1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2015 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 HeuristicLab.Common;
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24 | using HeuristicLab.Core;
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25 | using HeuristicLab.Data;
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26 | using HeuristicLab.Operators;
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27 | using HeuristicLab.Optimization;
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28 | using HeuristicLab.Parameters;
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29 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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30 | using HeuristicLab.Random;
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31 |
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32 | namespace HeuristicLab.Algorithms.ALPS.SteadyState {
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33 | [Item("RandomLayerProcessor", "An operator which applies a specified operator on a random selected sub-scope (layer).")]
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34 | [StorableClass]
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35 | public class RandomLayerProcessor : SingleSuccessorOperator, IStochasticOperator {
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36 | private OperatorParameter OperatorParameter {
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37 | get { return (OperatorParameter)Parameters["Operator"]; }
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38 | }
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39 | public ILookupParameter<IRandom> RandomParameter {
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40 | get { return (ILookupParameter<IRandom>)Parameters["Random"]; }
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41 | }
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42 |
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43 | private ILookupParameter<IntArray> PopulationSizeParameter {
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44 | get { return (ILookupParameter<IntArray>)Parameters["PopulationSize"]; }
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45 | }
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46 |
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47 | public IOperator Operator {
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48 | get { return OperatorParameter.Value; }
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49 | set { OperatorParameter.Value = value; }
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50 | }
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51 |
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52 | [StorableConstructor]
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53 | private RandomLayerProcessor(bool deserializing) : base(deserializing) { }
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54 | private RandomLayerProcessor(RandomLayerProcessor original, Cloner cloner)
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55 | : base(original, cloner) {
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56 | }
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57 | public RandomLayerProcessor()
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58 | : base() {
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59 | Parameters.Add(new OperatorParameter("Operator", "The operator which should be applied on a random sub-scopes of the current scope."));
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60 | Parameters.Add(new LookupParameter<IRandom>("Random", "The random number generator to use."));
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61 |
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62 | Parameters.Add(new LookupParameter<IntArray>("PopulationSize"));
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63 | }
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64 |
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65 | public override IDeepCloneable Clone(Cloner cloner) {
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66 | return new RandomLayerProcessor(this, cloner);
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67 | }
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68 |
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69 | public override IOperation Apply() {
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70 | var random = RandomParameter.ActualValue;
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71 |
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72 | var next = new OperationCollection(base.Apply());
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73 | if (Operator != null) {
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74 | var subScopes = ExecutionContext.Scope.SubScopes;
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75 | int index = random.Next(subScopes.Count);
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76 | var selectedLayer = subScopes[index];
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77 |
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78 | var layerParameters = new LayerIntermediateParameter {
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79 | new ValueParameter<IntValue>(PopulationSizeParameter.ActualName, new IntValue(PopulationSizeParameter.ActualValue[Math.Min(index, PopulationSizeParameter.ActualValue.Length - 1)]))
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80 | };
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81 | var immediateContext = new ExecutionContext(ExecutionContext.Parent, layerParameters, selectedLayer);
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82 | next.Insert(0, immediateContext.CreateChildOperation(Operator, selectedLayer));
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83 | }
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84 | return next;
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85 | }
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86 | }
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87 | } |
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