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source: branches/2521_ProblemRefactoring/HeuristicLab.Optimization/3.3/BasicProblems/Operators/MultiObjectiveAnalyzer.cs @ 16753

Last change on this file since 16753 was 16753, checked in by mkommend, 5 years ago

#2521: Made basic problem specific operators internal and sealed.

File size: 3.8 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21
22using System;
23using System.Collections.Generic;
24using System.Linq;
25using HEAL.Attic;
26using HeuristicLab.Common;
27using HeuristicLab.Core;
28using HeuristicLab.Data;
29using HeuristicLab.Operators;
30using HeuristicLab.Parameters;
31
32namespace HeuristicLab.Optimization {
33  [Item("Multi-objective Analyzer", "Calls the Analyze method of the problem definition.")]
34  [StorableType("903FE3D1-3179-4EA5-A7E1-63DE26239F9B")]
35  internal sealed class MultiObjectiveAnalyzer<TEncodedSolution> : SingleSuccessorOperator, IMultiObjectiveAnalysisOperator<TEncodedSolution>, IStochasticOperator
36  where TEncodedSolution : class, IEncodedSolution {
37    public bool EnabledByDefault { get { return true; } }
38
39    public ILookupParameter<IEncoding<TEncodedSolution>> EncodingParameter {
40      get { return (ILookupParameter<IEncoding<TEncodedSolution>>)Parameters["Encoding"]; }
41    }
42
43    public IScopeTreeLookupParameter<DoubleArray> QualitiesParameter {
44      get { return (IScopeTreeLookupParameter<DoubleArray>)Parameters["Qualities"]; }
45    }
46
47    public ILookupParameter<ResultCollection> ResultsParameter {
48      get { return (ILookupParameter<ResultCollection>)Parameters["Results"]; }
49    }
50
51    public ILookupParameter<IRandom> RandomParameter {
52      get { return (ILookupParameter<IRandom>)Parameters["Random"]; }
53    }
54
55    public Action<TEncodedSolution[], double[][], ResultCollection, IRandom> AnalyzeAction { get; set; }
56
57    [StorableConstructor]
58    private MultiObjectiveAnalyzer(StorableConstructorFlag _) : base(_) { }
59    private MultiObjectiveAnalyzer(MultiObjectiveAnalyzer<TEncodedSolution> original, Cloner cloner) : base(original, cloner) { }
60    public MultiObjectiveAnalyzer() {
61      Parameters.Add(new LookupParameter<IRandom>("Random", "The random number generator to use."));
62      Parameters.Add(new LookupParameter<IEncoding<TEncodedSolution>>("Encoding", "An item that holds the problem's encoding."));
63      Parameters.Add(new ScopeTreeLookupParameter<DoubleArray>("Qualities", "The qualities of the parameter vector."));
64      Parameters.Add(new LookupParameter<ResultCollection>("Results", "The results collection to write to."));
65    }
66
67    public override IDeepCloneable Clone(Cloner cloner) {
68      return new MultiObjectiveAnalyzer<TEncodedSolution>(this, cloner);
69    }
70
71    public override IOperation Apply() {
72      var encoding = EncodingParameter.ActualValue;
73      var results = ResultsParameter.ActualValue;
74      var random = RandomParameter.ActualValue;
75
76      IEnumerable<IScope> scopes = new[] { ExecutionContext.Scope };
77      for (var i = 0; i < QualitiesParameter.Depth; i++)
78        scopes = scopes.Select(x => (IEnumerable<IScope>)x.SubScopes).Aggregate((a, b) => a.Concat(b));
79
80      var individuals = scopes.Select(s => ScopeUtil.GetEncodedSolution(s, encoding)).ToArray();
81      AnalyzeAction(individuals, QualitiesParameter.ActualValue.Select(x => x.ToArray()).ToArray(), results, random);
82      return base.Apply();
83    }
84  }
85}
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