Package statechum.analysis.learning.experiments.PairSelection.PairQualityLearner

Examples of statechum.analysis.learning.experiments.PairSelection.PairQualityLearner.DifferenceToReference

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          PairQualityLearner.ReferenceLearner referenceLearner = new PairQualityLearner.ReferenceLearner(initConfiguration, referenceGraph, initPTA);
          referenceLearner.setPairQualityCounter(pairQualityCounter);
            LearnerGraph referenceOutcome = referenceLearner.learnMachine(new LinkedList<List<Label>>(),new LinkedList<List<Label>>());
            //referenceOutcome.storage.writeGraphML("resources/"+name+"-ref_"+frame+".xml");
           
            DifferenceToReference differenceF = DifferenceToReferenceLanguage.estimationOfDifference(referenceGraph, referenceOutcome, evaluationTestSet);
            DifferenceToReference differenceD = DifferenceToReferenceDiff.estimationOfDifferenceDiffMeasure(referenceGraph, referenceOutcome, initConfiguration.config, ExperimentRunner.getCpuNumber());
            System.out.println(new Date().toString()+" _R: For frame : "+frame+", long traces f-measure = "+ differenceF.getValue()+" diffmeasure = "+differenceD.getValue());
        uas_F.add(frame+"_R",differenceF.getValue(),"red");uas_Diff.add(frame+"_R",differenceD.getValue(),"red");gr_diff_to_f.add(differenceF.getValue(),differenceD.getValue());

        //PairQualityLearner.updateGraph(gr_PairQuality,pairQualityCounter);
        //gr_PairQuality.drawInteractive(gr);gr_PairQuality.drawPdf(gr);
      }

        {
            final RBoxPlot<Long> gr_PairQuality = new RBoxPlot<Long>("Correct v.s. wrong","%%",new File("percentage_score_huge_refM.pdf"));
          final Map<Long,TrueFalseCounter> pairQualityCounter = new TreeMap<Long,TrueFalseCounter>();

          LearnerGraph ptaAfterMergingBasedOnUniques = PairQualityLearner.mergeStatesForUnique(initPTA,uniqueLabel);
          PairQualityLearner.ReferenceLearner referenceLearner = new PairQualityLearner.ReferenceLearner(initConfiguration, referenceGraph, ptaAfterMergingBasedOnUniques);
          referenceLearner.setPairQualityCounter(pairQualityCounter);
            LearnerGraph referenceOutcome = referenceLearner.learnMachine(new LinkedList<List<Label>>(),new LinkedList<List<Label>>());
            //referenceOutcome.storage.writeGraphML("resources/"+name+"-ref_"+frame+".xml");
           
            DifferenceToReference differenceF = DifferenceToReferenceLanguage.estimationOfDifference(referenceGraph, referenceOutcome, evaluationTestSet);
            DifferenceToReference differenceD = DifferenceToReferenceDiff.estimationOfDifferenceDiffMeasure(referenceGraph, referenceOutcome, initConfiguration.config, ExperimentRunner.getCpuNumber());
            System.out.println(new Date().toString()+" _R: For frame : "+frame+", long traces f-measure = "+ differenceF+" diffmeasure = "+differenceD);
        uas_F.add(frame+"_RM",differenceF.getValue(),"red");uas_Diff.add(frame+"_RM",differenceD.getValue(),"red");gr_diff_to_f.add(differenceF.getValue(),differenceD.getValue());

        //PairQualityLearner.updateGraph(gr_PairQuality,pairQualityCounter);
        //gr_PairQuality.drawInteractive(gr);gr_PairQuality.drawPdf(gr);
      }
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                uas_S.add(frame+"T",difference.getValue());               
              }
            }
           */
              LearnerGraph initPTA = new LearnerGraph(learnerInitConfiguration.config);initPTA.paths.augmentPTA(collectionOfTraces.get(UAVAllSeeds).tracesForUAVandFrame.get(UAVAllSeeds).get(frame));
              DifferenceToReference difference = learnAndEstimateDifference(ifDepth, initPTA,referenceGraph,null,Collections.<Label>emptyList(),Collections.<Label>emptyList());
              uas_S.add(frame+"R",difference.getValue());
              synchronized(gr)
              {
                uas_S.drawInteractive(gr);
              }
          }
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            throw new RuntimeException("last merge in the learning process was not possible");
          }
          actualAutomaton = MergeStates.mergeCollectionOfVertices(actualAutomaton, null, verticesToMerge);
        }
       
        DifferenceToReference similarityMeasure = getMeasure(actualAutomaton,referenceGraph,testSet);
        System.out.println("similarity = "+similarityMeasure);
      }

      {// not merging based on a unique transition from an initial state
        learnerOfPairs = new PairQualityLearner.ReferenceLearner(learnerEval, referenceGraph, pta);
        synchronized (AbstractLearnerGraph.syncObj) {
          PaperUAS.computePTASize(selectionID+" no unique: ", pta, referenceGraph);
        }
        actualAutomaton = learnerOfPairs.learnMachine(new LinkedList<List<Label>>(),new LinkedList<List<Label>>());
        DifferenceToReference similarityMeasure = getMeasure(actualAutomaton,referenceGraph,testSet);
        System.out.println("similarity = "+similarityMeasure);
        System.out.println();
        /*
        LearnerGraph reducedPTA = PairQualityLearner.mergeStatesForUnique(pta,uniqueFromInitial);
        reducedPTA = reducedPTA.transform.trimGraph(3, reducedPTA.getInit());reducedPTA.setName("random_reduced");
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            throw new RuntimeException("last merge in the learning process was not possible");
          }
          actualAutomaton = MergeStates.mergeCollectionOfVertices(actualAutomaton, null, verticesToMerge);
        }
       
        DifferenceToReference similarityMeasure = getMeasure(actualAutomaton,referenceGraph,testSet);
        System.out.println("similarity = "+similarityMeasure);
      }

      {// not merging based on a unique transition from an initial state
        learnerOfPairs = new PairQualityLearner.ReferenceLearner(learnerEval, referenceGraph, pta,false);
        synchronized (AbstractLearnerGraph.syncObj) {
          PaperUAS.computePTASize(selectionID+" no unique: ", pta, referenceGraph);
        }
        actualAutomaton = learnerOfPairs.learnMachine(new LinkedList<List<Label>>(),new LinkedList<List<Label>>());
        DifferenceToReference similarityMeasure = getMeasure(actualAutomaton,referenceGraph,testSet);
        System.out.println("similarity = "+similarityMeasure);
        System.out.println();
        /*
        LearnerGraph reducedPTA = PairQualityLearner.mergeStatesForUnique(pta,uniqueFromInitial);
        reducedPTA = reducedPTA.transform.trimGraph(3, reducedPTA.getInit());reducedPTA.setName("random_reduced");
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          PairQualityLearner.ReferenceLearner referenceLearner = new PairQualityLearner.ReferenceLearner(initConfiguration, referenceGraph, initPTA);
          referenceLearner.setPairQualityCounter(pairQualityCounter);
            LearnerGraph referenceOutcome = referenceLearner.learnMachine(new LinkedList<List<Label>>(),new LinkedList<List<Label>>());
            //referenceOutcome.storage.writeGraphML("resources/"+name+"-ref_"+frame+".xml");
           
            DifferenceToReference differenceF = DifferenceToReferenceLanguage.estimationOfDifference(referenceGraph, referenceOutcome, evaluationTestSet);
            DifferenceToReference differenceD = DifferenceToReferenceDiff.estimationOfDifferenceDiffMeasure(referenceGraph, referenceOutcome, initConfiguration.config, ExperimentRunner.getCpuNumber());
            System.out.println(new Date().toString()+" _R: For frame : "+frame+", long traces f-measure = "+ differenceF.getValue()+" diffmeasure = "+differenceD.getValue());
        uas_F.add(frame+"_R",differenceF.getValue(),"red");uas_Diff.add(frame+"_R",differenceD.getValue(),"red");gr_diff_to_f.add(differenceF.getValue(),differenceD.getValue());

        //PairQualityLearner.updateGraph(gr_PairQuality,pairQualityCounter);
        //gr_PairQuality.drawInteractive(gr);gr_PairQuality.drawPdf(gr);
      }

        {
            final RBoxPlot<Long> gr_PairQuality = new RBoxPlot<Long>("Correct v.s. wrong","%%",new File("percentage_score_huge_refM.pdf"));
          final Map<Long,TrueFalseCounter> pairQualityCounter = new TreeMap<Long,TrueFalseCounter>();

          LearnerGraph ptaAfterMergingBasedOnUniques = PairQualityLearner.mergeStatesForUnique(initPTA,uniqueLabel);
          PairQualityLearner.ReferenceLearner referenceLearner = new PairQualityLearner.ReferenceLearner(initConfiguration, referenceGraph, ptaAfterMergingBasedOnUniques);
          referenceLearner.setPairQualityCounter(pairQualityCounter);
            LearnerGraph referenceOutcome = referenceLearner.learnMachine(new LinkedList<List<Label>>(),new LinkedList<List<Label>>());
            //referenceOutcome.storage.writeGraphML("resources/"+name+"-ref_"+frame+".xml");
           
            DifferenceToReference differenceF = DifferenceToReferenceLanguage.estimationOfDifference(referenceGraph, referenceOutcome, evaluationTestSet);
            DifferenceToReference differenceD = DifferenceToReferenceDiff.estimationOfDifferenceDiffMeasure(referenceGraph, referenceOutcome, initConfiguration.config, ExperimentRunner.getCpuNumber());
            System.out.println(new Date().toString()+" _R: For frame : "+frame+", long traces f-measure = "+ differenceF+" diffmeasure = "+differenceD);
        uas_F.add(frame+"_RM",differenceF.getValue(),"red");uas_Diff.add(frame+"_RM",differenceD.getValue(),"red");gr_diff_to_f.add(differenceF.getValue(),differenceD.getValue());

        //PairQualityLearner.updateGraph(gr_PairQuality,pairQualityCounter);
        //gr_PairQuality.drawInteractive(gr);gr_PairQuality.drawPdf(gr);
      }
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                uas_S.add(frame+"T",difference.getValue());               
              }
            }
           */
              LearnerGraph initPTA = new LearnerGraph(learnerInitConfiguration.config);initPTA.paths.augmentPTA(collectionOfTraces.get(UAVAllSeeds).tracesForUAVandFrame.get(UAVAllSeeds).get(frame));
              DifferenceToReference difference = learnAndEstimateDifference(ifDepth, initPTA,referenceGraph,null,Collections.<Label>emptyList(),Collections.<Label>emptyList());
              uas_S.add(frame+"R",difference.getValue());
              synchronized(gr)
              {
                uas_S.drawInteractive(gr);
              }
          }
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          PairQualityLearner.ReferenceLearner referenceLearner = new PairQualityLearner.ReferenceLearner(initConfiguration, referenceGraph, initPTA,false);
          referenceLearner.setPairQualityCounter(pairQualityCounter);
            LearnerGraph referenceOutcome = referenceLearner.learnMachine(new LinkedList<List<Label>>(),new LinkedList<List<Label>>());
            //referenceOutcome.storage.writeGraphML("resources/"+name+"-ref_"+frame+".xml");
           
            DifferenceToReference differenceF = DifferenceToReferenceFMeasure.estimationOfDifference(referenceGraph, referenceOutcome, evaluationTestSet);
            DifferenceToReference differenceD = DifferenceToReferenceDiff.estimationOfDifferenceDiffMeasure(referenceGraph, referenceOutcome, initConfiguration.config, ExperimentRunner.getCpuNumber());
            System.out.println(new Date().toString()+" _R: For frame : "+frame+", long traces f-measure = "+ differenceF.getValue()+" diffmeasure = "+differenceD.getValue());
        uas_F.add(frame+"_R",differenceF.getValue(),"red");uas_Diff.add(frame+"_R",differenceD.getValue(),"red");gr_diff_to_f.add(differenceF.getValue(),differenceD.getValue());

        //PairQualityLearner.updateGraph(gr_PairQuality,pairQualityCounter);
        //gr_PairQuality.drawInteractive(gr);gr_PairQuality.drawPdf(gr);
      }

        {
            final RBoxPlot<Long> gr_PairQuality = new RBoxPlot<Long>("Correct v.s. wrong","%%",new File("percentage_score_huge_refM.pdf"));
          final Map<Long,TrueFalseCounter> pairQualityCounter = new TreeMap<Long,TrueFalseCounter>();

          LearnerGraph ptaAfterMergingBasedOnUniques = PairQualityLearner.mergeStatesForUnique(initPTA,uniqueLabel);
          PairQualityLearner.ReferenceLearner referenceLearner = new PairQualityLearner.ReferenceLearner(initConfiguration, referenceGraph, ptaAfterMergingBasedOnUniques,false);
          referenceLearner.setPairQualityCounter(pairQualityCounter);
            LearnerGraph referenceOutcome = referenceLearner.learnMachine(new LinkedList<List<Label>>(),new LinkedList<List<Label>>());
            //referenceOutcome.storage.writeGraphML("resources/"+name+"-ref_"+frame+".xml");
           
            DifferenceToReference differenceF = DifferenceToReferenceFMeasure.estimationOfDifference(referenceGraph, referenceOutcome, evaluationTestSet);
            DifferenceToReference differenceD = DifferenceToReferenceDiff.estimationOfDifferenceDiffMeasure(referenceGraph, referenceOutcome, initConfiguration.config, ExperimentRunner.getCpuNumber());
            System.out.println(new Date().toString()+" _R: For frame : "+frame+", long traces f-measure = "+ differenceF+" diffmeasure = "+differenceD);
        uas_F.add(frame+"_RM",differenceF.getValue(),"red");uas_Diff.add(frame+"_RM",differenceD.getValue(),"red");gr_diff_to_f.add(differenceF.getValue(),differenceD.getValue());

        //PairQualityLearner.updateGraph(gr_PairQuality,pairQualityCounter);
        //gr_PairQuality.drawInteractive(gr);gr_PairQuality.drawPdf(gr);
      }
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                uas_S.add(frame+"T",difference.getValue());               
              }
            }
           */
              LearnerGraph initPTA = new LearnerGraph(learnerInitConfiguration.config);initPTA.paths.augmentPTA(collectionOfTraces.get(UAVAllSeeds).tracesForUAVandFrame.get(UAVAllSeeds).get(frame));
              DifferenceToReference difference = learnAndEstimateDifference(ifDepth, initPTA,referenceGraph,null,Collections.<Label>emptyList(),Collections.<Label>emptyList());
              uas_S.add(frame+"R",difference.getValue());
              synchronized(gr)
              {
                uas_S.drawInteractive(gr);
              }
          }
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Related Classes of statechum.analysis.learning.experiments.PairSelection.PairQualityLearner.DifferenceToReference

  • statechum.analysis.learning.experiments.PairSelection.SmallvsHugeExperiment
  • statechum.analysis.learning.experiments.PaperUAS
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