Package statechum.analysis.learning.rpnicore.WMethod

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

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    OtpErlangObject difference = DifferenceVisualiser.ChangesToGraph.computeGD(grA, grB, config);
    Assert.assertEquals("{'statemachinedifference',[{'P1000','a','P1001'}],[{'P1000','a','P1000'}],['P1001','N1000'],['P1002'],[],'P1000'}",ErlangLabel.dumpErlangObject(difference));

    LearnerGraphND shouldBeLikePrevious = new LearnerGraphND(grA,config);
    DifferenceVisualiser.ChangesToGraph.load(difference).applyDiff(shouldBeLikePrevious, config);
    DifferentFSMException ex = WMethod.checkM(grB, shouldBeLikePrevious);
    Assert.assertNull(ex);Assert.assertEquals(grB.getStateNumber(),shouldBeLikePrevious.getStateNumber());
  }
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    OtpErlangObject difference = DifferenceVisualiser.ChangesToGraph.computeGD(grA, grB, config);
    Assert.assertEquals("{'statemachinedifference',[{'P1000','a','P1001'}],[{'P1000','a','P1000'}],['P1001'],['N1000','P1002'],[],'P1000'}",ErlangLabel.dumpErlangObject(difference));

    LearnerGraphND shouldBeLikePrevious = new LearnerGraphND(grA,config);
    DifferenceVisualiser.ChangesToGraph.load(difference).applyDiff(shouldBeLikePrevious, config);
    DifferentFSMException ex = WMethod.checkM(grB, shouldBeLikePrevious);
    Assert.assertNull(ex);Assert.assertEquals(grB.getStateNumber(),shouldBeLikePrevious.getStateNumber());
  }
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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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    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.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.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.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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    Assert.assertNull(result);
  }
 
  static void compareGraphs(LearnerGraph A, LearnerGraph B)
  {
    DifferentFSMException ex= WMethod.checkM_and_colours(A, B, VERTEX_COMPARISON_KIND.NONE);
    Assert.assertNull(ex==null?"":ex.toString(),ex);
   
    // reachability of all states ensures that transition structures are isomorphic.
    Assert.assertEquals(A.getStateNumber(),A.pathroutines.computeShortPathsToAllStates().size());
    Assert.assertEquals(B.getStateNumber(),B.pathroutines.computeShortPathsToAllStates().size());
  }
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