[8417] | 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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[8323] | 21 |
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[8417] | 22 | using System;
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[8484] | 23 | using System.Collections.Generic;
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[8582] | 24 | using System.Linq;
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[8417] | 25 | using HeuristicLab.Common;
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| 26 | using HeuristicLab.Core;
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[8582] | 27 | using HeuristicLab.Data;
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[8417] | 28 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 29 |
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| 30 | namespace HeuristicLab.Algorithms.DataAnalysis {
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| 31 | [StorableClass]
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| 32 | [Item(Name = "CovariancePeriodic", Description = "Periodic covariance function for Gaussian processes.")]
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[8612] | 33 | public sealed class CovariancePeriodic : ParameterizedNamedItem, ICovarianceFunction {
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| 34 |
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| 35 | [Storable]
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| 36 | private double scale;
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| 37 | [Storable]
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| 38 | private readonly HyperParameter<DoubleValue> scaleParameter;
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[8582] | 39 | public IValueParameter<DoubleValue> ScaleParameter {
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| 40 | get { return scaleParameter; }
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| 41 | }
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[8612] | 42 |
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| 43 | [Storable]
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| 44 | private double inverseLength;
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| 45 | [Storable]
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| 46 | private readonly HyperParameter<DoubleValue> inverseLengthParameter;
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[8582] | 47 | public IValueParameter<DoubleValue> InverseLengthParameter {
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| 48 | get { return inverseLengthParameter; }
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| 49 | }
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[8612] | 50 |
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| 51 | [Storable]
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| 52 | private double period;
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| 53 | [Storable]
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| 54 | private readonly HyperParameter<DoubleValue> periodParameter;
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[8582] | 55 | public IValueParameter<DoubleValue> PeriodParameter {
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| 56 | get { return periodParameter; }
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| 57 | }
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| 58 |
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| 59 |
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[8417] | 60 | [StorableConstructor]
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[8612] | 61 | private CovariancePeriodic(bool deserializing) : base(deserializing) { }
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| 62 | private CovariancePeriodic(CovariancePeriodic original, Cloner cloner)
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[8417] | 63 | : base(original, cloner) {
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[8582] | 64 | this.scaleParameter = cloner.Clone(original.scaleParameter);
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| 65 | this.inverseLengthParameter = cloner.Clone(original.inverseLengthParameter);
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| 66 | this.periodParameter = cloner.Clone(original.periodParameter);
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| 67 | this.scale = original.scale;
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| 68 | this.inverseLength = original.inverseLength;
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| 69 | this.period = original.period;
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| 70 |
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| 71 | RegisterEvents();
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[8417] | 72 | }
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[8582] | 73 |
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[8417] | 74 | public CovariancePeriodic()
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| 75 | : base() {
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[8612] | 76 | Name = ItemName;
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| 77 | Description = ItemDescription;
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[8678] | 78 |
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[8582] | 79 | scaleParameter = new HyperParameter<DoubleValue>("Scale", "The scale of the periodic covariance function.");
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| 80 | inverseLengthParameter = new HyperParameter<DoubleValue>("InverseLength", "The inverse length parameter for the periodic covariance function.");
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| 81 | periodParameter = new HyperParameter<DoubleValue>("Period", "The period parameter for the periodic covariance function.");
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| 82 | Parameters.Add(scaleParameter);
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| 83 | Parameters.Add(inverseLengthParameter);
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| 84 | Parameters.Add(periodParameter);
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| 85 |
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| 86 | RegisterEvents();
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[8417] | 87 | }
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[8323] | 88 |
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[8582] | 89 | [StorableHook(HookType.AfterDeserialization)]
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| 90 | private void AfterDeserialization() {
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| 91 | RegisterEvents();
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| 92 | }
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| 93 |
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[8417] | 94 | public override IDeepCloneable Clone(Cloner cloner) {
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| 95 | return new CovariancePeriodic(this, cloner);
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[8323] | 96 | }
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| 97 |
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[8582] | 98 | // caching
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| 99 | private void RegisterEvents() {
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[8612] | 100 | Util.AttachValueChangeHandler<DoubleValue, double>(scaleParameter, () => { scale = scaleParameter.Value.Value; });
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| 101 | Util.AttachValueChangeHandler<DoubleValue, double>(inverseLengthParameter, () => { inverseLength = inverseLengthParameter.Value.Value; });
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| 102 | Util.AttachValueChangeHandler<DoubleValue, double>(periodParameter, () => { period = periodParameter.Value.Value; });
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[8323] | 103 | }
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| 104 |
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[8612] | 105 | public int GetNumberOfParameters(int numberOfVariables) {
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[8582] | 106 | return
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| 107 | (new[] { scaleParameter, inverseLengthParameter, periodParameter }).Count(p => !p.Fixed);
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| 108 | }
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| 109 |
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[8612] | 110 | public void SetParameter(double[] hyp) {
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[8582] | 111 | int i = 0;
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| 112 | if (!inverseLengthParameter.Fixed) {
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| 113 | inverseLengthParameter.SetValue(new DoubleValue(1.0 / Math.Exp(hyp[i])));
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| 114 | i++;
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| 115 | }
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| 116 | if (!periodParameter.Fixed) {
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| 117 | periodParameter.SetValue(new DoubleValue(Math.Exp(hyp[i])));
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| 118 | i++;
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| 119 | }
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| 120 | if (!scaleParameter.Fixed) {
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| 121 | scaleParameter.SetValue(new DoubleValue(Math.Exp(2 * hyp[i])));
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| 122 | i++;
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| 123 | }
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| 124 | if (hyp.Length != i) throw new ArgumentException("The length of the parameter vector does not match the number of free parameters for CovariancePeriod", "hyp");
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| 125 | }
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| 126 |
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[8678] | 127 | public double GetCovariance(double[,] x, int i, int j, IEnumerable<int> columnIndices) {
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| 128 | if (columnIndices == null || columnIndices.Count() != 1)
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| 129 | throw new ArgumentException("The periodic covariance function can only be used for one dimension.", "columnIndices");
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| 130 | double k = i == j ? 0.0 : GetDistance(x, x, i, j, columnIndices);
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[8582] | 131 | k = Math.PI * k / period;
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[8491] | 132 | k = Math.Sin(k) * inverseLength;
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[8484] | 133 | k = k * k;
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[8323] | 134 |
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[8582] | 135 | return scale * Math.Exp(-2.0 * k);
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[8323] | 136 | }
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| 137 |
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[8678] | 138 | public IEnumerable<double> GetGradient(double[,] x, int i, int j, IEnumerable<int> columnIndices) {
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| 139 | if (columnIndices == null || columnIndices.Count() != 1)
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| 140 | throw new ArgumentException("The periodic covariance function can only be used for one dimension.", "columnIndices");
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| 141 | double v = i == j ? 0.0 : Math.PI * GetDistance(x, x, i, j, columnIndices) / period;
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[8491] | 142 | double gradient = Math.Sin(v) * inverseLength;
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[8484] | 143 | gradient *= gradient;
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[8582] | 144 | yield return 4.0 * scale * Math.Exp(-2.0 * gradient) * gradient;
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[8491] | 145 | double r = Math.Sin(v) * inverseLength;
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[8582] | 146 | yield return 4.0 * scale * inverseLength * Math.Exp(-2 * r * r) * r * Math.Cos(v) * v;
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| 147 | yield return 2.0 * scale * Math.Exp(-2 * gradient);
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[8484] | 148 | }
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| 149 |
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[8678] | 150 | public double GetCrossCovariance(double[,] x, double[,] xt, int i, int j, IEnumerable<int> columnIndices) {
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| 151 | if (columnIndices == null || columnIndices.Count() != 1)
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| 152 | throw new ArgumentException("The periodic covariance function can only be used for one dimension.", "columnIndices");
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| 153 | double k = GetDistance(x, xt, i, j, columnIndices);
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[8582] | 154 | k = Math.PI * k / period;
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[8491] | 155 | k = Math.Sin(k) * inverseLength;
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[8323] | 156 | k = k * k;
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| 157 |
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[8582] | 158 | return scale * Math.Exp(-2.0 * k);
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[8323] | 159 | }
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| 160 |
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[8678] | 161 | private double GetDistance(double[,] x, double[,] xt, int i, int j, IEnumerable<int> columnIndices) {
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| 162 | return Math.Sqrt(Util.SqrDist(x, i, xt, j, 1, columnIndices));
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[8323] | 163 | }
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| 164 | }
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| 165 | }
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