Package statechum.analysis.learning

Examples of statechum.analysis.learning.DrawGraphs$RBoxPlotP

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  @SuppressWarnings("null")
  public static void runExperiment() throws Exception
  {
    DrawGraphs gr = new DrawGraphs();
    Configuration config = Configuration.getDefaultConfiguration().copy();config.setAskQuestions(false);config.setDebugMode(false);config.setGdLowToHighRatio(0.7);config.setRandomPathAttemptFudgeThreshold(1000);
    config.setTransitionMatrixImplType(STATETREE.STATETREE_LINKEDHASH);config.setLearnerScoreMode(ScoreMode.COMPATIBILITY);//ONLYOVERRIDE);
    ConvertALabel converter = new Transform.InternStringLabel();
    GlobalConfiguration.getConfiguration().setProperty(G_PROPERTIES.LINEARWARNINGS, "false");
    final int ThreadNumber = ExperimentRunner.getCpuNumber(); 
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  }
   
  @SuppressWarnings("null")
  public static void runExperiment() throws Exception
  {
    DrawGraphs gr = new DrawGraphs();
    Configuration config = Configuration.getDefaultConfiguration().copy();config.setAskQuestions(false);config.setDebugMode(false);config.setGdLowToHighRatio(0.7);config.setRandomPathAttemptFudgeThreshold(1000);
    config.setTransitionMatrixImplType(STATETREE.STATETREE_ARRAY);config.setLearnerScoreMode(ScoreMode.ONLYOVERRIDE);
    ConvertALabel converter = new Transform.InternStringLabel();
    GlobalConfiguration.getConfiguration().setProperty(G_PROPERTIES.LINEARWARNINGS, "false");
    final int ThreadNumber = ExperimentRunner.getCpuNumber(); 
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    mutationStages = mutationStagesArg;graphComplexityMax = graphComplexityMaxArg;
   
  }
 
  public void runExperiment(int initStates, boolean skip){
    DrawGraphs gr = new DrawGraphs();
    this.skipLanguage = skip;
    Random r = new Random(0);

    RBoxPlot<Integer>
      gr_Diff_States = new RBoxPlot<Integer>("States","Diff/Mutations",new File("diff_states.pdf")),
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  }
   
  @SuppressWarnings("null")
  public static void runExperiment() throws Exception
  {
    DrawGraphs gr = new DrawGraphs();
    Configuration config = Configuration.getDefaultConfiguration().copy();config.setAskQuestions(false);config.setDebugMode(false);config.setGdLowToHighRatio(0.7);config.setRandomPathAttemptFudgeThreshold(1000);
    config.setTransitionMatrixImplType(STATETREE.STATETREE_LINKEDHASH);config.setLearnerScoreMode(ScoreMode.COMPATIBILITY);
    ConvertALabel converter = new Transform.InternStringLabel();
    GlobalConfiguration.getConfiguration().setProperty(G_PROPERTIES.LINEARWARNINGS, "false");
    final int ThreadNumber = ExperimentRunner.getCpuNumber(); 
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   }
  
   public void runExperimentWithSingleAutomaton(int ifDepth, String name, String arffName, LearnerGraph referenceGraph) throws Exception
   {
     final Collection<List<Label>> evaluationTestSet = computeEvaluationSet(referenceGraph,-1,-1);
       DrawGraphs gr = new DrawGraphs();
    final RBoxPlot<String>
      uas_F=new RBoxPlot<String>("Time","F-measure",new File("time_"+name+"_f.pdf")),
      uas_Diff=new RBoxPlot<String>("Time","Diff-measure",new File("time_"+name+"_Diff.pdf"));
    SquareBagPlot gr_diff_to_f = new SquareBagPlot("f-measure","diff-based measure",new File("diff-to-f.pdf"),0,1,true);
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      //final Collection<List<Label>> evaluationTestSet = computeEvaluationSet(referenceGraph);
      
    // Here I need to moderate the effort because choosing traces for all seeds is good but I need
    // that many times more traces, so I have to create a graph in terms of effort v.s. quailty (or even better, scale
    // the existing one).
    final DrawGraphs gr = new DrawGraphs();

    final RBoxPlot<Pair<Integer,String>>
      uas_outcome = new RBoxPlot<Pair<Integer,String>>("Time","f-measure",new File("time_f.pdf"));
    final RBoxPlot<String>
          uas_A=new RBoxPlot<String>("Time","f-measure",new File("time_A_f.pdf")),
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  @SuppressWarnings("null")
  public static void runExperiment() throws Exception
  {
    DrawGraphs gr = new DrawGraphs();
    Configuration config = Configuration.getDefaultConfiguration().copy();config.setAskQuestions(false);config.setDebugMode(false);config.setGdLowToHighRatio(0.7);config.setRandomPathAttemptFudgeThreshold(1000);
    config.setTransitionMatrixImplType(STATETREE.STATETREE_LINKEDHASH);config.setLearnerScoreMode(ScoreMode.ONLYOVERRIDE);
    ConvertALabel converter = new Transform.InternStringLabel();
    GlobalConfiguration.getConfiguration().setProperty(G_PROPERTIES.LINEARWARNINGS, "false");
    final int ThreadNumber = ExperimentRunner.getCpuNumber(); 
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    mutationStages = mutationStagesArg;graphComplexityMax = graphComplexityMaxArg;
   
  }
 
  public void runExperiment(int initStates, boolean skip){
    DrawGraphs gr = new DrawGraphs();
    this.skipLanguage = skip;
    Random r = new Random(0);

    RBoxPlot<Integer>
      gr_Diff_States = new RBoxPlot<Integer>("States","Diff/Mutations",new File("diff_states.pdf")),
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       pathGen.generatePosNeg(2*(wMethod.size()-wPos), 1);
       wMethod.addAll(pathGen.getExtraSequences(0).getData());
       System.out.println("after rnd: "+wMethod.size()+" sequences");
      
      
       DrawGraphs gr = new DrawGraphs();
    final RBoxPlot<Integer>
        uas_S=new RBoxPlot<Integer>("Time","BCR",new File("time_S_"+name+"_bcr.pdf"));
    Set<Integer> allFrames = collectionOfTraces.get(UAVAllSeeds).tracesForUAVandFrame.get(UAVAllSeeds).keySet();
    ProgressIndicator progress = new ProgressIndicator("UAS", allFrames.size());
   
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    final Collection<List<Label>> wMethod = graphReference.wmethod.getFullTestSet(1);
       
    // Here I need to moderate the effort because choosing traces for all seeds is good but I need
    // that many times more traces, so I have to create a graph in terms of effort v.s. quailty (or even better, scale
    // the existing one).
    DrawGraphs gr = new DrawGraphs();

    final RBoxPlot<Pair<Integer,String>>
      uas_outcome = new RBoxPlot<Pair<Integer,String>>("Time","BCR",new File("time_bcr.pdf"));
    final RBoxPlot<Integer>
          uas_A=new RBoxPlot<Integer>("Time","BCR",new File("time_A_bcr.pdf")),
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  • org.rosuda.JRI.REXP
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  • statechum.analysis.learning.experiments.PairSelection.MarkovPassivePairSelection
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