[16607] | 1 | #region License Information
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| 2 | /* HeuristicLab
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| 3 | * Copyright (C) 2002-2019 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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[16609] | 22 | using System;
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| 23 | using System.Linq;
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[16607] | 24 | using HeuristicLab.Common;
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| 25 | using HeuristicLab.Core;
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| 26 | using HeuristicLab.Data;
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| 27 | using HeuristicLab.Encodings.RealVectorEncoding;
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| 28 | using HeuristicLab.Operators;
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[16609] | 29 | using HeuristicLab.Optimization;
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[16607] | 30 | using HeuristicLab.Parameters;
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| 31 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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[16609] | 32 | using HeuristicLab.Random;
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[16607] | 33 |
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| 34 | namespace HeuristicLab.Problems.MovingPeaksBenchmark {
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| 35 | [Item("MovingPeaksBenchmarkProblemEvaluator", "Evaluation operator for the Moving Peaks Benchmark.")]
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| 36 | [StorableClass]
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| 37 | public class MovingPeaksBenchmarkProblemEvaluator : InstrumentedOperator, IMovingPeaksBenchmarkProblemEvaluator {
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[16609] | 38 | [Storable]
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| 39 | IRandom uniformRandom;
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| 40 | [Storable]
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| 41 | long executions;
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| 42 |
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| 43 | public IValueLookupParameter<DoubleMatrix> PeakLocationsParameter {
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| 44 | get { return (IValueLookupParameter<DoubleMatrix>)Parameters["PeakLocations"]; }
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[16607] | 45 | }
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[16609] | 46 | public IValueLookupParameter<DoubleArray> PeakWidthsParameter {
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| 47 | get { return (IValueLookupParameter<DoubleArray>)Parameters["PeakWidths"]; }
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[16607] | 48 | }
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[16609] | 49 | public IValueLookupParameter<DoubleArray> PeakHeightsParameter {
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| 50 | get { return (IValueLookupParameter<DoubleArray>)Parameters["PeakHeights"]; }
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[16607] | 51 | }
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[16609] | 52 | public ILookupParameter<IntValue> MovingPeaksRandomSeedParameter {
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| 53 | get { return (ILookupParameter<IntValue>)Parameters["MovingPeaksRandomSeed"]; }
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| 54 | }
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| 55 | public ILookupParameter<IntValue> PeakMovementIntervalParameter {
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| 56 | get { return (ILookupParameter<IntValue>)Parameters["PeakMovementInterval"]; }
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| 57 | }
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| 58 | public ILookupParameter<DoubleValue> PeakMovementStrengthParameter {
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| 59 | get { return (ILookupParameter<DoubleValue>)Parameters["PeakMovementStrength"]; }
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| 60 | }
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[16607] | 61 | public ILookupParameter<RealVector> PointParameter {
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| 62 | get { return (ILookupParameter<RealVector>)Parameters["Point"]; }
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| 63 | }
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| 64 | public ILookupParameter<DoubleValue> QualityParameter {
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| 65 | get { return (ILookupParameter<DoubleValue>)Parameters["Quality"]; }
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| 66 | }
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[16609] | 67 | public ILookupParameter<DoubleValue> BestKnownQualityParameter {
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| 68 | get { return (ILookupParameter<DoubleValue>)Parameters["BestKnownQuality"]; }
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| 69 | }
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| 70 | public ILookupParameter<RealVector> BestKnownSolutionParameter {
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| 71 | get { return (ILookupParameter<RealVector>)Parameters["BestKnownSolution"]; }
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| 72 | }
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| 73 | public IValueLookupParameter<ResultCollection> ResultsParameter {
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| 74 | get { return (IValueLookupParameter<ResultCollection>)Parameters["Results"]; }
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| 75 | }
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[16607] | 76 |
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| 77 | [StorableConstructor]
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| 78 | protected MovingPeaksBenchmarkProblemEvaluator(bool deserializing) : base(deserializing) { }
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| 79 | protected MovingPeaksBenchmarkProblemEvaluator(MovingPeaksBenchmarkProblemEvaluator original, Cloner cloner) : base(original, cloner) { }
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| 80 | public MovingPeaksBenchmarkProblemEvaluator() : base() {
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[16609] | 81 | Parameters.Add(new ValueLookupParameter<DoubleMatrix>("PeakLocations", "Current position of the peaks."));
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| 82 | PeakLocationsParameter.ActualName = "InitialPeakLocations";
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| 83 | Parameters.Add(new ValueLookupParameter<DoubleArray>("PeakWidths", "Current width of the peaks."));
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| 84 | PeakWidthsParameter.ActualName = "InitialPeakWidths";
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| 85 | Parameters.Add(new ValueLookupParameter<DoubleArray>("PeakHeights", "Current height of the peaks."));
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| 86 | PeakHeightsParameter.ActualName = "InitialPeakHeights";
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| 87 | Parameters.Add(new LookupParameter<IntValue>("MovingPeaksRandomSeed", "The random seed for initializing the PRNG for changing the peaks."));
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| 88 | Parameters.Add(new LookupParameter<IntValue>("PeakMovementInterval", "The interval in evaluated solutions in which peaks are moved."));
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| 89 | Parameters.Add(new LookupParameter<DoubleValue>("PeakMovementStrength", "The length of the random vector used for changing peak locations."));
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[16607] | 90 | Parameters.Add(new LookupParameter<RealVector>("Point", "The point which should be evaluated."));
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| 91 | Parameters.Add(new LookupParameter<DoubleValue>("Quality", "Quality value of the evaluated point."));
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[16609] | 92 | Parameters.Add(new LookupParameter<DoubleValue>("BestKnownQuality", "Quality value of the highest peak."));
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| 93 | Parameters.Add(new LookupParameter<RealVector>("BestKnownSolution", "The location of the highest peak."));
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| 94 | Parameters.Add(new ValueLookupParameter<ResultCollection>("Results", "The result collection for storing result values."));
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| 95 |
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| 96 | PeakLocationsParameter.Hidden = true;
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| 97 | PeakWidthsParameter.Hidden = true;
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| 98 | PeakHeightsParameter.Hidden = true;
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| 99 | BestKnownQualityParameter.Hidden = true;
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| 100 | BestKnownSolutionParameter.Hidden = true;
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| 101 | ResultsParameter.Hidden = true;
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[16607] | 102 | }
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| 103 |
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| 104 | public override IDeepCloneable Clone(Cloner cloner) {
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| 105 | return new MovingPeaksBenchmarkProblemEvaluator(this, cloner);
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| 106 | }
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| 107 |
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| 108 | public override IOperation InstrumentedApply() {
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| 109 | DoubleMatrix peaks = PeakLocationsParameter.ActualValue;
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| 110 | DoubleArray widths = PeakWidthsParameter.ActualValue;
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| 111 | DoubleArray heights = PeakHeightsParameter.ActualValue;
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[16609] | 112 |
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| 113 | if (PeakLocationsParameter.Value == null) {
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| 114 | peaks = peaks.Clone() as DoubleMatrix;
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| 115 | widths = widths.Clone() as DoubleArray;
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| 116 | heights = heights.Clone() as DoubleArray;
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| 117 | PeakLocationsParameter.Value = peaks;
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| 118 | PeakWidthsParameter.Value = widths;
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| 119 | PeakHeightsParameter.Value = heights;
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| 120 |
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| 121 | ResultCollection results = ResultsParameter.ActualValue;
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| 122 | results.Add(new Result("Current Peak Locations", peaks));
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| 123 | results.Add(new Result("Current Peak Widths", widths));
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| 124 | results.Add(new Result("Current Peak Heights", heights));
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| 125 | }
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| 126 | if (uniformRandom == null) {
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| 127 | uniformRandom = new MersenneTwister();
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| 128 | uniformRandom.Reset(MovingPeaksRandomSeedParameter.ActualValue.Value);
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| 129 | }
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| 130 |
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| 131 | // move peaks if peaks movement interval is reached
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| 132 | lock (this) {
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| 133 | if ((executions % PeakMovementIntervalParameter.ActualValue.Value) == 0) {
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| 134 | MovePeaks(uniformRandom, peaks, widths, heights, PeakMovementStrengthParameter.ActualValue.Value);
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| 135 |
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| 136 | // update best known solution & quality according to highest peak
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| 137 | double maxHeight = heights.Max();
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| 138 | int peakIndex = Array.IndexOf(heights.CloneAsArray(), maxHeight);
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| 139 | double[] peak = new double[peaks.Columns];
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| 140 | for (int i = 0; i < peak.Length; i++) {
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| 141 | peak[i] = peaks[peakIndex, i];
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| 142 | }
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| 143 | BestKnownSolutionParameter.ActualValue = new RealVector(peak);
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| 144 | BestKnownQualityParameter.ActualValue.Value = heights.Max();
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| 145 | }
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| 146 | executions++;
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| 147 | }
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| 148 |
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[16607] | 149 | RealVector point = PointParameter.ActualValue;
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| 150 | double quality = Apply(peaks, widths, heights, point);
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| 151 | QualityParameter.ActualValue = new DoubleValue(quality);
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| 152 | return base.InstrumentedApply();
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| 153 | }
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| 154 |
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[16609] | 155 | public override void InitializeState() {
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| 156 | base.InitializeState();
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| 157 | executions = 0;
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| 158 | }
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| 159 |
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| 160 | public override void ClearState() {
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| 161 | base.ClearState();
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| 162 | uniformRandom = null;
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| 163 | PeakLocationsParameter.Value = null;
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| 164 | PeakWidthsParameter.Value = null;
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| 165 | PeakHeightsParameter.Value = null;
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| 166 | }
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| 167 |
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[16607] | 168 | public double Apply(DoubleMatrix peaks, DoubleArray widths, DoubleArray heights, RealVector point) {
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[16608] | 169 | double max = 0;
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| 170 | double val = 0;
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| 171 |
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| 172 | for (int i = 0; i < widths.Length; i++) {
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| 173 | val = 0;
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| 174 | for (int j = 0; j < point.Length; j++) {
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| 175 | val += (point[j] - peaks[i, j]) * (point[j] - peaks[i, j]);
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| 176 | }
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| 177 | val = heights[i] / (1 + widths[i] * val);
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| 178 | if (val > max) max = val;
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| 179 | }
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| 180 | return max;
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[16607] | 181 | }
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[16609] | 182 |
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| 183 | private void MovePeaks(IRandom uniformRandom, DoubleMatrix peaks, DoubleArray widths, DoubleArray heights, double strength) {
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| 184 | IRandom normalRandom = new NormalDistributedRandom(uniformRandom, 0, 1);
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| 185 | for (int i = 0; i < peaks.Rows; i++) {
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| 186 | double[] v = RandomVector(uniformRandom, peaks.Columns, strength);
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| 187 | for (int j = 0; j < v.Length; j++) {
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| 188 | peaks[i, j] += v[j];
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| 189 | }
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| 190 | widths[i] = widths[i] + 0.01 * normalRandom.NextDouble();
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| 191 | heights[i] = heights[i] + 7 * normalRandom.NextDouble();
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| 192 | }
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| 193 | }
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| 194 |
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| 195 | private double[] RandomVector(IRandom uniformRandom, int dimensions, double length) {
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| 196 | double[] vector = new double[dimensions];
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| 197 |
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| 198 | for (int i = 0; i < vector.Length; i++) {
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| 199 | vector[i] = uniformRandom.NextDouble() - 0.5;
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| 200 | }
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| 201 | double factor = length / Math.Sqrt(vector.Select(x => x * x).Sum());
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| 202 | for (int i = 0; i < vector.Length; i++) {
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| 203 | vector[i] *= factor;
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| 204 | }
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| 205 | return vector;
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| 206 | }
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[16607] | 207 | }
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| 208 | }
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