Minor changes.
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		@@ -146,7 +146,7 @@ public class MatlabEvalMediator {
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	private void logMPOrSysOut(String msg) {
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//		System.out.println("Hurz OR");
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		logMP(msg + "\n");
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		logMP(msg);
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//		else System.out.println("MEM has no MP! " + msg);
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	}
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@@ -174,18 +174,20 @@ public abstract class AbstractStatistics implements InterfaceTextListener, Inter
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	protected void finalizeOutput() {
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		if (printFinalVerbosity()) printToTextListener("*******\n Runs performed: " + optRunsPerformed + ", reached target " + convergenceCnt + " times with threshold " + m_StatsParams.getConvergenceRateThreshold() + ", rate " + convergenceCnt/(double)m_StatsParams.getMultiRuns() + '\n');
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		if (printFinalVerbosity()) printToTextListener(" Average function calls: " + (functionCallSum/optRunsPerformed) + "\n");
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		if (printFinalVerbosity() && (bestIndividualAllover != null)) printToTextListener(" Overall best individual		: " + BeanInspector.toString(bestIndividualAllover) + '\n');
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		if (printFinalVerbosity() && (bestIndividualAllover != null)) printToTextListener("     overall solution data	: " + AbstractEAIndividual.getDefaultDataString(bestIndividualAllover) + '\n');
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		if (printFinalVerbosity() && (bestIndividualAllover != null)) printToTextListener("     overall solution fit	: " + BeanInspector.toString(bestIndividualAllover.getFitness()) + '\n');
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		if (refineMultiRuns && (optRunsPerformed>1) && (meanCollection != null)) {
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			if (printFinalVerbosity()) printToTextListener("Averaged performance:\n");
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			for (int i=0; i<meanCollection.size(); i++) divideMean(meanCollection.get(i), optRunsPerformed);
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			if (printFinalVerbosity()) printToTextListener(refineToText(meanCollection, showAvgIntervals));
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		}
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		if ((meanBestOfRunFitness!=null) && (optRunsPerformed>1)) {
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			Mathematics.svDiv((double)optRunsPerformed, meanBestOfRunFitness, meanBestOfRunFitness);
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			if (printFinalVerbosity()) {
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				printToTextListener(" Averaged best run fitness: " + BeanInspector.toString(meanBestOfRunFitness)+"\n");
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		if (printFinalVerbosity() && (bestIndividualAllover != null)) printToTextListener(" Overall best individual: " + BeanInspector.toString(bestIndividualAllover) + '\n');
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		if (printFinalVerbosity() && (bestIndividualAllover != null)) printToTextListener("     Overall solution data	: " + AbstractEAIndividual.getDefaultDataString(bestIndividualAllover) + '\n');
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		if (printFinalVerbosity() && (bestIndividualAllover != null)) printToTextListener("     Overall solution fit	: " + BeanInspector.toString(bestIndividualAllover.getFitness()) + '\n');
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		if (optRunsPerformed>1) {
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			if (meanBestOfRunFitness!=null) {
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				Mathematics.svDiv((double)optRunsPerformed, meanBestOfRunFitness, meanBestOfRunFitness);
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				if (printFinalVerbosity()) {
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					printToTextListener(" Averaged best fitness per run: " + BeanInspector.toString(meanBestOfRunFitness)+"\n");
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				}
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			}
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			if (refineMultiRuns && (meanCollection != null)) {
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				if (printFinalVerbosity()) printToTextListener(" Averaged performance:\n");
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				for (int i=0; i<meanCollection.size(); i++) divideMean(meanCollection.get(i), optRunsPerformed);
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				if (printFinalVerbosity()) printToTextListener(refineToText(meanCollection, showAvgIntervals));
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			}
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		}
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		if (TRACE)
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@@ -198,7 +200,7 @@ public abstract class AbstractStatistics implements InterfaceTextListener, Inter
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			resultOut.close();
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		}
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	}
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    public static String refineToText(ArrayList<double[][]> result, int iterationsToShow) {
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    	double[][] mean;
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    	StringBuffer sbuf = new StringBuffer("Iteration\tFun.Calls\tBest\tMean\tWorst\n");
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