[7128] | 1 |
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| 2 | using System;
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| 3 | using System.Security.Cryptography;
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| 4 | using HeuristicLab.Common;
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| 5 | using HeuristicLab.Core;
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| 6 | using HeuristicLab.Data;
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| 7 | using HeuristicLab.Encodings.BinaryVectorEncoding;
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| 8 | using HeuristicLab.Operators;
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| 9 | using HeuristicLab.Parameters;
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| 10 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 11 | using System.Threading;
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| 12 | namespace HeuristicLab.Problems.NK {
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| 13 |
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| 14 | [Item("NK Landscape Evaluator", "Evaluates 'points' on an NK Landscape.")]
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| 15 | [StorableClass]
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| 16 | public class NKEvaluator : SingleSuccessorOperator, INKEvaluator {
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| 17 |
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| 18 | #region Parameters
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| 19 |
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| 20 | public ILookupParameter<DoubleValue> QualityParameter {
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| 21 | get { return (ILookupParameter<DoubleValue>)Parameters["Quality"]; }
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| 22 | }
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| 23 | public LookupParameter<DoubleArray> F_iParameter {
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| 24 | get { return (LookupParameter<DoubleArray>)Parameters["F_i"]; }
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| 25 | }
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| 26 | public ILookupParameter<BinaryVector> BinaryVectorParameter {
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| 27 | get { return (ILookupParameter<BinaryVector>)Parameters["BinaryVector"]; }
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| 28 | }
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| 29 | public LookupParameter<BoolMatrix> GeneInteractionsParameter {
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| 30 | get { return (LookupParameter<BoolMatrix>)Parameters["GeneInteractions"]; }
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| 31 | }
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| 32 | public LookupParameter<IntValue> InteractionSeedParameter {
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| 33 | get { return (LookupParameter<IntValue>)Parameters["InteractionSeed"]; }
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| 34 | }
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| 35 | public LookupParameter<DoubleArray> WeightsParameter {
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| 36 | get { return (LookupParameter<DoubleArray>)Parameters["Weights"]; }
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| 37 | }
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| 38 | public ValueLookupParameter<BoolValue> StoreComponentsParameter {
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| 39 | get { return (ValueLookupParameter<BoolValue>)Parameters["StoreComponents"]; }
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| 40 | }
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| 41 |
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| 42 | #endregion
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| 43 |
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| 44 | #region ParameterValues
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| 45 | private double Quality {
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| 46 | set { QualityParameter.ActualValue = new DoubleValue(value); }
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| 47 | }
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| 48 | private BinaryVector BinaryVector {
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| 49 | get { return BinaryVectorParameter.ActualValue; }
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| 50 | }
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| 51 | private BoolMatrix GeneInteractions {
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| 52 | get { return GeneInteractionsParameter.ActualValue; }
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| 53 | }
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| 54 | private int InteractionSeed {
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| 55 | get { return InteractionSeedParameter.ActualValue.Value; }
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| 56 | }
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| 57 | private DoubleArray Weights {
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| 58 | get { return WeightsParameter.ActualValue; }
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| 59 | }
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| 60 | private bool StoreComponents {
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| 61 | get {
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| 62 | IParameter param;
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| 63 | return Parameters.TryGetValue("StoreComponents", out param)
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| 64 | && ((ValueLookupParameter<BoolValue>)param).ActualValue.Value == true;
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| 65 | }
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| 66 | }
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| 67 | #endregion
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| 68 |
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| 69 | private ThreadLocal<HashAlgorithm> hashAlgorithm;
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| 70 |
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| 71 | [StorableConstructor]
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| 72 | protected NKEvaluator(bool deserializing) : base(deserializing) {
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| 73 | hashAlgorithm = new ThreadLocal<HashAlgorithm>(() => HashAlgorithm.Create("MD5"));
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| 74 | }
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| 75 | protected NKEvaluator(NKEvaluator original, Cloner cloner) : base(original, cloner) {
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| 76 | hashAlgorithm = new ThreadLocal<HashAlgorithm>(() => HashAlgorithm.Create("MD5"));
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| 77 | }
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| 78 | public NKEvaluator() {
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| 79 | Parameters.Add(new LookupParameter<DoubleValue>("Quality", "The evaluated quality of the OneMax solution."));
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| 80 | Parameters.Add(new LookupParameter<DoubleArray>("F_i", "Fitness component functions."));
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| 81 | Parameters.Add(new LookupParameter<BinaryVector>("BinaryVector", "The solution given in path representation which should be evaluated."));
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| 82 | Parameters.Add(new LookupParameter<BoolMatrix>("GeneInteractions", "Matrix indicating gene interactions."));
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| 83 | Parameters.Add(new LookupParameter<IntValue>("InteractionSeed", "Seed used for randomly generting gene interactions."));
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| 84 | Parameters.Add(new LookupParameter<DoubleArray>("Weights", "The weights for the component functions. If shorter, will be repeated."));
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| 85 | Parameters.Add(new ValueLookupParameter<BoolValue>("StoreComponents", "Inject values of component functions into the scope (F_i)", new BoolValue(false)));
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| 86 | hashAlgorithm = new ThreadLocal<HashAlgorithm>(() => HashAlgorithm.Create("MD5"));
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| 87 | }
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| 88 |
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| 89 | public override IDeepCloneable Clone(Cloner cloner) {
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| 90 | return new NKEvaluator(this, cloner);
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| 91 | }
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| 92 |
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| 93 | public long Hash(long x) {
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| 94 | return BitConverter.ToInt64(hashAlgorithm.Value.ComputeHash(BitConverter.GetBytes(x), 0, 8), 0);
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| 95 | }
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| 96 |
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| 97 | public double F_i(long x, long i, long g_i, long seed) {
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| 98 | return Math.Abs((double)Hash((x & g_i) ^ Hash(g_i ^ Hash(i ^ seed))))/long.MaxValue;
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| 99 | }
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| 100 |
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| 101 | public double F(long x, long[] g, double[] w, long seed, ref double[] f_i) {
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| 102 | double value = 0;
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| 103 | for (int i = 0; i<g.Length; i++) {
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| 104 | f_i[i] = F_i(x, i, g[i], seed);
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| 105 | value += w[i%w.Length] * f_i[i];
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| 106 | }
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| 107 | return value;
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| 108 | }
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| 109 |
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| 110 | public long Encode(BinaryVector v) {
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| 111 | long x = 0;
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| 112 | for (int i = 0; i<64 && i<v.Length; i++) {
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| 113 | x |= (v[i] ? (long)1 : (long)0) << i;
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| 114 | }
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| 115 | return x;
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| 116 | }
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| 117 |
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| 118 | public static long[] Encode(BoolMatrix m) {
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| 119 | long[] x = new long[m.Columns];
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| 120 | for (int c = 0; c<m.Columns; c++) {
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| 121 | x[c] = 0;
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| 122 | for (int r = 0; r<64 && r<m.Rows; r++) {
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| 123 | x[c] |= (m[r, c] ? (long)1 : (long)0) << r;
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| 124 | }
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| 125 | }
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| 126 | return x;
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| 127 | }
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| 128 |
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| 129 | public static double[] Normalize(DoubleArray weights) {
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| 130 | double sum = 0;
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| 131 | double[] w = new double[weights.Length];
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| 132 | foreach (var v in weights) {
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| 133 | sum += Math.Abs(v);
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| 134 | }
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| 135 | for (int i = 0; i<weights.Length; i++) {
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| 136 | w[i] = Math.Abs(weights[i])/sum;
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| 137 | }
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| 138 | return w;
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| 139 | }
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| 140 |
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| 141 | public sealed override IOperation Apply() {
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| 142 | double[] f_i;
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| 143 | Quality = Evaluate(BinaryVector, GeneInteractions, Weights, InteractionSeed, out f_i);
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| 144 | if (StoreComponents)
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| 145 | F_iParameter.ActualValue = new DoubleArray(f_i);
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| 146 | return base.Apply();
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| 147 | }
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| 148 |
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| 149 | public double Evaluate(BinaryVector vector, BoolMatrix interactions, DoubleArray weights, int seed, out double[] f_i) {
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| 150 | long x = Encode(vector);
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| 151 | long[] g = Encode(interactions);
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| 152 | double[] w = Normalize(weights);
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| 153 | f_i = new double[interactions.Columns];
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| 154 | return F(x, g, w, (long)seed, ref f_i);
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| 155 | }
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| 156 | }
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| 157 | }
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