Examples of clearColours()

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

201
202
203
204
205
206
207
208
209
210
211
        });
        assert sPlus.size() > 0;
        assert sMinus.size() > 0;
        final MarkovModel m= new MarkovModel(chunkLen,true,true,false);
        new MarkovClassifier(m, pta).updateMarkov(false);
        pta.clearColours();

        if (!onlyUsePositives)
          assert pta.getStateNumber() > pta.getAcceptStateNumber() : "graph with only accept states but onlyUsePositives is not set";
        else
          assert pta.getStateNumber() == pta.getAcceptStateNumber() : "graph with negatives but onlyUsePositives is set";
View Full Code Here

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

432
433
434
435
436
437
438
439
440
441
442
        else
          pta.paths.augmentPTA(generator.getAllSequences(0));

        final MarkovModel m= new MarkovModel(chunkLen,true,true,false);
        new MarkovClassifier(m, pta).updateMarkov(false);
        pta.clearColours();

        if (!onlyUsePositives)
          assert pta.getStateNumber() > pta.getAcceptStateNumber() : "graph with only accept states but onlyUsePositives is not set";
        else
          assert pta.getStateNumber() == pta.getAcceptStateNumber() : "graph with negatives but onlyUsePositives is set";
View Full Code Here

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

161
162
163
164
165
166
167
168
169
170
171
        PaperUAS.computePTASize(selectionID+" with unique "+uniqueFromInitial+" : ", pta, referenceGraph);
      }*/
      //Visualiser.updateFrame(referenceGraph, pta);
      //Visualiser.waitForKey();
     
      pta.clearColours();
     
      if (!onlyUsePositives)
      {
        assert pta.getStateNumber() > pta.getAcceptStateNumber() : "graph with only accept states but onlyUsePositives is not set";
        Map<Label,Set<Label>> infeasiblePairs = PairQualityLearner.computeInfeasiblePairs(referenceGraph);
View Full Code Here

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

211
212
213
214
215
216
217
218
219
220
221
   
        final MarkovModel m= new MarkovModel(chunkLen,true,true,false);

        new MarkovClassifier(m, pta).updateMarkov(false);// construct Markov chain if asked for.
       
        pta.clearColours();

        if (!onlyUsePositives)
          assert pta.getStateNumber() > pta.getAcceptStateNumber() : "graph with only accept states but onlyUsePositives is not set";
        else
          assert pta.getStateNumber() == pta.getAcceptStateNumber() : "graph with negatives but onlyUsePositives is set";
View Full Code Here

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

247
248
249
250
251
252
253
254
255
256
257
          assert scoreInitialMerge >= 0;
          ptaToUseForInference = MergeStates.mergeCollectionOfVertices(pta, null, verticesToMergeInitialMerge);
          final CmpVertex vertexWithMostTransitions = MarkovPassivePairSelection.findVertexWithMostTransitions(ptaToUseForInference,MarkovClassifier.computeInverseGraph(pta));
          if (useMostConnectedVertexToStartLearning)
          {
            ptaToUseForInference.clearColours();ptaToUseForInference.getInit().setColour(null);vertexWithMostTransitions.setColour(JUConstants.RED);
          }
          LearnerGraphND inverseOfPtaAfterInitialMerge = MarkovClassifier.computeInverseGraph(ptaToUseForInference);
          System.out.println("Centre vertex: "+vertexWithMostTransitions+" number of transitions: "+MarkovPassivePairSelection.countTransitions(ptaToUseForInference, inverseOfPtaAfterInitialMerge, vertexWithMostTransitions));
        }
       
View Full Code Here

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

302
303
304
305
306
307
308
309
310
311
312
        assert sPlus.size() > 0;
        assert sMinus.size() > 0;
        final MarkovModel m= new MarkovModel(chunkLen,true,true,false);
        m.createMarkovLearner(sPlus, sMinus,false);
       
        pta.clearColours();
        synchronized (AbstractLearnerGraph.syncObj) {
          //PaperUAS.computePTASize(selectionID+" attempt: "+attempt+" with unique: ", pta, referenceGraph);
        }
       
        if (!onlyUsePositives)
View Full Code Here

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

337
338
339
340
341
342
343
344
345
346
347
        LinkedList<AMEquivalenceClass<CmpVertex,LearnerGraphCachedData>> verticesToMergeInitialMerge = new LinkedList<AMEquivalenceClass<CmpVertex,LearnerGraphCachedData>>();
        int scoreInitialMerge = pta.pairscores.computePairCompatibilityScore_general(null, pairsListInitialMerge, verticesToMergeInitialMerge);
        assert scoreInitialMerge >= 0;
        final LearnerGraph ptaAfterInitialMerge = MergeStates.mergeCollectionOfVertices(pta, null, verticesToMergeInitialMerge);
        final CmpVertex vertexWithMostTransitions = MarkovPassivePairSelection.findVertexWithMostTransitions(ptaAfterInitialMerge,MarkovClassifier.computeInverseGraph(pta));
        ptaAfterInitialMerge.clearColours();ptaAfterInitialMerge.getInit().setColour(null);vertexWithMostTransitions.setColour(JUConstants.RED);
        ptaClassifier = new MarkovClassifier(m,ptaAfterInitialMerge);// rebuild the classifier
        LearnerGraphND inverseOfPtaAfterInitialMerge = MarkovClassifier.computeInverseGraph(ptaAfterInitialMerge);
        System.out.println("Centre vertex: "+vertexWithMostTransitions+" "+MarkovPassivePairSelection.countTransitions(ptaAfterInitialMerge, inverseOfPtaAfterInitialMerge, vertexWithMostTransitions));
       
        //learnerEval.config.setGeneralisationThreshold(1);
View Full Code Here

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

190
191
192
193
194
195
196
197
198
199
200
      });
      assert sPlus.size() > 0;
      final MarkovModel m= new MarkovModel(chunkLen,true,true);

      new MarkovClassifier(m, pta).updateMarkov(false);
      pta.clearColours();

      assert pta.getStateNumber() == pta.getAcceptStateNumber() : "graph with negatives but onlyUsePositives is set";
     
      final Configuration deepCopy = pta.config.copy();deepCopy.setLearnerCloneGraph(true);
      LearnerGraph ptaCopy = new LearnerGraph(deepCopy);LearnerGraph.copyGraphs(pta, ptaCopy);
View Full Code Here

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

213
214
215
216
217
218
219
220
221
222
223
      LinkedList<AMEquivalenceClass<CmpVertex,LearnerGraphCachedData>> verticesToMergeInitialMerge = new LinkedList<AMEquivalenceClass<CmpVertex,LearnerGraphCachedData>>();
      int scoreInitialMerge = pta.pairscores.computePairCompatibilityScore_general(null, pairsListInitialMerge, verticesToMergeInitialMerge);
      assert scoreInitialMerge >= 0;
      final LearnerGraph ptaAfterInitialMerge = MergeStates.mergeCollectionOfVertices(pta, null, verticesToMergeInitialMerge);
      final CmpVertex vertexWithMostTransitions = MarkovPassivePairSelection.findVertexWithMostTransitions(ptaAfterInitialMerge,MarkovClassifier.computeInverseGraph(pta));
      ptaAfterInitialMerge.clearColours();ptaAfterInitialMerge.getInit().setColour(null);vertexWithMostTransitions.setColour(JUConstants.RED);
      ptaClassifier = new MarkovClassifier(m,ptaAfterInitialMerge);// rebuild the classifier
      LearnerGraphND inverseOfPtaAfterInitialMerge = MarkovClassifier.computeInverseGraph(ptaAfterInitialMerge);
      //System.out.println("Centre vertex: "+vertexWithMostTransitions+" "+MarkovPassivePairSelection.countTransitions(ptaAfterInitialMerge, inverseOfPtaAfterInitialMerge, vertexWithMostTransitions));
     
      // These have been recorded, there is no specific reason for the numbers to be as they are. We need them for regression testing.
View Full Code Here

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

715
716
717
718
719
720
721
722
723
724
725
        assert sPlus.size() > 0;
        assert sMinus.size() > 0;
        final MarkovModel m= new MarkovModel(chunkLen,true,true);
        m.createMarkovLearner(sPlus, sMinus,false);
       
        pta.clearColours();
        synchronized (AbstractLearnerGraph.syncObj) {
          //PaperUAS.computePTASize(selectionID+" attempt: "+attempt+" with unique: ", pta, referenceGraph);
        }
       
        if (!onlyUsePositives)
View Full Code Here
TOP
Copyright © 2018 www.massapi.com. All rights reserved.
All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.