Examples of ConsistencyChecker

bnGUI.venn.geometry.ConsistencyChecker
@author muellera
com.barrybecker4.puzzle.tantrix.model.verfication.ConsistencyChecker
Checks the consistency of paths between tiles given a collection of tiles. @author Barry Becker
fr.neatmonster.nocheatplus.components.ConsistencyChecker
This component might be called periodically. Might not be called ever. @author mc_dev
statechum.analysis.learning.MarkovClassifier.ConsistencyChecker
statechum.analysis.learning.MarkovUniversalLearner.ConsistencyChecker

Examples of bnGUI.venn.geometry.ConsistencyChecker

     */
    public String getInconsistencies()
    {        
        StringBuffer buf = new StringBuffer();
       
        ConsistencyChecker checker = new ConsistencyChecker();
        tree.accept( checker );
        
        LinkedList result = checker.getResult();
        if( result != null )
        {
            if( result.size() > 0 )
                buf.append("missing overlaps:\n");

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Examples of com.barrybecker4.puzzle.tantrix.model.verfication.ConsistencyChecker


        int numTiles = path.size();
        double distance = path.getEndPointDistance();
        boolean isLoop = distance == 0 && path.isLoop();


        ConsistencyChecker checker = new ConsistencyChecker(path.getTilePlacements(), path.getPrimaryPathColor());
        int numFits = checker.numFittingTiles();
        boolean allFit = numFits == numTiles;
        boolean consistentLoop = isLoop && allFit;
        boolean perfectLoop = false;
        double compactness = determineCompactness(path);

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Examples of fr.neatmonster.nocheatplus.components.ConsistencyChecker

                nameSetPerms,
                getCoreListener(),
                // Put ReloadListener first, because Checks could also listen to it.
                new ReloadHook(),
                NCPExemptionManager.getListener(),
                new ConsistencyChecker() {
                    @Override
                    public void checkConsistency(final Player[] onlinePlayers) {
                        NCPExemptionManager.checkConsistency(onlinePlayers);
                    }
                },

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Examples of fr.neatmonster.nocheatplus.components.ConsistencyChecker

        final long tEnd = tStart + config.getLong(ConfPaths.DATA_CONSISTENCYCHECKS_MAXTIME, 1, 50, 2);
        if (consistencyCheckerIndex >= consistencyCheckers.size()) consistencyCheckerIndex = 0;
        final Player[] onlinePlayers = getServer().getOnlinePlayers();
        // Loop
        while (consistencyCheckerIndex < consistencyCheckers.size()){
            final ConsistencyChecker checker = consistencyCheckers.get(consistencyCheckerIndex);
            try{
                checker.checkConsistency(onlinePlayers);
            }
            catch (Throwable t){
                LogUtil.logSevere("[NoCheatPlus] ConsistencyChecker(" + checker.getClass().getName() + ") encountered an exception:");
                LogUtil.logSevere(t);
            }
            consistencyCheckerIndex ++; // Do not remove :).
            final long now = System.currentTimeMillis();
            if (now < tStart || now >= tEnd){

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Examples of statechum.analysis.learning.MarkovClassifier.ConsistencyChecker

        final Configuration deepCopy = pta.config.copy();deepCopy.setLearnerCloneGraph(true);
        LearnerGraph ptaCopy = new LearnerGraph(deepCopy);LearnerGraph.copyGraphs(pta, ptaCopy);


        // now use pathsToMerge to compute which states can/cannot be merged together.
        LearnerGraph trimmedReference = trimUncoveredTransitions(pta,referenceGraph);
        final ConsistencyChecker checker = new MarkovClassifier.DifferentPredictionsInconsistencyNoBlacklisting();
        //long inconsistencyForTheReferenceGraph = MarkovClassifier.computeInconsistency(trimmedReference, m, checker,false);
        //System.out.println("Inconsistency of trimmed reference : "+inconsistencyForTheReferenceGraph);
        
        //if (inconsistencyForTheReferenceGraph != 53)
        //  break;// ignore automata where we get good results.

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Examples of statechum.analysis.learning.MarkovClassifier.ConsistencyChecker

  {
    List<StatePair> pairsList = ptaClassifier.buildVerticesToMergeForPath(pathsOfInterest);
    LinkedList<AMEquivalenceClass<CmpVertex,LearnerGraphCachedData>> verticesToMerge = new LinkedList<AMEquivalenceClass<CmpVertex,LearnerGraphCachedData>>();
    ptaClassifier.graph.pairscores.computePairCompatibilityScore_general(null, pairsList, verticesToMerge);
    LearnerGraph merged = MergeStates.mergeCollectionOfVertices(ptaClassifier.graph, null, verticesToMerge);// after merging all paths of interest, we get this graph.
    ConsistencyChecker checker = new MarkovClassifier.DifferentPredictionsInconsistency();
    final long genScoreThreshold = 1;
    int nrOfMergers=0;
    List<StatePair> pairsToMerge = new LinkedList<StatePair>();
    for(Entry<CmpVertex,Map<Label,CmpVertex>> entry:merged.transitionMatrix.entrySet())
      for(Entry<Label,CmpVertex> transition:entry.getValue().entrySet())

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Examples of statechum.analysis.learning.MarkovClassifier.ConsistencyChecker

    LinkedList<AMEquivalenceClass<CmpVertex,LearnerGraphCachedData>> verticesToMerge = new LinkedList<AMEquivalenceClass<CmpVertex,LearnerGraphCachedData>>();
    int genScore = ptaClassifier.graph.pairscores.computePairCompatibilityScore_general(null, constructPairsToMergeBasedOnSetsToMerge(ptaClassifier.graph.transitionMatrix.keySet(),verticesToMergeBasedOnInitialPTA), verticesToMerge);
    LearnerGraph graph = MergeStates.mergeCollectionOfVertices(ptaClassifier.graph, null, verticesToMerge);
    
    Set<CmpVertex> tr=graph.transform.trimGraph(10, graph.getInit()).transitionMatrix.keySet();
    ConsistencyChecker checker = new MarkovClassifier.DifferentPredictionsInconsistency();


    constructPairsToMergeBasedOnSetsToMerge(graph.transitionMatrix.keySet(),verticesToMergeBasedOnInitialPTA);    
    for(CmpVertex v0:tr)
      for(CmpVertex v1:tr)
        if (v0 != v1)

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Examples of statechum.analysis.learning.MarkovClassifier.ConsistencyChecker

        final Configuration deepCopy = pta.config.copy();deepCopy.setLearnerCloneGraph(true);
        LearnerGraph ptaCopy = new LearnerGraph(deepCopy);LearnerGraph.copyGraphs(pta, ptaCopy);


        LearnerGraph trimmedReference = MarkovPassivePairSelection.trimUncoveredTransitions(pta,referenceGraph);
        
        final ConsistencyChecker checker = new MarkovClassifier.DifferentPredictionsInconsistencyNoBlacklisting();
        long inconsistencyForTheReferenceGraph = MarkovClassifier.computeInconsistency(referenceGraph, m, checker,false);
        
        learnerOfPairs = new LearnerMarkovPassive(learnerEval,referenceGraph,pta);learnerOfPairs.setMarkovModel(m);


        learnerOfPairs.setScoreComputationOverride(new statechum.analysis.learning.rpnicore.PairScoreComputation.RedNodeSelectionProcedure() {

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Examples of statechum.analysis.learning.MarkovClassifier.ConsistencyChecker

                            for(List<Label> seq:sMinus)
                              pta.paths.augmentPTA(seq,false,false,null);
                            final MarkovModel m= new MarkovModel(3,true,true,false);


                            new MarkovClassifier(m, pta).updateMarkov(false);// construct Markov chain if asked for.
                            final ConsistencyChecker checker = new MarkovClassifier.DifferentPredictionsInconsistencyNoBlacklistingIncludeMissingPrefixes();
                          
                            pta.clearColours();
                            EDSM_MarkovLearner learner = new EDSM_MarkovLearner(learnerInitConfiguration,pta,0) {


                              @Override

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Examples of statechum.analysis.learning.MarkovClassifier.ConsistencyChecker

    // transitions in the vicinity of the added ones. For instance, where a path has been folded in with some transitions sticking out, those new ones
    // may be inconsistent with predictions, based on the transitions in the red part of the graph.


    // mapping map to store all paths leave each state in different length
    double tentativeScore=0;
    @SuppressWarnings("rawtypes")
    ConsistencyChecker checker = new MarkovClassifier.InconsistencyNullVsPredicted();
    MarkovClassifier resultClassifier = new MarkovClassifier(cl.model,result);
    for(Entry<CmpVertex,Collection<Label>> entry:labelsAdded.entrySet())
      if (!entry.getValue().isEmpty())
      {

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