1 files changed, 44 insertions, 25 deletions

diff --git a/Metrics/Metrics-Calculation/ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator/src/ca/mcgill/ecse/dslreasoner/realistic/metrics/calculator/distance/KSDistance.xtend b/Metrics/Metrics-Calculation/ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator/src/ca/mcgill/ecse/dslreasoner/realistic/metrics/calculator/distance/KSDistance.xtend
index 58e0a8a3..86f5f23c 100644
--- a/Metrics/Metrics-Calculation/ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator/src/ca/mcgill/ecse/dslreasoner/realistic/metrics/calculator/distance/KSDistance.xtend
+++ b/Metrics/Metrics-Calculation/ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator/src/ca/mcgill/ecse/dslreasoner/realistic/metrics/calculator/distance/KSDistance.xtend
@@ -2,46 +2,65 @@ package ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.distance
 
 import ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.app.Domain
 import ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.io.RepMetricsReader
+import ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.metrics.MetricSampleGroup
+import java.util.HashMap
+import java.util.HashSet
 import java.util.List
+import java.util.Set
 import org.apache.commons.math3.stat.inference.KolmogorovSmirnovTest
 
-class KSDistance {
+class KSDistance extends CostDistance {
         var static ksTester = new KolmogorovSmirnovTest();
-        var double[] mpcSamples;
-        var double[] naSamples;
-        var double[] outDegreeSamples;
-        
+        var MetricSampleGroup g;
         new(Domain d){
                 var metrics = RepMetricsReader.read(d);
-                mpcSamples = metrics.mpcSamples;
-                naSamples = metrics.naSamples.stream.mapToDouble([it]).toArray();
-                outDegreeSamples = metrics.outDegreeSamples.stream.mapToDouble([it]).toArray();
+                this.g = metrics;
         }
         
-        def double mpcDistance(List<Double> samples){
-                // map list to array
-                var arr = samples.stream.mapToDouble([it]).toArray();
-                
+        override double mpcDistance(List<Double> samples){
                 //if the size of array is smaller than 2, ks distance cannot be performed, simply return 1
-                if(arr.size < 2) return 1;
-                return ksTester.kolmogorovSmirnovStatistic(mpcSamples, arr);
+                if(samples.size < 2) return 1;
+                return ksTester.kolmogorovSmirnovStatistic(g.mpcSamples, samples);
         }
         
-        def double naDistance(List<Double> samples){
-                // map list to array
-                var arr = samples.stream.mapToDouble([it]).toArray();
-                
+        override double naDistance(List<Double> samples){
                 //if the size of array is smaller than 2, ks distance cannot be performed, simply return 1
-                if(arr.size < 2) return 1;
-                return ksTester.kolmogorovSmirnovStatistic(naSamples as double[], arr);
+                if(samples.size < 2) return 1;
+                return ksTester.kolmogorovSmirnovStatistic(g.naSamples as double[], samples);
         }
         
-        def double outDegreeDistance(List<Double> samples){
+        override double outDegreeDistance(List<Double> samples){
+                //if the size of array is smaller than 2, ks distance cannot be performed, simply return 1
+                if(samples.size < 2) return 1;
+                return ksTester.kolmogorovSmirnovStatistic(g.outDegreeSamples, samples);
+        }
+        
+        def double typedOutDegreeDistance(HashMap<String, List<Integer>> map){
+                var value = 0.0;
                 // map list to array
-                var arr = samples.stream.mapToDouble([it]).toArray();
+                val keySet = new HashSet<String>(map.keySet);
+                keySet.addAll(g.typedOutDegreeSamples.keySet);
+                for(key : keySet){
+                        if(!map.containsKey(key) ){
+                                value += 1;
+                        }else if(!g.typedOutDegreeSamples.containsKey(key)){
+                                value += map.get(key).size * 100;       
+                        }else{
+                                var double[] rep = g.typedOutDegreeSamples.get(key).stream().mapToDouble([it|it]).toArray();
+                                var double[] ins = map.get(key).stream().mapToDouble([it|it]).toArray();
+                                if((rep.size < 2 || ins.size < 2) ){
+                                        if(rep.size < 2 && rep.containsAll(ins)){
+                                                value += 0;
+                                        }else{
+                                                value += 1;
+                                        }
+                                }else if(rep.size >= 2 && ins.size >= 2){
+                                        value += ksTester.kolmogorovSmirnovStatistic(rep, ins);
+                                }
+                        }
+                } 
                 
-                //if the size of array is smaller than 2, ks distance cannot be performed, simply return 1
-                if(arr.size < 2) return 1;
-                return ksTester.kolmogorovSmirnovStatistic(outDegreeSamples, arr);
+                
+                return value;
         }
 }
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