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Minor adaptions to post-processing, BeanInspector.

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This commit is contained in:
Marcel Kronfeld
2008-03-27 14:55:01 +00:00
parent ec20723dd9
commit 29b6c840ac
10 changed files with 451 additions and 150 deletions
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46
src/javaeva/server/go/operators/postprocess/PostProcess.java
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@@ -488,53 +488,55 @@ public class PostProcess {
* a list of solutions after post processing.
*
* @param params
* @param solutions
* @param inputPop
* @param problem
* @param listener
* @return the clustered, post-processed population
*/
public static Population postProcess(InterfacePostProcessParams params, Population solutions, AbstractOptimizationProblem problem, InterfaceTextListener listener) {
public static Population postProcess(InterfacePostProcessParams params, Population inputPop, AbstractOptimizationProblem problem, InterfaceTextListener listener) {
if (params.isDoPostProcessing()) {
Population outputPop;
Population clusteredPop, outputPop;
if (params.getPostProcessClusterSigma() > 0) {
outputPop = (Population)PostProcess.clusterBest(solutions, params.getPostProcessClusterSigma(), 0, PostProcess.KEEP_LONERS, PostProcess.BEST_ONLY).clone();
if (outputPop.size() < solutions.size()) {
if (listener != null) listener.println("Initial clustering reduced population size from " + solutions.size() + " to " + outputPop.size());
clusteredPop = (Population)PostProcess.clusterBest(inputPop, params.getPostProcessClusterSigma(), 0, PostProcess.KEEP_LONERS, PostProcess.BEST_ONLY).clone();
if (clusteredPop.size() < inputPop.size()) {
if (listener != null) listener.println("Initial clustering reduced population size from " + inputPop.size() + " to " + clusteredPop.size());
} else if (listener != null) listener.println("Initial clustering yielded no size reduction.");
} else outputPop = solutions;
} else clusteredPop = inputPop;
if (params.getPostProcessSteps() > 0) {
processWithHC(outputPop, problem, params.getPostProcessSteps());
if (listener != null) listener.println("HC post processing done.");
processWithHC(clusteredPop, problem, params.getPostProcessSteps());
if (listener != null) listener.println("HC post processing: " + params.getPostProcessSteps() + " steps done.");
// some individuals may have now converged again
if (params.getPostProcessClusterSigma() > 0) {
// so if wished, cluster again.
outputPop = (Population)PostProcess.clusterBest(outputPop, params.getPostProcessClusterSigma(), 0, PostProcess.KEEP_LONERS, PostProcess.BEST_ONLY).clone();
if (outputPop.size() < solutions.size()) {
if (listener != null) listener.println("Second clustering reduced population size from " + solutions.size() + " to " + outputPop.size());
outputPop = (Population)PostProcess.clusterBest(clusteredPop, params.getPostProcessClusterSigma(), 0, PostProcess.KEEP_LONERS, PostProcess.BEST_ONLY).clone();
if (outputPop.size() < clusteredPop.size()) {
if (listener != null) listener.println("Second clustering reduced population size from " + clusteredPop.size() + " to " + outputPop.size());
} else if (listener != null) listener.println("Second clustering yielded no size reduction.");
}
}
} else outputPop = clusteredPop;
} else outputPop = clusteredPop;
double upBnd = PhenotypeMetric.norm(outputPop.getWorstEAIndividual().getFitness())*1.1;
upBnd = Math.pow(10,Math.floor(Math.log10(upBnd)+1));
double lowBnd = 0;
int[] sols = PostProcess.createFitNormHistogram(outputPop, lowBnd, upBnd, 20);
// PostProcessInterim.outputResult((AbstractOptimizationProblem)goParams.getProblem(), outputPop, 0.01, System.out, 0, 2000, 20, goParams.getPostProcessSteps());
if (listener != null) listener.println("measures: " + BeanInspector.toString(outputPop.getPopulationMeasures()));
if (listener != null) listener.println("solution histogram in [" + lowBnd + "," + upBnd + "]: " + BeanInspector.toString(sols));
if (outputPop.size()>1) {
if (listener != null) listener.println("measures: " + BeanInspector.toString(outputPop.getPopulationMeasures()));
if (listener != null) listener.println("solution histogram in [" + lowBnd + "," + upBnd + "]: " + BeanInspector.toString(sols));
}
//////////// multimodal data output?
if (problem instanceof InterfaceMultimodalProblemKnown) procMultiModalKnown(outputPop, (InterfaceMultimodalProblemKnown)problem, listener);
Population resPop = outputPop.getBestNIndividuals(params.getPrintNBest()); // n individuals are returned and sorted, all of them if n<=0
if (listener != null) listener.println("Best after post process:" + ((outputPop.size()>resPop.size()) ? ( "(first " + resPop.size() + " of " + outputPop.size() + ")") : ""));
Population nBestPop = outputPop.getBestNIndividuals(params.getPrintNBest()); // n individuals are returned and sorted, all of them if n<=0
if (listener != null) listener.println("Best after post process:" + ((outputPop.size()>nBestPop.size()) ? ( "(first " + nBestPop.size() + " of " + outputPop.size() + ")") : ""));
//////////// output some individual data
if (listener != null) for (int i=0; i<resPop.size(); i++) {
listener.println(AbstractEAIndividual.getDefaultStringRepresentation(resPop.getEAIndividual(i)));
if (listener != null) for (int i=0; i<nBestPop.size(); i++) {
listener.println(AbstractEAIndividual.getDefaultStringRepresentation(nBestPop.getEAIndividual(i)));
}
return resPop;
} else return solutions;
return nBestPop;
} else return inputPop;
}
}