}

      }

      while(pickUniqueFromInitial && uniqueFromInitial == null);

     

      final Collection<List<Label>> testSet = 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);

  public void copyLogIntoAnotherLog(String logFileName)

  {

    try {

      final LearnerSimulator simulator = new LearnerSimulator(new java.io.FileInputStream(logFileName),true);

      final org.w3c.dom.Element nextElement = simulator.expectNextElement(StatechumXML.ELEM_INIT.name());

      final ProgressDecorator.InitialData initial = simulator.readInitialData(nextElement);

      simulator.setNextElement(nextElement);

 

      {

        @Override

        public Pair<Integer,String> CheckWithEndUser(

            @SuppressWarnings("unused")  LearnerGraph model,

            List<String> question,  @SuppressWarnings("unused") int answerForNoRestart,

    if (logFileName.contains(Configuration.LEARNER.LEARNER_BLUEFRINGE_DEC2007.name()))

      VertexID.comparisonKind = ComparisonKind.COMPARISON_LEXICOGRAPHIC_ORIG;// this is a major change in a configuration of learners, affecting the comparison between vertex IDs

    final LearnerSimulator simulator = new LearnerSimulator(new java.io.FileInputStream(logFileName),true);

    // Now we need to choose learner parameters based on the kind of file we are given

    // (given the pace of Statechum evolution, I cannot expect all the correct options

    // to be stored in log files).

    if (logFileName.contains(Configuration.LEARNER.LEARNER_BLUEFRINGE_MAY2008.name()))

    {

      evalData.config.setUseAmber(false);evalData.config.setUseLTL(false);

      evalData.config.setSpeculativeQuestionAsking(false);

      evalData.config.setIgnoreDepthInTheChoiceOfRepresentatives(true);evalData.config.setIgnoreVertexAttributesInLogReplay(true);

    }

    else    

      if (logFileName.contains(Configuration.LEARNER.LEARNER_BLUEAMBER_MAY2008.name()))

      {

        evalData.config.setUseAmber(true);evalData.config.setUseLTL(false);

        evalData.config.setSpeculativeQuestionAsking(false);

        evalData.config.setIgnoreDepthInTheChoiceOfRepresentatives(true);evalData.config.setIgnoreVertexAttributesInLogReplay(true);

      }

      else

        if (logFileName.contains(Configuration.LEARNER.LEARNER_BLUEFRINGE_DEC2007.name()))

        {// we'd like to make sure that the initial configuration is loaded with the correct configuration values.

          evalData.config.setInitialIDvalue(1);

          VertexID.comparisonKind = ComparisonKind.COMPARISON_LEXICOGRAPHIC_ORIG;

          evalData.config.setUseAmber(false);evalData.config.setUseLTL(false);

          evalData.config.setSpeculativeQuestionAsking(false);

          evalData.config.setDefaultInitialPTAName("Init");

          evalData.config.setIgnoreDepthInTheChoiceOfRepresentatives(true);evalData.config.setIgnoreVertexAttributesInLogReplay(true);

        }

        else

          Assert.fail("unknown type of log file");

    final org.w3c.dom.Element nextElement = simulator.expectNextElement(StatechumXML.ELEM_INIT.name());

    final ProgressDecorator.InitialData initial = simulator.readInitialData(nextElement);

    if (evalData.labelDetails != null)

    {

      initial.plus.addAll(evalData.labelDetails.getSPlus());initial.minus.addAll(evalData.labelDetails.getSMinus());

    }

    simulator.setNextElement(nextElement);

    Learner learner2 = null;

    if (logFileName.contains(Configuration.LEARNER.LEARNER_BLUEFRINGE_DEC2007.name()))

    {// have to patch the learner.

     

      {

        /* (non-Javadoc)

         * @see statechum.analysis.learning.observers.DummyLearner#init(java.util.Collection, java.util.Collection)

         */

        @Override

        public LearnerGraph init(Collection<List<String>> plus,  Collection<List<String>> minus)

        {

          return super.init(plus, minus);

        }

        /* (non-Javadoc)

         * @see statechum.analysis.learning.RPNIUniversalLearner#ComputeQuestions(statechum.analysis.learning.PairScore, statechum.analysis.learning.rpnicore.LearnerGraph, statechum.analysis.learning.rpnicore.LearnerGraph)

         */

        @Override

        public List<List<String>> ComputeQuestions(PairScore pair,  LearnerGraph original, LearnerGraph tempNew)

        {

          return ArrayOperations.sort(ComputeQuestions.computeQS_origReduced(pair,original,tempNew));

        }

        /* (non-Javadoc)

         * @see statechum.analysis.learning.RPNIUniversalLearner#MergeAndDeterminize(statechum.analysis.learning.rpnicore.LearnerGraph, statechum.analysis.learning.StatePair)

         */

        @Override

        public LearnerGraph MergeAndDeterminize(LearnerGraph original,  StatePair pair)

        {

          return MergeStates.mergeAndDeterminize(original,pair);

        }

       

        @Override

        public Pair<Integer,String> CheckWithEndUser(

            @SuppressWarnings("unused")  LearnerGraph model,

            List<String> question, @SuppressWarnings("unused") int answerForNoRestart,

            @SuppressWarnings("unused") List<Boolean> acceptedElements,

            @SuppressWarnings("unused")  final Object [] moreOptions)

          {

            return new Pair<Integer,String>(evalData.graph.paths.tracePathPrefixClosed(question),null);

          }

       

        @Override

        public void AugumentPTA_and_QuestionPTA(LearnerGraph pta, RestartLearningEnum ptaKind,

            List<String> sequence, boolean accepted, JUConstants newColour)

        {

          topLevelListener.AugmentPTA(pta, ptaKind, sequence, accepted, newColour);

        }

      };

       

    }

    else

    if (logFileName.contains(Configuration.LEARNER.LEARNER_BLUEFRINGE_MAY2008.name()) ||

        logFileName.contains(Configuration.LEARNER.LEARNER_BLUEAMBER_MAY2008.name())

     )

    {// have to patch the learner.

     

      {

        /* (non-Javadoc)

         * @see statechum.analysis.learning.observers.DummyLearner#init(java.util.Collection, java.util.Collection)

         */

        @Override

 

  public RPNIBlueFringeVariability(final LearnerEvaluationConfiguration evaluationConfiguration, boolean optimisedMerge, final List<PairOfPaths> lw, final List<PairOfPaths> lc)

  {

    listOfPairsToWrite = lw;useOptimizedMerge = optimisedMerge;

    if (lc != null) listOfPairsToCheckAgainstIterator = lc.iterator();else listOfPairsToCheckAgainstIterator = null;

    bfLearnerInitConfiguration.ifthenSequences = evaluationConfiguration.ifthenSequences;

    config = bfLearnerInitConfiguration.config;// our config is a copy of the one supplied as an argument.

    config.setAskQuestions(false);

    learner = new DummyLearner(new RPNIUniversalLearner(null, bfLearnerInitConfiguration))

    {

     

      ThreadResult outcome = new ThreadResult();

      MachineGenerator mg = new MachineGenerator(states, 400 , (int)Math.round((double)states/5));mg.setGenerateConnected(true);

      referenceGraph = mg.nextMachine(alphabet,seed, config, converter).pathroutines.buildDeterministicGraph();// reference graph has no reject-states, because we assume that undefined transitions lead to reject states.

     

      final Collection<List<Label>> testSet = PaperUAS.computeEvaluationSet(referenceGraph,states*3,makeEven(states*tracesAlphabet));

      for(int attempt=0;attempt<2;++attempt)

      {// try learning the same machine a few times

        LearnerGraph pta = new LearnerGraph(config);

      ThreadResult outcome = new ThreadResult();

      MachineGenerator mg = new MachineGenerator(states, 400 , (int)Math.round((double)states/5));mg.setGenerateConnected(true);

      referenceGraph = mg.nextMachine(alphabet,seed, config, converter).pathroutines.buildDeterministicGraph();// reference graph has no reject-states, because we assume that undefined transitions lead to reject states.

     

      final Collection<List<Label>> testSet = PaperUAS.computeEvaluationSet(referenceGraph,states*3,makeEven(states*alphabet));

      for(int attempt=0;attempt<2;++attempt)

      {// try learning the same machine a few times

        LearnerGraph pta = new LearnerGraph(config);

  {

    private static LearnerEvaluationConfiguration constructConfiguration(LearnerEvaluationConfiguration evalCnf, boolean allPaths, int k)

    {

      Configuration config = evalCnf.config.copy();config.setLearnerScoreMode(allPaths? Configuration.ScoreMode.KTAILS:Configuration.ScoreMode.KTAILS_ANY);config.setKlimit(k);

      copy.graph = evalCnf.graph;copy.testSet = evalCnf.testSet;

      copy.ifthenSequences = evalCnf.ifthenSequences;copy.labelDetails=evalCnf.labelDetails;

      return copy;

    }

        }

      }

      while(pickUniqueFromInitial && uniqueFromInitial == null);

     

      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);

      assert AbstractOracle.USER_ACCEPTED == expected.paths.tracePathPrefixClosed(AbstractLearnerGraph.buildList(Arrays.asList(path),config,getLabelConverter()));

    for(String [] path:minus)

      assert AbstractOracle.USER_ACCEPTED != expected.paths.tracePathPrefixClosed(AbstractLearnerGraph.buildList(Arrays.asList(path),config,getLabelConverter()));

    // Visualiser.getVisualiser()

    {

      @Override

      public LearnerGraph MergeAndDeterminize(LearnerGraph original, StatePair pair)

      {

        // Check that compatibility score computation gives the same response as if we did merge and computed a difference between the number of states.

    ByteArrayOutputStream output = new ByteArrayOutputStream();

    RecordProgressDecorator dumper = new RecordProgressDecorator(null,output,1,Configuration.getDefaultConfiguration(),false);

    dumper.topElement.appendChild(dumper.writeLearnerEvaluationConfiguration(

   

    xmlData = output.toString();

  }