Package statechum.analysis.learning.rpnicore.WMethod

Examples of statechum.analysis.learning.rpnicore.WMethod.DifferentFSMException

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    String graphSrc = "M1-c->C1 / M1-a->A1-b->M2-c->C2-a->A3-b->M4-c->C4-a->A4 / M2-a->A2-b->M3-c->C3-d-#D / M2-b->B";
    final LearnerGraph graph = FsmParser.buildLearnerGraph(graphSrc,"testCconstructPairsToMergeWithOutgoing1",mainConfiguration, converter),
        graphCopy = FsmParser.buildLearnerGraph(graphSrc,"testCconstructPairsToMergeWithOutgoing1",mainConfiguration, converter);// create a completely unrelated graph with same states and structure
    LearnerGraph actual = PairQualityLearner.mergeStatesForUnique(graph, AbstractLearnerGraph.generateNewLabel("c", mainConfiguration,converter));
    final LearnerGraph expected = FsmParser.buildLearnerGraph("M1-c->C1-d-#D / C1-a->A3-b->M4-c->P03 /  M1-a->A1-b->M2-c->C2 / M2-a->A2-b->M3-c->C3 / M2-b->B","testMergeStatesForUniqueFromInitial1b",mainConfiguration, converter);
    DifferentFSMException ex = WMethod.checkM(expected, actual);
    if (ex != null)
      throw ex;
    ex = WMethod.checkM(graphCopy, graph);
    if (ex != null)
      throw ex;
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    String graphSrc = "M1-c->C1 / M1-a->A1-b->M2-c->C2-a->A3-b->M4-c->C4-a->A4 / M2-a->A2-b->M3-c->C3-d-#D / M2-b->B";
    final LearnerGraph graph = FsmParser.buildLearnerGraph(graphSrc,"testCconstructPairsToMergeWithOutgoing1",mainConfiguration, converter),
        graphCopy = FsmParser.buildLearnerGraph(graphSrc,"testCconstructPairsToMergeWithOutgoing1",mainConfiguration, converter);// create a completely unrelated graph with same states and structure
    final LearnerGraph expected = FsmParser.buildLearnerGraph("M1-c->C1 / M1-a->A1-b->M2-c->C2-a->A3-b->M4-c->C4-a->A4 / M2-a->A2-b->M3-c->C3-d-#D / M2-b->B","testCconstructPairsToMergeWithOutgoing1",mainConfiguration, converter);
    LearnerGraph actual = PairQualityLearner.mergeStatesForUnique(graph, AbstractLearnerGraph.generateNewLabel("d", mainConfiguration,converter));
    DifferentFSMException ex = WMethod.checkM(expected, actual);
    if (ex != null)
      throw ex;
    ex = WMethod.checkM(graphCopy, graph);
    if (ex != null)
      throw ex;
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    Assert.assertSame(MarkovOutcome.positive, newTransitions.get(graph.findVertex("B")).get(lblB));
    Assert.assertSame(MarkovOutcome.positive, newTransitions.get(graph.findVertex("Z")).get(lblU));

    final LearnerGraph expected = FsmParser.buildLearnerGraph("A-a->B / A-c->B-c->Z-u->Y / B-b->C / T-b->T-u->T","testConstructExtendedGraph7b",config, converter);
    LearnerGraph actual = cl.constructMarkovTentative();
    DifferentFSMException ex = WMethod.checkM(expected, actual);
    if (ex != null)
      throw ex;
    Assert.assertNotSame(graph, actual);
  }
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    graph.config.setLearnerIdMode(Configuration.IDMode.POSITIVE_NEGATIVE);
    graph.paths.augmentPTA(minusStrings, false,true);

    final LearnerGraph expected = new LearnerGraph(mainConfiguration.copy());
    expected.getVertex(new LinkedList<Label>()).setAccept(false);
    DifferentFSMException result = WMethod.checkM(expected,graph);
    Assert.assertNull(result);
    checkDepthLabelling(graph);
  }
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    fsm.pairscores.computePairCompatibilityScore_general(null,Arrays.asList(new StatePair[]{
        new StatePair(fsm.findVertex("I"),fsm.findVertex("A1")),new StatePair(fsm.findVertex("I"),fsm.findVertex("B1")),new StatePair(fsm.findVertex("I"),fsm.findVertex("C1"))
        }), verticesToMerge);
    LearnerGraph mergeOutcome =  MergeStates.mergeCollectionOfVertices(fsm, null, verticesToMerge);
    LearnerGraph expected = FsmParser.buildLearnerGraph("I-d->I-b->I-c->I / I-a->B2-b->B3-c->C1", "testPairCompatible_general_Eb",config,getLabelConverter());
    DifferentFSMException diffEx = WMethod.checkM(expected, mergeOutcome);
    if (diffEx != null)
      throw diffEx;
   
    // Now test the "lite" version of state merging routine.
    LearnerGraph merge2 = MergeStates.mergeCollectionOfVerticesNoUpdateOfAuxiliaryInformation(fsm, verticesToMerge);
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    fsm.pairscores.computePairCompatibilityScore_general(null,Arrays.asList(new StatePair[]{
        new StatePair(fsm.findVertex("I"),fsm.findVertex("A1")),new StatePair(fsm.findVertex("I"),fsm.findVertex("B1")),new StatePair(fsm.findVertex("I"),fsm.findVertex("C1"))
        }), verticesToMerge);
    LearnerGraph mergeOutcome =  MergeStates.mergeCollectionOfVertices(fsm, null, verticesToMerge);
    LearnerGraph expected = FsmParser.buildLearnerGraph("I-b->I-c->I / I-a->I", "testPairCompatible_general_Fb",config,getLabelConverter());
    DifferentFSMException diffEx = WMethod.checkM(expected, mergeOutcome);
    if (diffEx != null)
      throw diffEx;

    // Now test the "lite" version of state merging routine.
    LearnerGraph merge2 = MergeStates.mergeCollectionOfVerticesNoUpdateOfAuxiliaryInformation(fsm, verticesToMerge);
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    fsm.pairscores.computePairCompatibilityScore_general(null,Arrays.asList(new StatePair[]{
        new StatePair(fsm.findVertex("I"),fsm.findVertex("A1")),new StatePair(fsm.findVertex("I"),fsm.findVertex("B1")),new StatePair(fsm.findVertex("I"),fsm.findVertex("C1"))
        }), verticesToMerge);
    LearnerGraph mergeOutcome =  MergeStates.mergeCollectionOfVertices(fsm, null, verticesToMerge);
    LearnerGraph expected = FsmParser.buildLearnerGraph("I-d->I-b->I-c->I / I-a->B2-b->B3-c->C1 / I-e->B2", "testPairCompatible_general_Gb",config,getLabelConverter());
    DifferentFSMException diffEx = WMethod.checkM(expected, mergeOutcome);
    if (diffEx != null)
      throw diffEx;

    // Now test the "lite" version of state merging routine.
    LearnerGraph merge2 = MergeStates.mergeCollectionOfVerticesNoUpdateOfAuxiliaryInformation(fsm, verticesToMerge);
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    fsm.pairscores.computePairCompatibilityScore_general(null,Arrays.asList(new StatePair[]{
        new StatePair(fsm.findVertex("I"),fsm.findVertex("A1")),new StatePair(fsm.findVertex("I"),fsm.findVertex("B1")),new StatePair(fsm.findVertex("I"),fsm.findVertex("C1"))
        }), verticesToMerge);
    LearnerGraph mergeOutcome =  MergeStates.mergeCollectionOfVertices(fsm, null, verticesToMerge);
    LearnerGraph expected = FsmParser.buildLearnerGraph("I-b->I-c->I / I-a->I-d->I", "testPairCompatible_general_Hb",config,getLabelConverter());
    DifferentFSMException diffEx = WMethod.checkM(expected, mergeOutcome);
    if (diffEx != null)
      throw diffEx;

    // Now test the "lite" version of state merging routine.
    LearnerGraph merge2 = MergeStates.mergeCollectionOfVerticesNoUpdateOfAuxiliaryInformation(fsm, verticesToMerge);
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    MarkovClassifier cl = new MarkovClassifier(m,graph);
    Map<CmpVertex, Map<Label, MarkovOutcome>> newTransitions = cl.predictTransitions();
    Assert.assertTrue(newTransitions.isEmpty());// not enough evidence to update, hence nothing should be recorded.
    final LearnerGraph expected = FsmParser.buildLearnerGraph("A-u->B-p->B","testConstructExtendedGraph1",config, converter);
    LearnerGraph actual = cl.constructMarkovTentative();
    DifferentFSMException ex = WMethod.checkM(expected, actual);
    if (ex != null)
      throw ex;
    Assert.assertNotSame(graph, actual);
  }
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    MarkovClassifier cl = new MarkovClassifier(m,graph);
    Map<CmpVertex, Map<Label, MarkovOutcome>> newTransitions = cl.predictTransitions();
    Assert.assertTrue(newTransitions.isEmpty());// not enough evidence to update, hence nothing should be recorded.
    final LearnerGraph expected = FsmParser.buildLearnerGraph("A-a->B","testConstructExtendedGraph2",config, converter);
    LearnerGraph actual = cl.constructMarkovTentative();
    DifferentFSMException ex = WMethod.checkM(expected, actual);
    if (ex != null)
      throw ex;
    Assert.assertNotSame(graph, actual);
  }
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