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 |
|
---|
22 | using System.Linq;
|
---|
23 | using HeuristicLab.Common;
|
---|
24 | using HeuristicLab.Core;
|
---|
25 | using HeuristicLab.Encodings.RealVectorEncoding;
|
---|
26 | using HeuristicLab.Optimization;
|
---|
27 | using HeuristicLab.Parameters;
|
---|
28 | using HEAL.Attic;
|
---|
29 |
|
---|
30 | namespace HeuristicLab.Problems.TestFunctions.MultiObjective {
|
---|
31 | [StorableType("720E2726-7F31-4425-B478-327D24BA2FF3")]
|
---|
32 | [Item("ScatterPlotAnalyzer", "Creates a Scatterplot for the current and the best known front (see Multi-Objective Performance Metrics - Shodhganga for more information)")]
|
---|
33 | public class ScatterPlotAnalyzer : MOTFAnalyzer {
|
---|
34 |
|
---|
35 | public IScopeTreeLookupParameter<RealVector> IndividualsParameter {
|
---|
36 | get { return (IScopeTreeLookupParameter<RealVector>)Parameters["Individuals"]; }
|
---|
37 | }
|
---|
38 |
|
---|
39 | public IResultParameter<ParetoFrontScatterPlot> ScatterPlotResultParameter {
|
---|
40 | get { return (IResultParameter<ParetoFrontScatterPlot>)Parameters["Scatterplot"]; }
|
---|
41 | }
|
---|
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 |
|
---|
57 | public override IOperation Apply() {
|
---|
58 | var qualities = QualitiesParameter.ActualValue;
|
---|
59 | var individuals = IndividualsParameter.ActualValue;
|
---|
60 | var testFunction = TestFunctionParameter.ActualValue;
|
---|
61 | int objectives = qualities[0].Length;
|
---|
62 | int problemSize = individuals[0].Length;
|
---|
63 |
|
---|
64 | double[][] optimalFront = new double[0][];
|
---|
65 | var front = testFunction.OptimalParetoFront(objectives);
|
---|
66 | if (front != null) optimalFront = front.ToArray();
|
---|
67 |
|
---|
68 | var qualityClones = qualities.Select(s => s.ToArray()).ToArray();
|
---|
69 | var solutionClones = individuals.Select(s => s.ToArray()).ToArray();
|
---|
70 |
|
---|
71 | ScatterPlotResultParameter.ActualValue = new ParetoFrontScatterPlot(qualityClones, solutionClones, optimalFront, objectives, problemSize);
|
---|
72 |
|
---|
73 | return base.Apply();
|
---|
74 | }
|
---|
75 | }
|
---|
76 | }
|
---|