1 files changed, 47 insertions, 0 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
new file mode 100644
index 00000000..1fb21529
--- /dev/null
+++ b/Metrics/Metrics-Calculation/ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator/src/ca/mcgill/ecse/dslreasoner/realistic/metrics/calculator/distance/KSDistance.xtend
@@ -0,0 +1,47 @@
+package ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.distance
+
+import ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.app.Domain
+import java.util.List
+import org.apache.commons.math3.stat.inference.KolmogorovSmirnovTest
+import ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.io.RepMetricsReader
+
+class KSDistance {
+        var static ksTester = new KolmogorovSmirnovTest();
+        var double[] mpcSamples;
+        var double[] naSamples;
+        var double[] outDegreeSamples;
+        
+        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();
+        }
+        
+        def double mpcDistance(List<Double> samples){
+                // map list to array
+                var arr = samples.stream.mapToDouble([it]).toArray();
+                
+                //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);
+        }
+        
+        def double naDistance(List<Double> samples){
+                // map list to array
+                var arr = samples.stream.mapToDouble([it]).toArray();
+                
+                //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);
+        }
+        
+        def double outDegreeDistance(List<Double> samples){
+                // map list to array
+                var arr = samples.stream.mapToDouble([it]).toArray();
+                
+                //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);
+        }
+}
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