Examples of statechum.analysis.learning.MarkovClassifier.constructMarkovTentative()

Class statechum.analysis.learning.MarkovClassifier

Examples of statechum.analysis.learning.MarkovClassifier.constructMarkovTentative()

statechum.analysis.learning.MarkovClassifier.constructMarkovTentative()
This function is predicts transitions from each state and then adds them to the supplied graph. Uses predictions from the model to add transitions without a second thought.
Can only be used to predict transition forward since inverse expects disconnected states to be added and QSM is not expected to deal with such states. We could certainly attempt to merge them somewhere but this seems to make little sense.
- Where predictForward is true, we are predicting transitions based on paths leading to the state of interest. Parameter Inverse_Graph should be the (non-deterministic) inverse of graph.
- Where predictForward is false, we are predicting transitions based on paths leading from the state of interest (sideways predictions). Parameter Inverse_Graph should be the same as graph.
directionForwardOrInverse determines whether to merge states identified with the supplied outgoing transitions or those that the supplied transitions lead into. For instance, one might frequently have a reset transition and all its target states could be merged together. @return the graph with predicted transitions added to it.

    Assert.assertSame(MarkovOutcome.negative, newTransitions.get(graph.findVertex("B")).get(lblU));
    
    Assert.assertSame(MarkovOutcome.positive, newTransitions.get(graph.findVertex("B")).get(lblB));


    final LearnerGraph expected = FsmParser.buildLearnerGraph("A-a->B-b->C / B-u-#D / T-b->T-u->T","testConstructExtendedGraph3b",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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    Assert.assertFalse(newTransitions.get(graph.findVertex("B")).containsKey(lblU));// failure ignored
    
    Assert.assertSame(MarkovOutcome.positive, newTransitions.get(graph.findVertex("B")).get(lblB));


    final LearnerGraph expected = FsmParser.buildLearnerGraph("A-a->B-b->C / T-b->T-u->T","testConstructExtendedGraph4b",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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    Assert.assertEquals(1,newTransitions.get(graph.findVertex("B")).size());
    
    Assert.assertSame(MarkovOutcome.positive,newTransitions.get(graph.findVertex("B")).get(lblB));


    final LearnerGraph expected = FsmParser.buildLearnerGraph("A-a->B-b->C / A-w->M-c->B / T-b->T-u->T","testConstructExtendedGraph5b",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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    Assert.assertEquals(1,newTransitions.get(graph.findVertex("B")).size());
    
    Assert.assertSame(MarkovOutcome.positive, newTransitions.get(graph.findVertex("B")).get(lblB));


    final LearnerGraph expected = FsmParser.buildLearnerGraph("A-a->B / A-c->B / B-b->C / T-b->T-u->T","testConstructExtendedGraph6b",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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    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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