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source: branches/HLScript/HeuristicLab.Tests/HeuristicLab.Encodings.BinaryVectorEncoding-3.3/NPointCrossoverTest.cs @ 12912

Last change on this file since 12912 was 9777, checked in by abeham, 11 years ago

#2088: Added test attributes and cleaned up tests of the encodings

File size: 5.8 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2013 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21
22using HeuristicLab.Core;
23using HeuristicLab.Data;
24using HeuristicLab.Tests;
25using Microsoft.VisualStudio.TestTools.UnitTesting;
26
27namespace HeuristicLab.Encodings.BinaryVectorEncoding.Tests {
28  /// <summary>
29  ///This is a test class for SinglePointCrossoverTest and is intended
30  ///to contain all SinglePointCrossoverTest Unit Tests
31  ///</summary>
32  [TestClass()]
33  public class NPointCrossoverTest {
34    /// <summary>
35    ///A test for Cross
36    ///</summary>
37    [TestMethod]
38    [TestCategory("Encodings.BinaryVector")]
39    [TestProperty("Time", "short")]
40    public void NPointCrossoverCrossTest() {
41      NPointCrossover_Accessor target = new NPointCrossover_Accessor(new PrivateObject(typeof(NPointCrossover)));
42      ItemArray<BinaryVector> parents;
43      TestRandom random = new TestRandom();
44      bool exceptionFired;
45      // The following test checks if there is an exception when there are more than 2 parents
46      random.Reset();
47      parents = new ItemArray<BinaryVector>(new BinaryVector[] { new BinaryVector(5), new BinaryVector(6), new BinaryVector(4) });
48      exceptionFired = false;
49      try {
50        BinaryVector actual;
51        actual = target.Cross(random, parents);
52      } catch (System.ArgumentException) {
53        exceptionFired = true;
54      }
55      Assert.IsTrue(exceptionFired);
56      // The following test checks if there is an exception when there are less than 2 parents
57      random.Reset();
58      parents = new ItemArray<BinaryVector>(new BinaryVector[] { new BinaryVector(4) });
59      exceptionFired = false;
60      try {
61        BinaryVector actual;
62        actual = target.Cross(random, parents);
63      } catch (System.ArgumentException) {
64        exceptionFired = true;
65      }
66      Assert.IsTrue(exceptionFired);
67    }
68
69    /// <summary>
70    ///A test for Apply
71    ///</summary>
72    [TestMethod]
73    [TestCategory("Encodings.BinaryVector")]
74    [TestProperty("Time", "short")]
75    public void NPointCrossoverApplyTest() {
76      TestRandom random = new TestRandom();
77      BinaryVector parent1, parent2, expected, actual;
78      IntValue n;
79      bool exceptionFired;
80      // The following test is based on Eiben, A.E. and Smith, J.E. 2003. Introduction to Evolutionary Computation. Natural Computing Series, Springer-Verlag Berlin Heidelberg, p. 48
81      random.Reset();
82      n = new IntValue(1);
83      random.IntNumbers = new int[] { 4 };
84      parent1 = new BinaryVector(new bool[] { false, false, false, false, true, false, false, false, false });
85      parent2 = new BinaryVector(new bool[] { true, true, false, true, false, false, false, false, true });
86      expected = new BinaryVector(new bool[] { false, false, false, false, false, false, false, false, true });
87      actual = NPointCrossover.Apply(random, parent1, parent2, n);
88      Assert.IsTrue(Auxiliary.BinaryVectorIsEqualByPosition(actual, expected));
89
90      // The following test is based on Eiben, A.E. and Smith, J.E. 2003. Introduction to Evolutionary Computation. Natural Computing Series, Springer-Verlag Berlin Heidelberg, p. 48
91      random.Reset();
92      n = new IntValue(2);
93      random.IntNumbers = new int[] { 4, 5 };
94      parent1 = new BinaryVector(new bool[] { false, false, false, false, true, false, false, false, false });
95      parent2 = new BinaryVector(new bool[] { true, true, false, true, false, false, false, false, true });
96      expected = new BinaryVector(new bool[] { false, false, false, false, false, false, false, false, false });
97      actual = NPointCrossover.Apply(random, parent1, parent2, n);
98      Assert.IsTrue(Auxiliary.BinaryVectorIsEqualByPosition(actual, expected));
99
100      // The following test is based on Eiben, A.E. and Smith, J.E. 2003. Introduction to Evolutionary Computation. Natural Computing Series, Springer-Verlag Berlin Heidelberg, p. 48
101      random.Reset();
102      n = new IntValue(2);
103      random.IntNumbers = new int[] { 4, 5 };
104      parent2 = new BinaryVector(new bool[] { false, false, false, false, true, false, false, false, false });
105      parent1 = new BinaryVector(new bool[] { true, true, false, true, false, false, false, false, true });
106      expected = new BinaryVector(new bool[] { true, true, false, true, true, false, false, false, true });
107      actual = NPointCrossover.Apply(random, parent1, parent2, n);
108      Assert.IsTrue(Auxiliary.BinaryVectorIsEqualByPosition(actual, expected));
109
110      // The following test is not based on any published examples
111      random.Reset();
112      random.IntNumbers = new int[] { 2 };
113      parent1 = new BinaryVector(new bool[] { false, true, true, false, false }); // this parent is longer
114      parent2 = new BinaryVector(new bool[] { false, true, true, false });
115      exceptionFired = false;
116      try {
117        actual = NPointCrossover.Apply(random, parent1, parent2, n);
118      } catch (System.ArgumentException) {
119        exceptionFired = true;
120      }
121      Assert.IsTrue(exceptionFired);
122    }
123  }
124}
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