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source: branches/2521_ProblemRefactoring/HeuristicLab.Problems.TestFunctions.MultiObjective/3.3/Analyzers/ScatterPlotAnalyzer.cs @ 17226

Last change on this file since 17226 was 17226, checked in by mkommend, 5 years ago

#2521: Merged trunk changes into problem refactoring branch.

File size: 3.5 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 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.Linq;
23using HeuristicLab.Common;
24using HeuristicLab.Core;
25using HeuristicLab.Data;
26using HeuristicLab.Encodings.RealVectorEncoding;
27using HeuristicLab.Optimization;
28using HeuristicLab.Parameters;
29using HEAL.Attic;
30
31namespace HeuristicLab.Problems.TestFunctions.MultiObjective {
32  [StorableType("720E2726-7F31-4425-B478-327D24BA2FF3")]
33  [Item("ScatterPlotAnalyzer", "Creates a Scatterplot for the current and the best known front (see Multi-Objective Performance Metrics - Shodhganga for more information)")]
34  public class ScatterPlotAnalyzer : MOTFAnalyzer {
35
36    public IScopeTreeLookupParameter<RealVector> IndividualsParameter {
37      get { return (IScopeTreeLookupParameter<RealVector>)Parameters["Individuals"]; }
38    }
39
40    public IResultParameter<ParetoFrontScatterPlot> ScatterPlotResultParameter {
41      get { return (IResultParameter<ParetoFrontScatterPlot>)Parameters["Scatterplot"]; }
42    }
43
44    [StorableConstructor]
45    protected ScatterPlotAnalyzer(StorableConstructorFlag _) : base(_) { }
46    protected ScatterPlotAnalyzer(ScatterPlotAnalyzer original, Cloner cloner) : base(original, cloner) { }
47    public override IDeepCloneable Clone(Cloner cloner) {
48      return new ScatterPlotAnalyzer(this, cloner);
49    }
50
51    public ScatterPlotAnalyzer() {
52      Parameters.Add(new ScopeTreeLookupParameter<RealVector>("Individuals", "The individual solutions to the problem"));
53      Parameters.Add(new ResultParameter<ParetoFrontScatterPlot>("Scatterplot", "The scatterplot for the current and optimal (if known front)"));
54    }
55
56    public override IOperation Apply() {
57      var qualities = QualitiesParameter.ActualValue;
58      var individuals = IndividualsParameter.ActualValue;
59      var testFunction = TestFunctionParameter.ActualValue;
60      var objectives = qualities.Length != 0 ? qualities[0].Length:0;   
61      var problemSize = individuals.Length != 0 ? individuals[0].Length:0;
62
63      var optimalFront = new double[0][];               
64      if (testFunction != null) {
65        var front = testFunction.OptimalParetoFront(objectives);
66        if (front != null) optimalFront = front.ToArray();
67      }
68      else {
69        var mat = BestKnownFrontParameter.ActualValue;
70        optimalFront = mat == null ? null : Enumerable.Range(0, mat.Rows).Select(r => Enumerable.Range(0, mat.Columns).Select(c => mat[r, c]).ToArray()).ToArray();
71      }
72
73      var qualityClones = qualities.Select(s => s.ToArray()).ToArray();
74      var solutionClones = individuals.Select(s => s.ToArray()).ToArray();
75
76      ScatterPlotResultParameter.ActualValue = new ParetoFrontScatterPlot(qualityClones, solutionClones, optimalFront, objectives, problemSize);
77      return base.Apply();
78    }
79  }
80}
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