Changeset 5549 for branches/DataAnalysis Refactoring/HeuristicLab.Encodings.SymbolicExpressionTreeEncoding/3.4/Tests/SubtreeCrossoverTest.cs

Timestamp:

02/22/11 19:04:54 (14 years ago)

Author:

gkronber

Message:

#1418 unified size/height vs. length/depth terminology and adapted unit tests for symbolic expression tree encoding version 3.4

File:

• branches/DataAnalysis Refactoring/HeuristicLab.Encodings.SymbolicExpressionTreeEncoding/3.4/Tests/SubtreeCrossoverTest.cs (modified) (3 diffs)

branches/DataAnalysis Refactoring/HeuristicLab.Encodings.SymbolicExpressionTreeEncoding/3.4/Tests/SubtreeCrossoverTest.cs

@@ -24 +24 @@
 using System.Diagnostics;
 using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
-using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding.Creators;
-using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding.Crossovers;
 using HeuristicLab.Random;
 using Microsoft.VisualStudio.TestTools.UnitTesting;
 
-namespace HeuristicLab.Encodings.SymbolicExpressionTreeEncoding_3._3.Tests {
+namespace HeuristicLab.Encodings.SymbolicExpressionTreeEncoding_3._4.Tests {
   [TestClass]
   public class SubtreeCrossoverTest {
@@ -51 +49 @@
     public void SubtreeCrossoverDistributionsTest() {
       int generations = 5;
-      var trees = new List<SymbolicExpressionTree>();
+      var trees = new List<ISymbolicExpressionTree>();
       var grammar = Grammars.CreateArithmeticAndAdfGrammar();
       var random = new MersenneTwister(31415);
-      List<SymbolicExpressionTree> crossoverTrees;
+      List<ISymbolicExpressionTree> crossoverTrees;
       double msPerCrossoverEvent;
 
@@ -63 +61 @@
       stopwatch.Start();
       for (int gCount = 0; gCount < generations; gCount++) {
-        var newPopulation = new List<SymbolicExpressionTree>();
+        var newPopulation = new List<ISymbolicExpressionTree>();
         for (int i = 0; i < POPULATION_SIZE; i++) {
           var par0 = (SymbolicExpressionTree)trees.SelectRandom(random).Clone();
           var par1 = (SymbolicExpressionTree)trees.SelectRandom(random).Clone();
-          bool success;
-          newPopulation.Add(SubtreeCrossover.Cross(random, par0, par1, 0.9, 100, 10, out success));
-          Assert.IsTrue(success);
+          newPopulation.Add(SubtreeCrossover.Cross(random, par0, par1, 0.9, 100, 10));
         }
         crossoverTrees = newPopulation;