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source: trunk/HeuristicLab.Tests/HeuristicLab.Encodings.BinaryVectorEncoding-3.3/SomePositionsBitflipManipulatorTest.cs @ 17277

Last change on this file since 17277 was 17180, checked in by swagner, 5 years ago

#2875: Removed years in copyrights

File size: 2.3 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 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.Data;
23using HeuristicLab.Tests;
24using Microsoft.VisualStudio.TestTools.UnitTesting;
25
26namespace HeuristicLab.Encodings.BinaryVectorEncoding.Tests {
27  /// <summary>
28  ///This is a test class for SomePositionsBitflipManipulator and is intended
29  ///to contain all SomePositionsBitflipManipulator Unit Tests
30  ///</summary>
31  [TestClass()]
32  public class SomePositionsBitflipManipulatorTest {
33    /// <summary>
34    ///A test for Apply
35    ///</summary>
36    [TestMethod]
37    [TestCategory("Encodings.BinaryVector")]
38    [TestProperty("Time", "short")]
39    public void SomePositionsBitflipManipulatorApplyTest() {
40      TestRandom random = new TestRandom();
41      BinaryVector parent, expected;
42      DoubleValue pm;
43      // The following test is based on Michalewicz, Z. 1999. Genetic Algorithms + Data Structures = Evolution Programs. Third, Revised and Extended Edition, Spring-Verlag Berlin Heidelberg, p. 21.
44      random.Reset();
45      random.DoubleNumbers = new double[] { 0.3, 0.3, 0.1, 0.1, 0.3, 0.3, 0.3, 0.1, 0.3 };
46      pm = new DoubleValue(0.2);
47      parent = new BinaryVector(new bool[] { true, false, true, false, false, false, false, true, false });
48      expected = new BinaryVector(new bool[] { true, false, false, true, false, false, false, false, false });
49      SomePositionsBitflipManipulator.Apply(random, parent, pm);
50      Assert.IsTrue(Auxiliary.BinaryVectorIsEqualByPosition(expected, parent));
51    }
52  }
53}
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