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source: branches/ProblemRefactoring/HeuristicLab.Optimization/3.3/BasicProblems/Operators/SingleObjectiveAnalyzer.cs @ 13336

Last change on this file since 13336 was 13336, checked in by mkommend, 9 years ago

#2521: Refactored encodings and problems.

File size: 3.8 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2015 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 HeuristicLab.Common;
26using HeuristicLab.Core;
27using HeuristicLab.Data;
28using HeuristicLab.Operators;
29using HeuristicLab.Parameters;
30using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
31
32namespace HeuristicLab.Optimization {
33  [Item("Single-objective Analyzer", "Calls the script's Analyze method to be able to write into the results collection.")]
34  [StorableClass]
35  public sealed class SingleObjectiveAnalyzer<TSolution> : SingleSuccessorOperator, ISingleObjectiveAnalysisOperator<TSolution>, IAnalyzer, IStochasticOperator
36  where TSolution : class, ISolution {
37    public bool EnabledByDefault { get { return true; } }
38
39    public ILookupParameter<IEncoding<TSolution>> EncodingParameter {
40      get { return (ILookupParameter<IEncoding<TSolution>>)Parameters["Encoding"]; }
41    }
42
43    public IScopeTreeLookupParameter<DoubleValue> QualityParameter {
44      get { return (IScopeTreeLookupParameter<DoubleValue>)Parameters["Quality"]; }
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<TSolution[], double[], ResultCollection, IRandom> AnalyzeAction { get; set; }
56
57    [StorableConstructor]
58    private SingleObjectiveAnalyzer(bool deserializing) : base(deserializing) { }
59    private SingleObjectiveAnalyzer(SingleObjectiveAnalyzer<TSolution> original, Cloner cloner) : base(original, cloner) { }
60    public SingleObjectiveAnalyzer() {
61      Parameters.Add(new LookupParameter<IEncoding<TSolution>>("Encoding", "An item that holds the problem's encoding."));
62      Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", "The quality of the parameter vector."));
63      Parameters.Add(new LookupParameter<ResultCollection>("Results", "The results collection to write to."));
64      Parameters.Add(new LookupParameter<IRandom>("Random", "The random number generator to use."));
65    }
66
67    public override IDeepCloneable Clone(Cloner cloner) {
68      return new SingleObjectiveAnalyzer<TSolution>(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 < QualityParameter.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.GetSolution(s, encoding)).ToArray();
81      AnalyzeAction(individuals, QualityParameter.ActualValue.Select(x => x.Value).ToArray(), results, random);
82      return base.Apply();
83    }
84  }
85}
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