1 files changed, 93 insertions, 0 deletions

diff --git a/Metrics/Metrics-Calculation/ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator/xtend-gen/ca/mcgill/ecse/dslreasoner/realistic/metrics/calculator/distance/KSDistance.java b/Metrics/Metrics-Calculation/ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator/xtend-gen/ca/mcgill/ecse/dslreasoner/realistic/metrics/calculator/distance/KSDistance.java
new file mode 100644
index 00000000..638ff332
--- /dev/null
+++ b/Metrics/Metrics-Calculation/ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator/xtend-gen/ca/mcgill/ecse/dslreasoner/realistic/metrics/calculator/distance/KSDistance.java
@@ -0,0 +1,93 @@
+package ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.distance;
+
+import ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.distance.CostDistance;
+import ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.metrics.MetricSampleGroup;
+import java.util.ArrayList;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Set;
+import org.eclipse.xtext.xbase.lib.CollectionLiterals;
+
+@SuppressWarnings("all")
+public class KSDistance extends CostDistance {
+  private static Object ksTester /* Skipped initializer because of errors */;
+  
+  private MetricSampleGroup g;
+  
+  public KSDistance(final MetricSampleGroup g) {
+    this.g = g;
+  }
+  
+  @Override
+  public double mpcDistance(final List<Double> samples) {
+    throw new Error("Unresolved compilation problems:"
+      + "\nThe field KSDistance.ksTester refers to the missing type Object"
+      + "\nkolmogorovSmirnovStatistic cannot be resolved");
+  }
+  
+  @Override
+  public double naDistance(final List<Double> samples) {
+    throw new Error("Unresolved compilation problems:"
+      + "\nThe field KSDistance.ksTester refers to the missing type Object"
+      + "\nkolmogorovSmirnovStatistic cannot be resolved");
+  }
+  
+  @Override
+  public double outDegreeDistance(final List<Double> samples) {
+    throw new Error("Unresolved compilation problems:"
+      + "\nThe field KSDistance.ksTester refers to the missing type Object"
+      + "\nkolmogorovSmirnovStatistic cannot be resolved");
+  }
+  
+  public double typedOutDegreeDistance(final HashMap<String, List<Integer>> map) {
+    throw new Error("Unresolved compilation problems:"
+      + "\nThe field KSDistance.ksTester refers to the missing type Object"
+      + "\nkolmogorovSmirnovStatistic cannot be resolved");
+  }
+  
+  public double nodeTypeDistance(final HashMap<String, Double> samples) {
+    HashMap<String, Double> typesDistMap = this.g.nodeTypeSamples;
+    ArrayList<Double> sourceDist = CollectionLiterals.<Double>newArrayList();
+    ArrayList<Double> instanceDist = CollectionLiterals.<Double>newArrayList();
+    Set<String> _keySet = typesDistMap.keySet();
+    for (final String key : _keySet) {
+      {
+        sourceDist.add(typesDistMap.get(key));
+        instanceDist.add(samples.getOrDefault(key, Double.valueOf(0.0)));
+      }
+    }
+    return this.ks_distance_two_dist(sourceDist, instanceDist);
+  }
+  
+  public double edgeTypeDistance(final HashMap<String, Double> samples) {
+    HashMap<String, Double> typesDistMap = this.g.edgeTypeSamples;
+    ArrayList<Double> sourceDist = CollectionLiterals.<Double>newArrayList();
+    ArrayList<Double> instanceDist = CollectionLiterals.<Double>newArrayList();
+    Set<String> _keySet = typesDistMap.keySet();
+    for (final String key : _keySet) {
+      {
+        sourceDist.add(typesDistMap.get(key));
+        instanceDist.add(samples.getOrDefault(key, Double.valueOf(0.0)));
+      }
+    }
+    return this.ks_distance_two_dist(sourceDist, instanceDist);
+  }
+  
+  public double ks_distance_two_dist(final List<Double> dist1, final List<Double> dist2) {
+    double ksStatistics = 0.0;
+    double sum1 = 0.0;
+    double sum2 = 0.0;
+    for (int i = 0; (i < dist1.size()); i++) {
+      {
+        double _sum1 = sum1;
+        Double _get = dist1.get(i);
+        sum1 = (_sum1 + (_get).doubleValue());
+        double _sum2 = sum2;
+        Double _get_1 = dist2.get(i);
+        sum2 = (_sum2 + (_get_1).doubleValue());
+        ksStatistics = Math.max(ksStatistics, Math.abs((sum1 - sum2)));
+      }
+    }
+    return ksStatistics;
+  }
+}