source: branches/1614_GeneralizedQAP/HeuristicLab.Analysis.FitnessLandscape/3.3/ProblemCharacteristicAnalysis/DoubleMatrixCharacteristicCalculator.cs @ 15713

Last change on this file since 15713 was 14678, checked in by abeham, 5 years ago

#2457: worked on problem instance detection

File size: 2.5 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2016 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.Data;
24using System;
25using System.Linq;
26
27namespace HeuristicLab.Analysis.FitnessLandscape {
28  public static class DoubleMatrixCharacteristicCalculator {
29    public static double CoeffVariation(DoubleMatrix m) {
30      var avg = m.Average();
31      var stdDev = m.StandardDeviation();
32      return stdDev / avg;
33    }
34
35    public static double Sparsity(DoubleMatrix m) {
36      return m.Count(x => x == 0) / (double)(m.Rows * m.Columns);
37    }
38
39    public static double Disparity(DoubleMatrix m) {
40      if (m.Rows != m.Columns) throw new ArgumentException("not a quadratic matrix", "m");
41      var n = m.Rows;
42      var avg = m.Sum() / n;
43      var disparity = 0.0;
44      for (var i = 0; i < n; i++) {
45        var tmp = 0.0;
46        for (var j = 0; j < n; j++) {
47          tmp += m[i, j];
48        }
49        disparity += (tmp - avg) * (tmp - avg);
50      }
51      return Math.Sqrt(disparity / n) / avg;
52    }
53
54    public static double Skewness(DoubleMatrix m) {
55      double mean = 0, variance = 0, skewness = 0, kurtosis = 0;
56      alglib.basestat.samplemoments(m.ToArray(), m.Rows * m.Columns, ref mean, ref variance, ref skewness, ref kurtosis);
57      return skewness;
58    }
59
60    public static double Asymmetry(DoubleMatrix m) {
61      if (m.Rows != m.Columns) throw new ArgumentException("not a quadratic matrix", "m");
62      var n = m.Rows;
63      var count = 0;
64      for (var i = 0; i < n; i++) {
65        for (var j = 0; j < i; j++) {
66          var v = Math.Abs(m[i, j] - m[j, i]);
67          if (v > 0) {
68            count++;
69          }
70        }
71      }
72      return count / (n * (n - 1) / 2.0);
73    }
74  }
75}
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