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source: trunk/sources/HeuristicLab.Encodings.PermutationEncoding/3.3/Tests/EdgeRecombinationCrossoverTest.cs @ 3063

Last change on this file since 3063 was 3063, checked in by svonolfe, 14 years ago

Updated assembly reference in test cases (#889)

File size: 4.7 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2010 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 Microsoft.VisualStudio.TestTools.UnitTesting;
24using HeuristicLab.Encodings.PermutationEncoding;
25
26namespace HeuristicLab.Encodings.PermutationEncoding_33.Tests {
27  /// <summary>
28  ///This is a test class for EdgeRecombinationCrossover and is intended
29  ///to contain all EdgeRecombinationCrossover Unit Tests
30  ///</summary>
31  [TestClass()]
32  public class EdgeRecombinationCrossoverTest {
33
34
35    private TestContext testContextInstance;
36
37    /// <summary>
38    ///Gets or sets the test context which provides
39    ///information about and functionality for the current test run.
40    ///</summary>
41    public TestContext TestContext {
42      get {
43        return testContextInstance;
44      }
45      set {
46        testContextInstance = value;
47      }
48    }
49
50    #region Additional test attributes
51    //
52    //You can use the following additional attributes as you write your tests:
53    //
54    //Use ClassInitialize to run code before running the first test in the class
55    //[ClassInitialize()]
56    //public static void MyClassInitialize(TestContext testContext)
57    //{
58    //}
59    //
60    //Use ClassCleanup to run code after all tests in a class have run
61    //[ClassCleanup()]
62    //public static void MyClassCleanup()
63    //{
64    //}
65    //
66    //Use TestInitialize to run code before running each test
67    //[TestInitialize()]
68    //public void MyTestInitialize()
69    //{
70    //}
71    //
72    //Use TestCleanup to run code after each test has run
73    //[TestCleanup()]
74    //public void MyTestCleanup()
75    //{
76    //}
77    //
78    #endregion
79
80
81    /// <summary>
82    ///A test for Cross
83    ///</summary>
84    [TestMethod()]
85    [DeploymentItem("HeuristicLab.Encodings.PermutationEncoding-3.3.dll")]
86    public void EdgeRecombinationCrossoverCrossoverCrossTest() {
87      TestRandom random = new TestRandom();
88      EdgeRecombinationCrossover_Accessor target =
89        new EdgeRecombinationCrossover_Accessor(new PrivateObject(typeof(EdgeRecombinationCrossover)));
90      // perform a test with more than two parents
91      random.Reset();
92      bool exceptionFired = false;
93      try {
94        target.Cross(random, new ItemArray<Permutation>(new Permutation[] {
95          new Permutation(4), new Permutation(4), new Permutation(4)}));
96      }
97      catch (System.InvalidOperationException) {
98        exceptionFired = true;
99      }
100      Assert.IsTrue(exceptionFired);
101    }
102
103    /// <summary>
104    ///A test for Apply
105    ///</summary>
106    [TestMethod()]
107    public void EdgeRecombinationCrossoverApplyTest() {
108      TestRandom random = new TestRandom();
109      Permutation parent1, parent2, expected, actual;
110      // The following test is based on an example from Eiben, A.E. and Smith, J.E. 2003. Introduction to Evolutionary Computation. Natural Computing Series, Springer-Verlag Berlin Heidelberg, pp. 54-55
111      random.Reset();
112      random.IntNumbers = new int[] { 0 };
113      random.DoubleNumbers = new double[] { 0.5, 0, 0, 0 };
114      parent1 = new Permutation(new int[] { 0, 1, 2, 3, 4, 5, 6, 7, 8 });
115      Assert.IsTrue(parent1.Validate());
116      parent2 = new Permutation(new int[] { 8, 2, 6, 7, 1, 5, 4, 0, 3 });
117      Assert.IsTrue(parent2.Validate());
118      expected = new Permutation(new int[] { 0, 4, 5, 1, 7, 6, 2, 8, 3 });
119      Assert.IsTrue(expected.Validate());
120      actual = EdgeRecombinationCrossover.Apply(random, parent1, parent2);
121      Assert.IsTrue(actual.Validate());
122      Assert.IsTrue(Auxiliary.PermutationIsEqualByPosition(expected, actual));
123     
124      // perform a test when the two permutations are of unequal length
125      random.Reset();
126      bool exceptionFired = false;
127      try {
128        EdgeRecombinationCrossover.Apply(random, new Permutation(8), new Permutation(6));
129      }
130      catch (System.ArgumentException) {
131        exceptionFired = true;
132      }
133      Assert.IsTrue(exceptionFired);
134    }
135  }
136}
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