Changeset 14875 for branches/PushGP/HeuristicLab.PushGP/HeuristicLab.Problems.ProgramSynthesis/Push/Selector/LexicaseSelector.cs

Timestamp:

04/18/17 01:15:25 (7 years ago)

Author:

pkimmesw

Message:

#2665 BenchmarkSuite, all examples, partially tested, VectorExpressions added

File:

• branches/PushGP/HeuristicLab.PushGP/HeuristicLab.Problems.ProgramSynthesis/Push/Selector/LexicaseSelector.cs (modified) (3 diffs)

branches/PushGP/HeuristicLab.PushGP/HeuristicLab.Problems.ProgramSynthesis/Push/Selector/LexicaseSelector.cs

@@ -70 +70 @@
       var repeats = Math.Ceiling(count / (double)population.Count);
       var caseCount = caseQualities[0].Length;
-      var source = population.Select((x, i) => Tuple.Create(i, x));
+      var source = Enumerable.Range(0, population.Count).ToList();
 
       for (var k = 0; k < repeats; k++) {
         // The fitness cases are shuffled.
         var fitnessCaseIndexes = Enumerable.Range(0, caseCount).Shuffle(random).ToArray();
-        var pool = source.ToList();
+
+        // copy list if required
+        var pool = k == repeats - 1 ? source : new List<int>(source);
         var countLimit = Math.Min(count - k * population.Count, population.Count);
 
@@ -86 +88 @@
           /*  If only one individual remains, it is the chosen parent. If no more fitness cases are left, a parent is
               chosen randomly from the remaining individuals */
-          var currentSelected = bestIndividuals.Count == 1 ? bestIndividuals[0] : bestIndividuals.Random(random);
-          selected[k * population.Count + i] = copy ? (IScope)currentSelected.Item2.Clone() : currentSelected.Item2;
+          var bestIndividualIndex = bestIndividuals.Count == 1 ? bestIndividuals[0] : bestIndividuals.Random(random);
+          var bestIndividual = population[bestIndividualIndex];
 
-          pool.Remove(currentSelected);
+          selected[k * population.Count + i] = copy ? (IScope)bestIndividual.Clone() : bestIndividual;
+
+          pool.Remove(bestIndividualIndex);
         }
       }
@@ -96 +100 @@
     }
 
-    private static List<Tuple<int, IScope>> GetBestIndividuals(bool maximization, ItemArray<DoubleArray> caseQualities, List<Tuple<int, IScope>> bestIndividuals, int index) {
+    private static List<int> GetBestIndividuals(bool maximization, ItemArray<DoubleArray> caseQualities, List<int> bestIndividuals, int index) {
       var bestFitness = maximization ? double.NegativeInfinity : double.PositiveInfinity;
-      var result = new List<Tuple<int, IScope>>();
+      var result = new List<int>();
 
       for (var l = 0; l < bestIndividuals.Count; l++) {
         var individual = bestIndividuals[l];
-        var caseQuality = caseQualities[individual.Item1][index];
+        var caseQuality = caseQualities[individual][index];
 
-        if (bestFitness == caseQuality) {
+        if (bestFitness.IsAlmost(caseQuality)) {
           result.Add(individual);
         } else if (maximization && bestFitness < caseQuality ||