1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2012 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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4 | *
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5 | * This file is part of HeuristicLab.
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6 | *
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7 | * HeuristicLab is free software: you can redistribute it and/or modify
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8 | * it under the terms of the GNU General Public License as published by
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9 | * the Free Software Foundation, either version 3 of the License, or
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10 | * (at your option) any later version.
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11 | *
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12 | * HeuristicLab is distributed in the hope that it will be useful,
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13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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15 | * GNU General Public License for more details.
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16 | *
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17 | * You should have received a copy of the GNU General Public License
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18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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19 | */
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20 | #endregion
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21 |
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22 | using System.Collections.Generic;
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23 | using HeuristicLab.Data;
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24 | using HeuristicLab.Encodings.PermutationEncoding;
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25 |
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26 | namespace HeuristicLab.Problems.QuadraticAssignment {
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27 | public static class QAPPermutationProximityCalculator {
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28 |
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29 | public static double CalculateGenotypeSimilarity(Permutation a, Permutation b) {
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30 | int similar = 0;
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31 | for (int i = 0; i < a.Length; i++) {
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32 | if (a[i] == b[i]) similar++;
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33 | }
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34 | return similar / (double)a.Length;
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35 | }
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36 |
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37 | public static double CalculateGenotypeDistance(Permutation a, Permutation b) {
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38 | return 1.0 - CalculateGenotypeSimilarity(a, b);
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39 | }
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40 |
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41 | public static double CalculatePhenotypeSimilarity(Permutation a, Permutation b, DoubleMatrix weights, DoubleMatrix distances) {
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42 | return 1.0 - CalculatePhenotypeDistance(a, b, weights, distances);
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43 | }
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44 |
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45 | public static double CalculatePhenotypeDistance(Permutation a, Permutation b, DoubleMatrix weights, DoubleMatrix distances) {
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46 | Dictionary<double, Dictionary<double, int>> alleles = new Dictionary<double, Dictionary<double, int>>();
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47 | int distance = 0, len = a.Length;
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48 | for (int x = 0; x < len; x++) {
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49 | for (int y = 0; y < len; y++) {
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50 | // there's a limited universe of double values as they're all drawn from the same matrix
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51 | double dA = distances[a[x], a[y]], dB = distances[b[x], b[y]];
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52 | if (dA == dB) continue;
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53 |
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54 | Dictionary<double, int> dAlleles;
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55 | if (!alleles.ContainsKey(weights[x, y])) {
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56 | dAlleles = new Dictionary<double, int>();
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57 | alleles.Add(weights[x, y], dAlleles);
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58 | } else dAlleles = alleles[weights[x, y]];
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59 |
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60 | int countA = 1, countB = -1;
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61 |
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62 | if (dAlleles.ContainsKey(dA)) countA += dAlleles[dA];
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63 | if (dAlleles.ContainsKey(dB)) countB += dAlleles[dB];
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64 |
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65 | if (countA <= 0) distance--; // we've found in A an allele that was present in B
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66 | else distance++; // we've found in A a new allele
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67 | dAlleles[dA] = countA;
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68 |
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69 | if (countB >= 0) distance--; // we've found in B an allele that was present in A
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70 | else distance++; // we've found in B a new allele
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71 | dAlleles[dB] = countB;
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72 | }
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73 | }
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74 | return distance / (double)(2 * len * len);
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75 | }
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76 | }
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77 | }
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