Changeset 16955 for branches/2457_ExpertSystem/HeuristicLab.Analysis.FitnessLandscape

Timestamp:

05/15/19 13:28:57 (5 years ago)

Author:

abeham

Message:

#2457: worked on thesis

Location:

branches/2457_ExpertSystem/HeuristicLab.Analysis.FitnessLandscape/3.3

Files:

• Analysis/InformationAnalysis.cs (modified) (3 diffs)
• Analysis/InformationAnalyzer.cs (modified) (1 diff)
• Utilities/CurveAnalysis.cs (modified) (1 diff)

branches/2457_ExpertSystem/HeuristicLab.Analysis.FitnessLandscape/3.3/Analysis/InformationAnalysis.cs

@@ -46 +46 @@
     public List<double> QualityDelta { get; private set; }
     public double InformationStability { get; private set; }
-    public int Regularity { get; private set; }
-    public int Diversity { get; private set; }
+    public double Regularity { get; private set; }
+    public double Diversity { get; private set; }
     public Peak PeakInformationContent { get; private set; }
     public Peak PeakSymmetricInformationContent { get; private set; }
@@ -71 +71 @@
       var differences = Differences(qualities).ToList();
       InformationStability = differences.Select(Math.Abs).Max();
-      Regularity = new HashSet<double>(differences).Count;
-      Diversity = new HashSet<double>(qualities).Count;
+      Regularity = new HashSet<double>(differences).Count / (double)differences.Count;
+      Diversity = new HashSet<double>(qualities).Count / (double)qualities.Count;
       var absDifferences = differences.Select(Math.Abs).OrderBy(d => d).ToList();
       nQuantiles = Math.Min(nQuantiles, absDifferences.Count);
@@ -118 +118 @@
       PeakTotalEntropy = GetPeak(QualityDelta, TotalEntropy);
       PeakSymmetricTotalEntropy = GetPeak(QualityDelta, SymmetricTotalEntropy);
+    }
+
+    public IEnumerable<Tuple<string, object>> GetFeatures() {
+      yield return Tuple.Create("InformationContent", (object)InformationContent[0]);
+      yield return Tuple.Create("DensityBasinInformation", (object)DensityBasinInformation[0]);
+      yield return Tuple.Create("PartialInformationContent", (object)PartialInformationContent[0]);
+      yield return Tuple.Create("TotalEntropy", (object)TotalEntropy[0]);
+      yield return Tuple.Create("InformationStability", (object)InformationStability);
+      yield return Tuple.Create("Regularity", (object)Regularity);
+      yield return Tuple.Create("Diversity", (object)Diversity);
+      yield return Tuple.Create("SymmetricInformationContent", (object)SymmetricInformationContent[0]);
+      yield return Tuple.Create("SymmetricDensityBasinInformation", (object)SymmetricDensityBasinInformation[0]);
+      yield return Tuple.Create("SymmetricTotalEntropy", (object)SymmetricTotalEntropy[0]);
+      yield return Tuple.Create("PeakInformationContent", (object)PeakInformationContent.Value);
+      yield return Tuple.Create("PeakDensityBasinInformation", (object)PeakDensityBasinInformation.Value);
+      yield return Tuple.Create("PeakTotalEntropy", (object)PeakTotalEntropy.Value);
+      yield return Tuple.Create("PeakSymmetricInformationContent", (object)PeakSymmetricInformationContent.Value);
+      yield return Tuple.Create("PeakSymmetricDensityBasinInformation", (object)PeakSymmetricDensityBasinInformation.Value);
+      yield return Tuple.Create("PeakSymmetricTotalEntropy", (object)PeakSymmetricTotalEntropy.Value);
     }
 

branches/2457_ExpertSystem/HeuristicLab.Analysis.FitnessLandscape/3.3/Analysis/InformationAnalyzer.cs

@@ -132 +132 @@
       InformationStabilityParameter.ActualValue = @is;
       results.AddOrUpdateResult(InformationStabilityParameter.Name, @is);
-      var regularity = new DoubleValue(1.0 * analysis.Regularity / qualities.Count);
+      var regularity = new DoubleValue(analysis.Regularity);
       RegularityParameter.ActualValue = regularity;
       results.AddOrUpdateResult(RegularityParameter.Name, regularity);
-      var diversity = new DoubleValue(1.0 * analysis.Diversity / qualities.Count);
+      var diversity = new DoubleValue(analysis.Diversity);
       DiversityParameter.ActualValue = diversity;
       results.AddOrUpdateResult(DiversityParameter.Name, diversity);

branches/2457_ExpertSystem/HeuristicLab.Analysis.FitnessLandscape/3.3/Utilities/CurveAnalysis.cs

@@ -26 +26 @@
 namespace HeuristicLab.Analysis.FitnessLandscape {
   public static class CurveAnalysis<T> {
-    public static CurveAnalysisResult GetCharacteristics(List<List<Tuple<T, double>>> trajectories, Func<T, T, double> distFunc) {
-      trajectories = trajectories.Where(x => x.Count > 5).ToList();
-      if (trajectories.Count == 0) return new CurveAnalysisResult(0, 0, 0, new[] { 0.0, 0.0, 0.0 }, new[] { 0.0, 0.0, 0.0 }, new[] { 0.0, 0.0, 0.0 });
+    public static CurveAnalysisResult GetCharacteristics(IEnumerable<List<Tuple<T, double>>> trajectories, Func<T, T, double> distFunc) {
+      var traj = trajectories.Where(x => x.Count > 5).ToList();
+      if (traj.Count == 0) return new CurveAnalysisResult(0, 0, 0, new[] { 0.0, 0.0, 0.0 }, new[] { 0.0, 0.0, 0.0 }, new[] { 0.0, 0.0, 0.0 });
 
-      var symbols = GetSymbols(trajectories);
-      var f1 = trajectories.Select(path => ApproximateDerivative(path, distFunc).ToList()).ToList();
+      var symbols = GetSymbols(traj);
+      var f1 = traj.Select(path => ApproximateDerivative(path, distFunc).ToList()).ToList();
       var f2 = f1.Select(d1 => ApproximateDerivative(d1, distFunc).ToList()).ToList();