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source: branches/Trunk/HeuristicLab.Tests/HeuristicLab.Encodings.BinaryVectorEncoding-3.3/NPointCrossoverTest.cs @ 6844

Last change on this file since 6844 was 6844, checked in by mkommend, 13 years ago

#1653: Restructured unit tests.

File size: 7.1 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2011 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.Encodings.BinaryVectorEncoding;
25using Microsoft.VisualStudio.TestTools.UnitTesting;
26
27namespace HeuristicLab.Encodings.BinaryVectorEncoding_33.Tests {
28
29
30  /// <summary>
31  ///This is a test class for SinglePointCrossoverTest and is intended
32  ///to contain all SinglePointCrossoverTest Unit Tests
33  ///</summary>
34  [TestClass()]
35  public class NPointCrossoverTest {
36
37
38    private TestContext testContextInstance;
39
40    /// <summary>
41    ///Gets or sets the test context which provides
42    ///information about and functionality for the current test run.
43    ///</summary>
44    public TestContext TestContext {
45      get {
46        return testContextInstance;
47      }
48      set {
49        testContextInstance = value;
50      }
51    }
52
53    #region Additional test attributes
54    //
55    //You can use the following additional attributes as you write your tests:
56    //
57    //Use ClassInitialize to run code before running the first test in the class
58    //[ClassInitialize()]
59    //public static void MyClassInitialize(TestContext testContext)
60    //{
61    //}
62    //
63    //Use ClassCleanup to run code after all tests in a class have run
64    //[ClassCleanup()]
65    //public static void MyClassCleanup()
66    //{
67    //}
68    //
69    //Use TestInitialize to run code before running each test
70    //[TestInitialize()]
71    //public void MyTestInitialize()
72    //{
73    //}
74    //
75    //Use TestCleanup to run code after each test has run
76    //[TestCleanup()]
77    //public void MyTestCleanup()
78    //{
79    //}
80    //
81    #endregion
82
83    /// <summary>
84    ///A test for Cross
85    ///</summary>
86    [TestMethod()]
87    [DeploymentItem("HeuristicLab.Encodings.BinaryVectorEncoding-3.3.dll")]
88    public void SinglePointCrossoverCrossTest() {
89      NPointCrossover_Accessor target = new NPointCrossover_Accessor(new PrivateObject(typeof(NPointCrossover)));
90      ItemArray<BinaryVector> parents;
91      TestRandom random = new TestRandom();
92      bool exceptionFired;
93      // The following test checks if there is an exception when there are more than 2 parents
94      random.Reset();
95      parents = new ItemArray<BinaryVector>(new BinaryVector[] { new BinaryVector(5), new BinaryVector(6), new BinaryVector(4) });
96      exceptionFired = false;
97      try {
98        BinaryVector actual;
99        actual = target.Cross(random, parents);
100      }
101      catch (System.ArgumentException) {
102        exceptionFired = true;
103      }
104      Assert.IsTrue(exceptionFired);
105      // The following test checks if there is an exception when there are less than 2 parents
106      random.Reset();
107      parents = new ItemArray<BinaryVector>(new BinaryVector[] { new BinaryVector(4) });
108      exceptionFired = false;
109      try {
110        BinaryVector actual;
111        actual = target.Cross(random, parents);
112      }
113      catch (System.ArgumentException) {
114        exceptionFired = true;
115      }
116      Assert.IsTrue(exceptionFired);
117    }
118
119    /// <summary>
120    ///A test for Apply
121    ///</summary>
122    [TestMethod()]
123    public void SinglePointCrossoverApplyTest() {
124      TestRandom random = new TestRandom();
125      BinaryVector parent1, parent2, expected, actual;
126      IntValue n;
127      bool exceptionFired;
128      // 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
129      random.Reset();
130      n = new IntValue(1);
131      random.IntNumbers = new int[] { 4 };
132      parent1 = new BinaryVector(new bool[] { false, false, false, false, true, false, false, false, false });
133      parent2 = new BinaryVector(new bool[] { true, true, false, true, false, false, false, false, true });
134      expected = new BinaryVector(new bool[] { false, false, false, false, false, false, false, false, true });
135      actual = NPointCrossover.Apply(random, parent1, parent2, n);
136      Assert.IsTrue(Auxiliary.BinaryVectorIsEqualByPosition(actual, expected));
137
138      // 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
139      random.Reset();
140      n = new IntValue(2);
141      random.IntNumbers = new int[] { 4, 5 };
142      parent1 = new BinaryVector(new bool[] { false, false, false, false, true, false, false, false, false });
143      parent2 = new BinaryVector(new bool[] { true, true, false, true, false, false, false, false, true });
144      expected = new BinaryVector(new bool[] { false, false, false, false, false, false, false, false, false });
145      actual = NPointCrossover.Apply(random, parent1, parent2, n);
146      Assert.IsTrue(Auxiliary.BinaryVectorIsEqualByPosition(actual, expected));
147
148      // 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
149      random.Reset();
150      n = new IntValue(2);
151      random.IntNumbers = new int[] { 4, 5 };
152      parent2 = new BinaryVector(new bool[] { false, false, false, false, true, false, false, false, false });
153      parent1 = new BinaryVector(new bool[] { true, true, false, true, false, false, false, false, true });
154      expected = new BinaryVector(new bool[] { true, true, false, true, true, false, false, false, true });
155      actual = NPointCrossover.Apply(random, parent1, parent2, n);
156      Assert.IsTrue(Auxiliary.BinaryVectorIsEqualByPosition(actual, expected));
157
158      // The following test is not based on any published examples
159      random.Reset();
160      random.IntNumbers = new int[] { 2 };
161      parent1 = new BinaryVector(new bool[] { false, true, true, false, false }); // this parent is longer
162      parent2 = new BinaryVector(new bool[] { false, true, true, false });
163      exceptionFired = false;
164      try {
165        actual = NPointCrossover.Apply(random, parent1, parent2, n);
166      }
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}
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