Package statechum.model.testset.PTASequenceEngine

Examples of statechum.model.testset.PTASequenceEngine.SequenceSet.cross()

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  @Test
  public final void test_sequenceSet5_1() // a more complex composition
  {
    SequenceSet seq = en.new SequenceSet();seq.setIdentity();
    seq.cross(TestFSMAlgo.buildList(new String[][] {
        new String[] {"a","b","c"}
    },mainConfiguration,converter)).crossWithSet(new LinkedList<Label>());
    Map<String,String> actual = getDebugDataMap(en,en.new SequenceSet().cross(TestFSMAlgo.buildList(new String[][] {// here the new sequenceSet is empty, hence whatever I do, there should be no changes
        new String[] {"a","b","c","d"},
        new String[] {"c"}
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    ));
    SequenceSet seqStart2 = en.new SequenceSet();seqStart2.crossWithSequence(labelList(
        new String[] {"t"}
    ));
    SequenceSet seqDifferent1 = en.new SequenceSet();seqDifferent1.setIdentity();
    SequenceSet seqDifferent2 = en.new SequenceSet();seqDifferent2.setIdentity();seqDifferent2.cross(TestFSMAlgo.buildList(new String[][] {
        new String[] {"a"}
       
    },mainConfiguration,converter));
    equalityTestingHelper(seqStart1,seqStart2,seqDifferent1,seqDifferent2, true);
  }
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      LearnerGraph learnt = learn(l,sMinus);
      PTA_computePrecisionRecall precRec = new PTA_computePrecisionRecall(learnt);
      PTASequenceEngine engine = new PTA_FSMStructure(graph,null);
      precRec.crossWith(sMinus);PosNegPrecisionRecall ptaPR = precRec.getPosNegPrecisionRecallNum();
      SequenceSet ptaTestSet = engine.new SequenceSet();ptaTestSet.setIdentity();
      ptaTestSet = ptaTestSet.cross(graph.wmethod.getFullTestSet(1));
      precRec.crossWith(engine);PosNegPrecisionRecall prNeg = precRec.getPosNegPrecisionRecallNum();
     
      assert questionNumber.get() == l.getQuestionCounter();
     
      // Column 0 is the name of the learner.
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    characterisationSet = computeWSet_reducedmemory(coregraph);if (characterisationSet.isEmpty()) characterisationSet.add(Arrays.asList(new Label[]{}));
    transitionCover = crossWithSet(stateCover,alphabet);transitionCover.addAll(stateCover);

    PTASequenceEngine engine = new PTA_FSMStructure(coregraph,initialState);
    SequenceSet partialPTA = engine.new SequenceSet();partialPTA.setIdentity();
    partialPTA = partialPTA.cross(stateCover);
   
    partialPTA.cross(characterisationSet);
    for(int i=0;i<=numberOfExtraStates;i++)
    {
      partialPTA = partialPTA.crossWithSet(alphabet);
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    PTASequenceEngine engine = new PTA_FSMStructure(coregraph,initialState);
    SequenceSet partialPTA = engine.new SequenceSet();partialPTA.setIdentity();
    partialPTA = partialPTA.cross(stateCover);
   
    partialPTA.cross(characterisationSet);
    for(int i=0;i<=numberOfExtraStates;i++)
    {
      partialPTA = partialPTA.crossWithSet(alphabet);
      partialPTA.cross(characterisationSet);
    }
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    partialPTA.cross(characterisationSet);
    for(int i=0;i<=numberOfExtraStates;i++)
    {
      partialPTA = partialPTA.crossWithSet(alphabet);
      partialPTA.cross(characterisationSet);
    }
   
    return engine;
  }
 
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      LearnerGraph learnt = learn(l,sMinus);
      PTA_computePrecisionRecall precRec = new PTA_computePrecisionRecall(learnt);
      PTASequenceEngine engine = new PTA_FSMStructure(graph,null);
      precRec.crossWith(sMinus);PosNegPrecisionRecall ptaPR = precRec.getPosNegPrecisionRecallNum();
      SequenceSet ptaTestSet = engine.new SequenceSet();ptaTestSet.setIdentity();
      ptaTestSet = ptaTestSet.cross(graph.wmethod.getFullTestSet(1));
      precRec.crossWith(engine);PosNegPrecisionRecall prNeg = precRec.getPosNegPrecisionRecallNum();
     
      assert questionNumber.get() == l.getQuestionCounter();
     
      // Column 0 is the name of the learner.
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                Set<List<Label>> traceData = traces.get(uav).get(earlierFrame);
               
                if (traceData != null)
                {
                  SequenceSet initSeq = traceDetailsUAV.new SequenceSet();initSeq.setIdentity();((Automaton)traceDetailsUAV.getFSM()).setAccept(isAccept);
                  initSeq.cross(traceData);
                }
               }
            }
          }
        }
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    generator.generateRandomPosNeg(posOrNegPerChunk*2,1);
    Collection<List<Label>> sequences = cvsGraph.wmethod.getFullTestSet(1);//generator.getAllSequences(0).getData(PTASequenceEngine.truePred);

    PTASequenceEngine walkEngine = new PTA_FSMStructure(cvsGraph,null);
    SequenceSet ptaWalk = walkEngine.new SequenceSet();ptaWalk.setIdentity();
    ptaWalk = ptaWalk.cross(sequences);
   
   
   
    PTA_computePrecisionRecall precRec = null;
   
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      PTASequenceEngine engine = null;
      if (!useNegatives)
      {
        PTASequenceEngine positives = new PTASequenceEngine();positives.init(new Automaton());
          SequenceSet initSeq = positives.new SequenceSet();initSeq.setIdentity();
          initSeq.cross(engineArg.getData());
          engine = positives;
      }
      else
        engine = engineArg;
     
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