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source: branches/DataPreprocessing/HeuristicLab.Problems.TestFunctions/3.3/SimilarityCalculators/SingleObjectiveTestFunctionSimilarityCalculator.cs @ 10188

Last change on this file since 10188 was 9456, checked in by swagner, 12 years ago

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

File size: 3.8 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 System;
23using HeuristicLab.Common;
24using HeuristicLab.Core;
25using HeuristicLab.Data;
26using HeuristicLab.Encodings.RealVectorEncoding;
27using HeuristicLab.Optimization.Operators;
28using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
29
30namespace HeuristicLab.Problems.TestFunctions {
31  /// <summary>
32  /// An operator that performs similarity calculation between two test functions solutions.
33  /// </summary>
34  /// <remarks>
35  /// The operator calculates the similarity based on the euclidean distance of the two solutions in n-dimensional space.
36  /// </remarks>
37  [Item("SingleObjectiveTestFunctionSimilarityCalculator", "An operator that performs similarity calculation between two test functions solutions. The operator calculates the similarity based on the euclidean distance of the two solutions in n-dimensional space.")]
38  [StorableClass]
39  public sealed class SingleObjectiveTestFunctionSimilarityCalculator : SingleObjectiveSolutionSimilarityCalculator {
40    #region Properties
41    [Storable]
42    public DoubleMatrix Bounds { get; set; }
43    #endregion
44
45    [StorableConstructor]
46    private SingleObjectiveTestFunctionSimilarityCalculator(bool deserializing) : base(deserializing) { }
47    private SingleObjectiveTestFunctionSimilarityCalculator(SingleObjectiveTestFunctionSimilarityCalculator original, Cloner cloner)
48      : base(original, cloner) {
49      this.Bounds = cloner.Clone(original.Bounds);
50    }
51    public SingleObjectiveTestFunctionSimilarityCalculator() : base() { }
52
53    public override IDeepCloneable Clone(Cloner cloner) {
54      return new SingleObjectiveTestFunctionSimilarityCalculator(this, cloner);
55    }
56
57    public static double CalculateSimilarity(RealVector left, RealVector right, DoubleMatrix bounds) {
58      if (left == null || right == null)
59        throw new ArgumentException("Cannot calculate similarity because one of the provided solutions or both are null.");
60      if (bounds == null)
61        throw new ArgumentException("Cannot calculate similarity because no bounds were provided.");
62      if (left.Length != right.Length)
63        throw new ArgumentException("Cannot calculate similarity because the provided solutions have different lengths.");
64      if (left == right) return 1.0;
65
66      double maxSum = 0.0;
67      for (int i = 0; i < left.Length; i++)
68        maxSum += Math.Pow(bounds[0, 0] - bounds[0, 1], 2);
69      double maxDistance = Math.Sqrt(maxSum) / left.Length;
70
71      double sum = 0.0;
72      for (int i = 0; i < left.Length; i++)
73        sum += Math.Pow(left[i] - right[i], 2);
74      double distance = Math.Sqrt(sum) / left.Length;
75
76      return 1.0 - distance / maxDistance;
77    }
78
79    public override double CalculateSolutionSimilarity(IScope leftSolution, IScope rightSolution) {
80      var sol1 = leftSolution.Variables[SolutionVariableName].Value as RealVector;
81      var sol2 = rightSolution.Variables[SolutionVariableName].Value as RealVector;
82
83      return CalculateSimilarity(sol1, sol2, Bounds);
84    }
85  }
86}
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