source: branches/PerformanceComparison/HeuristicLab.Analysis.FitnessLandscape/3.3/CharacteristicCalculator/AdaptiveWalkCalculator.cs @ 13920

Last change on this file since 13920 was 13920, checked in by abeham, 3 years ago

#2457: added repetitions to LocalAnalysis and computing average

File size: 4.1 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2016 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 HeuristicLab.Common;
23using HeuristicLab.Core;
24using HeuristicLab.Data;
25using HeuristicLab.Optimization;
26using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
27using System;
28using System.Collections.Generic;
29using System.Linq;
30using System.Threading;
31
32namespace HeuristicLab.Analysis.FitnessLandscape {
33  [Item("Adaptive Walk Calculator", "Calculates characteristics from an adaptive walk.")]
34  [StorableClass]
35  public class AdaptiveWalkCalculator : NamedItem, ICharacteristicCalculator {
36
37    [Storable]
38    private IProblem problem;
39    public IProblem Problem {
40      get { return problem; }
41      set {
42        if (problem == value) return;
43        problem = value;
44        var soProblem = problem as ISingleObjectiveHeuristicOptimizationProblem;
45        walker.Problem = soProblem;
46      }
47    }
48
49    [Storable]
50    private AdaptiveWalk walker;
51
52    [StorableConstructor]
53    private AdaptiveWalkCalculator(bool deserializing) : base(deserializing) { }
54    private AdaptiveWalkCalculator(AdaptiveWalkCalculator original, Cloner cloner)
55      : base(original, cloner) {
56      problem = cloner.Clone(original.problem);
57      walker = cloner.Clone(original.walker);
58      characteristics = cloner.Clone(original.characteristics);
59    }
60    public AdaptiveWalkCalculator() {
61      Name = ItemName;
62      Description = ItemDescription;
63      walker = new AdaptiveWalk();
64      characteristics = new CheckedItemList<StringValue>(
65        new[] { "AutoCorrelation1", "CorrelationLength", "InformationContent",
66        "PartialInformationContent", "DensityBasinInformation", "InformationStability", 
67        "Diversity", "Regularity", "TotalEntropy", "PeakInformationContent",
68        "PeakDensityBasinInformation" }.Select(x => new StringValue(x)));
69    }
70
71    public override IDeepCloneable Clone(Cloner cloner) {
72      return new AdaptiveWalkCalculator(this, cloner);
73    }
74
75    private CheckedItemList<StringValue> characteristics;
76    public ReadOnlyCheckedItemList<StringValue> Characteristics {
77      get { return characteristics.AsReadOnly(); }
78    }
79
80    public bool CanCalculate() {
81      return Problem is ISingleObjectiveHeuristicOptimizationProblem
82        && Problem.Operators.Any(x => x is IManipulator);
83    }
84
85    public IEnumerable<IResult> Calculate() {
86      walker.Prepare(true);
87      using (var waitHandle = new AutoResetEvent(false)) {
88        EventHandler evHandle = (sender, e) => {
89          if (walker.ExecutionState == ExecutionState.Paused
90          || walker.ExecutionState == ExecutionState.Stopped) waitHandle.Set();
91        };
92        walker.ExecutionStateChanged += evHandle;
93        walker.Start();
94        waitHandle.WaitOne();
95        walker.ExecutionStateChanged -= evHandle;
96      }
97      foreach (var p in characteristics.CheckedItems) {
98        yield return new Result("AdaptiveWalk." + walker.MutatorParameter.Value.Name + "." + p.Value.Value, walker.Results[p.Value.Value].Value);
99      }
100      walker.Prepare(true);
101    }
102
103    public void CollectParameterValues(IDictionary<string, IItem> values) {
104      walker.CollectParameterValues(values);
105    }
106
107    public IKeyedItemCollection<string, IParameter> Parameters {
108      get { return ((IParameterizedItem)walker).Parameters; }
109    }
110  }
111}
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