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source: stable/HeuristicLab.Optimization/3.3/BasicProblems/Operators/MultiObjectiveAnalyzer.cs @ 15491

Last change on this file since 15491 was 14186, checked in by swagner, 8 years ago

#2526: Updated year of copyrights in license headers

File size: 3.6 KB
RevLine 
[11961]1#region License Information
2/* HeuristicLab
[14186]3 * Copyright (C) 2002-2016 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
[11961]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;
[11400]23using System.Collections.Generic;
24using System.Linq;
25using HeuristicLab.Common;
26using HeuristicLab.Core;
27using HeuristicLab.Data;
28using HeuristicLab.Operators;
29using HeuristicLab.Parameters;
30using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
31
[11949]32namespace HeuristicLab.Optimization {
[11484]33  [Item("Multi-objective Analyzer", "Calls the Analyze method of the problem definition.")]
[11400]34  [StorableClass]
[11880]35  public class MultiObjectiveAnalyzer : SingleSuccessorOperator, IMultiObjectiveAnalysisOperator, IStochasticOperator {
[11400]36    public bool EnabledByDefault { get { return true; } }
37
[11559]38    public ILookupParameter<IEncoding> EncodingParameter {
39      get { return (ILookupParameter<IEncoding>)Parameters["Encoding"]; }
[11400]40    }
41
42    public IScopeTreeLookupParameter<DoubleArray> QualitiesParameter {
43      get { return (IScopeTreeLookupParameter<DoubleArray>)Parameters["Qualities"]; }
44    }
45
46    public ILookupParameter<ResultCollection> ResultsParameter {
47      get { return (ILookupParameter<ResultCollection>)Parameters["Results"]; }
48    }
49
[11880]50    public ILookupParameter<IRandom> RandomParameter {
51      get { return (ILookupParameter<IRandom>)Parameters["Random"]; }
52    }
[11739]53
[11880]54    public Action<Individual[], double[][], ResultCollection, IRandom> AnalyzeAction { get; set; }
55
[11400]56    [StorableConstructor]
57    protected MultiObjectiveAnalyzer(bool deserializing) : base(deserializing) { }
58    protected MultiObjectiveAnalyzer(MultiObjectiveAnalyzer original, Cloner cloner) : base(original, cloner) { }
59    public MultiObjectiveAnalyzer() {
60      Parameters.Add(new LookupParameter<IRandom>("Random", "The random number generator to use."));
[11559]61      Parameters.Add(new LookupParameter<IEncoding>("Encoding", "An item that holds the problem's encoding."));
[11400]62      Parameters.Add(new ScopeTreeLookupParameter<DoubleArray>("Qualities", "The qualities of the parameter vector."));
63      Parameters.Add(new LookupParameter<ResultCollection>("Results", "The results collection to write to."));
64    }
65
66    public override IDeepCloneable Clone(Cloner cloner) {
67      return new MultiObjectiveAnalyzer(this, cloner);
68    }
69
70    public override IOperation Apply() {
[11598]71      var encoding = EncodingParameter.ActualValue;
[11400]72      var results = ResultsParameter.ActualValue;
[11880]73      var random = RandomParameter.ActualValue;
[11400]74
75      IEnumerable<IScope> scopes = new[] { ExecutionContext.Scope };
76      for (var i = 0; i < QualitiesParameter.Depth; i++)
77        scopes = scopes.Select(x => (IEnumerable<IScope>)x.SubScopes).Aggregate((a, b) => a.Concat(b));
78
[11619]79      var individuals = scopes.Select(encoding.GetIndividual).ToArray();
[11880]80      AnalyzeAction(individuals, QualitiesParameter.ActualValue.Select(x => x.ToArray()).ToArray(), results, random);
[11400]81      return base.Apply();
82    }
83  }
84}
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