Merging changes from mk-branch 122:123.

src/eva2/EvAInfo.java

@@ -4,8 +4,10 @@ package eva2;
  * Main product and version information strings.
  * 
  * --- Changelog
+ * 2.028: Tuned the Population to sort only when necessary on calls to getBestN... Added StatisticsDummy.
+ * 			Slightly tuned SimpleProblemWrapper to call initProblem of simple problems if available.
  * 2.027: Renamed SetData and SetDataLamarckian from individual datatype interfaces to SetGenotype and SetPhenotype.
- * 			Repaired the GenericArrayEditor. Population measures can now be plottet in stats.
+ * 			Repaired the GenericArrayEditor. Population measures can now be plotted in stats.
  * 2.026: Added DiversityTerminator and KnownOptimaTerminator, slightly changed InterfaceTerminator for these
  * 			and InterfaceStatistics to provide termination message to text window. 
  * 			Killed redundant method getGenerations() in Population. Population.getAllSolutions now returns a 
@@ -25,7 +27,7 @@ package eva2;
 public class EvAInfo {
 	public static final String productName = "EvA 2";
 	public static final String productLongName = "Evolutionary Algorithms Workbench 2";
-	public static final String versionNum = new String ("2.027");
+	public static final String versionNum = new String ("2.028");
 	public static final String url = "http://www.ra.cs.uni-tuebingen.de/software/EvA2";
 
 	public static final String propertyFile = "resources/EvA2.props";

src/eva2/OptimizerRunnable.java

@@ -16,6 +16,7 @@ import eva2.server.go.populations.Population;
 import eva2.server.modules.GOParameters;
 import eva2.server.modules.Processor;
 import eva2.server.stat.AbstractStatistics;
+import eva2.server.stat.StatisticsDummy;
 import eva2.server.stat.InterfaceTextListener;
 import eva2.server.stat.StatisticsStandalone;
 
@@ -33,13 +34,42 @@ public class OptimizerRunnable implements Runnable {
 	private boolean postProcessOnly = false;
 	private InterfaceTextListener listener = null;
 	
+	/**
+	 * Construct an OptimizerRunnable with given parameters and a StatisticsStandalone instance without restart,
+	 * meaning that the population will be initialized randomly.
+	 * 
+	 * @param params
+	 * @param outputFilePrefix
+	 */
 	public OptimizerRunnable(GOParameters params, String outputFilePrefix) {
 		this(params, outputFilePrefix, false);
 	}
 		
+	/**
+	 * This constructor assumes that DummyStatistics are enough. This saves time e.g. for small populations.
+	 * If restart is true, the processor will not reinitialize the population allowing search on predefined populations.
+	 * 
+	 * @param params
+	 * @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;
+	}
+	
+	/**
+	 * Construct an OptimizerRunnable with given parameters and a StatisticsStandalone instance with optional restart.
+	 * If restart is true, the processor will not reinitialize the population allowing search on predefined populations.
+	 * The outputFilePrefix may be null.
+	 * 
+	 * @param params
+	 * @param outputFilePrefix
+	 * @param restart
+	 */
 	public OptimizerRunnable(GOParameters params, String outputFilePrefix, boolean restart) {
 		proc = new Processor(new StatisticsStandalone(outputFilePrefix), null, params);
-		((AbstractStatistics)proc.getStatistics()).setSaveParams(false);
+		if (proc.getStatistics() instanceof AbstractStatistics) ((AbstractStatistics)proc.getStatistics()).setSaveParams(false);
 		doRestart = restart;
 	}
 	

src/eva2/server/go/operators/mutation/MutateESMutativeStepSizeControl.java

@@ -96,7 +96,7 @@ public class MutateESMutativeStepSizeControl implements InterfaceMutation, java.
                 if (range[i][1] < x[i]) x[i] = range[i][1];
             }
             ((InterfaceESIndividual)individual).SetDGenotype(x);
-            System.out.println("new step size: " + m_MutationStepSize);
+            // System.out.println("new step size: " + m_MutationStepSize);
         }
         //System.out.println("After Mutate:  " +((GAIndividual)individual).getSolutionRepresentationFor());
     }

src/eva2/server/go/operators/postprocess/PostProcess.java

@@ -22,6 +22,7 @@ import eva2.server.go.problems.FM0Problem;
 import eva2.server.go.problems.InterfaceMultimodalProblemKnown;
 import eva2.server.go.strategies.HillClimbing;
 import eva2.server.stat.InterfaceTextListener;
+import eva2.server.stat.StatsParameter;
 import eva2.tools.Pair;
 
 
@@ -371,8 +372,9 @@ public class PostProcess {
 		}
 		hc.setPopulation(pop);
 //		hc.initByPopulation(pop, false);
-		hcRunnable = new OptimizerRunnable(OptimizerFactory.makeParams(hc, pop, problem, 0, term), null, true);
+		hcRunnable = new OptimizerRunnable(OptimizerFactory.makeParams(hc, pop, problem, 0, term), true);
 		hcRunnable.getGOParams().setDoPostProcessing(false);
+		hcRunnable.setVerbosityLevel(StatsParameter.VERBOSITY_NONE);
 		hcRunnable.run();
 		hcRunnable.getGOParams().setDoPostProcessing(true);
 		hcRunnable = null;

src/eva2/server/go/populations/Population.java

@@ -34,6 +34,8 @@ public class Population extends ArrayList implements PopulationInterface, Clonea
     protected int           m_FunctionCalls = 0;
     protected int           m_Size          = 50;
     protected Population    m_Archive       = null;
+    transient private ArrayList<AbstractEAIndividual> sortedArr = null;
+    private int lastQModCount = -1;
     transient protected InterfacePopulationChangedEventListener	m_Listener = null;
     protected int 			notifyEvalInterval	= 0;
     protected HashMap<String, Object>		additionalPopData = null;
@@ -161,7 +163,7 @@ public class Population extends ArrayList implements PopulationInterface, Clonea
     	useHistory = useHist;
     }
     
-    /** This method will allow cou to increment the current number of function calls.
+    /** This method will allow you to increment the current number of function calls.
      */
     public void incrFunctionCalls() {
         this.m_FunctionCalls++;
@@ -178,17 +180,23 @@ public class Population extends ArrayList implements PopulationInterface, Clonea
      */
     public void incrFunctionCallsby(int d) {
     	if (doEvalNotify()) {
-    		System.out.println("checking funcall event...");
-    		int nextStep = ((m_FunctionCalls/notifyEvalInterval)+1) * notifyEvalInterval; // next interval boundary
-    		if (nextStep <= (m_FunctionCalls+d)) {
+//    		System.out.println("checking funcall event...");
+    		int nextStep; // next interval boundary
+    		while ((nextStep = calcNextBoundary()) <= (m_FunctionCalls+d)) {
     			// 	the notify interval will be stepped over or hit
     			int toHit = (nextStep - m_FunctionCalls);
     			this.m_FunctionCalls += toHit; // little cheat, notify may be after some more evals
     			firePropertyChangedEvent(funCallIntervalReached);
-    			this.m_FunctionCalls += (d-toHit);
+    			d = d-toHit;
+//    			this.m_FunctionCalls += (d-toHit);
     		}
+    		if (d>0) this.m_FunctionCalls += d; // add up the rest
     	} else this.m_FunctionCalls += d;
     }
+
+	private int calcNextBoundary() {
+		return ((m_FunctionCalls/notifyEvalInterval)+1) * notifyEvalInterval;
+	}
     
     /** Something has changed
      */
@@ -363,32 +371,69 @@ public class Population extends ArrayList implements PopulationInterface, Clonea
     }
 
     /** 
-     * This method returns the n current best individuals from the population, where
+     * This method returns the n currently best individuals from the population, where
      * the sorting criterion is delivered by an AbstractEAIndividualComparator.
      * There are less than n individuals returned if the population is smaller than n.
-     * If n is <= 0, then all individuals are returned and effectively just sorted
-     * by fitness.
+     * The comparator does not check constraints!
      * 
      * @param n	number of individuals to look out for
      * @return The m best individuals, where m <= n
      * 
      */
     public Population getBestNIndividuals(int n) {
-    	if (n <= 0) n = super.size();
+    	return getSortedNIndividuals(n, true);
+    }
+    
+    /** 
+     * This method returns the n current best individuals from the population, where
+     * the sorting criterion is delivered by an AbstractEAIndividualComparator.
+     * There are less than n individuals returned if the population is smaller than n.
+     * The comparator does not check constraints!
+     * 
+     * @param n	number of individuals to look out for
+     * @param bBestOrWorst if true, the best n are returned, else the worst n individuals
+     * @return The m sorted best or worst individuals, where m <= n
+     * 
+     */
+    public Population getSortedNIndividuals(int n, boolean bBestOrWorst) {
+    	if ((n < 0) || (n>super.size())) {
+    		System.err.println("invalid request to getSortedNIndividuals: n="+n + ", size is " + super.size());
+    		n = super.size();
+    	}
+    	int skip = 0;
+    	if (!bBestOrWorst) skip = super.size()-n;
+    	
     	Population result = new Population(n);
-    	PriorityQueue<AbstractEAIndividual> queue = new PriorityQueue<AbstractEAIndividual>(super.size(), new AbstractEAIndividualComparator());
+    	ArrayList<AbstractEAIndividual> sorted = getSorted();
 
-        for (int i = 0; i < super.size(); i++) {
-        	queue.add(getEAIndividual(i));
-        }
-        for (int i = 0; i<n ; i++) {
-        	if (queue.size() == 0) break;
-        	result.add(queue.poll());
+        for (int i = skip; i < skip+n; i++) {
+        	result.add(sorted.get(i));
         }
         result.setPopulationSize(result.size());
     	return result;
     }
     
+    /**
+     * Avoids having to sort again in several calls without modifications in between.
+     * The returned array should not be modified!
+     * 
+     * @return
+     */
+    protected ArrayList<AbstractEAIndividual> getSorted() {
+    	if (sortedArr == null || (super.modCount != lastQModCount)) {
+    		PriorityQueue<AbstractEAIndividual> sQueue = new PriorityQueue<AbstractEAIndividual>(super.size(), new AbstractEAIndividualComparator());
+    		for (int i = 0; i < super.size(); i++) {
+    			sQueue.add(getEAIndividual(i));
+    		}
+    		lastQModCount = super.modCount;
+    		if (sortedArr==null) sortedArr = new ArrayList<AbstractEAIndividual>(this.size());
+    		else sortedArr.clear();
+    		AbstractEAIndividual indy;
+    		while ((indy=sQueue.poll())!=null) sortedArr.add(indy);
+    	}
+    	return sortedArr;
+    }
+    	
     /** This method returns n random best individuals from the population.
      * 
      * @param n	number of individuals to look out for
@@ -662,6 +707,15 @@ public class Population extends ArrayList implements PopulationInterface, Clonea
     	return addIndividual((IndividualInterface)o);
     }
     
+    /**
+	 * ArrayList does not increase the modCount in set. Why???
+     */
+    public Object set(int index, Object element) {
+    	Object prev = super.set(index, element);
+    	modCount++;
+    	return prev;
+    }
+    
     public boolean addIndividual(IndividualInterface ind) {
         super.add(ind);
         return true;

src/eva2/server/go/problems/F1Problem.java

@@ -50,6 +50,7 @@ public class F1Problem extends AbstractProblemDouble implements Interface2DBorde
      */
     public void initProblem() {
 //        this.m_OverallBest = null;
+    	initTemplate();
     }
 
 	protected double[] getEvalArray(AbstractEAIndividual individual){

src/eva2/server/go/problems/F6Problem.java

@@ -1,7 +1,7 @@
 package eva2.server.go.problems;
 
 import eva2.server.go.individuals.ESIndividualDoubleData;
-import eva2.server.go.strategies.ParticleSwarmOptimization;
+import eva2.tools.Mathematics;
 import wsi.ra.math.Jama.Matrix;
 
 /**
@@ -32,10 +32,12 @@ public class F6Problem extends F1Problem implements InterfaceMultimodalProblem,
      */
     public void initProblem() {
         super.initProblem();
-        rotation = new Matrix(m_ProblemDimension, m_ProblemDimension);
-        Matrix vec = new Matrix(m_ProblemDimension, 1);
-        for (int i=0; i<m_ProblemDimension; i++) vec.set(i,0, i+1);
-        rotation = ParticleSwarmOptimization.getRotationMatrix(vec).transpose();
+        if (doRotation) {
+        	rotation = new Matrix(m_ProblemDimension, m_ProblemDimension);
+        	Matrix vec = new Matrix(m_ProblemDimension, 1);
+        	for (int i=0; i<m_ProblemDimension; i++) vec.set(i,0, i+1);
+        	rotation = Mathematics.getRotationMatrix(vec).transpose();
+        } else rotation = null;
     }
     
     /** This method returns a deep clone of the problem.

src/eva2/server/go/strategies/ParticleSwarmOptimization.java

@@ -20,6 +20,7 @@ import eva2.server.go.problems.Interface2DBorderProblem;
 import eva2.server.go.problems.InterfaceOptimizationProblem;
 import wsi.ra.math.RNG;
 import eva2.tools.EVAERROR;
+import eva2.tools.Mathematics;
 import eva2.tools.SelectedTag;
 
 import wsi.ra.chart2d.DPoint;
@@ -797,7 +798,7 @@ public class ParticleSwarmOptimization implements InterfaceOptimizer, java.io.Se
 			for (int i=1; i<dim; i++) {
 				randVec.set(i, 0, project(-len/2, len/2, RNG.gaussianDouble(len/(scale*2))));
 			}
-			Matrix rotation = getRotationMatrix(dir);
+			Matrix rotation = Mathematics.getRotationMatrix(dir);
 			rotation = rotation.transpose();
 			//printMatrix(rotation);
 			resVec = rotation.times(randVec);
@@ -860,75 +861,6 @@ public class ParticleSwarmOptimization implements InterfaceOptimizer, java.io.Se
 //		vec.setElement(j, val1);
 //	}
 	
-	/**
-	 * Return a matrix A which performs the rotation of vec to (1,0,0,...0) if forward is true, else
-	 * return a matrix B which performs the reverted rotation, where B=A' (transposition).
-	 *   
-	 * @param vec
-	 * @return
-	 */
-	public static Matrix getRotationMatrix(Matrix vec) {
-		Matrix A = Matrix.identity(vec.getRowDimension(), vec.getRowDimension());
-		Matrix tmp = Matrix.identity(vec.getRowDimension(), vec.getRowDimension());
-		Matrix z = (Matrix)vec.clone();
-
-		double w, cosw, sinw;
-
-		z.multi(z.norm2()); // normalize
-
-
-		for (int i=1; i<vec.getRowDimension(); i++) {
-			w = Math.atan2(z.get(i,0), z.get(0,0));// calc angle between the projection of x and x0 in x0-xi-plane
-
-			cosw = Math.cos(w);
-			sinw = Math.sin(w);
-			tmp.set(0, 0, cosw);	// make partial rotation matrix
-			tmp.set(0, i, sinw);
-			tmp.set(i, 0, -sinw);
-			tmp.set(i, i, cosw);
-
-			A = tmp.times(A);			// add to resulting rotation
-			z = tmp.times(z);			// z is now 0 in i-th component
-
-			tmp.set(0, 0, 1); // reset tmp matrix to unity
-			tmp.set(0, i, 0);
-			tmp.set(i, 0, 0);
-			tmp.set(i, i, 1);
-		}
-		return A;
-	}
-
-//	protected GMatrix nrotate(GVector vec) {	
-//		GMatrix A = new GMatrix(vec.getSize(), vec.getSize());
-//		GMatrix tmp = new GMatrix(vec.getSize(), vec.getSize());
-//		GVector z = new GVector(vec);
-//
-//		double w, cosw, sinw;
-//
-//		z.normalize();
-//		
-//		
-//		for (int i=1; i<vec.getSize(); i++) {
-//			w = Math.atan2(z.getElement(i), z.getElement(0));// calc angle between the projection of x and x0 in x0-xi-plane
-//
-//			cosw = Math.cos(w);
-//			sinw = Math.sin(w);
-//			tmp.setElement(0, 0, cosw);	// make partial rotation matrix
-//			tmp.setElement(0, i, sinw);
-//			tmp.setElement(i, 0, -sinw);
-//			tmp.setElement(i, i, cosw);
-//			
-//			A.mul(tmp, A);			// add to resulting rotation
-//			z.mul(tmp, z);			// z is now 0 in i-th component
-//			
-//			tmp.setElement(0, 0, 1); // reset tmp matrix to unity
-//			tmp.setElement(0, i, 0);
-//			tmp.setElement(i, 0, 0);
-//			tmp.setElement(i, i, 1);
-//		}
-//		return A;
-//	}
-
 	/**
 	 * In the topology range for the given index, find the best stored individual and return its position.
 	 *

src/eva2/server/stat/StatisticsDummy.java

@@ -0,0 +1,76 @@
+package eva2.server.stat;
+
+import eva2.server.go.IndividualInterface;
+import eva2.server.go.PopulationInterface;
+import eva2.server.go.problems.InterfaceAdditionalPopulationInformer;
+
+/**
+ * This may be given to a Processor if no further stats are required. It speeds up
+ * optimization especially with small populations (e.g. HC as local search operator).
+ * 
+ * @author mkron
+ *
+ */
+public class StatisticsDummy implements InterfaceStatistics, InterfaceTextListener {
+	boolean consoleOut = false;
+	StatsParameter sParams = null;
+	
+	public StatisticsDummy() {
+		sParams = new StatsParameter();
+		sParams.setOutputVerbosityK(StatsParameter.VERBOSITY_NONE);
+	}
+	
+	public StatisticsDummy(boolean doConsoleOut) {
+		sParams = new StatsParameter();
+		sParams.setOutputVerbosityK(StatsParameter.VERBOSITY_NONE);
+		consoleOut = doConsoleOut;
+	}
+	
+	public void addTextListener(InterfaceTextListener listener) {
+		System.err.println("addTextListener not provided!");
+	}
+
+	public void createNextGenerationPerformed(PopulationInterface Pop,
+			InterfaceAdditionalPopulationInformer informer) {
+	}
+
+	public void createNextGenerationPerformed(double[] bestfit,
+			double[] worstfit, int calls) {
+	}
+
+	public double[] getBestFitness() {
+		System.err.println("getBestFitness not provided!");
+		return null;
+	}
+
+	public IndividualInterface getBestSolution() {
+		System.err.println("getBestSolution not provided!");
+		return null;
+	}
+
+	public InterfaceStatisticsParameter getStatisticsParameter() {
+		return sParams;
+	}
+
+	public void printToTextListener(String s) {
+		if (consoleOut) System.out.println(s);
+	}
+
+	public boolean removeTextListener(InterfaceTextListener listener) {
+		System.err.println("removeTextListener not provided!");
+		return false;
+	}
+
+	public void startOptPerformed(String InfoString, int runnumber,
+			Object params) {}
+
+	public void stopOptPerformed(boolean normal, String stopMessage) {}
+	
+	public void print(String str) {
+		if (consoleOut) System.out.print(str);
+	}
+	public void println(String str) {
+		if (consoleOut) System.out.println(str);
+	}
+
+}

src/eva2/tools/Mathematics.java

@@ -1,6 +1,8 @@
 package eva2.tools;
 
 import java.util.Arrays;
+
+import wsi.ra.math.Jama.Matrix;
 import wsi.ra.math.interpolation.BasicDataSet;
 import wsi.ra.math.interpolation.InterpolationException;
 import wsi.ra.math.interpolation.SplineInterpolation;
@@ -609,4 +611,42 @@ public class Mathematics {
 	public static void normalizeSum(double[] v, double[] res) {
 		svMult(1./sum(v), v, res);
 	}
+
+	/**
+	 * Return a matrix A which performs the rotation of vec to (1,0,0,...0) if forward is true, else
+	 * return a matrix B which performs the reverted rotation, where B=A' (transposition).
+	 *   
+	 * @param vec
+	 * @return
+	 */
+	public static Matrix getRotationMatrix(Matrix vec) {
+		Matrix A = Matrix.identity(vec.getRowDimension(), vec.getRowDimension());
+		Matrix tmp = Matrix.identity(vec.getRowDimension(), vec.getRowDimension());
+		Matrix z = (Matrix)vec.clone();
+	
+		double w, cosw, sinw;
+	
+		z.multi(z.norm2()); // normalize
+	
+	
+		for (int i=1; i<vec.getRowDimension(); i++) {
+			w = Math.atan2(z.get(i,0), z.get(0,0));// calc angle between the projection of x and x0 in x0-xi-plane
+	
+			cosw = Math.cos(w);
+			sinw = Math.sin(w);
+			tmp.set(0, 0, cosw);	// make partial rotation matrix
+			tmp.set(0, i, sinw);
+			tmp.set(i, 0, -sinw);
+			tmp.set(i, i, cosw);
+	
+			A = tmp.times(A);			// add to resulting rotation
+			z = tmp.times(z);			// z is now 0 in i-th component
+	
+			tmp.set(0, 0, 1); // reset tmp matrix to unity
+			tmp.set(0, i, 0);
+			tmp.set(i, 0, 0);
+			tmp.set(i, i, 1);
+		}
+		return A;
+	}
 }