estimate value function with simple linear regression

3 files changed, 151 insertions, 58 deletions

diff --git a/Metrics/Metrics-Calculation/ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator/src/ca/mcgill/ecse/dslreasoner/realistic/metrics/calculator/app/PartialInterpretationMetric.xtend b/Metrics/Metrics-Calculation/ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator/src/ca/mcgill/ecse/dslreasoner/realistic/metrics/calculator/app/PartialInterpretationMetric.xtend
index 71fa5fed..5e62b586 100644
--- a/Metrics/Metrics-Calculation/ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator/src/ca/mcgill/ecse/dslreasoner/realistic/metrics/calculator/app/PartialInterpretationMetric.xtend
+++ b/Metrics/Metrics-Calculation/ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator/src/ca/mcgill/ecse/dslreasoner/realistic/metrics/calculator/app/PartialInterpretationMetric.xtend
@@ -24,40 +24,6 @@ class PartialInterpretationMetric {
         def static void initPaths(){
                 new File("debug/metric/").mkdir();
                 new File("debug/metric/trajectories/").mkdir();
-                ks = new KSDistance(Domain.Yakinduum);
-                js = new JSDistance(Domain.Yakinduum);
-        }
-        
-        def static MetricDistanceGroup calculateMetricDistance(PartialInterpretation partial){
-                val metrics = new ArrayList<Metric>();
-                metrics.add(new OutDegreeMetric());
-                metrics.add(new NodeActivityMetric());
-                metrics.add(new MultiplexParticipationCoefficientMetric());
-                
-                val metricCalculator = new PartialInterpretationGraph(partial, metrics, null);          
-                var metricSamples = metricCalculator.evaluateAllMetricsToSamples();
-                
-                var mpc = js.mpcDistance(metricSamples.mpcSamples);
-                var na = js.naDistance(metricSamples.naSamples);
-                var outDegree = js.outDegreeDistance(metricSamples.outDegreeSamples);
-                
-                return new MetricDistanceGroup(mpc, na, outDegree);
-        }
-        
-        def static MetricDistanceGroup calculateMetricDistanceKS(PartialInterpretation partial){
-                val metrics = new ArrayList<Metric>();
-                metrics.add(new OutDegreeMetric());
-                metrics.add(new NodeActivityMetric());
-                metrics.add(new MultiplexParticipationCoefficientMetric());
-                
-                val metricCalculator = new PartialInterpretationGraph(partial, metrics, null);          
-                var metricSamples = metricCalculator.evaluateAllMetricsToSamples();
-                
-                var mpc = ks.mpcDistance(metricSamples.mpcSamples);
-                var na = ks.naDistance(metricSamples.naSamples);
-                var outDegree = ks.outDegreeDistance(metricSamples.outDegreeSamples);
-                
-                return new MetricDistanceGroup(mpc, na, outDegree);
         }
         
         // calculate the metrics for a state
@@ -116,28 +82,4 @@ class PartialInterpretationMetric {
                         }
                 }                       
         }
-}
-
-class MetricDistanceGroup{
-        var double mpcDistance;
-        var double naDistance;
-        var double outDegreeDistance;
-        
-        new(double mpcDistance, double naDistance, double outDegreeDistance){
-                this.mpcDistance = mpcDistance;
-                this.naDistance = naDistance;
-                this.outDegreeDistance = outDegreeDistance;
-        }
-        
-        def double getMPCDistance(){
-                return this.mpcDistance
-        }
-        
-        def double getNADistance(){
-                return this.naDistance
-        }
-        
-        def double getOutDegreeDistance(){
-                return this.outDegreeDistance
-        }
 }
\ No newline at end of file
diff --git a/Metrics/Metrics-Calculation/ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator/src/ca/mcgill/ecse/dslreasoner/realistic/metrics/calculator/app/PartialInterpretationMetricDistance.xtend b/Metrics/Metrics-Calculation/ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator/src/ca/mcgill/ecse/dslreasoner/realistic/metrics/calculator/app/PartialInterpretationMetricDistance.xtend
new file mode 100644
index 00000000..b63451e8
--- /dev/null
+++ b/Metrics/Metrics-Calculation/ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator/src/ca/mcgill/ecse/dslreasoner/realistic/metrics/calculator/app/PartialInterpretationMetricDistance.xtend
@@ -0,0 +1,122 @@
+package ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.app
+
+import ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.distance.JSDistance
+import ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.distance.KSDistance
+import ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.distance.StateData
+import ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.graph.PartialInterpretationGraph
+import ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.metrics.Metric
+import ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.metrics.MultiplexParticipationCoefficientMetric
+import ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.metrics.NodeActivityMetric
+import ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.metrics.OutDegreeMetric
+import hu.bme.mit.inf.dslreasoner.viatrasolver.partialinterpretationlanguage.partialinterpretation.PartialInterpretation
+import java.util.ArrayList
+import java.util.HashMap
+import java.util.Map
+import org.apache.commons.math3.stat.regression.SimpleRegression
+import java.util.stream.DoubleStream.Builder
+
+class PartialInterpretationMetricDistance {
+        
+        var KSDistance ks;
+        var JSDistance js;
+        var Map<Object, StateData> stateAndHistory;
+        var SimpleRegression regression;
+        
+        
+        new(){
+                ks = new KSDistance(Domain.Yakinduum);
+                js = new JSDistance(Domain.Yakinduum);
+                regression = new SimpleRegression();
+                stateAndHistory = new HashMap<Object, StateData>();
+        }
+        
+        def MetricDistanceGroup calculateMetricDistanceKS(PartialInterpretation partial){
+                val metrics = new ArrayList<Metric>();
+                metrics.add(new OutDegreeMetric());
+                metrics.add(new NodeActivityMetric());
+                metrics.add(new MultiplexParticipationCoefficientMetric());
+                
+                val metricCalculator = new PartialInterpretationGraph(partial, metrics, null);          
+                var metricSamples = metricCalculator.evaluateAllMetricsToSamples();
+                
+                var mpc = ks.mpcDistance(metricSamples.mpcSamples);
+                var na = ks.naDistance(metricSamples.naSamples);
+                var outDegree = ks.outDegreeDistance(metricSamples.outDegreeSamples);
+                
+                return new MetricDistanceGroup(mpc, na, outDegree);
+        }
+        
+        def MetricDistanceGroup calculateMetricDistance(PartialInterpretation partial){
+                val metrics = new ArrayList<Metric>();
+                metrics.add(new OutDegreeMetric());
+                metrics.add(new NodeActivityMetric());
+                metrics.add(new MultiplexParticipationCoefficientMetric());
+                
+                val metricCalculator = new PartialInterpretationGraph(partial, metrics, null);          
+                var metricSamples = metricCalculator.evaluateAllMetricsToSamples();
+                
+                var mpc = js.mpcDistance(metricSamples.mpcSamples);
+                var na = js.naDistance(metricSamples.naSamples);
+                var outDegree = js.outDegreeDistance(metricSamples.outDegreeSamples);
+                
+                return new MetricDistanceGroup(mpc, na, outDegree);
+        }
+        
+        def resetRegression(Object state){
+                regression = new SimpleRegression();
+                
+                if(stateAndHistory.containsKey(state)){
+                        var data = stateAndHistory.get(state);
+                        regression.addData(data.numOfNodeFeature, data.value);
+                        
+                        while(stateAndHistory.containsKey(data.lastState)){
+                                data = stateAndHistory.get(data.lastState);
+                                regression.addData(data.numOfNodeFeature, data.value);
+                        }
+                }
+        }
+        
+        def feedData(Object state, int numOfNodes, double value, Object lastState){
+                var data = new StateData(numOfNodes, value, lastState);
+                stateAndHistory.put(state, data);
+                regression.addData(data.numOfNodeFeature, data.value);
+        }
+        
+        def getPredictionForNextDataSample(int numOfNodes, double value, int numberOfNodesToPredict){
+                var data = new StateData(numOfNodes, value, null);
+                regression.addData(data.numOfNodeFeature, data.value);
+                
+                var prediction = predict(numberOfNodesToPredict);
+                regression.removeData(data.numOfNodeFeature, data.value);
+                return prediction;
+        }
+        
+        def predict(int numOfNodes){
+                var data = new StateData(numOfNodes, 0, null);
+                return regression.predict(data.numOfNodeFeature);
+        }
+}
+
+class MetricDistanceGroup{
+        var double mpcDistance;
+        var double naDistance;
+        var double outDegreeDistance;
+        
+        new(double mpcDistance, double naDistance, double outDegreeDistance){
+                this.mpcDistance = mpcDistance;
+                this.naDistance = naDistance;
+                this.outDegreeDistance = outDegreeDistance;
+        }
+        
+        def double getMPCDistance(){
+                return this.mpcDistance
+        }
+        
+        def double getNADistance(){
+                return this.naDistance
+        }
+        
+        def double getOutDegreeDistance(){
+                return this.outDegreeDistance
+        }
+}
\ No newline at end of file
diff --git a/Metrics/Metrics-Calculation/ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator/src/ca/mcgill/ecse/dslreasoner/realistic/metrics/calculator/distance/CostDistance.xtend b/Metrics/Metrics-Calculation/ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator/src/ca/mcgill/ecse/dslreasoner/realistic/metrics/calculator/distance/CostDistance.xtend
new file mode 100644
index 00000000..ee856201
--- /dev/null
+++ b/Metrics/Metrics-Calculation/ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator/src/ca/mcgill/ecse/dslreasoner/realistic/metrics/calculator/distance/CostDistance.xtend
@@ -0,0 +1,29 @@
+package ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.distance
+
+import org.apache.commons.math3.stat.regression.SimpleRegression
+import org.eclipse.xtend.lib.annotations.Accessors
+
+class CostDistance {
+        
+        var SimpleRegression regression;
+        
+        new(){
+                regression = new SimpleRegression(true);
+        }
+        
+}
+
+class StateData{
+        @Accessors(PUBLIC_GETTER)
+        var double numOfNodeFeature;
+        @Accessors(PUBLIC_GETTER)
+        var double value;
+        @Accessors(PUBLIC_GETTER)
+        var Object lastState;
+        
+        new(int numOfNode, double value, Object lastState){
+                this.numOfNodeFeature = 1.0 / numOfNode;
+                this.value = value
+                this.lastState = lastState;
+        }
+}
\ No newline at end of file