[11961] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[14185] | 3 | * Copyright (C) 2002-2016 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[11961] | 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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[11396] | 23 | using System.Collections.Generic;
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| 24 | using System.Linq;
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| 25 | using HeuristicLab.Common;
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| 26 | using HeuristicLab.Core;
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| 27 | using HeuristicLab.Data;
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| 28 | using HeuristicLab.Operators;
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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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[11949] | 32 | namespace HeuristicLab.Optimization {
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[11396] | 33 | [Item("Single-objective Analyzer", "Calls the script's Analyze method to be able to write into the results collection.")]
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| 34 | [StorableClass]
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[11880] | 35 | public sealed class SingleObjectiveAnalyzer : SingleSuccessorOperator, ISingleObjectiveAnalysisOperator, IAnalyzer, IStochasticOperator {
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[11396] | 36 | public bool EnabledByDefault { get { return true; } }
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| 37 |
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[11559] | 38 | public ILookupParameter<IEncoding> EncodingParameter {
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| 39 | get { return (ILookupParameter<IEncoding>)Parameters["Encoding"]; }
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[11396] | 40 | }
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| 41 |
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| 42 | public IScopeTreeLookupParameter<DoubleValue> QualityParameter {
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| 43 | get { return (IScopeTreeLookupParameter<DoubleValue>)Parameters["Quality"]; }
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| 44 | }
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| 45 |
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| 46 | public ILookupParameter<ResultCollection> ResultsParameter {
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| 47 | get { return (ILookupParameter<ResultCollection>)Parameters["Results"]; }
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| 48 | }
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| 49 |
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[11880] | 50 | public ILookupParameter<IRandom> RandomParameter {
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| 51 | get { return (ILookupParameter<IRandom>)Parameters["Random"]; }
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| 52 | }
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[11739] | 53 |
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[11880] | 54 | public Action<Individual[], double[], ResultCollection, IRandom> AnalyzeAction { get; set; }
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| 55 |
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[11396] | 56 | [StorableConstructor]
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[11739] | 57 | private SingleObjectiveAnalyzer(bool deserializing) : base(deserializing) { }
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| 58 | private SingleObjectiveAnalyzer(SingleObjectiveAnalyzer original, Cloner cloner) : base(original, cloner) { }
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[11396] | 59 | public SingleObjectiveAnalyzer() {
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[11559] | 60 | Parameters.Add(new LookupParameter<IEncoding>("Encoding", "An item that holds the problem's encoding."));
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[11396] | 61 | Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", "The quality of the parameter vector."));
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| 62 | Parameters.Add(new LookupParameter<ResultCollection>("Results", "The results collection to write to."));
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[11880] | 63 | Parameters.Add(new LookupParameter<IRandom>("Random", "The random number generator to use."));
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[11396] | 64 | }
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| 65 |
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| 66 | public override IDeepCloneable Clone(Cloner cloner) {
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| 67 | return new SingleObjectiveAnalyzer(this, cloner);
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| 68 | }
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| 69 |
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| 70 | public override IOperation Apply() {
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[11598] | 71 | var encoding = EncodingParameter.ActualValue;
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[11396] | 72 | var results = ResultsParameter.ActualValue;
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[11880] | 73 | var random = RandomParameter.ActualValue;
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[11396] | 74 |
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| 75 | IEnumerable<IScope> scopes = new[] { ExecutionContext.Scope };
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| 76 | for (var i = 0; i < QualityParameter.Depth; i++)
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| 77 | scopes = scopes.Select(x => (IEnumerable<IScope>)x.SubScopes).Aggregate((a, b) => a.Concat(b));
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| 78 |
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[11619] | 79 | var individuals = scopes.Select(encoding.GetIndividual).ToArray();
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[11880] | 80 | AnalyzeAction(individuals, QualityParameter.ActualValue.Select(x => x.Value).ToArray(), results, random);
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[11396] | 81 | return base.Apply();
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| 82 | }
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| 83 | }
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| 84 | }
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