List of nextID() Examples

Examples of nextID()

com.facebook.LinkBench.distributions.AccessDistributions.AccessDistribution.nextID()
com.hazelcast.multimap.MultiMapContainer.nextId()
com.hazelcast.multimap.impl.MultiMapContainer.nextId()
com.taobao.metamorphosis.utils.IdWorker.nextId()
com.thinkaurelius.titan.graphdb.database.idassigner.StandardIDPool.nextID()
org.apache.uima.aae.UIDGenerator.nextId()
org.dspace.content.ItemIterator.nextID()
return the id of the next item. @return the next id or -1 if none
org.fusesource.stomp.client.BlockingConnection.nextId()
org.neo4j.kernel.impl.nioneo.store.IdGenerator.nextId()
org.neo4j.kernel.impl.nioneo.store.PropertyIndexStore.nextId()
org.neo4j.kernel.impl.nioneo.store.PropertyStore.nextId()
org.neo4j.kernel.impl.nioneo.store.RelationshipTypeStore.nextId()
org.neo4j.kernel.impl.nioneo.store.Store.nextId()
Returns the id of next free record. @return The id of the next free record @throws IOException If unable to
org.tinyuml.model.IdGenerator.nextId()
Returns the next id. @return the next id
statechum.analysis.learning.rpnicore.LearnerGraph.nextID()
Generates vertex IDs. Since it modifies instance ID-related variables, it has to be synchronized.

Examples of statechum.analysis.learning.rpnicore.LearnerGraph.nextID()

          {
            assert rejectVertexID == null : "multiple reject vertices in learnt automaton, such as "+rejectVertexID+" and "+v;
            rejectVertexID = v;break;
          }
        if (rejectVertexID == null)
          rejectVertexID = actualAutomaton.nextID(false);
        SampleData dataSample = new SampleData(null,null);
        if (learnUsingReferenceLearner)
        {
          dataSample.actualLearner=estimateDifference(referenceGraph,actualAutomaton,testSet);
          LearnerGraph outcomeOfReferenceLearner = new ReferenceLearner(learnerEval,referenceGraph,pta,false).learnMachine(new LinkedList<List<Label>>(),new LinkedList<List<Label>>());

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Examples of statechum.analysis.learning.rpnicore.LearnerGraph.nextID()

          {
            assert rejectVertexID == null : "multiple reject vertices in learnt automaton, such as "+rejectVertexID+" and "+v;
            rejectVertexID = v;break;
          }
        if (rejectVertexID == null)
          rejectVertexID = actualAutomaton.nextID(false);
        SampleData dataSample = new SampleData(null,null);
        if (learnUsingReferenceLearner)
        {
          dataSample.actualLearner=estimateDifference(referenceGraph,actualAutomaton,testSet);
          LearnerGraph outcomeOfReferenceLearner = new ReferenceLearner(learnerEval,referenceGraph,pta,false).learnMachine(new LinkedList<List<Label>>(),new LinkedList<List<Label>>());

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Examples of statechum.analysis.learning.rpnicore.LearnerGraph.nextID()

          {
            assert rejectVertexID == null : "multiple reject vertices in learnt automaton, such as "+rejectVertexID+" and "+v;
            rejectVertexID = v;break;
          }
        if (rejectVertexID == null)
          rejectVertexID = actualAutomaton.nextID(false);
        SampleData dataSample = new SampleData(null,null);
        if (learnUsingReferenceLearner)
        {
          dataSample.difference = estimateDifference(referenceGraph,actualAutomaton,testSet);
          LearnerGraph outcomeOfReferenceLearner = new ReferenceLearner(learnerEval,referenceGraph,pta).learnMachine(new LinkedList<List<Label>>(),new LinkedList<List<Label>>());

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Examples of statechum.analysis.learning.rpnicore.LearnerGraph.nextID()

          {
            assert rejectVertexID == null : "multiple reject vertices in learnt automaton, such as "+rejectVertexID+" and "+v;
            rejectVertexID = v;break;
          }
        if (rejectVertexID == null)
          rejectVertexID = actualAutomaton.nextID(false);
        SampleData dataSample = new SampleData(null,null);
        if (learnUsingReferenceLearner)
        {
          dataSample.difference = estimateDifference(referenceGraph,actualAutomaton,testSet);
          LearnerGraph outcomeOfReferenceLearner = new ReferenceLearner(learnerEval,referenceGraph,pta).learnMachine(new LinkedList<List<Label>>(),new LinkedList<List<Label>>());

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Examples of statechum.analysis.learning.rpnicore.LearnerGraph.nextID()

            LearnerGraph.copyGraphs(initPta, graph);
          else
          {
            if (alphabet != null)
            {// Create a state to ensure that the entire alphabet is visible when if-then automata are loaded.
              CmpVertex dummyState = AbstractLearnerGraph.generateNewCmpVertex(graph.nextID(true), bfLearnerInitConfiguration.config);
              Map<Label,CmpVertex> row = graph.createNewRow();
              for(Label lbl:alphabet.keySet()) graph.addTransition(row, lbl, dummyState);
              graph.transitionMatrix.put(dummyState, row);
            }
          }

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Examples of statechum.analysis.learning.rpnicore.LearnerGraph.nextID()

          {
            assert rejectVertexID == null : "multiple reject vertices in learnt automaton, such as "+rejectVertexID+" and "+v;
            rejectVertexID = v;break;
          }
        if (rejectVertexID == null)
          rejectVertexID = actualAutomaton.nextID(false);
        SampleData dataSample = new SampleData(null,null);
        if (learnUsingReferenceLearner)
        {
          dataSample.difference = estimateDifference(referenceGraph,actualAutomaton,testSet);
          LearnerGraph outcomeOfReferenceLearner = new ReferenceLearner(learnerEval,referenceGraph,pta).learnMachine(new LinkedList<List<Label>>(),new LinkedList<List<Label>>());

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Examples of statechum.analysis.learning.rpnicore.LearnerGraph.nextID()

        public LearnerGraph init(PTASequenceEngine engine, int plusSize, int minusSize) 
        {
          LearnerGraph graph = decoratedLearner.init(engine,plusSize,minusSize);
          Set<Label> alphabet = graph.pathroutines.computeAlphabet();
          // Create a state to ensure that the entire alphabet is visible when if-then automata are loaded.
          phantomVertex = graph.nextID(true);
          CmpVertex dummyState = AbstractLearnerGraph.generateNewCmpVertex(phantomVertex, bfLearnerInitConfiguration.config);
          Map<Label,CmpVertex> row = graph.createNewRow();
          for(Label lbl:alphabet) graph.addTransition(row, lbl, dummyState);
          graph.transitionMatrix.put(dummyState, row);

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Examples of statechum.analysis.learning.rpnicore.LearnerGraph.nextID()

          }
          else
          {
            Set<Label> alphabet = graph.pathroutines.computeAlphabet();
            // Create a state to ensure that the entire alphabet is visible when if-then automata are loaded.
            phantomVertex = graph.nextID(true);
            CmpVertex dummyState = AbstractLearnerGraph.generateNewCmpVertex(phantomVertex, bfLearnerInitConfiguration.config);
            Map<Label,CmpVertex> row = graph.createNewRow();
            for(Label lbl:alphabet) graph.addTransition(row, lbl, dummyState);
            graph.transitionMatrix.put(dummyState, row);
          }

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Examples of statechum.analysis.learning.rpnicore.LearnerGraph.nextID()

          {
            assert rejectVertexID == null : "multiple reject vertices in learnt automaton, such as "+rejectVertexID+" and "+v;
            rejectVertexID = v;break;
          }
        if (rejectVertexID == null)
          rejectVertexID = actualAutomaton.nextID(false);
        SampleData dataSample = new SampleData(null,null);
        if (learnUsingReferenceLearner)
        {
          dataSample.actualLearner=estimateDifference(referenceGraph,actualAutomaton,testSet);
          LearnerGraph outcomeOfReferenceLearner = new ReferenceLearner(learnerEval,referenceGraph,pta,false).learnMachine(new LinkedList<List<Label>>(),new LinkedList<List<Label>>());

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Examples of statechum.analysis.learning.rpnicore.LearnerGraph.nextID()

          {
            assert rejectVertexID == null : "multiple reject vertices in learnt automaton, such as "+rejectVertexID+" and "+v;
            rejectVertexID = v;break;
          }
        if (rejectVertexID == null)
          rejectVertexID = actualAutomaton.nextID(false);
        SampleData dataSample = new SampleData(null,null);
        if (learnUsingReferenceLearner)
        {
          dataSample.difference = estimateDifference(referenceGraph,actualAutomaton,testSet);
          LearnerGraph outcomeOfReferenceLearner = new ReferenceLearner(learnerEval,referenceGraph,pta).learnMachine(new LinkedList<List<Label>>(),new LinkedList<List<Label>>());

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