,x1)),*(0.0021813,*(x2,x2))))");
AbstractGPNode.parseFromString("+(+(9.300961,*(0.0047026,*(x2,x4))), +(*(0.0012547,*(x0,x2)),*(0.0019085,*(x2,x3))))");
System.out.println("Parsed GPNode: " + node.getStringRepresentation());
node = AbstractGPNode.parseFromString(node.getStringRepresentation());
double[] sol= new double[]{4.755837346122817, 0.0, 1.618818602745894, 7.941611605461133, 7.949805645271173, 7.9567145687445695, 4.8033535294211225, 7.96718976492528, 1.641971622483205, 7.973813526015599, 7.980394418430633, 7.98301197251176, 7.98590997257042, 1.6493767411801206, 7.994756424330215, 7.994983501150322, 7.9971658558418035, 8.00273733683876, 8.00492865462689, 8.006601147955184};
double[] sol2={7.897269942114308, 0.0, 7.939346674715275, 1.6272963933436047, 7.952303730484389, 7.960893192129872, 4.804987144876599, 7.9682843963405805, 7.977546251710085, 7.981109017707746, 1.642081396353059, 7.985246784301232, 4.827113167927753, 1.6448751122424057, 7.997468593784776, 8.00165633007073, 8.000613763831703, 8.003920903217887, 8.005789437120203, 8.012425280944097};
double[] sol3={4.705970234231343, 4.71343334004773, 7.845971927185614, 4.708648989456629, 4.723918978896874, 7.864710619970946, 1.5776948341096448, 7.854961967305262, 7.858760422458277, 1.5743212019457036, 7.8488102514506, 1.5637070804731334, 1.5778078319616269, 1.5757833862993071, 4.711995406637344, 4.715448624806491, 7.8434193487088155, 4.7036514083601535, 7.848371610694223, 7.856489370257257};
test("-(0.75,prod(x))", sol3);
test("-(sum(x),*(7.5,n))", sol3);
// test("+(*(1000,+(sin(-(-0.25,x2)),sin(-(-0.25,x3)))), -(894.8,x0))", new double[]{1.,2,0,0,});
double[] solG5lit = new double[]{679.9453, 1026.067, 0.1188764, -0.3962336};
double[] solG5 = new double[] {891.702675571982, 808.9201991846442, -0.028381806025171354, -0.4684444512076402};
test("-(x2,+(x3,0.55))", solG5);
test("-(x3,+(x2,0.55))", solG5);
test("+(*(1000,+(sin(-(-0.25,x2)),sin(-(-0.25,x3)))), -(894.8,x0))", solG5);
test("+(*(1000,+(sin(+(-0.25,x2)),sin(-(x2,+(x3,0.25))))), -(894.8,x1))", solG5);
test("+(*(1000,+(sin(+(-0.25,x3)),sin(-(x3,+(x2,0.25))))), 1294.8)", solG5);
double[] solG13lit = new double[] {-1.717143,1.595709,1.827247,-0.7636413,-0.763645};
// double[] solG13 = new double[] {-0.999977165120676, -0.03949641197962931, 2.9901909235593664, 0.11170038214968671, -0.21164083835675082};
//NMS: double[] solG13 = new double[] {-1.20317028354022, 0.9052295512320271, 2.580255691052748, 0.5210663754783309, 0.8965551458319728};
double[] solG13 = {-1.717136209326236, 1.5957142570821299, -1.8272614459011625, -0.7636708932891901, 0.7636501970281446};
test("-(+(+(pow2(x0),pow2(x1)),+(pow2(x2),+(pow2(x3),pow2(x4)))),10)", solG13);
test("-(*(x1,x2),*(5,*(x3,x4)))", solG13);
test("+(pow3(x0),+(pow3(x1),1))", solG13);
System.out.println("" + Math.exp(Mathematics.product(solG13)));
test("-(sum(x),*(7.5,n))", solG5);
}
public static void test(String constr, double[] pos) {
AbstractGPNode node = AbstractGPNode.parseFromString(constr);
GPFunctionProblem func = new GPFunctionProblem(node, null, pos.length, 0., 0.);
double[] ret = func.eval(pos);
System.out.println("testing " + constr + " evaluated to " + BeanInspector.toString(ret));
}
/** This method returns the depth of the current node
* @return The depth.

3
src/eva2/server/go/individuals/codings/gp/GPNodeMult.java
View File

@@ -3,7 +3,7 @@ package eva2.server.go.individuals.codings.gp;
import eva2.server.go.problems.InterfaceProgramProblem;
/** A multiplicator node taking to arguments.
/** A multiplicator node taking two arguments.
* Created by IntelliJ IDEA.
* User: streiche
* Date: 04.04.2003
@@ -70,6 +70,7 @@ public class GPNodeMult extends AbstractGPNode implements java.io.Serializable {
for (int i = 0; i < this.m_Nodes.length; i++) {
tmpObj = this.m_Nodes[i].evaluate(environment);
if (tmpObj instanceof Double) result = result * ((Double)tmpObj).doubleValue();
else System.err.println("Unexpected type returned in evaluate for "+this.getClass().getSimpleName());
}
return new Double(result);
}

89
src/eva2/server/go/individuals/codings/gp/GPNodeNeg.java Normal file
View File

@@ -0,0 +1,89 @@
package eva2.server.go.individuals.codings.gp;
import eva2.server.go.problems.InterfaceProgramProblem;
/** A substraction node using two arguments.
* Created by IntelliJ IDEA.
* User: streiche
* Date: 04.04.2003
* Time: 15:49:47
* To change this template use Options | File Templates.
*/
public class GPNodeNeg extends AbstractGPNode implements java.io.Serializable {
public GPNodeNeg() {
}
public GPNodeNeg(GPNodeNeg node) {
this.m_Depth = node.m_Depth;
this.m_Parent = node.m_Parent;
this.m_Nodes = new AbstractGPNode[node.m_Nodes.length];
for (int i = 0; i < node.m_Nodes.length; i++) this.m_Nodes[i] = (AbstractGPNode) node.m_Nodes[i].clone();
}
/** This method allows you to determine wehter or not two subtrees
* are actually the same.
* @param obj The other subtree.
* @return boolean if equal true else false.
*/
public boolean equals(Object obj) {
if (obj instanceof GPNodeNeg) {
GPNodeNeg node = (GPNodeNeg)obj;
if (this.m_Nodes.length != node.m_Nodes.length) return false;
for (int i = 0; i < this.m_Nodes.length; i++) {
if (!this.m_Nodes[i].equals(node.m_Nodes[i])) return false;
}
return true;
} else {
return false;
}
}
/** This method will be used to identify the node in the GPAreaEditor
* @return The name.
*/
public String getName() {
return "Neg";
}
/** This method allows you to clone the Nodes
* @return the clone
*/
public Object clone() {
return (Object) new GPNodeNeg(this);
}
/** This method will return the current arity
* @return Arity.
*/
public int getArity() {
return 1;
}
/** This method will evaluate a given node
* @param environment
*/
public Object evaluate(InterfaceProgramProblem environment) {
Object tmpObj;
double result = 0;
tmpObj = this.m_Nodes[0].evaluate(environment);
if (tmpObj instanceof Double) result += ((Double)tmpObj).doubleValue();
for (int i = 1; i < this.m_Nodes.length; i++) {
tmpObj = this.m_Nodes[i].evaluate(environment);
if (tmpObj instanceof Double) result -= ((Double)tmpObj).doubleValue();
}
return new Double(result);
}
@Override
public String getOpIdentifier() {
return "neg";
}
// /** This method returns a string representation
// * @return string
// */
// public String getStringRepresentation() {
// return AbstractGPNode.makeStringRepresentation(m_Nodes, "-");
// }
}

75
src/eva2/server/go/individuals/codings/gp/GPNodeProd.java Normal file
View File

@@ -0,0 +1,75 @@
package eva2.server.go.individuals.codings.gp;
import eva2.server.go.problems.InterfaceProgramProblem;
import eva2.tools.Mathematics;
/**
* A simple product node with a single, possibly vectorial (array), argument.
*
*/
public class GPNodeProd extends AbstractGPNode implements java.io.Serializable {
public GPNodeProd() {
}
public GPNodeProd(GPNodeProd node) {
this.m_Depth = node.m_Depth;
this.m_Parent = node.m_Parent;
this.m_Nodes = new AbstractGPNode[node.m_Nodes.length];
for (int i = 0; i < node.m_Nodes.length; i++) this.m_Nodes[i] = (AbstractGPNode) node.m_Nodes[i].clone();
}
/** This method allows you to determine wehter or not two subtrees
* are actually the same.
* @param obj The other subtree.
* @return boolean if equal true else false.
*/
public boolean equals(Object obj) {
if (obj instanceof GPNodeProd) {
GPNodeProd node = (GPNodeProd)obj;
if (this.m_Nodes.length != node.m_Nodes.length) return false;
for (int i = 0; i < this.m_Nodes.length; i++) {
if (!this.m_Nodes[i].equals(node.m_Nodes[i])) return false;
}
return true;
} else {
return false;
}
}
/** This method will be used to identify the node in the GPAreaEditor
* @return The name.
*/
public String getName() {
return "Prod";
}
public Object clone() {
return (Object) new GPNodeProd(this);
}
public int getArity() {
return 1;
}
public Object evaluate(InterfaceProgramProblem environment) {
Object tmpObj;
double result = 1;
for (int i = 0; i < this.m_Nodes.length; i++) {
tmpObj = this.m_Nodes[i].evaluate(environment);
if (tmpObj instanceof double[]) result*=Mathematics.product((double[])tmpObj);
else if (tmpObj instanceof Double[]) {
Double[] vals = (Double[])tmpObj;
for (int j=0; j<vals.length; j++) result*=vals[j];
} else if (tmpObj instanceof Double) result=(Double)tmpObj;
}
return new Double(result);
}
@Override
public String getOpIdentifier() {
return "prod";
}
}

84
src/eva2/server/go/individuals/codings/gp/GPNodeSum.java Normal file
View File

@@ -0,0 +1,84 @@
package eva2.server.go.individuals.codings.gp;
import eva2.server.go.problems.InterfaceProgramProblem;
import eva2.tools.Mathematics;
/**
* A simple sum node with a single, possibly vectorial (array), argument.
*
*/
public class GPNodeSum extends AbstractGPNode implements java.io.Serializable {
public GPNodeSum() {
}
public GPNodeSum(GPNodeSum node) {
this.m_Depth = node.m_Depth;
this.m_Parent = node.m_Parent;
this.m_Nodes = new AbstractGPNode[node.m_Nodes.length];
for (int i = 0; i < node.m_Nodes.length; i++) this.m_Nodes[i] = (AbstractGPNode) node.m_Nodes[i].clone();
}
/** This method allows you to determine wehter or not two subtrees
* are actually the same.
* @param obj The other subtree.
* @return boolean if equal true else false.
*/
public boolean equals(Object obj) {
if (obj instanceof GPNodeSum) {
GPNodeSum node = (GPNodeSum)obj;
if (this.m_Nodes.length != node.m_Nodes.length) return false;
for (int i = 0; i < this.m_Nodes.length; i++) {
if (!this.m_Nodes[i].equals(node.m_Nodes[i])) return false;
}
return true;
} else {
return false;
}
}
/** This method will be used to identify the node in the GPAreaEditor
* @return The name.
*/
public String getName() {
return "Sum";
}
/** This method allows you to clone the Nodes
* @return the clone
*/
public Object clone() {
return (Object) new GPNodeSum(this);
}
/** This method will return the current arity
* @return Arity.
*/
public int getArity() {
return 1;
}
/** This method will evaluate a given node
* @param environment
*/
public Object evaluate(InterfaceProgramProblem environment) {
Object tmpObj;
double result = 0;
for (int i = 0; i < this.m_Nodes.length; i++) {
tmpObj = this.m_Nodes[i].evaluate(environment);
if (tmpObj instanceof double[]) result+=Mathematics.sum((double[])tmpObj);
else if (tmpObj instanceof Double[]) {
Double[] vals = (Double[])tmpObj;
for (int j=0; j<vals.length; j++) result+=vals[j];
} else if (tmpObj instanceof Double) result=(Double)tmpObj;
}
return new Double(result);
}
@Override
public String getOpIdentifier() {
return "sum";
}
}

196
src/eva2/server/go/operators/constraint/AbstractConstraint.java Normal file
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@@ -0,0 +1,196 @@
package eva2.server.go.operators.constraint;
import java.io.Serializable;
import eva2.gui.GenericObjectEditor;
import eva2.server.go.individuals.AbstractEAIndividual;
import eva2.server.go.operators.paramcontrol.ConstantParameters;
import eva2.server.go.operators.paramcontrol.GenericParamAdaption;
import eva2.server.go.operators.paramcontrol.InterfaceParameterControl;
import eva2.server.go.operators.paramcontrol.NoParamAdaption;
import eva2.server.go.operators.paramcontrol.ParamAdaption;
import eva2.server.go.operators.paramcontrol.ParameterControlManager;
import eva2.tools.EVAERROR;
/**
* An abstract constraint contains a penalty factor with control strategy (for dynamic penalties)
* and a relation.
*
* @author mkron
*
*/
public abstract class AbstractConstraint implements InterfaceDoubleConstraint, Serializable {
// private transient GPFunctionProblem func = null;
protected ConstraintRelationEnum relation = ConstraintRelationEnum.lessEqZero;
protected ConstraintHandlingEnum handling = ConstraintHandlingEnum.specificTag;
protected static boolean TRACE = false;
protected double equalityEpsilon = 0.0001; // threshold below which equality constraints are seen as satisfied
private double penaltyFactor = 1.;
// protected ParamAdaption penaltyFactAdaption = new NoParamAdaption();
protected ParameterControlManager paramCtrl = new ParameterControlManager(new NoParamAdaption());
private static String penaltyPropName = "penaltyFactor";
public AbstractConstraint() {
relation = ConstraintRelationEnum.lessEqZero;
penaltyFactor = 1.;
paramCtrl = new ParameterControlManager(new NoParamAdaption());
// penaltyFactAdaption = new NoParamAdaption();
}
public AbstractConstraint(AbstractConstraint o) {
// penaltyFactAdaption = (ParamAdaption)o.penaltyFactAdaption.clone();
paramCtrl = new ParameterControlManager(o.paramCtrl);
penaltyFactor = o.penaltyFactor;
relation = o.relation;
}
public void hideHideable() {
setRelation(getRelation());
}
public abstract Object clone();
public InterfaceParameterControl getParamControl() {
return paramCtrl;
}
/**
* Return the raw degree of violation - usually the function value of the constraint function.
*/
protected abstract double getRawViolationValue(double[] indyX);
/**
* Return the absolute (positive) degree of violation or zero if the constraint is fulfilled.
* The penalty factor is included here.
*/
public double getViolation(double[] indyX) {
double viol = getRawViolationValue(indyX);
return getViolationConsideringRelation(viol);
}
/**
* Check whether the given individual violates the constraint and immediately add
* the violation if it is the case. Expect that the fitness has already been set.
* This regards the handling strategy and adds the violation to the fitness (in each dimension) or
* sets the individual constraint violation.
*
* @param indy the individual to check for constraint violation.
*/
public void addViolation(AbstractEAIndividual indy, double[] indyX) {
double v = getViolation(indyX);
switch (handling) {
case penaltyAdditive:
if (v>0) {
indy.SetMarkPenalized(true);
for (int i=0; i<indy.getFitness().length; i++) {
indy.SetFitness(i, indy.getFitness(i)+v+penaltyFactor);
}
}
break;
case penaltyMultiplicative:
if (v>0) {
indy.SetMarkPenalized(true);
for (int i=0; i<indy.getFitness().length; i++) {
indy.SetFitness(i, indy.getFitness(i)*(1+v));
}
}
case specificTag:
if (v>0) indy.addConstraintViolation(v);
break;
}
}
private double getViolationConsideringRelation(double val) {
// System.out.println("Penalty is " + penaltyFactor);
val *= penaltyFactor;
switch (relation) {
// case linearLessEqZero:
case lessEqZero:
return (val <= 0.) ? 0 : val;
case eqZero:
val = Math.abs(val);
if (val<=equalityEpsilon) return 0.;
else return val;
case greaterEqZero:
return (val >= 0.) ? 0. : -val;
}
System.err.println("Unknown relation!");
return 0.;
}
public boolean isViolated(double[] pos) {
return (getViolation(pos)>0);
}
public boolean isSatisfied(double[] pos) {
return (getViolation(pos)==0.);
}
public ConstraintRelationEnum getRelation() {
return relation;
}
public void setRelation(ConstraintRelationEnum relation) {
this.relation = relation;
GenericObjectEditor.setShowProperty(this.getClass(), "equalityEpsilon", relation==ConstraintRelationEnum.eqZero);
}
public ParamAdaption getPenaltyFactControl() {
return paramCtrl.getSingleAdapters()[0];
}
public void setPenaltyFactControl(ParamAdaption penaltyAdaption) {
// this.penaltyFactAdaption = penaltyFact;
if (!(penaltyAdaption instanceof NoParamAdaption)) {
if (penaltyAdaption instanceof GenericParamAdaption) {
((GenericParamAdaption)penaltyAdaption).setControlledParam(penaltyPropName);
} else {
if (!penaltyPropName.equals(penaltyAdaption.getControlledParam())) System.err.println("Warning: penalty factor control may have different target");
}
}
paramCtrl.setSingleAdapters(new ParamAdaption[]{penaltyAdaption});
}
public String penaltyFactControlTipText() {
return "Adaptive penalty may used. For generic adaption mechanisms, the target string will be set automatically.";
}
public double getPenaltyFactor() {
return penaltyFactor;
}
public void setPenaltyFactor(double penaltyFactor) {
if (penaltyFactor<0) {
EVAERROR.errorMsgOnce("Error: a negative penalty factor is not allowed!");
} else this.penaltyFactor = penaltyFactor;
}
public String penaltyFactorTipText() {
return "Penalty factor by which a constraint violation is multiplied.";
}
public ConstraintHandlingEnum getHandlingMethod() {
return handling;
}
public void setHandlingMethod(ConstraintHandlingEnum handling) {
this.handling = handling;
}
public String handlingMethodTipText() {
return "Select the method the constraint is handled.";
}
public double getEqualityEpsilon() {
return equalityEpsilon;
}
public void setEqualityEpsilon(double equalityEpsilon) {
this.equalityEpsilon = equalityEpsilon;
}
public String equalityEpsilonTipText() {
return "The threshold below which equality constraints are said to be satisfied.";
}
}

75
src/eva2/server/go/operators/constraint/ConstraintCollection.java Normal file
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@@ -0,0 +1,75 @@
package eva2.server.go.operators.constraint;
import eva2.server.go.individuals.AbstractEAIndividual;
/**
* To handle a set of constraints with a single parameter adaption mechanism.
* Single constraints are
*
* @author mkron
*
*/
public class ConstraintCollection extends AbstractConstraint {
private AbstractConstraint[] constraintArray = new AbstractConstraint[]{};
public ConstraintCollection() {
super();
constraintArray = new AbstractConstraint[]{};
}
public ConstraintCollection(AbstractConstraint[] constrArr) {
super();
constraintArray = constrArr;
}
public ConstraintCollection(AbstractConstraint[] constrArr, ConstraintHandlingEnum handling, double penaltyFact) {
this(constrArr);
setHandlingMethod(handling);
setPenaltyFactor(penaltyFact);
}
public ConstraintCollection(ConstraintCollection o) {
super(o);
constraintArray = o.constraintArray.clone();
for (int i=0; i<constraintArray.length; i++) {
constraintArray[i]=(AbstractConstraint)o.constraintArray[i].clone();
}
}
@Override
public Object clone() {
return new ConstraintCollection(this);
}
@Override
protected double getRawViolationValue(double[] indyX) {
double v, sum=0;
if (TRACE) System.out.println("Viol (pen "+getPenaltyFactor()+")");
for (AbstractConstraint constr : constraintArray) {
v=constr.getViolation(indyX);
sum += v;
if (TRACE) System.out.println(constr.getClass().getSimpleName() + " " + v);
}
return sum;
}
public AbstractConstraint[] getConstraints() {
return constraintArray;
}
public void setConstraints(AbstractConstraint[] constrArray) {
this.constraintArray = constrArray;
}
public String constraintsTipText() {
return "A set of constraints which is handled uniformly";
}
public String getName() {
return constraintArray.length + " constr./" + getPenaltyFactor() + "/" + getHandlingMethod() + "/" + getPenaltyFactControl().getClass().getSimpleName();
}
public String globalInfo() {
return "A set of constraints with a single parameter adaption mechanism.";
}
}

5
src/eva2/server/go/operators/constraint/ConstraintHandlingEnum.java Normal file
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@@ -0,0 +1,5 @@
package eva2.server.go.operators.constraint;
public enum ConstraintHandlingEnum {
specificTag, penaltyAdditive, penaltyMultiplicative;
}

5
src/eva2/server/go/operators/constraint/ConstraintRelationEnum.java Normal file
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@@ -0,0 +1,5 @@
package eva2.server.go.operators.constraint;
public enum ConstraintRelationEnum {
lessEqZero, eqZero, greaterEqZero;//, linearLessEqZero;
}

30
src/eva2/server/go/operators/constraint/DummyConstraint.java Normal file
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@@ -0,0 +1,30 @@
package eva2.server.go.operators.constraint;
import eva2.gui.GenericObjectEditor;
import eva2.server.go.individuals.AbstractEAIndividual;
/**
* This constraint is always satisfied.
* @author mkron
*
*/
public class DummyConstraint extends AbstractConstraint {
@Override
public Object clone() {
return new DummyConstraint();
}
public void hideHideable() {
GenericObjectEditor.setHideAllProperties(this.getClass(), true);
}
@Override
protected double getRawViolationValue(double[] indyX) {
return 0;
}
public String globalInfo() {
return "This constraint is always fulfilled.";
}
}

109
src/eva2/server/go/operators/constraint/GenericConstraint.java Normal file
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@@ -0,0 +1,109 @@
package eva2.server.go.operators.constraint;
import java.io.Serializable;
import eva2.server.go.individuals.AbstractEAIndividual;
import eva2.server.go.individuals.codings.gp.AbstractGPNode;
import eva2.server.go.problems.GPFunctionProblem;
import eva2.tools.EVAERROR;
/**
* A generic constraint is defined by a String describing a function of the x0...xn values of potential solutions.
* The function String is parsed to a GP function tree using AbstractGPNode and GPFunctionProblem.
*
* @author mkron
*
*/
public class GenericConstraint extends AbstractConstraint implements InterfaceDoubleConstraint, Serializable {
private String constraintString="+(x0,x1)";
private transient AbstractGPNode constraintProgram = null;
GPFunctionProblem func = null;
public GenericConstraint() {
super();
constraintProgram = null;
// compileConstraint(constraintString);
}
public GenericConstraint(String str) {
this();
setConstraintString(str);
compileConstraint();
}
public GenericConstraint(String str, ConstraintRelationEnum relation) {
this(str);
setRelation(relation);
}
public GenericConstraint(GenericConstraint o) {
super(o);
constraintString = o.constraintString;
constraintProgram = null;
// compileConstraint(constraintString);
}
public Object clone() {
return new GenericConstraint(this);
}
private void compileConstraint() {
func=null;
constraintProgram = AbstractGPNode.parseFromString(constraintString);
if (constraintProgram==null) System.err.println("Error: invalid expression: " + constraintString);
if (TRACE) {
System.out.println("Compiled constraint " + constraintString);
System.out.println("Program: " + constraintProgram.getStringRepresentation());
}
}
/**
* Return true if there is a valid generic function represented within the instance.
* @return
*/
public boolean checkValid() {
if (constraintProgram==null) compileConstraint();
return (constraintProgram!=null);
}
@Override
public double getRawViolationValue(double[] indyX) {
switch (relation) {
case eqZero:
case greaterEqZero:
case lessEqZero:
if (constraintProgram==null) compileConstraint();
if (constraintProgram!=null) {
if (func==null) func = new GPFunctionProblem(constraintProgram, null, indyX.length, 0., 0.);
return func.eval(indyX)[0];
} else return 0.;
// case linearLessEqZero:
// return getViolation(evalLinearConstr(indy));
}
EVAERROR.errorMsgOnce("Error: unknown relation for GenericConstraint!");
return 0.;
}
// private double evalLinearConstr(AbstractEAIndividual indy) {
// // TODO Auto-generated method stub
// return null;
// }
public String getConstraintString() {
return constraintString;
}
public void setConstraintString(String constraintString) {
this.constraintString = constraintString;
constraintProgram = null;
if (TRACE) System.out.println(" NEW CONSTRAINT STRING SET! in " + this);
}
public String getName() {
return this.getClass().getSimpleName() + " " + constraintString;
}
public String globalInfo() {
return "A generic constraint which is parsed from a String; n is dimension, x0..xn are solution components. Use prefix notation as in \"+(-(sum(x),n),sqrt(*(pi,x0)))\".";
}
}

54
src/eva2/server/go/operators/constraint/ImplicitConstraint.java Normal file
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@@ -0,0 +1,54 @@
package eva2.server.go.operators.constraint;
/**
* A constraint that is already calculated by the fitness function as an
* independent criterion. This class can be used to transform it into
* a fitness penalty.
*
* @author mkron
*
*/
public class ImplicitConstraint extends AbstractConstraint {
int index=0;
public ImplicitConstraint() {}
public ImplicitConstraint(int cIndex) {
index=cIndex;
}
@Override
public Object clone() {
return new ImplicitConstraint(index);
}
@Override
protected double getRawViolationValue(double[] indyX) {
if (index<0 || index>=indyX.length) {
System.err.println("Error in ImplicitConstraint!");
return 0.;
}
return indyX[index];
}
public String getName() {
return "ImplicitCnstr-"+index;
}
public String globalInfo() {
return "Similar to a multi-objective translation into fitness, this class allows to interpret fitness criteria as constraints.";
}
public int getIndex() {
return index;
}
public void setIndex(int index) {
if (index>0) this.index = index;
else System.err.println("Error, invalid index (<=0) in ImplicitConstraint.");
}
public String indexTipText() {
return "Set the index of the fitness criterion to be translated into a constraint, must be > 0";
}
}

33
src/eva2/server/go/operators/constraint/InterfaceDoubleConstraint.java Normal file
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@@ -0,0 +1,33 @@
package eva2.server.go.operators.constraint;
import eva2.server.go.individuals.AbstractEAIndividual;
/**
* A constraint delivering a double valued degree of violation.
*/
public interface InterfaceDoubleConstraint {
/**
* This method allows you to make a deep clone of
* the object
* @return the deep clone
*/
public Object clone();
/**
* Returns the boolean information whether the constraint is satisfied.
*
* @param indy
* @return
*/
public boolean isSatisfied(double[] indyX);
/**
* Return the absolute (positive) degree of violation or zero if the constraint
* is fulfilled.
*
* @param indy The individual to check.
* @param indyX possibly the decoded individual position
* @return true if valid false else.
*/
public double getViolation(double[] indyX);
}

123
src/eva2/server/go/operators/constraint/IntervalConstraint.java Normal file
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@@ -0,0 +1,123 @@
package eva2.server.go.operators.constraint;
import java.io.Serializable;
import eva2.gui.GenericObjectEditor;
import eva2.server.go.individuals.AbstractEAIndividual;
import eva2.tools.EVAERROR;
import eva2.tools.Mathematics;
/**
* A constraint for a parameter or a generic function to lie within certain bounds.
* @author mkron
*
*/
public class IntervalConstraint extends AbstractConstraint implements InterfaceDoubleConstraint, Serializable{
double lower=0;
double upper=1;
int index = 0;
GenericConstraint genericConstr = null;
public IntervalConstraint() {
this(0,0.,1.);
genericConstr = null;
}
public void hideHideable() {
GenericObjectEditor.setHideProperty(this.getClass(), "relation", true);
}
public IntervalConstraint(int index, double lowerBnd, double upperBnd) {
this.index=index;
this.lower=lowerBnd;
this.upper=upperBnd;
setRelation(ConstraintRelationEnum.lessEqZero);
genericConstr = null;
}
public IntervalConstraint(String genericFunctionString, double lowerBnd, double upperBnd) {
this(0, lowerBnd, upperBnd);
setGenericFunction(genericFunctionString);
}
public IntervalConstraint(IntervalConstraint o) {
this(o.index, o.lower, o.upper);
genericConstr = o.genericConstr;
}
@Override
public Object clone() {
return new IntervalConstraint(this);
}
@Override
protected double getRawViolationValue(double[] indyX) {
if (genericConstr!=null) {
double constrFuncValue = genericConstr.getRawViolationValue(indyX);
return distanceToInterval(constrFuncValue);
} else {
if (index<0) {
double violSum=0;
for (int i=0;i<indyX.length; i++) {
violSum += violInDim(i, indyX);
}
return violSum;
} else {
if (index>=indyX.length) {
EVAERROR.errorMsgOnce("Error, invalid index for " + this.getClass().getSimpleName());
return 0.;
} else {
return violInDim(index, indyX);
}
}
}
}
public String getName() {
String clsName=this.getClass().getSimpleName();
if (genericConstr!=null) return clsName+"/"+genericConstr.getConstraintString()+ " in ["+lower+","+upper+"]";
else {
if (index<0) return clsName+"/x_i in ["+lower+","+upper+"]";
else return clsName+"/x_" + index + " in ["+lower+","+upper+"]";
}
}
/**
* Return zero if the position respects the range, else the positive distance.
*
* @param i
* @param pos
* @return
*/
private double violInDim(int i, double[] pos) {
return distanceToInterval(pos[i]);
}
/**
* Return zero if the position respects the range, else the positive distance.
*
* @param i
* @param pos
* @return
*/
private double distanceToInterval(double v) {
double tmp=Mathematics.projectValue(v, lower, upper);
return Math.abs(tmp-v);
}
public void setGenericFunction(String str) {
if (str!=null && (str.length()>0)) {
genericConstr = new GenericConstraint(str);
if (!genericConstr.checkValid()) genericConstr=null;
} else genericConstr=null;
}
public String getGenericFunction() {
if (genericConstr==null) return "";
else return genericConstr.getConstraintString();
}
public String genericConstrTipText() {
return "A generic function can be used as in GenericConstraint - it has priority.";
}
}

34
src/eva2/server/go/operators/paramcontrol/NoParamAdaption.java Normal file
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@@ -0,0 +1,34 @@
package eva2.server.go.operators.paramcontrol;
import java.io.Serializable;
import eva2.server.go.populations.Population;
/**
* A dummy implementation which does not do any adaption.
*
* @author mkron
*
*/
public class NoParamAdaption implements ParamAdaption, Serializable {
public Object clone() {
return new NoParamAdaption();
}
public Object calcValue(Object obj, Population pop, int iteration, int maxIteration) {
return null;
}
public String getControlledParam() {
return null;
}
public String globalInfo() {
return "A dummy implementation which will not change parameters.";
}
public void finish(Object obj, Population pop) {}
public void init(Object obj, Population pop, Object[] initialValues) {}
}

33
src/eva2/server/go/problems/AbstractOptimizationProblem.java
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@@ -1,6 +1,7 @@
package eva2.server.go.problems;
import java.awt.BorderLayout;
import java.io.Serializable;
import javax.swing.JComponent;
import javax.swing.JPanel;
@@ -32,9 +33,9 @@ import eva2.tools.Mathematics;
* Time: 13:40:12
* To change this template use Options | File Templates.
*/
public abstract class AbstractOptimizationProblem implements InterfaceOptimizationProblem, java.io.Serializable {
public abstract class AbstractOptimizationProblem implements InterfaceOptimizationProblem /*, InterfaceParamControllable*/, Serializable {
protected AbstractEAIndividual m_Template;
// private transient ArrayList<ParamChangeListener> changeListeners = null;
/** This method returns a deep clone of the problem.
* @return the clone
@@ -61,8 +62,10 @@ public abstract class AbstractOptimizationProblem implements InterfaceOptimizati
evaluatePopulationStart(population);
for (int i = 0; i < population.size(); i++) {
tmpIndy = (AbstractEAIndividual) population.get(i);
tmpIndy.resetConstraintViolation();
this.evaluate(tmpIndy);
synchronized (tmpIndy) {
tmpIndy.resetConstraintViolation();
this.evaluate(tmpIndy);
}
population.incrFunctionCalls();
}
evaluatePopulationEnd(population);
@@ -335,6 +338,28 @@ public abstract class AbstractOptimizationProblem implements InterfaceOptimizati
else return false;
}
// /**********************************************************************************************************************
// * These are for InterfaceParamControllable
// */
// public Object[] getParamControl() {
// return null;
// }
//
// public void notifyParamChanged(String member, Object oldVal, Object newVal) {
// if (changeListeners != null) for (ParamChangeListener l : changeListeners) {
// l.notifyChange(this, oldVal, newVal, null);
// }
// }
//
// public void addChangeListener(ParamChangeListener l) {
// if (changeListeners==null) changeListeners = new ArrayList<ParamChangeListener>();
// if (!changeListeners.contains(l)) changeListeners.add(l);
// }
//
// public void removeChangeListener(ParamChangeListener l) {
// if (changeListeners!=null) changeListeners.remove(l);
// }
/**********************************************************************************************************************
* These are for GUI
*/

120
src/eva2/server/go/problems/AbstractProblemDouble.java
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@@ -1,12 +1,16 @@
package eva2.server.go.problems;
import wsi.ra.math.RNG;
import eva2.gui.GenericObjectEditor;
import eva2.server.go.PopulationInterface;
import eva2.server.go.individuals.AbstractEAIndividual;
import eva2.server.go.individuals.ESIndividualDoubleData;
import eva2.server.go.individuals.InterfaceDataTypeDouble;
import eva2.server.go.operators.constraint.AbstractConstraint;
import eva2.server.go.operators.constraint.GenericConstraint;
import eva2.server.go.populations.Population;
import eva2.server.go.strategies.InterfaceOptimizer;
import wsi.ra.math.RNG;
import eva2.server.go.problems.Interface2DBorderProblem;
import eva2.tools.Pair;
/**
* For a double valued problem, there are two main methods to implement: {@link #getProblemDimension()}
@@ -29,17 +33,21 @@ import eva2.server.go.problems.Interface2DBorderProblem;
* @author mkron
*
*/
public abstract class AbstractProblemDouble extends AbstractOptimizationProblem implements InterfaceProblemDouble, Interface2DBorderProblem {
public abstract class AbstractProblemDouble extends AbstractOptimizationProblem implements InterfaceProblemDouble, Interface2DBorderProblem/*, InterfaceParamControllable */{
private double m_DefaultRange = 10;
private double m_Noise = 0;
// PropertySelectableList<AbstractConstraint> constraintList = new PropertySelectableList<AbstractConstraint>(new AbstractConstraint[]{new GenericConstraint()});
private AbstractConstraint[] constraintArray = new AbstractConstraint[]{new GenericConstraint()};
private boolean withConstraints = false;
public AbstractProblemDouble() {
initTemplate();
}
// public AbstractProblemDouble(AbstractProblemDouble o) {
// cloneObjects(o);
// }
public AbstractProblemDouble(AbstractProblemDouble o) {
cloneObjects(o);
}
protected void initTemplate() {
if (m_Template == null) m_Template = new ESIndividualDoubleData();
@@ -49,16 +57,25 @@ public abstract class AbstractProblemDouble extends AbstractOptimizationProblem
}
}
public void hideHideable() {}
public void hideHideable() {
setWithConstraints(isWithConstraints());
}
protected void cloneObjects(AbstractProblemDouble o) {
this.m_DefaultRange = o.m_DefaultRange;
this.m_Noise = o.m_Noise;
if (o.m_Template != null) this.m_Template = (AbstractEAIndividual)o.m_Template.clone();
if (o.constraintArray!=null) {
this.constraintArray=o.constraintArray.clone();
for (int i=0; i<constraintArray.length; i++) constraintArray[i]=(AbstractConstraint)o.constraintArray[i].clone();
}
this.withConstraints=o.withConstraints;
}
/**
* Retrieve and copy the double solution representation from an individual.
* Retrieve and copy the double solution representation from an individual. This
* may also perform a coding adaption. The result is stored as phenotype within
* the evaluate method.
*
* @param individual
* @return the double solution representation
@@ -80,14 +97,31 @@ public abstract class AbstractProblemDouble extends AbstractOptimizationProblem
double[] fitness;
x = getEvalArray(individual);
((InterfaceDataTypeDouble)individual).SetDoublePhenotype(x);
// evaluate the vector
fitness = this.eval(x);
// if indicated, add Gaussian noise
if (m_Noise != 0) RNG.addNoise(fitness, m_Noise);
// set the fitness
setEvalFitness(individual, x, fitness);
if (isWithConstraints()) addConstraints(individual, x);
}
/**
* Add all constraint violations to the individual. Expect that the fitness has already been set.
*
* @param individual
* @param indyPos may contain the decoded individual position
*/
protected void addConstraints(AbstractEAIndividual individual, double[] indyPos) {
AbstractConstraint[] cnstr = getConstraints();
for (int i=0; i<cnstr.length; i++) {
// String name= (String)BeanInspector.callIfAvailable(cnstr[i], "getName", new Object[]{});
// System.out.println("checking constraint " + (name==null ? cnstr[i].getClass().getSimpleName() : name));
((AbstractConstraint)cnstr[i]).addViolation(individual, indyPos);
}
}
/**
* Write a fitness value back to an individual. May be overridden to add constraints.
*
@@ -237,8 +271,16 @@ public abstract class AbstractProblemDouble extends AbstractOptimizationProblem
public String defaultRangeTipText() {
return "Absolute limit for the symmetric range in any dimension";
}
/**********************************************************************************************************************
* These are for InterfaceParamControllable
*/
public Object[] getParamControl() {
if (isWithConstraints()) {
return constraintArray;
// return constraintList.getObjects();
} else return null;
}
/**********************************************************************************************************************
* These are for Interface2DBorderProblem
*/
@@ -290,4 +332,64 @@ public abstract class AbstractProblemDouble extends AbstractOptimizationProblem
sb.append(this.m_Noise);
return sb.toString();
}
// public PropertySelectableList<AbstractConstraint> getConstraints() {
// return constraintList;
// }
//
// public void setConstraints(PropertySelectableList<AbstractConstraint> constraintArray) {
// this.constraintList = constraintArray;
// }
public AbstractConstraint[] getConstraints() {
return constraintArray;
}
public void setConstraints(AbstractConstraint[] constrArray) {
this.constraintArray = constrArray;
}
public String constraintsTipText() {
return "Add constraints to the problem.";
}
public boolean isWithConstraints() {
return withConstraints;
}
public void setWithConstraints(boolean withConstraints) {
this.withConstraints = withConstraints;
GenericObjectEditor.setShowProperty(this.getClass(), "constraints", withConstraints);
}
public String withConstraintsTipText() {
return "(De-)Activate constraints for the problem.";
}
@Override
public String getAdditionalFileStringHeader(PopulationInterface pop) {
String superHeader = super.getAdditionalFileStringHeader(pop);
if (isWithConstraints()) return superHeader + " \tNum.Viol. \t Sum.Viol.";
else return superHeader;
}
@Override
public String getAdditionalFileStringValue(PopulationInterface pop) {
String superVal = super.getAdditionalFileStringValue(pop);
if (isWithConstraints()) {
Pair<Integer,Double> violation= getConstraintViolation((AbstractEAIndividual)pop.getBestIndividual());
return superVal + " \t" + violation.head() + " \t" + violation.tail();
} else return superVal;
}
protected Pair<Integer,Double> getConstraintViolation(AbstractEAIndividual indy) {
double sum=0;
int numViol=0;
for (AbstractConstraint constr : constraintArray) {
double v= constr.getViolation(getEvalArray(indy));
if (v>0) numViol++;
sum += v;
}
return new Pair<Integer,Double>(numViol, sum);
}
}

83
src/eva2/server/go/problems/ConstrHimmelblauProblem.java Normal file
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@@ -0,0 +1,83 @@
package eva2.server.go.problems;
import java.io.Serializable;
import java.util.Vector;
import eva2.server.go.operators.constraint.AbstractConstraint;
import eva2.server.go.operators.constraint.ConstraintCollection;
import eva2.server.go.operators.constraint.IntervalConstraint;
public class ConstrHimmelblauProblem extends AbstractProblemDouble implements Serializable {
private static double yOffset = 31025.5602425; // moving the optimum close to zero
private boolean useYOffset = true;
public ConstrHimmelblauProblem() {
setWithConstraints(true);
setDefaultRange(100);
setConstraints(new AbstractConstraint[]{new ConstraintCollection(makeDefaultConstraints())});
}
public ConstrHimmelblauProblem(
ConstrHimmelblauProblem o) {
super();
super.cloneObjects(o);
useYOffset=o.useYOffset;
}
@Override
public Object clone() {
return new ConstrHimmelblauProblem(this);
}
// @Override
// public void initProblem() {
// super.initProblem();
// setConstraints(new AbstractConstraint[]{new ConstraintCollection(makeDefaultConstraints())});
// }
public static AbstractConstraint[] makeDefaultConstraints() {
Vector<AbstractConstraint> constraints = new Vector<AbstractConstraint>();
constraints.add(new IntervalConstraint("+(+(85.334407,*(0.0056858,*(x1,x4))), +(*(0.00026,*(x0,x3)),*(-0.0022053,*(x2,x4))))", 0, 92));
constraints.add(new IntervalConstraint("+(+(80.51249,*(0.0071317,*(x1,x4))), +(*(0.0029955,*(x0,x1)),*(0.0021813,*(x2,x2))))", 90, 110));
constraints.add(new IntervalConstraint("+(+(9.300961,*(0.0047026,*(x2,x4))), +(*(0.0012547,*(x0,x2)),*(0.0019085,*(x2,x3))))", 20, 25));
constraints.add(new IntervalConstraint(0, 78, 102));
constraints.add(new IntervalConstraint(1, 33, 45));
constraints.add(new IntervalConstraint(2, 27, 45));
constraints.add(new IntervalConstraint(3, 27, 45));
constraints.add(new IntervalConstraint(4, 27, 45));
return constraints.toArray(new AbstractConstraint[constraints.size()]);
}
@Override
public double[] eval(double[] x) {
double v=5.3578547*x[2]*x[2]+0.8356891*x[0]*x[4]+37.293239*x[0]-40792.141;
if (useYOffset) v+=yOffset;
return new double[]{v};
}
@Override
public int getProblemDimension() {
return 5;
}
public String getName() {
return "Constrained Himmelblau Problem";
}
public String globalInfo() {
return "Himmelblau's nonlinear optimization problem with 5 simple boundary constraints and 3 nonlinear boundary constraints.";
}
public boolean isUseYOffset() {
return useYOffset;
}
public void setUseYOffset(boolean useYOffset) {
this.useYOffset = useYOffset;
}
public String useYOffsetTipText() {
return "Activate offset moving the optimum (close) to zero.";
}
}

142
src/eva2/server/go/problems/ConstrPressureVessel.java Normal file
View File

@@ -0,0 +1,142 @@
package eva2.server.go.problems;
import java.util.Iterator;
import java.util.Vector;
import eva2.gui.GenericObjectEditor;
import eva2.server.go.individuals.AbstractEAIndividual;
import eva2.server.go.operators.constraint.AbstractConstraint;
import eva2.server.go.operators.constraint.ConstraintCollection;
import eva2.server.go.operators.constraint.ConstraintHandlingEnum;
import eva2.server.go.operators.constraint.ConstraintRelationEnum;
import eva2.server.go.operators.constraint.GenericConstraint;
public class ConstrPressureVessel extends AbstractProblemDouble {
private boolean discreteThickness = true;
private double minThickness=0.0625;
private double maxThickness=2;
private double minRad=10, maxRad=300;
private double minLen=10, maxLen=300;
// L=200;
// R=40.3239;
// thickS=0.8125;
// thickH=0.4375;
public ConstrPressureVessel() {
setWithConstraints(true);
setConstraints(new AbstractConstraint[]{new ConstraintCollection(makeDefaultConstraints(), ConstraintHandlingEnum.penaltyAdditive, 1000)});
// setConstraints(makeDefaultConstraints());
}
public ConstrPressureVessel(ConstrPressureVessel o) {
super();
super.cloneObjects(o);
}
public static AbstractConstraint[] makeDefaultConstraints() {
Vector<AbstractConstraint> constraints = new Vector<AbstractConstraint>();
// constraints.add(new IntervalConstraint("+(+(85.334407,*(0.0056858,*(x1,x4))), +(*(0.00026,*(x0,x3)),*(-0.0022053,*(x2,x4))))", 0, 92));
constraints.add(new GenericConstraint("-(*(0.0193,x2),x0)", ConstraintRelationEnum.lessEqZero));
constraints.add(new GenericConstraint("-(*(0.00954,x2),x1)", ConstraintRelationEnum.lessEqZero));
constraints.add(new GenericConstraint("-(1296000, +(*(pi, *(pow2(x2),x3)),*(/(4,3),*(pi,pow3(x2))))))", ConstraintRelationEnum.lessEqZero));
constraints.add(new GenericConstraint("-(x3,240)", ConstraintRelationEnum.lessEqZero));
// for (Iterator<AbstractConstraint> iterator = constraints.iterator(); iterator.hasNext();) {
// AbstractConstraint constr = iterator.next();
// constr.setHandlingMethod(ConstraintHandlingEnum.penaltyAdditive);
// constr.setPenaltyFactor(10000);
// }
return constraints.toArray(new AbstractConstraint[constraints.size()]);
}
@Override
protected double[] getEvalArray(AbstractEAIndividual individual) {
double[] x = super.getEvalArray(individual);
if (discreteThickness) {// integer multiple of minimal thickness
int n=(int)(x[0]/minThickness);
x[0]=n*minThickness;
n=(int)(x[1]/minThickness);
x[1]=n*minThickness;
}
//double thickS=x[0], thickH=x[1], R=x[2], L=x[3];
// x[0]=0.8125; //thickS=0.8125;
// x[1]=0.4375; //thickH=0.4375;
// x[2]=40.3239; //R=40.3239;
// x[3]=200; //L=200;
return x;
}
@Override
public double[] eval(double[] x) {
double v, thickS=x[0], thickH=x[1], R=x[2], L=x[3];
v = 0.6224*thickS*R*L+1.7781*thickH*R*R+3.1661*thickS*thickS*L+19.84*thickS*thickS*R;
// v = 0.6224*x(0)*x(2)*x(3)+1.7781*x(1)*x(2)*x(2)+3.1661*x(0)*x(0)*x(3)+19.84*x(0)*x(0)*x(2);
return new double[]{v};
}
@Override
public int getProblemDimension() {
return 4;
}
@Override
public Object clone() {
return new ConstrPressureVessel(this);
}
@Override
protected double getRangeLowerBound(int dim) {
switch (dim) {
case 0:
case 1: return minThickness/2;
case 2: return minRad;
case 3: return minLen;
}
System.err.println("Invalid dimension for lower bound (ConstrPressureVessel)");
return 0.;
// if (dim<=1) return minThickness/2;
// else return minLen;
}
@Override
protected double getRangeUpperBound(int dim) {
switch (dim) {
case 0:
case 1: return maxThickness;
case 2: return maxRad;
case 3: return maxLen;
}
System.err.println("Invalid dimension for upper bound (ConstrPressureVessel)");
return 100.;
// if (dim<=1) {
// return maxThickness;
// } else if (dim==2) return maxRad;
// else return maxLen;
}
@Override
public String getName() {
return "Constrained-Pressure-Vessel";
}
@Override
public String globalInfo() {
return "Minimize the material cost of a pressure vessel";
}
@Override
public void hideHideable() {
super.hideHideable();
GenericObjectEditor.setHideProperty(this.getClass(), "defaultRange", true);
}
public boolean isDiscreteThickness() {
return discreteThickness;
}
public void setDiscreteThickness(boolean discreteThickness) {
this.discreteThickness = discreteThickness;
}
}

3
src/eva2/server/go/problems/F13Problem.java
View File

@@ -1,9 +1,6 @@
package eva2.server.go.problems;
import eva2.server.go.individuals.AbstractEAIndividual;
import eva2.server.go.individuals.ESIndividualDoubleData;
import eva2.server.go.individuals.InterfaceDataTypeDouble;
import eva2.server.go.populations.Population;
/**
* Schwefels sine root function (1981) with a minimum at 420.9687^n of value 0.

83
src/eva2/server/go/problems/F1Problem.java
View File

@@ -1,9 +1,7 @@
package eva2.server.go.problems;
import wsi.ra.math.RNG;
import eva2.server.go.individuals.AbstractEAIndividual;
import eva2.server.go.individuals.InterfaceDataTypeDouble;
import eva2.server.go.populations.Population;
import eva2.server.go.operators.constraint.GenericConstraint;
import eva2.server.go.strategies.InterfaceOptimizer;
/**
@@ -23,7 +21,7 @@ public class F1Problem extends AbstractProblemDouble implements Interface2DBorde
protected int m_ProblemDimension = 10;
protected double m_XOffSet = 0.0;
protected double m_YOffSet = 0.0;
protected boolean m_UseTestConstraint = false;
// protected boolean m_UseTestConstraint = false;
public F1Problem() {
super();
@@ -36,7 +34,7 @@ public class F1Problem extends AbstractProblemDouble implements Interface2DBorde
this.m_ProblemDimension = b.m_ProblemDimension;
this.m_XOffSet = b.m_XOffSet;
this.m_YOffSet = b.m_YOffSet;
this.m_UseTestConstraint = b.m_UseTestConstraint;
// this.m_UseTestConstraint = b.m_UseTestConstraint;
}
public F1Problem(int dim) {
@@ -55,32 +53,7 @@ public class F1Problem extends AbstractProblemDouble implements Interface2DBorde
public Object clone() {
return (Object) new F1Problem(this);
}
// @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);
// if (tmpIndy instanceof InterfaceDataTypeDouble) {
// double[] v = ((InterfaceDataTypeDouble)tmpIndy).getDoubleData();
// for (int j=0; j<v.length; j++) {
// v[j] = 3; //getDefaultRange() * ((j % 2 == 0) ? 1 : 1);
// v[j]+=RNG.gaussianDouble(.2);
// }
// ((InterfaceDataTypeDouble)tmpIndy).SetDoubleGenotype(v);
// }
//
// population.add(tmpIndy);
// }
// // population init must be last
// // it set's fitcalls and generation to zero
// population.init();
// }
/** This method inits the Problem to log multiruns
*/
public void initProblem() {
@@ -88,32 +61,16 @@ public class F1Problem extends AbstractProblemDouble implements Interface2DBorde
initTemplate();
}
protected double[] getEvalArray(AbstractEAIndividual individual){
double[] x = super.getEvalArray(individual);
// add an offset in solution space
for (int i = 0; i < x.length; i++) x[i] = x[i] - this.m_XOffSet;
return x;
}
protected void setEvalFitness(AbstractEAIndividual individual, double[] x, double[] fit) {
super.setEvalFitness(individual, x, fit);
if (this.m_UseTestConstraint) {
if (x[0] < 1) individual.addConstraintViolation(1-x[0]);
}
// if ((this.m_OverallBest == null) || (this.m_OverallBest.getFitness(0) > individual.getFitness(0))) {
// this.m_OverallBest = (AbstractEAIndividual)individual.clone();
// }
}
/** Ths method allows you to evaluate a simple bit string to determine the fitness
* @param x The n-dimensional input vector
* @return The m-dimensional output vector.
*/
public double[] eval(double[] x) {
double[] result = new double[1];
result[0] = 0;
result[0] = m_YOffSet;
// add an offset in solution space
for (int i = 0; i < x.length; i++) {
result[0] += Math.pow(x[i], 2);
result[0] += Math.pow(x[i] - this.m_XOffSet, 2);
}
return result;
}
@@ -189,18 +146,18 @@ public class F1Problem extends AbstractProblemDouble implements Interface2DBorde
return this.m_ProblemDimension;
}
public String problemDimensionTipText() {
return "Length of the x vector at is to be optimized.";
}
/** This method allows you to toggle the application of a simple test constraint.
* @param b The mode for the test constraint
*/
public void setUseTestConstraint(boolean b) {
this.m_UseTestConstraint = b;
}
public boolean getUseTestConstraint() {
return this.m_UseTestConstraint;
}
public String useTestConstraintTipText() {
return "Just a simple test constraint of x[0] >= 1.";
return "Length of the x vector to be optimized.";
}
// /** This method allows you to toggle the application of a simple test constraint.
// * @param b The mode for the test constraint
// */
// public void setUseTestConstraint(boolean b) {
// this.m_UseTestConstraint = b;
// }
// public boolean getUseTestConstraint() {
// return this.m_UseTestConstraint;
// }
// public String useTestConstraintTipText() {
// return "Just a simple test constraint of x[0] >= 1.";
// }
}

29
src/eva2/server/go/problems/F7Problem.java
View File

@@ -65,40 +65,13 @@ public class F7Problem extends F1Problem implements java.io.Serializable {
evaluatePopulationEnd(population);
}
/** This method evaluate a single individual and sets the fitness values
* @param individual The individual that is to be evalutated
*/
public void evaluate(AbstractEAIndividual individual) {
double[] x;
double[] fitness;
x = new double[((InterfaceDataTypeDouble) individual).getDoubleData().length];
System.arraycopy(((InterfaceDataTypeDouble) individual).getDoubleData(), 0, x, 0, x.length);
for (int i = 0; i < x.length; i++) x[i] = x[i] - this.m_XOffSet;
fitness = this.eval(x);
for (int i = 0; i < fitness.length; i++) {
// add noise to the fitness
fitness[i] += RNG.gaussianDouble(this.getNoise());
fitness[i] += this.m_YOffSet;
// set the fitness of the individual
individual.SetFitness(i, fitness[i]);
}
if (this.m_UseTestConstraint) {
if (x[0] < 1) individual.addConstraintViolation(1-x[0]);
}
// if ((this.m_OverallBest == null) || (this.m_OverallBest.getFitness(0) > individual.getFitness(0))) {
// this.m_OverallBest = (AbstractEAIndividual)individual.clone();
// }
}
/** Ths method allows you to evaluate a double[] to determine the fitness
* @param x The n-dimensional input vector
* @return The m-dimensional output vector.
*/
public double[] eval(double[] x) {
double[] result = new double[1];
result[0] = 0;
result[0] = m_YOffSet;
if ((Math.floor(this.m_CurrentTimeStamp / this.m_t)%2) == 0) {
for (int i = 0; i < x.length-1; i++) {
result[0] += Math.pow(x[i], 2);

139
src/eva2/server/go/problems/GPFunctionProblem.java Normal file
View File

@@ -0,0 +1,139 @@
package eva2.server.go.problems;
import eva2.server.go.individuals.ESIndividualDoubleData;
import eva2.server.go.individuals.codings.gp.GPArea;
import eva2.server.go.individuals.codings.gp.InterfaceProgram;
import eva2.server.go.strategies.InterfaceOptimizer;
import eva2.tools.EVAERROR;
/**
* A helper problem class which takes a GP program as argument and serves as target function
* for evaluating the GP function in optimization. A scaling option is implemented to flatten the
* function by scaling it logarithmically. This avoids ugly functions in GP. To activate scaling,
* set the scStart and scLimit parameters to positive values. Function values y with |y|>scStart
* will be rescaled to values below scLimit.
*
* @author mkron
*
*/
public class GPFunctionProblem extends AbstractProblemDouble implements InterfaceProgramProblem {
InterfaceProgram gpProblem = null;
GPArea gpArea = new GPArea();
double[] pos = null;
int dim = 2;
double scalingStart=10.;
double scalingLimit=20.;
public static boolean hideFromGOE = true;
/**
* Initialize a default GP function problem in 2D with scaling.
* @param gpProb
* @param area
*/
public GPFunctionProblem(InterfaceProgram gpProb, GPArea area) {
this(gpProb, area, 0., 0.);
}
/**
* By default, a 2-D problem is initialized with given scaling bounds. Set the scaling limit to 0 to
* deactivate scaling.
*
* @param gpProb
* @param area
* @param scStart
* @param scLim
*/
public GPFunctionProblem(InterfaceProgram gpProb, GPArea area, double scStart, double scLim) {
this(gpProb, area, 2, scStart, scLim);
}
/**
* A GP function problem is initialized with given scaling bounds. Set the scaling limit to 0 to
* deactivate scaling.
*
* @param gpProb
* @param area
* @param scStart
* @param scLim
*/
public GPFunctionProblem(InterfaceProgram gpProb, GPArea area, int pDim, double scStart, double scLim) {
dim = pDim;
((ESIndividualDoubleData)m_Template).setDoubleDataLength(dim);
gpProblem = gpProb;
gpArea = area;
scalingStart=scStart;
scalingLimit=scLim;
}
public GPFunctionProblem(GPFunctionProblem functionProblem) {
dim = functionProblem.dim;
if (functionProblem.pos != null) {
pos = new double[dim];
System.arraycopy(functionProblem.pos, 0, pos, 0, dim);
}
gpArea = (GPArea) functionProblem.gpArea.clone();
gpProblem = functionProblem.gpProblem;
}
@Override
public Object clone() {
return new GPFunctionProblem(this);
}
@Override
public double[] eval(double[] x) {
if (x.length != dim) EVAERROR.errorMsgOnce("mismatching dimension of GPFunctionProblem!");
pos = x;
Double res = (Double) gpProblem.evaluate(this);
double[] fit = new double[1];
fit[0] = scaleFit(res.doubleValue());
return fit;
}
/**
* Scale the allover fitness value.
*
* @param doubleValue
* @return
*/
public double scaleFit(double v) {
if (scalingLimit==0.) return v;
else {
double aV = Math.abs(v);
if (aV > scalingStart) {
double logVal=Math.log(aV)/Math.log(scalingStart);
double tmp=1./(logVal);
return (scalingLimit - tmp)*Math.signum(v);
} else return v;
}
}
// public static void main(String[] args) {
// for (double x=1.; x<100000000; x*=10.) {
// System.out.println("x: " + -x + " sc: " + scaleFit(-x));
// }
// }
@Override
public int getProblemDimension() {
return dim;
}
public String getStringRepresentationForProblem(InterfaceOptimizer opt) {
return "GP find a function problem";
}
public Object getSensorValue(String sensor) {
return PSymbolicRegression.getSensorValue(sensor, pos, null);
}
public void setActuatorValue(String actuator, Object parameter) {
// nothing to do here
}
public GPArea getArea() {
return gpArea;
}
}

12
src/eva2/server/go/problems/PSymbolicRegression.java
View File

@@ -280,6 +280,8 @@ public class PSymbolicRegression extends AbstractOptimizationProblem implements
* This method allows a GP program to sense the environment, e.g.
* input values, current time etc. Specialized to constants and variables
* in arrays whose identifiers have the form "Xi" and "Ci".
* For an identifier X only, the full vars array is returned. For an
* identifier N only, the array dimension is returned.
*
* @param sensor The identifier for the sensor.
* @param vars array of x_i
@@ -288,11 +290,17 @@ public class PSymbolicRegression extends AbstractOptimizationProblem implements
*/
public static Object getSensorValue(String sensor, double[] vars, double[] consts) {
if (sensor.charAt(0)=='X') {
int index=Integer.parseInt(sensor.substring(1));
return new Double(vars[index]);
try {
int index=Integer.parseInt(sensor.substring(1));
return new Double(vars[index]);
} catch(Exception e) {
return vars;
}
} else if (sensor.charAt(0)=='C') {
int index=Integer.parseInt(sensor.substring(1));
return new Double(consts[index]);
} else if (sensor.charAt(0)=='N') {
return (double)vars.length;
} else return new Double(0);
// for (int i = 0; i < this.m_X.length; i++) if (sensor.equalsIgnoreCase("X"+i)) return new Double(this.m_X[i]);
// for (int i = 0; i < this.m_C.length; i++) if (sensor.equalsIgnoreCase("C"+i)) return new Double(this.m_C[i]);

3
src/eva2/server/go/tools/AbstractObjectEditor.java
View File

@@ -245,6 +245,9 @@ public abstract class AbstractObjectEditor implements PropertyEditor, java.beans
return result;
}
}
if (result==null) {
System.err.println("Warning: unknown property or unable to create editor for property " + prop + ", object " + this.getClass().getName());
}
return result;
}

172
src/eva2/server/stat/AbstractStatistics.java
View File

@@ -4,7 +4,9 @@ import java.io.FileOutputStream;
import java.io.PrintWriter;
import java.text.SimpleDateFormat;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Date;
import java.util.Iterator;
import java.util.List;
import eva2.gui.BeanInspector;
@@ -41,6 +43,7 @@ public abstract class AbstractStatistics implements InterfaceTextListener, Inter
private boolean refineMultiRuns = true;
private ArrayList<double[][]> meanCollection;
// say whether the object should be written to a file every time
private boolean saveParams = true;
private boolean firstPlot = true;
@@ -58,14 +61,17 @@ public abstract class AbstractStatistics implements InterfaceTextListener, Inter
protected int optRunsPerformed;
protected double[] currentBestFit;
protected double[] currentBestFeasibleFit;
protected double[] meanBestFeasibleFit;
// protected double[] meanBestFeasibleFit;
protected double[] meanFitness;
protected double[] currentWorstFit;
protected double[] meanBestOfRunFitness;
// protected double[] meanBestOfRunFitness;
protected double avgPopDist;
protected double maxPopDist;
protected IndividualInterface bestCurrentIndividual, bestRunIndividual, bestRunFeasibleIndy, bestIndividualAllover;
protected IndividualInterface bestCurrentIndividual, bestRunIndividual, bestRunFeasibleIndy, bestFeasibleAllover, bestIndividualAllover;
// collect feasible results of a run
private ArrayList<IndividualInterface> runBestFeasibleList;
private ArrayList<IndividualInterface> runBestFitList;
private ArrayList<InterfaceTextListener> textListeners;
@@ -96,7 +102,7 @@ public abstract class AbstractStatistics implements InterfaceTextListener, Inter
SimpleDateFormat formatter = new SimpleDateFormat("E'_'yyyy.MM.dd'_at_'hh.mm.ss");
String startDate = formatter.format(new Date());
// open the result file:
if ((m_StatsParams.getOutputTo().getSelectedTagID()!=1) // not "text only"
if (doFileOutput() // not "text-window only"
&& (m_StatsParams.getOutputVerbosity().getSelectedTagID() > StatsParameter.VERBOSITY_NONE)) { // verbosity accordingly high
//!resFName.equalsIgnoreCase("none") && !resFName.equals("")) {
String fname = makeOutputFileName(m_StatsParams.getResultFilePrefix(), infoString, startDate);
@@ -112,6 +118,10 @@ public abstract class AbstractStatistics implements InterfaceTextListener, Inter
} else resultOut = null;
}
protected boolean doFileOutput() {
return (m_StatsParams.getOutputTo().getSelectedTagID()!=1); // not "text-window only"
}
private String makeOutputFileName(String prefix, String infoString, String startDate) {
return (prefix + "_" + infoString).replace(' ', '_') + "_" + startDate + ".txt";
}
@@ -126,7 +136,11 @@ public abstract class AbstractStatistics implements InterfaceTextListener, Inter
}
public void startOptPerformed(String infoString, int runNumber, Object params) {
if (TRACE) System.out.println("AbstractStatistics.startOptPerformed " + runNumber);
if (TRACE) {
System.out.println("AbstractStatistics.startOptPerformed " + runNumber);
System.out.println("Statsparams were " + BeanInspector.toString(m_StatsParams));
}
if (runNumber == 0) {
functionCallSum = 0;
firstPlot = true;
@@ -135,8 +149,11 @@ public abstract class AbstractStatistics implements InterfaceTextListener, Inter
if (saveParams) m_StatsParams.saveInstance();
initOutput(infoString);
bestIndividualAllover = null;
meanBestOfRunFitness = null;
meanBestFeasibleFit = null;
bestFeasibleAllover = null;
// meanBestOfRunFitness = null;
// meanBestFeasibleFit = null;
runBestFeasibleList = new ArrayList<IndividualInterface>();
runBestFitList = new ArrayList<IndividualInterface>();
if (refineMultiRuns) meanCollection = new ArrayList<double[][]>();
else meanCollection = null;
feasibleFoundAfterSum=-1;
@@ -174,17 +191,14 @@ public abstract class AbstractStatistics implements InterfaceTextListener, Inter
if (Mathematics.norm(bestCurrentIndividual.getFitness()) < this.m_StatsParams.getConvergenceRateThreshold()) {
convergenceCnt++;
}
if (printRunStoppedVerbosity()) printToTextListener(" Last best individual : " + BeanInspector.toString(bestCurrentIndividual) + "\n");
if (printRunStoppedVerbosity()) printToTextListener(" Last solution data : " + AbstractEAIndividual.getDefaultDataString(bestCurrentIndividual) + "\n");
if (printRunStoppedVerbosity()) printToTextListener(" Last solution fit : " + BeanInspector.toString(bestCurrentIndividual.getFitness()) + "\n");
if (printRunStoppedVerbosity()) printIndy("Last best", bestCurrentIndividual);
}
if (bestRunIndividual != null) {
if (printRunStoppedVerbosity()) printToTextListener(" Run best individual : " + BeanInspector.toString(bestRunIndividual) + "\n");
if (printRunStoppedVerbosity()) printToTextListener(" Run solution data : " + AbstractEAIndividual.getDefaultDataString(bestRunIndividual) + "\n");
if (printRunStoppedVerbosity()) printToTextListener(" Run solution fit : " + BeanInspector.toString(bestRunIndividual.getFitness()) + "\n");
if (meanBestOfRunFitness==null) {
meanBestOfRunFitness=bestRunIndividual.getFitness().clone();
} else addMean(meanBestOfRunFitness, bestRunIndividual.getFitness());
runBestFitList.add(bestRunIndividual);
if (printRunStoppedVerbosity()) printIndy("Run best", bestRunIndividual);
// if (meanBestOfRunFitness==null) {
// meanBestOfRunFitness=bestRunIndividual.getFitness().clone();
// } else addSecond(meanBestOfRunFitness, bestRunIndividual.getFitness());
}
if (feasibleFoundAfter>0) {
if (printRunStoppedVerbosity()) printToTextListener(" Feasible ind. found after " + feasibleFoundAfter + " evaluations.\n");
@@ -192,23 +206,21 @@ public abstract class AbstractStatistics implements InterfaceTextListener, Inter
if (printRunStoppedVerbosity()) printToTextListener(" NO feasible individual found.\n");
}
if (bestRunFeasibleIndy != null) {
if (meanBestFeasibleFit==null) {
meanBestFeasibleFit=currentBestFeasibleFit.clone();
} else addMean(meanBestFeasibleFit, currentBestFeasibleFit);
runBestFeasibleList.add(bestRunFeasibleIndy);
// if (meanBestFeasibleFit==null) {
// meanBestFeasibleFit=bestRunFeasibleIndy.getFitness().clone();
// } else addSecond(meanBestFeasibleFit, bestRunFeasibleIndy.getFitness());
if (printRunStoppedVerbosity()) {
if ((bestRunFeasibleIndy instanceof AbstractEAIndividual) && ((AbstractEAIndividual)bestRunFeasibleIndy).equalGenotypes((AbstractEAIndividual)bestRunIndividual)) {
printToTextListener(" Run best feasible individual equals best individual.\n");
printToTextListener("* Run best feasible individual equals best individual.\n");
} else {
if (bestRunFeasibleIndy instanceof AbstractEAIndividual) {
if (bestRunIndividual instanceof AbstractEAIndividual) {
if (((AbstractEAIndividual)bestRunIndividual).violatesConstraint())
printToTextListener(" Run best individual violates constraints by " + ((AbstractEAIndividual)bestRunIndividual).getConstraintViolation() + "\n");
if (((AbstractEAIndividual)bestRunIndividual).isMarkedPenalized())
printToTextListener(" Run best individual is penalized.\n");
}
printToTextListener(" Run best feasible ind.: " + BeanInspector.toString(bestRunFeasibleIndy) + "\n");
printToTextListener(" Feas. solution data : " + AbstractEAIndividual.getDefaultDataString(bestRunFeasibleIndy) + "\n");
printToTextListener(" Feas. solution fit : " + BeanInspector.toString(bestRunFeasibleIndy.getFitness()) + "\n");
printIndy("Run best feasible", bestRunFeasibleIndy);
}
}
}
@@ -218,6 +230,18 @@ public abstract class AbstractStatistics implements InterfaceTextListener, Inter
if (optRunsPerformed == m_StatsParams.getMultiRuns()) finalizeOutput();
}
private void printIndy(String prefix, IndividualInterface indy) {
printToTextListener("* " + prefix + " ind.: " + BeanInspector.toString(indy) + '\n');
printToTextListener(" solution data : " + AbstractEAIndividual.getDefaultDataString(indy) + '\n');
printToTextListener(" solution fit : " + BeanInspector.toString(indy.getFitness()));
if (!(indy instanceof AbstractEAIndividual)) printToTextListener(" - feasibility unknown\n");
else {
if (((AbstractEAIndividual)indy).isMarkedPenalized() || ((AbstractEAIndividual)indy).violatesConstraint()) printToTextListener(" - infeasible\n");
else printToTextListener("\n");
}
}
protected void finalizeOutput() {
if (printFinalVerbosity()) printToTextListener("*******\n Runs performed: " + optRunsPerformed + ", reached target " + convergenceCnt + " times with threshold " + m_StatsParams.getConvergenceRateThreshold() + ", rate " + convergenceCnt/(double)m_StatsParams.getMultiRuns() + '\n');
if (printFinalVerbosity()) printToTextListener(" Average function calls: " + (functionCallSum/optRunsPerformed) + "\n");
@@ -227,20 +251,25 @@ public abstract class AbstractStatistics implements InterfaceTextListener, Inter
printToTextListener(" Average evaluations until feasible ind. was found in " + numOfRunsFeasibleFound + " runs: " + feasibleFoundAfterSum/numOfRunsFeasibleFound + " evaluations\n");
}
if (printFinalVerbosity() && (bestIndividualAllover != null)) printToTextListener(" Overall best individual: " + BeanInspector.toString(bestIndividualAllover) + '\n');
if (printFinalVerbosity() && (bestIndividualAllover != null)) printToTextListener(" Overall solution data : " + AbstractEAIndividual.getDefaultDataString(bestIndividualAllover) + '\n');
if (printFinalVerbosity() && (bestIndividualAllover != null)) printToTextListener(" Overall solution fit : " + BeanInspector.toString(bestIndividualAllover.getFitness()) + '\n');
if (printFinalVerbosity() && (bestIndividualAllover != null)) printIndy("Overall best", bestIndividualAllover);
if (optRunsPerformed>1) {
if (meanBestOfRunFitness!=null) {
Mathematics.svDiv((double)optRunsPerformed, meanBestOfRunFitness, meanBestOfRunFitness);
if (runBestFitList.size()>0) {
// Mathematics.svDiv((double)optRunsPerformed, meanBestOfRunFitness, meanBestOfRunFitness);
if (printFinalVerbosity()) {
printToTextListener(" Average best fitness per run: " + BeanInspector.toString(meanBestOfRunFitness)+"\n");
double[] meanBestFit=calcMeanFit(runBestFitList);
printToTextListener(" MultiRun stats: Mean best fitness: " + BeanInspector.toString(meanBestFit)+"\n");
if (meanBestFit.length==1) printToTextListener(" MultiRun stats: Variance/Std.Dev.: " + BeanInspector.toString(calcStdDevVar(runBestFitList, meanBestFit[0])) + "\n");
printToTextListener(" MultiRun stats: Median best fitn.: " + BeanInspector.toString(calcMedianFit(runBestFitList))+"\n");
}
}
if (meanBestFeasibleFit!=null) {
Mathematics.svDiv((double)numOfRunsFeasibleFound, meanBestFeasibleFit, meanBestFeasibleFit);
if (printFinalVerbosity() && (bestFeasibleAllover != null)) printIndy("Overall best feasible", bestFeasibleAllover);
// if ((runBestFeasibleList.size()>0) && (!equalLists(runBestFeasibleList, runBestFitList))) { // is there a difference between best feasibles and best fit?
if (runBestFeasibleList.size()>0) { // always output feasible stats even if theyre equal
if (printFinalVerbosity()) {
printToTextListener(" Average best feasible fitness in " + numOfRunsFeasibleFound + " runs: " + BeanInspector.toString(meanBestFeasibleFit)+"\n");
double[] meanBestFeasibleFit=calcMeanFit(runBestFeasibleList);
printToTextListener(" MultiRun stats: Mean best feasible fitness (" + numOfRunsFeasibleFound + " runs): " + BeanInspector.toString(meanBestFeasibleFit)+"\n");
if (meanBestFeasibleFit.length==1) printToTextListener(" MultiRun stats: Variance/Std.Dev.: " + BeanInspector.toString(calcStdDevVar(runBestFeasibleList, meanBestFeasibleFit[0])) + "\n");
printToTextListener(" MultiRun stats: Median best feasible fitn. (: " + numOfRunsFeasibleFound + " runs): " + BeanInspector.toString(calcMedianFit(runBestFeasibleList))+"\n");
}
}
if (refineMultiRuns && (meanCollection != null)) {
@@ -261,7 +290,59 @@ public abstract class AbstractStatistics implements InterfaceTextListener, Inter
}
}
public static String refineToText(ArrayList<double[][]> result, int iterationsToShow) {
/**
* Perform a deep equals test on the fitness vectors of both individual lists.
* @param l1
* @param l2
* @return
*/
private boolean equalLists(
ArrayList<IndividualInterface> l1,
ArrayList<IndividualInterface> l2) {
boolean equal = true;
Iterator<IndividualInterface> iter1=l1.iterator();
Iterator<IndividualInterface> iter2=l2.iterator();
IndividualInterface indy1, indy2;
if (l1.size()!=l2.size()) return false;
else while (equal && (iter1.hasNext() && iter2.hasNext())) {
equal = Arrays.equals(iter1.next().getFitness(), iter2.next().getFitness());
}
return equal;
}
private double[] calcStdDevVar(ArrayList<IndividualInterface> list, double meanFit) {
double tmp=0, sum=0;
for (Iterator iter = list.iterator(); iter.hasNext();) {
IndividualInterface indy = (IndividualInterface) iter.next();
tmp=indy.getFitness()[0]-meanFit;
sum+=(tmp*tmp);
}
double[] res = new double[2];
res[0]=sum/list.size();
res[1]=Math.sqrt(res[0]);
return res;
}
/**
* Calculate the mean fitness of a list of individuals.
* @param list
* @return
*/
public static double[] calcMeanFit(List<IndividualInterface> list) {
double[] sumFit = list.get(0).getFitness().clone();
for (int i=1; i<list.size(); i++) addSecond(sumFit, list.get(i).getFitness());
Mathematics.svDiv(list.size(), sumFit, sumFit);
return sumFit;
}
public static double[] calcMedianFit(List<IndividualInterface> list) {
ArrayList<double[]> dblAList = new ArrayList<double[]>(list.size());
for (int i=0; i<list.size(); i++) dblAList.add(list.get(i).getFitness());
return Mathematics.median(dblAList, false);
}
public static String refineToText(ArrayList<double[][]> result, int iterationsToShow) {
double[][] mean;
StringBuffer sbuf = new StringBuffer("Iteration\tFun.Calls\tBest\tMean\tWorst\n");
double step = result.size()/(iterationsToShow-1.);
@@ -350,7 +431,7 @@ public abstract class AbstractStatistics implements InterfaceTextListener, Inter
}
/**
*
* @deprecated The method {@link #createNextGenerationPerformed(PopulationInterface, List)} should be used instead.
*/
public synchronized void createNextGenerationPerformed(double[] bestfit,
double[] worstfit, int calls) {
@@ -424,7 +505,6 @@ public abstract class AbstractStatistics implements InterfaceTextListener, Inter
}
if (pop instanceof Population) {
AbstractEAIndividual curBestFeasible = ((Population)pop).getBestFeasibleIndividual(-1);
if (curBestFeasible!=null) { // a feasible ind. was found!
if (currentBestFeasibleFit==null) { // feasible indy found for the first time
numOfRunsFeasibleFound++;
@@ -434,10 +514,14 @@ public abstract class AbstractStatistics implements InterfaceTextListener, Inter
}
currentBestFeasibleFit = curBestFeasible.getFitness().clone();
if ((bestRunFeasibleIndy==null) || (secondIsBetter(bestRunFeasibleIndy, curBestFeasible))) {
bestRunFeasibleIndy=curBestFeasible;
bestRunFeasibleIndy=(AbstractEAIndividual)curBestFeasible.clone();
// System.out.println("New best feasible: " + AbstractEAIndividual.getDefaultStringRepresentation((AbstractEAIndividual)bestRunFeasibleIndy));
}
}
}
if ((bestFeasibleAllover == null) || (secondIsBetter(bestFeasibleAllover, bestRunFeasibleIndy))) {
bestFeasibleAllover = bestRunFeasibleIndy;
}
}
} else System.err.println("INVALID POPULATION (AbstractStatistics)");
meanFitness = pop.getMeanFitness().clone();
currentWorstFit = pop.getWorstIndividual().getFitness().clone();
@@ -504,9 +588,9 @@ public abstract class AbstractStatistics implements InterfaceTextListener, Inter
private void updateMeans(double[][] means, double funCalls, double[] bestFit, double[] meanFit, double[] worstFit) {
means[0][0]+=funCalls;
addMean(means[1], bestFit);
addMean(means[2], meanFit);
addMean(means[3], worstFit);
addSecond(means[1], bestFit);
addSecond(means[2], meanFit);
addSecond(means[3], worstFit);
}
private static void divideMean(double[][] mean, double d) {
@@ -515,7 +599,7 @@ public abstract class AbstractStatistics implements InterfaceTextListener, Inter
}
}
private void addMean(double[] mean, double[] fit) {
public static void addSecond(double[] mean, double[] fit) {
for (int i=0; i<mean.length; i++) mean[i] += fit[i];
}

10
src/eva2/server/stat/GraphSelectionEnum.java
View File

@@ -3,7 +3,7 @@ package eva2.server.stat;
import eva2.tools.StringSelection;
public enum GraphSelectionEnum {
currentBest, currentWorst, runBest, bestFeasible, avgPopDistance, maxPopDistance;
currentBest, currentWorst, runBest, currentBestFeasible, runBestFeasible, avgPopDistance, maxPopDistance;
public static boolean doPlotCurrentBest(StringSelection sel) {
return sel.isSelected(GraphSelectionEnum.currentBest.ordinal());
@@ -17,8 +17,12 @@ public enum GraphSelectionEnum {
return sel.isSelected(GraphSelectionEnum.currentWorst.ordinal());
}
public static boolean doPlotBestFeasible(StringSelection sel) {
return sel.isSelected(GraphSelectionEnum.bestFeasible.ordinal());
public static boolean doPlotCurrentBestFeasible(StringSelection sel) {
return sel.isSelected(GraphSelectionEnum.currentBestFeasible.ordinal());
}
public static boolean doPlotRunBestFeasible(StringSelection sel) {
return sel.isSelected(GraphSelectionEnum.runBestFeasible.ordinal());
}
public static boolean doPlotAvgDist(StringSelection sel) {

69
src/eva2/server/stat/StatisticsStandalone.java
View File

@@ -19,12 +19,11 @@ import java.io.PrintWriter;
import java.io.Serializable;
import java.net.InetAddress;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
import eva2.server.go.InterfaceGOParameters;
import eva2.server.go.PopulationInterface;
import eva2.server.go.problems.InterfaceAdditionalPopulationInformer;
import eva2.tools.Mathematics;
/*
@@ -36,10 +35,6 @@ import eva2.server.go.problems.InterfaceAdditionalPopulationInformer;
*
*/
public class StatisticsStandalone extends AbstractStatistics implements InterfaceStatistics, Serializable {
/**
*
*/
private static final long serialVersionUID = 2621394534751748968L;
private static String m_MyHostName = "not def";
@@ -53,30 +48,31 @@ public class StatisticsStandalone extends AbstractStatistics implements Interfac
private double m_SumOfBestFit = 0;
private double[] m_BestFitnessAtEnd;
private double m_FitnessMedianofALL;
/**
*
*/
public StatisticsStandalone(InterfaceStatisticsParameter statParams) {
super();
m_StatsParams = statParams;
try {
m_MyHostName = InetAddress.getLocalHost().getHostName();
} catch (Exception e) {
System.out.println("ERROR getting HostName " + e.getMessage());
System.err.println("ERROR getting HostName " + e.getMessage());
}
}
/**
*
*/
public StatisticsStandalone(String resultFileName) {
this(new StatsParameter());
this(StatsParameter.getInstance());
m_StatsParams.SetResultFilePrefix(resultFileName);
m_StatsParams.setOutputTo(m_StatsParams.getOutputTo().setSelectedTag(StatsParameter.OUTPUT_FILE));
}
/**
*
*/
public StatisticsStandalone(String resultFileName, int multiRuns, int verbosity) {
this(StatsParameter.getInstance());
m_StatsParams.setMultiRuns(multiRuns);
m_StatsParams.setOutputVerbosity(m_StatsParams.getOutputVerbosity().setSelectedTag(verbosity));
m_StatsParams.SetResultFilePrefix(resultFileName);
m_StatsParams.setOutputTo(m_StatsParams.getOutputTo().setSelectedTag(StatsParameter.OUTPUT_FILE));
}
public StatisticsStandalone() {
this(new StatsParameter());
}
@@ -100,9 +96,6 @@ public class StatisticsStandalone extends AbstractStatistics implements Interfac
}
}
/**
*
*/
private void initContainer(String[] description) {
for (int i = 0; i < description.length; i++) {
m_Result.add(new ArrayList[m_StatsParams.getMultiRuns()]);
@@ -127,7 +120,6 @@ public class StatisticsStandalone extends AbstractStatistics implements Interfac
public void stopOptPerformed(boolean normal, String stopMessage) {
super.stopOptPerformed(normal, stopMessage);
if (bestCurrentIndividual != null) {
m_SumOfBestFit = m_SumOfBestFit + bestCurrentIndividual.getFitness()[0];
m_BestFitnessAtEnd[optRunsPerformed-1] = bestCurrentIndividual.getFitness()[0];
@@ -137,24 +129,12 @@ public class StatisticsStandalone extends AbstractStatistics implements Interfac
if (optRunsPerformed == m_StatsParams.getMultiRuns()) {
m_FitnessMeanofALL = m_SumOfBestFit / ((double) optRunsPerformed);
//System.out.println("m_FitnessMeanofALL "+m_FitnessMeanofALL);
m_FitnessMedianofALL = getMedian(m_BestFitnessAtEnd);
m_FitnessMedianofALL = Mathematics.median(m_BestFitnessAtEnd, true);
// finalizeOutput();
}
}
/**
*
*/
private static double getMedian(double[] in) {
double[] x = (double[]) in.clone();
// double ret = 0;
Arrays.sort(x);
int m = (int) (x.length / 2.0);
return x[m];
}
/**
* write result of all runs.
*/
@@ -264,25 +244,6 @@ public class StatisticsStandalone extends AbstractStatistics implements Interfac
// return ret;
// }
/**
*
*/
public static File writeString(String FileName, String Result) {
File f = null;
try {
f = new File(FileName + ".txt");
f.createNewFile();
PrintWriter Out = new PrintWriter(new FileOutputStream(f));
Out.println(Result);
Out.flush();
Out.close();
} catch (Exception e) {
System.out.println("Error:" + e.getMessage());
}
return f;
}
/**
*
*/

8
src/eva2/server/stat/StatisticsWithGUI.java
View File

@@ -239,7 +239,8 @@ public class StatisticsWithGUI extends AbstractStatistics implements Serializabl
boolean doPlotCurrentBest = GraphSelectionEnum.doPlotCurrentBest(lastGraphSelection);
boolean doPlotRunBest = GraphSelectionEnum.doPlotRunBest(lastGraphSelection);
boolean doPlotWorst= GraphSelectionEnum.doPlotWorst(lastGraphSelection);
boolean doPlotBestFeasible = GraphSelectionEnum.doPlotBestFeasible(lastGraphSelection);
boolean doPlotCurBestFeasible = GraphSelectionEnum.doPlotCurrentBestFeasible(lastGraphSelection);
boolean doPlotRunBestFeasible = GraphSelectionEnum.doPlotRunBestFeasible(lastGraphSelection);
boolean doPlotAvgDist= GraphSelectionEnum.doPlotAvgDist(lastGraphSelection);
boolean doPlotMaxPopDist= GraphSelectionEnum.doPlotMaxPopDist(lastGraphSelection);
@@ -257,9 +258,12 @@ public class StatisticsWithGUI extends AbstractStatistics implements Serializabl
if (doPlotAvgDist) plotFitnessPoint(0, subGraph++, functionCalls, avgPopDist);
if (doPlotMaxPopDist) plotFitnessPoint(0, subGraph++, functionCalls, maxPopDist);
if (doPlotBestFeasible && currentBestFeasibleFit!=null) {
if (doPlotCurBestFeasible && currentBestFeasibleFit!=null) {
plotFitnessPoint(0, subGraph++, functionCalls, currentBestFeasibleFit[0]);
}
if (doPlotRunBestFeasible && bestRunFeasibleIndy!=null) {
plotFitnessPoint(0, subGraph++, functionCalls, bestRunFeasibleIndy.getFitness()[0]);
}
}
}

16
src/eva2/server/stat/StatsParameter.java
View File

@@ -20,16 +20,9 @@ import eva2.gui.GenericObjectEditor;
import eva2.tools.SelectedTag;
import eva2.tools.Serializer;
import eva2.tools.StringSelection;
import eva2.tools.Tag;
/*==========================================================================*
* CLASS DECLARATION
*==========================================================================*/
/**
*
*/
public class StatsParameter implements InterfaceStatisticsParameter, Serializable {
private static boolean TRACE = false;
// public final static int PLOT_BEST = 0;
// public final static int PLOT_WORST = 1;
// public final static int PLOT_BEST_AND_WORST = 2;
@@ -59,7 +52,7 @@ public class StatsParameter implements InterfaceStatisticsParameter, Serializabl
private int m_Textoutput = 0;
private int m_Plotoutput = 1;
private int m_MultiRuns = 1;
private String m_ResultFilePrefix = "JE2";
private String m_ResultFilePrefix = "EvA2";
protected String m_Name = "not defined";
protected String m_InfoString = "";
private boolean m_useStatPlot = true;
@@ -72,9 +65,12 @@ public class StatsParameter implements InterfaceStatisticsParameter, Serializabl
*
*/
public static StatsParameter getInstance() {
if (TRACE ) System.out.println("Loading serialized stats..");
StatsParameter Instance = (StatsParameter) Serializer.loadObject("Statistics.ser");
if (Instance == null)
if (Instance == null) {
Instance = new StatsParameter();
if (TRACE) System.out.println("Loading failed!");
}
return Instance;
}