Examples of statechum.analysis.learning.rpnicore.LearnerGraphND$ignoreZeroClass

Package statechum.analysis.learning.rpnicore

Examples of statechum.analysis.learning.rpnicore.LearnerGraphND$ignoreZeroClass

statechum.analysis.learning.rpnicore.LearnerGraphND
Ignores all states with no outgoing transitions to accept-states. The main idea is to eliminate as many states as possible for the construction of a matrix. A pair consisting of an arbitrary state and a reject state will never have positive scores, either INCOMPATIBLE (if the former is an accept) or a zero (if the former is reject) because there are no outgoing transitions from reject states. The same can be said if the latter state is an accept one but without outgoing transitions - there will also be no matched transitions. If there are some outgoing transitions from a state, it cannot be ignored since any transitions leading to it (if there is none, we should've not included it in a graph anyway) may be matched by transitions from some other states and a score associated with the pair may be needed for computation of a score of a pair with matched transitions leading to this state.

        }
        if(!found)
          throw new RuntimeException();//adjustArtificialTargetSize();
      }
      
      LearnerGraphND outcome = new LearnerGraphND(machine.config);AbstractLearnerGraph.copyGraphs(machine,outcome);
      return outcome;
    }

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  {
    this.forwards = argForward;this.backwards = argBackward;selfLoop=argSelfloop;
    if(!(argForward > 0 && argForward < 1) || !(argBackward > 0 && argBackward <= 1))
      throw new IllegalArgumentException("invalid scopes for backwards or forwards");
    visited = new HashSet<CmpVertex>();
    machine = new LearnerGraphND(Configuration.getDefaultConfiguration());
    vertices = new ArrayList<CmpVertex>();
    generator  = new MersenneTwister(seed);
    this.alphabet = alphabet;
    boolGenerator = new Random(seed);
    CmpVertex v= AbstractLearnerGraph.generateNewCmpVertex(new VertexID(VertexID.VertKind.NEUTRAL,0), Configuration.getDefaultConfiguration());  //new ();

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  protected LearnerGraphND buildMachine(int size) 
  {
    buildGraph(size);
    Configuration conf = Configuration.getDefaultConfiguration();
    //conf.setAllowedToCloneNonCmpVertex(true);
    return new LearnerGraphND(machine,conf);
  }

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    GDLearnerGraph(AbstractLearnerGraph<TARGET_A_TYPE,CACHE_A_TYPE> coregraph,
    StatesToConsider stateFilter, 
    boolean direction)
  {
    alphabet = coregraph.learnerCache.getAlphabet();config=coregraph.config;filter=stateFilter;
    matrixInverse = new LearnerGraphND(config);matrixInverse.initEmpty();
    matrixForward = new LearnerGraphND(config);matrixForward.initEmpty();
    pairCompatibility = coregraph.pairCompatibility;
    
    stateToNumberMap = new TreeMap<CmpVertex,Integer>();
    numberToStateArray = coregraph.buildStateToIntegerMap(filter,stateToNumberMap);
    assert numberToStateArray.length == stateToNumberMap.size();

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    public ChangesRecorder(PatchGraph nextInStack)
    {
      next = nextInStack;
      Configuration config = Configuration.getDefaultConfiguration().copy();config.setLearnerCloneGraph(false);
      added = new LearnerGraphND(config);removed = new LearnerGraphND(config);removed.initEmpty();
      added.setInit(null);added.initEmpty();// to make sure we can handle an assignment of a reject-state to an initial state
      addedPatcher = new LearnerGraphMutator<List<CmpVertex>,LearnerGraphNDCachedData>(added, config,null);
      removedPatcher = new LearnerGraphMutator<List<CmpVertex>,LearnerGraphNDCachedData>(removed,config,null);
    }

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     * @param elem element containing the difference.
     */
    static public void loadDiff(PatchGraph graphPatcher, Element elem)
    {
      Configuration config = Configuration.getDefaultConfiguration().copy();config.setLearnerCloneGraph(false);
      LearnerGraphND gr = new LearnerGraphND(config);AbstractPersistence.loadGraph(getGraphElement(elem, StatechumXML.gdRemoved.toString(),false,true),gr);
      //System.out.println("removed: "+gr.transitionMatrix.keySet());
      for(Entry<CmpVertex,Map<Label,List<CmpVertex>>> entry:gr.transitionMatrix.entrySet())
        for(Entry<Label,List<CmpVertex>> transition:entry.getValue().entrySet())
          for(CmpVertex target:gr.getTargets(transition.getValue()))
            graphPatcher.removeTransition(entry.getKey(), transition.getKey(), target);
          
      for(Entry<CmpVertex,Map<CmpVertex,JUConstants.PAIRCOMPATIBILITY>> incompatibles:gr.pairCompatibility.compatibility.entrySet())
        for(CmpVertex target:incompatibles.getValue().keySet())
          graphPatcher.removeFromCompatibility(incompatibles.getKey(), target);
      
      AbstractPersistence.loadGraph(getGraphElement(elem, StatechumXML.gdAdded.toString(),false,true),gr);
      //System.out.println("added: "+gr.transitionMatrix.keySet()+"\n with incompatibles : "+gr.pairCompatibility.keySet());
      
      for(Entry<CmpVertex,Map<Label,List<CmpVertex>>> entry:gr.transitionMatrix.entrySet())
      {
        if (entry.getValue().isEmpty())
          graphPatcher.addVertex(entry.getKey());
        else
          for(Entry<Label,List<CmpVertex>> transition:entry.getValue().entrySet())
            for(CmpVertex target:gr.getTargets(transition.getValue()))
              graphPatcher.addTransition(entry.getKey(), transition.getKey(), target);
      }
      for(Entry<CmpVertex,Map<CmpVertex,JUConstants.PAIRCOMPATIBILITY>> incompatibles:gr.pairCompatibility.compatibility.entrySet())
        for(Entry<CmpVertex,JUConstants.PAIRCOMPATIBILITY> targetEntry:incompatibles.getValue().entrySet())
          graphPatcher.addToCompatibility(incompatibles.getKey(), targetEntry.getKey(), targetEntry.getValue());
      
      NodeList relabellingElementList=  StatechumXML.getChildWithTag(elem,StatechumXML.gdRelabelling.toString());
      if (relabellingElementList.getLength() > 0)
      {// load the relabelling if present.
        getGraphElement(elem, StatechumXML.gdRelabelling.toString(),true,false);// check that XML structure is consistent and there are pairs stored - will throw otherwise
        Element relabellingElement = (Element)relabellingElementList.item(0); 
        NodeList children = relabellingElement.getChildNodes();
        for(int childNum=0;childNum<children.getLength();++childNum)
          if (children.item(childNum).getNodeType() == Node.ELEMENT_NODE)
          {
            PairScore pair=ProgressDecorator.readPair(gr, (Element)children.item(childNum));
            graphPatcher.addRelabelling(pair.getQ().getID(), pair.getR().getID());
          }
      }
      graphPatcher.setInitial(gr.getInit());
    }

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            fileA1 = files[fileNum], 
            fileA2 = files[(fileNum+1)%files.length],
            fileB1 = files[(fileNum+2)%files.length],
            fileB2 = files[(fileNum+3)%files.length];
        
          LearnerGraphND grA = null, grB = null;
          {
            LearnerGraphND loadedA1 = new LearnerGraphND(config);AbstractPersistence.loadGraph(fileA1, loadedA1);
            LearnerGraph loadedA2 = new LearnerGraph(config);AbstractPersistence.loadGraph(fileA2, loadedA2);
            grA = LearnerGraphND.UniteTransitionMatrices(loadedA1,loadedA2);
            addColourAndTransitionsRandomly(grA, new Random(0));
          }
          
          {
            LearnerGraphND loadedB1 = new LearnerGraphND(config);AbstractPersistence.loadGraph(fileB1, loadedB1);
            LearnerGraph loadedB2 = new LearnerGraph(config);AbstractPersistence.loadGraph(fileB2, loadedB2);
            grB = LearnerGraphND.UniteTransitionMatrices(loadedB1,loadedB2);
            addColourAndTransitionsRandomly(grB, new Random(1));
          }

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  static void linearDiff(LearnerGraph cvsGraphD, LearnerGraphND otherGraph)
  {
    //GD<CmpVertex,CmpVertex,LearnerGraphCachedData,LearnerGraphCachedData> gd = new GD<CmpVertex,CmpVertex,LearnerGraphCachedData,LearnerGraphCachedData>();
    GD<List<CmpVertex>,List<CmpVertex>,LearnerGraphNDCachedData,LearnerGraphNDCachedData> gd = new GD<List<CmpVertex>,List<CmpVertex>,LearnerGraphNDCachedData,LearnerGraphNDCachedData>();
    LearnerGraphND cvsGraph = new LearnerGraphND(cvsGraphD,config);
    ChangesCounter<List<CmpVertex>,List<CmpVertex>,LearnerGraphNDCachedData,LearnerGraphNDCachedData>  rec3 = new ChangesCounter<List<CmpVertex>,List<CmpVertex>,LearnerGraphNDCachedData,LearnerGraphNDCachedData>(cvsGraph,otherGraph,null);
    gd.computeGD(cvsGraph, otherGraph, 1, rec3, config);
    int intersection = cvsGraph.pathroutines.countEdges()-rec3.getRemoved();
    assert otherGraph.pathroutines.countEdges() == intersection+rec3.getAdded();
    System.out.println(otherGraph.getName()+": precision = "+((double)intersection/otherGraph.pathroutines.countEdges())+" recall = "+((double)intersection/cvsGraph.pathroutines.countEdges()));

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        "q10-appendfile->q11 /" +
        "q13-retrievefile->q13","sd_cvs",config,null),
        markovD = buildLearnerGraphND(markovString.replace("PART2", "a").replace("PART3", "a"),"sd_markovD",config,null).pathroutines.buildDeterministicGraph(),
        edsm = buildLearnerGraph("a-initialise->b-connect->c-login->d-storefile->e-changedir->d-listfiles->e-retrievefile->e-logout->i-disconnect->l\nd-delete->d-makedir->d-changedir->f-listnames->d-logout->g-disconnect->j\nd-setfiletype->h-storefile->k-appendfile->m-setfiletype->n-rename->o-storefile->m\nd-appendfile->o-logout->p-disconnect->q","sd_edsm",config,null)
        ;
    LearnerGraphND 
      markov = buildLearnerGraphND(markovString,"sd_markov",config,null);
    markovD.setName("sd_markovD");


    Set<Label> origAlphabet = cvsGraph.pathroutines.computeAlphabet();
    assert origAlphabet.equals(markov.pathroutines.computeAlphabet());
    assert origAlphabet.equals(markovD.pathroutines.computeAlphabet());
    assert origAlphabet.equals(edsm.pathroutines.computeAlphabet());
    final RandomPathGenerator generator = new RandomPathGenerator(cvsGraph,new Random(0),5,null);
    final int posOrNegPerChunk = 50;
    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;
    
    {
      precRec = new PTA_computePrecisionRecall(markovD);
      precRec.crossWith(walkEngine);PosNegPrecisionRecall result = precRec.getPosNegPrecisionRecallNum(); 
      final String name = "Markov";
      System.out.println(name+": +precision "+result.getPosprecision()+" +recall: "+result.getPosrecall());
      System.out.println(name+": -precision "+result.getNegprecision()+" -recall: "+result.getNegrecall());
      System.out.println(name+": =precision "+result.getPrecision()+" =recall: "+result.getRecall());
    }


    {
      precRec = new PTA_computePrecisionRecall(edsm);
      precRec.crossWith(walkEngine);PosNegPrecisionRecall result = precRec.getPosNegPrecisionRecallNum(); 
      final String name = "EDSM";
      System.out.println(name+": +precision "+result.getPosprecision()+" +recall: "+result.getPosrecall());
      System.out.println(name+": -precision "+result.getNegprecision()+" -recall: "+result.getNegrecall());
      System.out.println(name+": =precision "+result.getPrecision()+" =recall: "+result.getRecall());
    }
    
    linearDiff(cvsGraph, markov);
    linearDiff(cvsGraph, new LearnerGraphND(edsm,config));
  }

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  }


  static void linearDiff(LearnerGraph cvsGraphD, LearnerGraphND otherGraph)
  {
    GD<List<CmpVertex>,List<CmpVertex>,LearnerGraphNDCachedData,LearnerGraphNDCachedData> gd = new GD<List<CmpVertex>,List<CmpVertex>,LearnerGraphNDCachedData,LearnerGraphNDCachedData>();
    LearnerGraphND cvsGraph = new LearnerGraphND(cvsGraphD,config);
    ChangesCounter<List<CmpVertex>,List<CmpVertex>,LearnerGraphNDCachedData,LearnerGraphNDCachedData>  rec3 = new ChangesCounter<List<CmpVertex>,List<CmpVertex>,LearnerGraphNDCachedData,LearnerGraphNDCachedData>(cvsGraph,otherGraph,null);
    gd.computeGD(cvsGraph, otherGraph, 1, rec3, config);
    int intersection = cvsGraph.pathroutines.countEdges()-rec3.getRemoved();
    assert otherGraph.pathroutines.countEdges() == intersection+rec3.getAdded();
    System.out.println("PLTSDIFF, "+otherGraph.getName()+": precision = "+((double)intersection/otherGraph.pathroutines.countEdges())+" recall = "+((double)intersection/cvsGraph.pathroutines.countEdges()));

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