Free cookie consent management tool by TermsFeed Policy Generator

source: trunk/sources/HeuristicLab.Encodings.BinaryVectorEncoding/3.3/Tests/NPointCrossoverTest.cs @ 3742

Last change on this file since 3742 was 3742, checked in by gkronber, 14 years ago

Fixed GPL license headers and deleted files which are not referenced by projects. #893

File size: 7.2 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.Encodings.BinaryVectorEncoding;
23using Microsoft.VisualStudio.TestTools.UnitTesting;
24using HeuristicLab.Common;
25using HeuristicLab.Core;
26using HeuristicLab.Data;
27using HeuristicLab.Parameters;
28
29namespace HeuristicLab.Encodings.BinaryVectorEncoding_33.Tests {
30
31
32  /// <summary>
33  ///This is a test class for SinglePointCrossoverTest and is intended
34  ///to contain all SinglePointCrossoverTest Unit Tests
35  ///</summary>
36  [TestClass()]
37  public class NPointCrossoverTest {
38
39
40    private TestContext testContextInstance;
41
42    /// <summary>
43    ///Gets or sets the test context which provides
44    ///information about and functionality for the current test run.
45    ///</summary>
46    public TestContext TestContext {
47      get {
48        return testContextInstance;
49      }
50      set {
51        testContextInstance = value;
52      }
53    }
54
55    #region Additional test attributes
56    //
57    //You can use the following additional attributes as you write your tests:
58    //
59    //Use ClassInitialize to run code before running the first test in the class
60    //[ClassInitialize()]
61    //public static void MyClassInitialize(TestContext testContext)
62    //{
63    //}
64    //
65    //Use ClassCleanup to run code after all tests in a class have run
66    //[ClassCleanup()]
67    //public static void MyClassCleanup()
68    //{
69    //}
70    //
71    //Use TestInitialize to run code before running each test
72    //[TestInitialize()]
73    //public void MyTestInitialize()
74    //{
75    //}
76    //
77    //Use TestCleanup to run code after each test has run
78    //[TestCleanup()]
79    //public void MyTestCleanup()
80    //{
81    //}
82    //
83    #endregion
84
85    /// <summary>
86    ///A test for Cross
87    ///</summary>
88    [TestMethod()]
89    [DeploymentItem("HeuristicLab.Encodings.BinaryVectorEncoding-3.3.dll")]
90    public void SinglePointCrossoverCrossTest() {
91      NPointCrossover_Accessor target = new NPointCrossover_Accessor(new PrivateObject(typeof(NPointCrossover)));
92      ItemArray<BinaryVector> parents;
93      TestRandom random = new TestRandom();
94      bool exceptionFired;
95      // The following test checks if there is an exception when there are more than 2 parents
96      random.Reset();
97      parents = new ItemArray<BinaryVector>(new BinaryVector[] { new BinaryVector(5), new BinaryVector(6), new BinaryVector(4) });
98      exceptionFired = false;
99      try {
100        BinaryVector actual;
101        actual = target.Cross(random, parents);
102      }
103      catch (System.ArgumentException) {
104        exceptionFired = true;
105      }
106      Assert.IsTrue(exceptionFired);
107      // The following test checks if there is an exception when there are less than 2 parents
108      random.Reset();
109      parents = new ItemArray<BinaryVector>(new BinaryVector[] { new BinaryVector(4) });
110      exceptionFired = false;
111      try {
112        BinaryVector actual;
113        actual = target.Cross(random, parents);
114      } catch (System.ArgumentException) {
115        exceptionFired = true;
116      }
117      Assert.IsTrue(exceptionFired);
118    }
119
120    /// <summary>
121    ///A test for Apply
122    ///</summary>
123    [TestMethod()]
124    public void SinglePointCrossoverApplyTest() {
125      TestRandom random = new TestRandom();
126      BinaryVector parent1, parent2, expected, actual;
127      IntValue n;
128      bool exceptionFired;
129      // 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
130      random.Reset();
131      n = new IntValue(1);
132      random.IntNumbers = new int[] { 4 };
133      parent1 = new BinaryVector(new bool[] { false, false, false, false, true, false, false, false, false });
134      parent2 = new BinaryVector(new bool[] { true, true, false, true, false, false, false, false, true });
135      expected = new BinaryVector(new bool[] { false, false, false, false, false, false, false, false, true });
136      actual = NPointCrossover.Apply(random, parent1, parent2, n);
137      Assert.IsTrue(Auxiliary.BinaryVectorIsEqualByPosition(actual, expected));
138     
139      // 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
140      random.Reset();
141      n = new IntValue(2);
142      random.IntNumbers = new int[] { 4, 5 };
143      parent1 = new BinaryVector(new bool[] { false, false, false, false, true, false, false, false, false });
144      parent2 = new BinaryVector(new bool[] { true, true, false, true, false, false, false, false, true });
145      expected = new BinaryVector(new bool[] { false, false, false, false, false, false, false, false, false });
146      actual = NPointCrossover.Apply(random, parent1, parent2, n);
147      Assert.IsTrue(Auxiliary.BinaryVectorIsEqualByPosition(actual, expected));
148
149      // 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
150      random.Reset();
151      n = new IntValue(2);
152      random.IntNumbers = new int[] { 4, 5 };
153      parent2 = new BinaryVector(new bool[] { false, false, false, false, true, false, false, false, false });
154      parent1 = new BinaryVector(new bool[] { true, true, false, true, false, false, false, false, true });
155      expected = new BinaryVector(new bool[] { true, true, false, true, true, false, false, false, true });
156      actual = NPointCrossover.Apply(random, parent1, parent2, n);
157      Assert.IsTrue(Auxiliary.BinaryVectorIsEqualByPosition(actual, expected));
158
159      // The following test is not based on any published examples
160      random.Reset();
161      random.IntNumbers = new int[] { 2 };
162      parent1 = new BinaryVector(new bool[] { false, true, true, false, false }); // this parent is longer
163      parent2 = new BinaryVector(new bool[] { false, true, true, false });
164      exceptionFired = false;
165      try {
166        actual = NPointCrossover.Apply(random, parent1, parent2, n);
167      } catch (System.ArgumentException) {
168        exceptionFired = true;
169      }
170      Assert.IsTrue(exceptionFired);
171    }
172
173    /// <summary>
174    ///A test for SinglePointCrossover Constructor
175    ///</summary>
176    [TestMethod()]
177    public void SinglePointCrossoverConstructorTest() {
178      NPointCrossover target = new NPointCrossover();
179    }
180  }
181}
Note: See TracBrowser for help on using the repository browser.