Package statechum.analysis.learning.observers.ProgressDecorator

Examples of statechum.analysis.learning.observers.ProgressDecorator.LearnerEvaluationConfiguration

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  @Test
  public final void testLearnerEvaluation12()
  {
    ByteArrayOutputStream output = new ByteArrayOutputStream();
    RecordProgressDecorator dumper = new RecordProgressDecorator(null,output,1,Configuration.getDefaultConfiguration(),false);
    Element learnerConfig = dumper.writeLearnerEvaluationConfiguration(new LearnerEvaluationConfiguration(graph,testData,anotherconfig,ltl,labels));
    learnerConfig.appendChild(labels.storeToXML(dumper.doc));
    dumper.topElement.appendChild(learnerConfig);dumper.close();xmlData = output.toString();
   
    final LearnerSimulator loader = new LearnerSimulator(new ByteArrayInputStream(xmlData.getBytes()),false);
    checkForCorrectException(new whatToRun() { public @Override void run() {
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    // now sanity checking on the plus and minus sets
    for(String [] path:plus)
      assert AbstractOracle.USER_ACCEPTED == expected.paths.tracePathPrefixClosed(Arrays.asList(path));
    for(String [] path:minus)
      assert AbstractOracle.USER_ACCEPTED != expected.paths.tracePathPrefixClosed(Arrays.asList(path));
    Learner l = new RPNIUniversalLearner(null,new LearnerEvaluationConfiguration(null,null,testConfig,null,null))
    {
      @Override
      public Pair<Integer,String> CheckWithEndUser(
          @SuppressWarnings("unused")  LearnerGraph model,
          List<String> question, @SuppressWarnings("unused") int responseForNoRestart,
          @SuppressWarnings("unused") List<Boolean> acceptedElements,
          @SuppressWarnings("unused")  final Object [] moreOptions)
      {
        return new Pair<Integer,String>(expected.paths.tracePathPrefixClosed(question),null);
      }
    };
    testConfig.setLearnerIdMode(IDMode.POSITIVE_NEGATIVE);
    ByteArrayOutputStream logStream = new ByteArrayOutputStream();
    RecordProgressDecorator recorder = new RecordProgressDecorator(l,logStream,1,testConfig,useZip);
    Collection<List<String>> testSet = new LinkedList<List<String>>();
    recorder.writeLearnerEvaluationData(new LearnerEvaluationConfiguration(expected, testSet, testConfig, null, null));
    LearnerGraph learntStructureA = recorder.learnMachine(buildSet(plus), buildSet(minus));
   
    //System.out.println("compression rate: "+recorder.getCompressionRate());
    //System.out.println(logStream.toString()+"============");
    //System.out.println(logStream.toByteArray().length);
    LearnerGraph learntMachineNoRejects = new LearnerGraph(testConfig);
    AbstractPathRoutines.removeRejectStates(learntStructureA,learntMachineNoRejects);
    Assert.assertNull(WMethod.checkM(learntMachineNoRejects, expected));
   
    switch(kind)
    {
      case RECORDERTEST_SS:
      {// matching two simulators
        final LearnerSimulator
          simulator = new LearnerSimulator(new ByteArrayInputStream(logStream.toByteArray()),useZip),
          simulator2 = new LearnerSimulator(new ByteArrayInputStream(logStream.toByteArray()),useZip);
       
        LearnerEvaluationConfiguration eval1 = simulator.readLearnerConstructionData();
        Assert.assertNull(WMethod.checkM(expected, eval1.graph));
        Assert.assertEquals(testSet, eval1.testSet);
        Assert.assertEquals(expected.config, testConfig);
        LearnerEvaluationConfiguration eval2 = simulator2.readLearnerConstructionData();
        Assert.assertNull(WMethod.checkM(expected, eval2.graph));
        Assert.assertEquals(testSet, eval2.testSet);
        Assert.assertEquals(expected.config, testConfig);
       
        new Test_LearnerComparator(simulator,simulator2,true).learnMachine(buildSet(plus), buildSet(minus));
        break;
      }
     
      case RECORDERTEST_SL:
      {// now a simulator to a learner
        final LearnerSimulator simulator = new LearnerSimulator(new ByteArrayInputStream(logStream.toByteArray()),useZip);
        LearnerEvaluationConfiguration eval1 = simulator.readLearnerConstructionData();
        Assert.assertNull(WMethod.checkM(expected, eval1.graph));
        Assert.assertEquals(testSet, eval1.testSet);
        Assert.assertEquals(expected.config, testConfig);
 
        Learner learner2 = new RPNIUniversalLearner(null,new LearnerEvaluationConfiguration(null,null,expected.config,null,null))
        {
          @Override
          public Pair<Integer,String> CheckWithEndUser(
              @SuppressWarnings("unused")  LearnerGraph model,
              List<String> question, @SuppressWarnings("unused") int responseForNoRestart,
              @SuppressWarnings("unused") List<Boolean> acceptedElements,
              @SuppressWarnings("unused")  final Object [] moreOptions)
          {
            return new Pair<Integer,String>(expected.paths.tracePathPrefixClosed(question),null);
          }
        };
        new Test_LearnerComparator(learner2,simulator,true).learnMachine(buildSet(plus), buildSet(minus));
        break;
      }

      case RECORDERTEST_LL:
      {// now two learners
        Learner learnerA = new RPNIUniversalLearner(null,new LearnerEvaluationConfiguration(null,null,testConfig,null,null))
        {
          @Override
          public Pair<Integer,String> CheckWithEndUser(
              @SuppressWarnings("unused")  LearnerGraph model,
              List<String> question, @SuppressWarnings("unused") int responseForNoRestart,
              @SuppressWarnings("unused") List<Boolean> acceptedElements,
              @SuppressWarnings("unused")  final Object [] moreOptions)
          {
            return new Pair<Integer,String>(expected.paths.tracePathPrefixClosed(question),null);
          }
        };
        Learner learnerB = new RPNIUniversalLearner(null,new LearnerEvaluationConfiguration(null,null,testConfig,null,null))
        {
          @Override
          public Pair<Integer,String> CheckWithEndUser(
              @SuppressWarnings("unused")  LearnerGraph model,
              List<String> question, @SuppressWarnings("unused") int responseForNoRestart,
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    //"B-e->A\nC-e->A\nD-e->A\nE-e->A\nF-e->A\nG-e->A\n","testAutoAnswers0"),Configuration.getDefaultConfiguration()),null);
    Configuration testConfig = Configuration.getDefaultConfiguration().copy();
    testConfig.setGdFailOnDuplicateNames(false);
    testConfig.setLearnerIdMode(IDMode.POSITIVE_NEGATIVE);

    RPNILearner learner = new RPNIUniversalLearner(null,new LearnerEvaluationConfiguration(null,null,testConfig,null,null))
    {
      @Override
      public Pair<Integer,String> CheckWithEndUser(
          @SuppressWarnings("unused")  LearnerGraph model,
          List<String> question, @SuppressWarnings("unused") int responseForNoRestart,
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    final AutoAnswers semiUser = new AutoAnswers(null);
    semiUser.loadAnswers(new StringReader(
        partA
    ));
   
    RPNILearner learner = new RPNIUniversalLearner(null,new LearnerEvaluationConfiguration(null,null,testConfig,null,null))
    {
      @Override
      public Pair<Integer,String> CheckWithEndUser(
          @SuppressWarnings("unused")  LearnerGraph model,
          List<String> question, @SuppressWarnings("unused") int responseForNoRestart,
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  {
    Configuration testConfig = Configuration.getDefaultConfiguration().copy();
    testConfig.setGdFailOnDuplicateNames(false);
    testConfig.setLearnerIdMode(IDMode.POSITIVE_NEGATIVE);

    RPNILearner learner = new RPNIUniversalLearner(null,new LearnerEvaluationConfiguration(null,null,testConfig,null,null))
    {
      @Override
      public Pair<Integer,String> CheckWithEndUser(
          @SuppressWarnings("unused")  LearnerGraph model,
          @SuppressWarnings("unused")  List<String> question, @SuppressWarnings("unused") int responseForNoRestart,
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    for(String [] path:plus)
      assert AbstractOracle.USER_ACCEPTED == expected.paths.tracePathPrefixClosed(Arrays.asList(path));
    for(String [] path:minus)
      assert AbstractOracle.USER_ACCEPTED != expected.paths.tracePathPrefixClosed(Arrays.asList(path));
    // Visualiser.getVisualiser()
    Learner l = new RPNIUniversalLearner(null,new LearnerEvaluationConfiguration(null,null,testConfig,null,null))
    {
      @Override
      public Pair<Integer,String> CheckWithEndUser(
          @SuppressWarnings("unused")  LearnerGraph model,
          List<String> question, @SuppressWarnings("unused") int valueForNoRestart,
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          }
        }
      }
      while(pickUniqueFromInitial && uniqueFromInitial == null);
     
      LearnerEvaluationConfiguration learnerEval = new LearnerEvaluationConfiguration(config);learnerEval.setLabelConverter(converter);
      final Collection<List<Label>> testSet = null;//PaperUAS.computeEvaluationSet(referenceGraph,states*3,states*alphabet);
     
      for(int attempt=0;attempt<2;++attempt)
      {// try learning the same machine a few times
        LearnerGraph pta = new LearnerGraph(config);
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  public static class EDSMReferenceLearner extends LearnerThatCanClassifyPairs
  {
    private static LearnerEvaluationConfiguration constructConfiguration(LearnerEvaluationConfiguration evalCnf, int threshold)
    {
      Configuration config = evalCnf.config.copy();config.setRejectPositivePairsWithScoresLessThan(threshold);
      LearnerEvaluationConfiguration copy = new LearnerEvaluationConfiguration(config);
      copy.graph = evalCnf.graph;copy.testSet = evalCnf.testSet;
      copy.setLabelConverter(evalCnf.getLabelConverter());
      copy.ifthenSequences = evalCnf.ifthenSequences;copy.labelDetails=evalCnf.labelDetails;
      return copy;
    }
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    }

    try
    {
      Configuration config = mainConfiguration.copy();
      RPNIUniversalLearner l = new RPNIUniversalLearner(null,new LearnerEvaluationConfiguration(null,null,config,null,null));
      config.setLearnerIdMode(Configuration.IDMode.POSITIVE_NEGATIVE);
      l.init(plusStrings, minusStrings);
      actualC = l.getTentativeAutomaton().pathroutines.getGraph();
    }
    catch(IllegalArgumentException e)
    {
      // ignore this - it might be expected.
      eC = e;
    }

    try
    {
      Configuration config = mainConfiguration.copy();
      RPNIUniversalLearner l = new RPNIUniversalLearner(null,new LearnerEvaluationConfiguration(null,null,config,null,null));
      config.setLearnerIdMode(Configuration.IDMode.POSITIVE_NEGATIVE);
      PTASequenceEngine engine = buildPTA(plusStrings, minusStrings);
      checkPTAConsistency(engine, plusStrings, true);if (engine.numberOfLeafNodes()>0) checkPTAConsistency(engine, minusStrings, false);
      l.init(engine,0,0);
      actualD = l.getTentativeAutomaton().pathroutines.getGraph();
    }
    catch(IllegalArgumentException e)
    {
      // ignore this - it might be expected.
      eD = e;
    }

    try
    {
      Configuration config = mainConfiguration.copy();
      RPNIUniversalLearner l = new RPNIUniversalLearner(null,new LearnerEvaluationConfiguration(null,null,config,null,null));
      config.setLearnerIdMode(Configuration.IDMode.POSITIVE_NEGATIVE);
      l.init(buildPTA(plusStrings, buildSet(new String[][] {},config,converter)),0,0);
      for(List<Label> seq:minusStrings)
      {
        Set<List<Label>> negativeSeq = new HashSet<List<Label>>();negativeSeq.add(seq);
        l.getTentativeAutomaton().paths.augmentPTA(buildPTA(buildSet(new String[][] {},config,converter),negativeSeq));
      }
      actualE = l.getTentativeAutomaton().pathroutines.getGraph();
    }
    catch(IllegalArgumentException e)
    {
      // ignore this - it might be expected.
      eE = e;
    }

    try
    {
      Configuration config = mainConfiguration.copy();
      RPNIUniversalLearner l = new RPNIUniversalLearner(null,new LearnerEvaluationConfiguration(null,null,config,null,null));
      config.setLearnerIdMode(Configuration.IDMode.POSITIVE_NEGATIVE);
      l.getTentativeAutomaton().initPTA();
      l.getTentativeAutomaton().paths.augmentPTA(minusStrings, false,true);
      l.getTentativeAutomaton().paths.augmentPTA(plusStrings, true,true);
      actualF = l.getTentativeAutomaton().pathroutines.getGraph();
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  /** Make sure that we can augment a graph with a single state which is a reject-state. */
  @Test
  public void testPTAconstruction_singleRejectState()
  {
    Configuration config = mainConfiguration.copy();
    RPNIUniversalLearner l = new RPNIUniversalLearner(null,new LearnerEvaluationConfiguration(null,null,config,null,null));
    config.setLearnerIdMode(Configuration.IDMode.POSITIVE_NEGATIVE);
    // set the initial state to be reject
    l.getTentativeAutomaton().initPTA();l.getTentativeAutomaton().getVertex(new LinkedList<Label>()).setAccept(false);
    // and check how augmentPTA works with such a PTA
    for(boolean maxAutomaton:new boolean[]{true,false})
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Related Classes of statechum.analysis.learning.observers.ProgressDecorator.LearnerEvaluationConfiguration

  • statechum.analysis.Erlang.Synapse$StatechumProcess
  • statechum.analysis.Erlang.TestErlangModule
  • statechum.analysis.learning.experiments.IncrementalAccuracyAndQuestionsExperiment$RPNIEvaluator
  • statechum.analysis.learning.experiments.IterativeEvaluatorExperiment$IterativeEvaluator
  • statechum.analysis.learning.experiments.ManualAccuracyTracker
  • statechum.analysis.learning.experiments.PairSelection.ASE2014$EDSM_MarkovLearner
  • statechum.analysis.learning.experiments.PairSelection.ASE2014$LearnerRunner
  • statechum.analysis.learning.experiments.PairSelection.Cav2014$EDSMReferenceLearner
  • statechum.analysis.learning.experiments.PairSelection.Cav2014$EvaluationOfExisingLearnerRunner
  • statechum.analysis.learning.experiments.PairSelection.Cav2014$KTailsReferenceLearner
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