Examples of statechum.Configuration

statechum.Configuration
Represents a configuration for a learner. The purpose is a possibility of a global customisation of all objects used by a learner in the course of learning by the same object.
When you add to this class, please add the corresponding entries to hashCode and equals.
This class is using the built-in clone method, hence all attributes have to be either primitives or immutable (such as String).

  public final void testChooseStatePairs(String fsm, String [] initialReds, String [][] expectedReds, List<PairScore> expectedPairs, String graphName)
  {
    final DirectedSparseGraph gB = FsmParser.buildGraph(fsm, graphName);
    //Visualiser.updateFrame(new LearnerGraph(gB,Configuration.getDefaultConfiguration()), null);Visualiser.waitForKey();
    // check how the reference pair selection function performs
    Configuration conf = testConfig.copy();conf.setLearnerUseStrings(false);conf.setLearnerCloneGraph(false);
    testChooseStatePairsInternal(gB,new LearnerGraph(gB, conf), initialReds, expectedReds, expectedPairs, new InterfaceChooserToTest() {
      public @Override Stack<StatePair> choosePairs() {// Here I need to convert the old type of pairs to the new one.
        Stack<OrigStatePair> pairs = chooseStatePairs(gB, new HashSet<List<String>>(), new HashSet<List<String>>());
        Stack<StatePair> result = new Stack<StatePair>();
        for(OrigStatePair pair:pairs) result.add(new StatePair((CmpVertex)pair.getQ(),(CmpVertex)pair.getR()));

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  @Test
  public void testAuto0()
  {
    //Visualiser.updateFrame(new LearnerGraph(FsmParser.buildGraph("A-e->A-c->B-b->C-p->G-e->A\nB-a->D-a->E-a->D\nE-b->F-p->G\n"+
    //"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(

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  }  
  
  @Test
  public void testAuto1()
  {
    Configuration testConfig = Configuration.getDefaultConfiguration().copy();
    testConfig.setGdFailOnDuplicateNames(false);
    testConfig.setLearnerIdMode(IDMode.POSITIVE_NEGATIVE);


    final AutoAnswers semiUser = new AutoAnswers(null);
    semiUser.loadAnswers(new StringReader(
        partA
    ));

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  }
  
  @Test
  public void testAuto2()
  {
    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(

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                          if (command.equals(msgDisplayFSM) && message.arity() >= 4) 
                          {
                            OtpErlangObject outcome = null;
                            try
                            {
                              Configuration config = Configuration.getDefaultConfiguration().copy();
                              LearnerGraphND machine = new LearnerGraphND(config);Synapse.StatechumProcess.parseStatemachine(message.elementAt(2),machine,null,true);
                              DirectedSparseGraph fsmPicture = machine.pathroutines.getGraph();
                              if (!fsmPicture.containsUserDatumKey(JUConstants.LAYOUTOPTIONS))
                                fsmPicture.addUserDatum(JUConstants.LAYOUTOPTIONS,new LayoutOptions(), UserData.SHARED);
                              int windowNumber = setOptions(message,3,fsmPicture);

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    assert coregraph.transitionMatrix.containsKey(pair.firstElem);
    assert coregraph.transitionMatrix.containsKey(pair.secondElem);
    Map<CmpVertex,List<CmpVertex>> mergedVertices = coregraph.config.getTransitionMatrixImplType() == STATETREE.STATETREE_ARRAY?
        new ArrayMapWithSearch<CmpVertex,List<CmpVertex>>(coregraph.getStateNumber()):
        new HashMapWithSearch<CmpVertex,List<CmpVertex>>(coregraph.getStateNumber());
    Configuration shallowCopy = coregraph.config.copy();shallowCopy.setLearnerCloneGraph(false);


    long pairScore = coregraph.pairscores.computePairCompatibilityScore_internal(pair,mergedVertices);
    if (pairScore < 0)
      return -1;

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      else
      {// only create a top-level element if writing pure XML.
        outputStream=outStream;
        topElement = doc.createElement(StatechumXML.ELEM_STATECHUM_TESTTRACE.name());doc.appendChild(topElement);topElement.appendChild(AbstractPersistence.endl(doc));
      }
      Configuration seriesConfiguration = config.copy();seriesConfiguration.setGdMaxNumberOfStatesInCrossProduct(0);
      series = new GraphSeries(doc,threadNumber,seriesConfiguration);
    }
    catch(ParserConfigurationException e)
    {
      statechum.Helper.throwUnchecked("failed to construct DOM document",e);

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    @SuppressWarnings("rawtypes")
  @Override
    public void update(@SuppressWarnings("unused") final Observable s, Object arg) {
      int graphNumber = graphs.size();// should match the position of the graph in the list of graphs
        if (arg instanceof AbstractLearnerGraph) {
          Configuration cloneConfig = ((AbstractLearnerGraph) arg).config.copy();
          cloneConfig.setLearnerCloneGraph(true);
          LearnerGraphND gr = new LearnerGraphND((AbstractLearnerGraph)arg,cloneConfig);
          gr.config.setLearnerCloneGraph(false);
          graphsOrig.add( gr );
            graphs.add(((AbstractLearnerGraph) arg).pathroutines.getGraph());
            layoutOptions.put(graphNumber,gr.getLayoutOptions());

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  {
    InitialConfigurationAndData outcome = new InitialConfigurationAndData();
    
    final java.io.FileInputStream inputStream = new java.io.FileInputStream(argPTAFileName);
    final LearnerSimulator simulator = new LearnerSimulator(inputStream,true,converter);
    Configuration defaultConfig = configToUse.copy();
    //defaultConfig.setRejectPositivePairsWithScoresLessThan(1);
    assert converter != null : "we expect this methods to be used with large graphs and Array matrix types hence converter must be set";
    outcome.learnerInitConfiguration = simulator.readLearnerConstructionData(defaultConfig);
    outcome.learnerInitConfiguration.setLabelConverter(converter);

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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);
    ConvertALabel converter = new Transform.InternStringLabel();
    //gr_NewToOrig.setLimit(7000);
    GlobalConfiguration.getConfiguration().setProperty(G_PROPERTIES.LINEARWARNINGS, "false");
    final int ThreadNumber = ExperimentRunner.getCpuNumber();

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Related Classes of statechum.Configuration

statechum.analysis.Erlang.ErlangAppReader

statechum.analysis.Erlang.ErlangModule

statechum.analysis.Erlang.Signatures.TestTypes

statechum.analysis.Erlang.Synapse$StatechumProcess

statechum.analysis.Erlang.TestErlangGraphs

statechum.analysis.Erlang.TestErlangModule

statechum.analysis.Erlang.TestSynapseAuxiliaryFunctions

statechum.analysis.learning.experiments.Benchmarklinear

statechum.analysis.learning.experiments.ExperimentRunner$GeneratorConfiguration

statechum.analysis.learning.experiments.ExperimentRunner$LearnerEvaluator

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