[4420] | 1 | #region License Information
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| 2 | /* HeuristicLab
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| 3 | * Copyright (C) 2002-2010 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;
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| 23 | using System.Linq;
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| 24 | using HeuristicLab.Core;
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| 25 | using HeuristicLab.Data;
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| 26 | using HeuristicLab.Encodings.PermutationEncoding;
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| 27 | using HeuristicLab.Operators;
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| 28 | using HeuristicLab.Optimization;
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| 29 | using HeuristicLab.Parameters;
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| 30 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 31 |
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| 32 | namespace HeuristicLab.Problems.TravelingSalesman {
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| 33 | /// <summary>
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| 34 | /// An operator for analyzing the diversity of a population of solutions for a Traveling Salesman Problems given in path representation using city coordinates.
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| 35 | /// </summary>
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| 36 | [Item("TSPPopulationDiversityAnalyzer", "An operator for analyzing the diversity of a population of solutions for a Traveling Salesman Problems given in path representation using city coordinates.")]
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| 37 | [StorableClass]
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| 38 | public sealed class TSPPopulationDiversityAnalyzer : SingleSuccessorOperator, IAnalyzer {
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| 39 |
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| 40 | // TODO:
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| 41 | // - iterations sampling
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| 42 | // - decide whether old results shall be stored or disposed
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| 43 | // - view
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| 44 | // - check results for identical solutions
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| 45 |
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| 46 | public ScopeTreeLookupParameter<Permutation> PermutationParameter {
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| 47 | get { return (ScopeTreeLookupParameter<Permutation>)Parameters["Permutation"]; }
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| 48 | }
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| 49 | public ScopeTreeLookupParameter<DoubleValue> QualityParameter {
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| 50 | get { return (ScopeTreeLookupParameter<DoubleValue>)Parameters["Quality"]; }
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| 51 | }
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| 52 | public LookupParameter<ItemList<DoubleMatrix>> SimilaritiesParameter {
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| 53 | get { return (LookupParameter<ItemList<DoubleMatrix>>)Parameters["Similarities"]; }
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| 54 | }
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| 55 | public LookupParameter<ItemList<DoubleArray>> MaximumSimilaritiesParameter {
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| 56 | get { return (LookupParameter<ItemList<DoubleArray>>)Parameters["MaximumSimilarities"]; }
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| 57 | }
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| 58 | public LookupParameter<ItemList<DoubleValue>> AverageMaximumSimilaritiesParameter {
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| 59 | get { return (LookupParameter<ItemList<DoubleValue>>)Parameters["AverageMaximumSimilarities"]; }
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| 60 | }
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| 61 | public LookupParameter<ItemList<DoubleValue>> AverageSimilaritiesParameter {
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| 62 | get { return (LookupParameter<ItemList<DoubleValue>>)Parameters["AverageSimilarities"]; }
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| 63 | }
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| 64 |
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| 65 | [NonSerialized]
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| 66 | private int[] rxData, ryData;
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| 67 | [NonSerialized]
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| 68 | private Permutation lastX, lastY;
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| 69 |
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| 70 | public TSPPopulationDiversityAnalyzer()
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| 71 | : base() {
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| 72 | Parameters.Add(new ScopeTreeLookupParameter<Permutation>("Permutation", "The TSP solutions given in path representation from which the best solution should be analyzed."));
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| 73 | Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", "The qualities of the TSP solutions which should be analyzed."));
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| 74 | Parameters.Add(new LookupParameter<ItemList<DoubleMatrix>>("Similarities", "The similarities of the TSP solutions which should be analyzed."));
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| 75 | Parameters.Add(new LookupParameter<ItemList<DoubleArray>>("MaximumSimilarities", "The maximum similarities of the TSP solutions which should be analyzed."));
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| 76 | Parameters.Add(new LookupParameter<ItemList<DoubleValue>>("AverageMaximumSimilarities", "The average maximum similarities of the TSP solutions which should be analyzed."));
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| 77 | Parameters.Add(new LookupParameter<ItemList<DoubleValue>>("AverageSimilarities", "The average similarities of the TSP solutions which should be analyzed."));
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| 78 | rxData = null;
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| 79 | ryData = null;
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| 80 | lastX = null;
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| 81 | lastY = null;
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| 82 | }
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| 83 |
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| 84 | public override IOperation Apply() {
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| 85 |
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| 86 | ItemArray<Permutation> permutations = PermutationParameter.ActualValue;
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| 87 | ItemArray<DoubleValue> qualities = QualityParameter.ActualValue;
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| 88 | Permutation[] permutationsArray = permutations.ToArray();
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| 89 | DoubleValue[] qualitiesArray = qualities.ToArray();
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| 90 | int cities = permutationsArray.Length;
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| 91 | #region sort permutations array
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| 92 | for (int i = 0; i < cities; i++) {
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| 93 | int minIndex = i;
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| 94 | for (int j = i + 1; j < cities; j++) {
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| 95 | if (qualitiesArray[j].Value < qualitiesArray[minIndex].Value)
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| 96 | minIndex = j;
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| 97 | }
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| 98 | if (minIndex != i) {
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| 99 | Permutation p = permutationsArray[i];
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| 100 | permutationsArray[i] = permutationsArray[minIndex];
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| 101 | permutationsArray[minIndex] = p;
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| 102 | DoubleValue d = qualitiesArray[i];
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| 103 | qualitiesArray[i] = qualitiesArray[minIndex];
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| 104 | qualitiesArray[minIndex] = d;
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| 105 | }
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| 106 | }
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| 107 | #endregion
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| 108 |
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| 109 | DoubleMatrix similarities = new DoubleMatrix(cities, cities);
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| 110 | DoubleArray maxSimilarities = new DoubleArray(cities);
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| 111 | double avgSimilarity = 0;
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| 112 | int n = 0;
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| 113 | for (int i = 0; i < cities; i++) {
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| 114 | similarities[i, i] = 1;
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| 115 | // for (int j = (i + 1); j < cities; j++) {
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| 116 | for (int j = (i); j < cities; j++) {
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| 117 | double similarity = CalculateSimilarity(permutationsArray[i], permutationsArray[j]);
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| 118 | avgSimilarity += similarity;
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| 119 | n++;
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| 120 | similarities[i, j] = similarity;
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| 121 | similarities[j, i] = similarity;
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| 122 | if (maxSimilarities[i] < similarity)
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| 123 | maxSimilarities[i] = similarity;
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| 124 | if (maxSimilarities[j] < similarity)
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| 125 | maxSimilarities[j] = similarity;
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| 126 | }
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| 127 | }
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| 128 | DoubleValue averageMaximumSimilarity = new DoubleValue(maxSimilarities.Average());
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| 129 | DoubleValue averageSimilarity = new DoubleValue(avgSimilarity / n);
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| 130 |
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| 131 | if (SimilaritiesParameter.ActualValue == null) {
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| 132 | SimilaritiesParameter.ActualValue = new ItemList<DoubleMatrix>();
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| 133 | MaximumSimilaritiesParameter.ActualValue = new ItemList<DoubleArray>();
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| 134 | AverageMaximumSimilaritiesParameter.ActualValue = new ItemList<DoubleValue>();
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| 135 | AverageSimilaritiesParameter.ActualValue = new ItemList<DoubleValue>();
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| 136 | }
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| 137 | SimilaritiesParameter.ActualValue.Add(similarities);
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| 138 | MaximumSimilaritiesParameter.ActualValue.Add(maxSimilarities);
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| 139 | AverageMaximumSimilaritiesParameter.ActualValue.Add(averageMaximumSimilarity);
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| 140 | AverageSimilaritiesParameter.ActualValue.Add(averageSimilarity);
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| 141 |
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| 142 | return base.Apply();
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| 143 | }
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| 144 |
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| 145 | private double CalculateSimilarity(Permutation x, Permutation y) {
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| 146 |
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| 147 | int cities = x.Length;
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| 148 | if (rxData == null || rxData.Length != cities) {
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| 149 | rxData = new int[cities];
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| 150 | ryData = new int[cities];
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| 151 | }
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| 152 |
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| 153 | if (x.Length != y.Length) throw new InvalidOperationException("ERROR in " + Name + ": Similarity can only be calculated between instances of an equal number of cities");
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| 154 | #region Performance savings when calling the function with at least one parameter identical to the last call
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| 155 | if (x == lastX) { // if Solution1 stayed the same
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| 156 | if (y != lastY) { // and Solution2 changed
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| 157 | for (int i = 0; i < y.Length; i++)
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| 158 | ryData[y[i]] = i;
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| 159 | }
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| 160 | } else {
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| 161 | if (y == lastX && x == lastY) { // if Solution1 and Solution2 were reversed the call before
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| 162 | int[] h = ryData;
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| 163 | ryData = rxData;
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| 164 | rxData = h;
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| 165 | } else if (y == lastX) { // or if just Solution1 is different now
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| 166 | ryData = rxData;
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| 167 | rxData = new int[x.Length];
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| 168 | for (int i = 0; i < x.Length; i++)
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| 169 | rxData[x[i]] = i;
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| 170 | } else if (x == lastY) { // or just Solution2 is different now
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| 171 | rxData = ryData;
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| 172 | ryData = new int[y.Length];
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| 173 | for (int i = 0; i < y.Length; i++)
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| 174 | ryData[y[i]] = i;
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| 175 | } else if (y != lastY) { // or none are the same
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| 176 | for (int i = 0; i < x.Length; i++) {
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| 177 | rxData[x[i]] = i;
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| 178 | ryData[y[i]] = i;
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| 179 | }
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| 180 | } else { // or just Solution2 is the same
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| 181 | for (int i = 0; i < x.Length; i++)
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| 182 | rxData[x[i]] = i;
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| 183 | }
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| 184 | }
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| 185 | lastX = x;
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| 186 | lastY = y;
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| 187 | #endregion
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| 188 | int similarEdges = 0;
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| 189 | for (int i = 1; i <= x.Length; i++) {
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| 190 | if (Math.Abs(ryData[x[(i < x.Length) ? (i) : (0)]] - ryData[x[i - 1]]) == 1
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| 191 | || Math.Abs(ryData[x[(i < x.Length) ? (i) : (0)]] - ryData[x[i - 1]]) == x.Length)
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| 192 | similarEdges++;
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| 193 | }
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| 194 | return (double)similarEdges / (double)x.Length;
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| 195 |
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| 196 | }
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| 197 |
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| 198 | }
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| 199 | }
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