1 files changed, 60 insertions, 50 deletions

diff --git a/Solvers/VIATRA-Solver/hu.bme.mit.inf.dslreasoner.viatrasolver.reasoner/src/hu/bme/mit/inf/dslreasoner/viatrasolver/reasoner/dse/HillClimbingOnRealisticMetricStrategyForModelGeneration.java b/Solvers/VIATRA-Solver/hu.bme.mit.inf.dslreasoner.viatrasolver.reasoner/src/hu/bme/mit/inf/dslreasoner/viatrasolver/reasoner/dse/HillClimbingOnRealisticMetricStrategyForModelGeneration.java
index 148cb243..d9f6f2aa 100644
--- a/Solvers/VIATRA-Solver/hu.bme.mit.inf.dslreasoner.viatrasolver.reasoner/src/hu/bme/mit/inf/dslreasoner/viatrasolver/reasoner/dse/HillClimbingOnRealisticMetricStrategyForModelGeneration.java
+++ b/Solvers/VIATRA-Solver/hu.bme.mit.inf.dslreasoner.viatrasolver.reasoner/src/hu/bme/mit/inf/dslreasoner/viatrasolver/reasoner/dse/HillClimbingOnRealisticMetricStrategyForModelGeneration.java
@@ -26,6 +26,7 @@ import org.eclipse.viatra.query.runtime.api.ViatraQueryMatcher;
 
 import ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.app.MetricDistanceGroup;
 import ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.app.PartialInterpretationMetric;
+import ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.app.PartialInterpretationMetricDistance;
 import hu.bme.mit.inf.dslreasoner.logic.model.builder.DocumentationLevel;
 import hu.bme.mit.inf.dslreasoner.logic.model.builder.LogicReasoner;
 import hu.bme.mit.inf.dslreasoner.logic.model.logicproblem.LogicProblem;
@@ -62,12 +63,12 @@ public class HillClimbingOnRealisticMetricStrategyForModelGeneration implements
                 private Collection<ViatraQueryMatcher<? extends IPatternMatch>> mayMatchers;
                 private Map<Object, List<Object>> stateAndActivations;
                 private Map<TrajectoryWithFitness, Double> trajectoryFit; 
-                
                 // Statistics
                 private int numberOfStatecoderFail = 0;
                 private int numberOfPrintedModel = 0;
                 private int numberOfSolverCalls = 0;
-                
+                private PartialInterpretationMetricDistance metricDistance; 
+
                 public HillClimbingOnRealisticMetricStrategyForModelGeneration(
                                 ReasonerWorkspace workspace,
                                 ViatraReasonerConfiguration configuration,
@@ -112,7 +113,7 @@ public class HillClimbingOnRealisticMetricStrategyForModelGeneration implements
                         this.solutionStoreWithCopy = new SolutionStoreWithCopy();
                         this.solutionStoreWithDiversityDescriptor = new SolutionStoreWithDiversityDescriptor(configuration.diversityRequirement);
 
-                        final ObjectiveComparatorHelper objectiveComparatorHelper = context.getObjectiveComparatorHelper();
+                        //final ObjectiveComparatorHelper objectiveComparatorHelper = context.getObjectiveComparatorHelper();
                         trajectoryFit = new HashMap<TrajectoryWithFitness, Double>();
 
                         this.comparator = new Comparator<TrajectoryWithFitness>() {
@@ -124,6 +125,7 @@ public class HillClimbingOnRealisticMetricStrategyForModelGeneration implements
 
                         trajectoiresToExplore = new PriorityQueue<TrajectoryWithFitness>(11, comparator);
                         stateAndActivations = new HashMap<Object, List<Object>>();
+                        metricDistance = new PartialInterpretationMetricDistance();
                 }
 
                 @Override
@@ -145,11 +147,11 @@ public class HillClimbingOnRealisticMetricStrategyForModelGeneration implements
                         TrajectoryWithFitness currentTrajectoryWithFittness = new TrajectoryWithFitness(firstTrajectory, firstFittness);
                         trajectoryFit.put(currentTrajectoryWithFittness, Double.MAX_VALUE);
                         trajectoiresToExplore.add(currentTrajectoryWithFittness);
+                        Object lastState = null;
                         
                         //if(configuration)
                         visualiseCurrentState();
                         
-                        PartialInterpretationMetric.initPaths();
                         //create matcher
                         int count = 0;
                         mainLoop: while (!isInterrupted && !configuration.progressMonitor.isCancelled()) {
@@ -165,6 +167,9 @@ public class HillClimbingOnRealisticMetricStrategyForModelGeneration implements
                                                         logger.debug("New trajectory is chosen: " + currentTrajectoryWithFittness);
                                                 }
                                                 context.getDesignSpaceManager().executeTrajectoryWithMinimalBacktrackWithoutStateCoding(currentTrajectoryWithFittness.trajectory);
+                                                
+                                                // reset the regression for this trajectory
+                                                metricDistance.getLinearModel().resetRegression(context.getCurrentStateId());
                                         }
                                 }
                                 
@@ -178,10 +183,10 @@ public class HillClimbingOnRealisticMetricStrategyForModelGeneration implements
                                 //init epsilon and draw
                                 double epsilon = 0;
                                 double draw = 1;
-                                MetricDistanceGroup heuristics =  PartialInterpretationMetric.calculateMetricDistanceKS(model);
-                                
-                                if(!stateAndActivations.containsKey(model)) {
-                                        stateAndActivations.put(model, new ArrayList<Object>());
+                                MetricDistanceGroup heuristics =  metricDistance.calculateMetricDistanceKS(model);
+
+                                if(!stateAndActivations.containsKey(context.getCurrentStateId())) {
+                                        stateAndActivations.put(context.getCurrentStateId(), new ArrayList<Object>());
                                 }
                                 
                                 //Output intermediate model
@@ -190,41 +195,26 @@ public class HillClimbingOnRealisticMetricStrategyForModelGeneration implements
                                         draw = Math.random();
                                         count++;
                                         // cut off the trajectory for bad graph
-                                        double distance = heuristics.getMPCDistance();
                                         System.out.println("KS");
                                         System.out.println("NA distance: " + heuristics.getNADistance());       
                                         System.out.println("MPC distance: " + heuristics.getMPCDistance());                             
                                         System.out.println("Out degree distance:" + heuristics.getOutDegreeDistance()); 
                                         
-                                        MetricDistanceGroup lsHeuristic = PartialInterpretationMetric.calculateMetricDistance(model);
-                                        System.out.println("LS");
-                                        System.out.println("NA distance: " + lsHeuristic.getNADistance());      
-                                        System.out.println("MPC distance: " + lsHeuristic.getMPCDistance());                            
-                                        System.out.println("Out degree distance:" + lsHeuristic.getOutDegreeDistance());        
-                                                                                
-                                        if(distance <= 0.23880597014925373 + 0.00001 && distance >= 0.23880597014925373 - 0.00001) {
-                                                context.backtrack();
-                                                final Fitness nextFitness = context.calculateFitness();
-                                                currentTrajectoryWithFittness = new TrajectoryWithFitness(context.getTrajectory().toArray(), nextFitness);
-                                                continue;
-                                        }
+//                                      MetricDistanceGroup lsHeuristic = metricDistance.calculateMetricDistance(model);
+//                                      System.out.println("LS");
+//                                      System.out.println("NA distance: " + lsHeuristic.getNADistance());      
+//                                      System.out.println("MPC distance: " + lsHeuristic.getMPCDistance());                            
+//                                      System.out.println("Out degree distance:" + lsHeuristic.getOutDegreeDistance());        
                                         
                                         //check for next value when doing greedy move
+                                        
                                         valueMap = sortWithWeight(activationIds, currentTrajectoryWithFittness.trajectory.length+1);
-//                                      if(activationIds.isEmpty() || (model.getNewElements().size() >= 20 && valueMap.get(activationIds.get(0)) > currentValue && epsilon < draw)) {
-//                                              context.backtrack();
-//                                              final Fitness nextFitness = context.calculateFitness();
-//                                              currentTrajectoryWithFittness = new TrajectoryWithFitness(context.getTrajectory().toArray(), nextFitness);
-//                                              continue;
-//                                      }
                                 }
+                                lastState = context.getCurrentStateId();
                                 while (!isInterrupted && !configuration.progressMonitor.isCancelled() && activationIds.size() > 0) {
                                         final Object nextActivation = drawWithEpsilonProbabilty(activationIds, valueMap, epsilon, draw);
-//                                      if (!iterator.hasNext()) {
-//                                              logger.debug("Last untraversed activation of the state.");
-//                                              trajectoiresToExplore.remove(currentTrajectoryWithFittness);
-//                                      }
-                                        stateAndActivations.get(context.getModel()).add(nextActivation);
+                                                                                
+                                        stateAndActivations.get(context.getCurrentStateId()).add(nextActivation);
                                         logger.debug("Executing new activation: " + nextActivation);
                                         context.executeAcitvationId(nextActivation);
                                         visualiseCurrentState();
@@ -242,15 +232,17 @@ public class HillClimbingOnRealisticMetricStrategyForModelGeneration implements
                                                 logger.debug("Global contraint is not satisifed.");
                                                 context.backtrack();
                                         } else*/// {
-                                        if(getNumberOfViolations(mustMatchers) > 8) {
+                                        /*if(getNumberOfViolations(mustMatchers) > 0) {
+                                                context.backtrack();
+                                        }else*/ if(model.getNewElements().size() > 90 && heuristics.getNADistance() + heuristics.getMPCDistance() + heuristics.getOutDegreeDistance() > 0.3) {
                                                 context.backtrack();
-                                        }else if(model.getNewElements().size() > 90 && heuristics.getNADistance() + heuristics.getMPCDistance() + heuristics.getOutDegreeDistance() > 0.18) {
+                                        }else if(model.getNewElements().size() > 70 && heuristics.getNADistance() + heuristics.getMPCDistance() + heuristics.getOutDegreeDistance() > 0.45) {
                                                 context.backtrack();
-                                        }else if(model.getNewElements().size() > 70 && heuristics.getNADistance() + heuristics.getMPCDistance() + heuristics.getOutDegreeDistance() > 0.36) {
+                                        } else if(model.getNewElements().size() > 50 && heuristics.getNADistance() + heuristics.getMPCDistance() + heuristics.getOutDegreeDistance() > 0.60) {
                                                 context.backtrack();
-                                        } else if(model.getNewElements().size() > 50 && heuristics.getNADistance() + heuristics.getMPCDistance() + heuristics.getOutDegreeDistance() > 0.72) {
+                                        } else if(model.getNewElements().size() > 30 && heuristics.getNADistance() + heuristics.getMPCDistance() + heuristics.getOutDegreeDistance() > 0.70) {
                                                 context.backtrack();
-                                        }  else {
+                                        }else {
                                                 final Fitness nextFitness = context.calculateFitness();
                                                 
                                                 // the only hard objectives are the size
@@ -271,9 +263,14 @@ public class HillClimbingOnRealisticMetricStrategyForModelGeneration implements
                                                         continue;
                                                 }
         
+                                                
                                                 TrajectoryWithFitness nextTrajectoryWithFittness = new TrajectoryWithFitness(
                                                                 context.getTrajectory().toArray(), nextFitness);
-                                                trajectoryFit.put(nextTrajectoryWithFittness, calculateCurrentStateValue(nextTrajectoryWithFittness.trajectory.length));
+                                                int step = nextTrajectoryWithFittness.trajectory.length;
+                                                int violation = getNumberOfViolations(mustMatchers) + getNumberOfViolations(mayMatchers);
+                                                metricDistance.getLinearModel().feedData(context.getCurrentStateId(), metricDistance.calculateFeature(step, violation), calculateCurrentStateValue(step, violation), lastState);
+                                                
+                                                trajectoryFit.put(nextTrajectoryWithFittness, calculateCurrentStateValue(step, violation));
                                                 trajectoiresToExplore.add(nextTrajectoryWithFittness);
                                                 
                                                 int compare = objectiveComparatorHelper.compare(currentTrajectoryWithFittness.fitness,
@@ -298,9 +295,9 @@ public class HillClimbingOnRealisticMetricStrategyForModelGeneration implements
                                 currentTrajectoryWithFittness = null;
                                 context.backtrack();
                         }
-                        PartialInterpretation model = (PartialInterpretation) context.getModel();
-                        PartialInterpretationMetric.calculateMetric(model, "debug/metric/output", context.getCurrentStateId().toString(), count);
-                        count++;
+//                      PartialInterpretation model = (PartialInterpretation) context.getModel();
+//                      PartialInterpretationMetric.calculateMetric(model, "debug/metric/output", context.getCurrentStateId().toString(), count);
+//                      count++;
                         logger.info("Interrupted.");
                 }
 
@@ -314,8 +311,8 @@ public class HillClimbingOnRealisticMetricStrategyForModelGeneration implements
                         // do hill climbing
                         for(Object id : activationIds) {
                                 context.executeAcitvationId(id);
-                                
-                                valueMap.put(id, calculateCurrentStateValue(factor));
+                                int violation = getNumberOfViolations(mayMatchers) + getNumberOfViolations(mustMatchers);
+                                valueMap.put(id, calculateFutureStateValue(factor, violation));
                                 context.backtrack();
                         }
                         
@@ -323,14 +320,27 @@ public class HillClimbingOnRealisticMetricStrategyForModelGeneration implements
                         return valueMap;
                 }
                 
-                private double calculateCurrentStateValue(int factor) {
+                private double calculateFutureStateValue(int step, int violation) {
+                        double currentValue = calculateCurrentStateValue(step, violation);
+                        if(step > 40) {
+                                double[] toPredict = metricDistance.calculateFeature(200, violation);
+                                try {
+                                        return metricDistance.getLinearModel().getPredictionForNextDataSample(metricDistance.calculateFeature(step, violation), currentValue, toPredict);
+                                }catch(IllegalArgumentException e) {
+                                        return currentValue;
+                                }
+                        }else {
+                                return currentValue;
+                        }
+                }
+                
+                private double calculateCurrentStateValue(int factor, int violation) {
                         PartialInterpretation model = (PartialInterpretation) context.getModel();
-                        MetricDistanceGroup g = PartialInterpretationMetric.calculateMetricDistanceKS(model);
+                        MetricDistanceGroup g = metricDistance.calculateMetricDistanceKS(model);
                         
-                        int violations = getNumberOfViolations(mayMatchers);
-                        double consistenceWeights = 1.0/(1+violations);
+                        double consistenceWeights = 1- 1.0/(1+violation);
                                                 
-                        return(2.5 / Math.log(factor) * (g.getNADistance() + g.getMPCDistance() + g.getOutDegreeDistance()) + 1-consistenceWeights);
+                        return( /*/ Math.log(factor)*/(g.getNADistance() + g.getMPCDistance() + g.getOutDegreeDistance()) + consistenceWeights);
                 }
                 
                 private int getNumberOfViolations(Collection<ViatraQueryMatcher<? extends IPatternMatch>> matchers) {
@@ -379,8 +389,8 @@ public class HillClimbingOnRealisticMetricStrategyForModelGeneration implements
                         List<Object> activationIds;
                         try {
                                 activationIds = new ArrayList<Object>(context.getCurrentActivationIds());
-                                if(stateAndActivations.containsKey(context.getModel())) {
-                                        activationIds.removeAll(stateAndActivations.get(context.getModel()));
+                                if(stateAndActivations.containsKey(context.getCurrentStateId())) {
+                                        activationIds.removeAll(stateAndActivations.get(context.getCurrentStateId()));
                                 }
                                 Collections.shuffle(activationIds);
                         } catch (NullPointerException e) {