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source: stable/HeuristicLab.Encodings.BinaryVectorEncoding/3.3/Manipulators/SomePositionsBitflipManipulator.cs @ 10164

Last change on this file since 10164 was 9456, checked in by swagner, 12 years ago

Updated copyright year and added some missing license headers (#1889)

File size: 3.7 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.Common;
23using HeuristicLab.Core;
24using HeuristicLab.Data;
25using HeuristicLab.Parameters;
26using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
27
28namespace HeuristicLab.Encodings.BinaryVectorEncoding {
29  /// <summary>
30  /// Flips some bits of a binary vector.
31  /// </summary>
32  /// <remarks>
33  /// It is implemented as described in Eiben, A.E. and Smith, J.E. 2003. Introduction to Evolutionary Computation. Natural Computing Series, Springer-Verlag Berlin Heidelberg, p. 43.
34  /// </remarks>
35  [Item("SomePositionsBitflipManipulator", "Flips some bits of a binary vector, each position is flipped with a probability of pm. It is implemented as described in Eiben, A.E. and Smith, J.E. 2003. Introduction to Evolutionary Computation. Natural Computing Series, Springer-Verlag Berlin Heidelberg, p. 43.")]
36  [StorableClass]
37  public sealed class SomePositionsBitflipManipulator : BinaryVectorManipulator {
38    /// <summary>
39    /// Mmutation probability for each position.
40    /// </summary>
41    public ValueLookupParameter<DoubleValue> MutationProbabilityParameter {
42      get { return (ValueLookupParameter<DoubleValue>)Parameters["MutationProbability"]; }
43    }
44
45    [StorableConstructor]
46    private SomePositionsBitflipManipulator(bool deserializing) : base(deserializing) { }
47    private SomePositionsBitflipManipulator(SomePositionsBitflipManipulator original, Cloner cloner) : base(original, cloner) { }
48    /// <summary>
49    /// Initializes a new instance of <see cref="NPointCrossover"/>
50    /// </summary>
51    public SomePositionsBitflipManipulator()
52      : base() {
53      Parameters.Add(new ValueLookupParameter<DoubleValue>("MutationProbability", "The mutation probability for each position", new DoubleValue(0.2)));
54    }
55
56    public override IDeepCloneable Clone(Cloner cloner) {
57      return new SomePositionsBitflipManipulator(this, cloner);
58    }
59
60    /// <summary>
61    /// Performs the some positions bitflip mutation on a binary vector.
62    /// </summary>
63    /// <param name="random">The random number generator to use.</param>
64    /// <param name="vector">The vector that should be manipulated.</param>
65    /// <param name="pm">The probability a bit is flipped.</param>
66    public static void Apply(IRandom random, BinaryVector vector, DoubleValue pm) {
67      for (int i = 0; i < vector.Length; i++) {
68        if (random.NextDouble() < pm.Value) {
69          vector[i] = !vector[i];
70        }
71      }
72    }
73
74    /// <summary>
75    /// Forwards the call to <see cref="Apply(IRandom, BinaryVector)"/>.
76    /// </summary>
77    /// <param name="random">The random number generator to use.</param>
78    /// <param name="realVector">The vector of binary values to manipulate.</param>
79    protected override void Manipulate(IRandom random, BinaryVector binaryVector) {
80      Apply(random, binaryVector, MutationProbabilityParameter.Value);
81    }
82  }
83}
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