[13672] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[15583] | 3 | * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[13672] | 4 | *
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| 5 | * This file is part of HeuristicLab.
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| 6 | *
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| 7 | * HeuristicLab is free software: you can redistribute it and/or modify
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| 8 | * it under the terms of the GNU General Public License as published by
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| 9 | * the Free Software Foundation, either version 3 of the License, or
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| 10 | * (at your option) any later version.
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| 11 | *
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| 12 | * HeuristicLab is distributed in the hope that it will be useful,
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| 13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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| 14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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| 15 | * GNU General Public License for more details.
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| 16 | *
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| 17 | * You should have received a copy of the GNU General Public License
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| 18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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| 19 | */
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| 20 | #endregion
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[14044] | 21 |
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[13672] | 22 | using System.Linq;
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| 23 | using HeuristicLab.Common;
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[13725] | 24 | using HeuristicLab.Core;
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[13672] | 25 | using HeuristicLab.Encodings.RealVectorEncoding;
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| 26 | using HeuristicLab.Optimization;
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[14044] | 27 | using HeuristicLab.Parameters;
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[13725] | 28 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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[13672] | 29 |
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[14111] | 30 | namespace HeuristicLab.Problems.TestFunctions.MultiObjective {
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[13725] | 31 | [StorableClass]
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| 32 | [Item("ScatterPlotAnalyzer", "Creates a Scatterplot for the current and the best known front (see Multi-Objective Performance Metrics - Shodhganga for more information)")]
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| 33 | public class ScatterPlotAnalyzer : MOTFAnalyzer {
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[13672] | 34 |
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[14044] | 35 | public IScopeTreeLookupParameter<RealVector> IndividualsParameter {
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| 36 | get { return (IScopeTreeLookupParameter<RealVector>)Parameters["Individuals"]; }
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[13672] | 37 | }
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[14044] | 38 |
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[15203] | 39 | public IResultParameter<ParetoFrontScatterPlot> ScatterPlotResultParameter {
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| 40 | get { return (IResultParameter<ParetoFrontScatterPlot>)Parameters["Scatterplot"]; }
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[14097] | 41 | }
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| 42 |
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| 43 |
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[13725] | 44 | [StorableConstructor]
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| 45 | protected ScatterPlotAnalyzer(bool deserializing) : base(deserializing) { }
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[14044] | 46 | protected ScatterPlotAnalyzer(ScatterPlotAnalyzer original, Cloner cloner) : base(original, cloner) { }
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[13672] | 47 | public override IDeepCloneable Clone(Cloner cloner) {
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| 48 | return new ScatterPlotAnalyzer(this, cloner);
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| 49 | }
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[13725] | 50 |
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[14044] | 51 | public ScatterPlotAnalyzer() {
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| 52 | Parameters.Add(new ScopeTreeLookupParameter<RealVector>("Individuals", "The individual solutions to the problem"));
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[15203] | 53 | Parameters.Add(new ResultParameter<ParetoFrontScatterPlot>("Scatterplot", "The scatterplot for the current and optimal (if known front)"));
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[14097] | 54 |
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[14044] | 55 | }
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[13672] | 56 |
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[14044] | 57 | public override IOperation Apply() {
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| 58 | var qualities = QualitiesParameter.ActualValue;
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[15203] | 59 | var individuals = IndividualsParameter.ActualValue;
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[14044] | 60 | var testFunction = TestFunctionParameter.ActualValue;
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[13672] | 61 | int objectives = qualities[0].Length;
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[15203] | 62 | int problemSize = individuals[0].Length;
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[13672] | 63 |
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[14044] | 64 | double[][] optimalFront = new double[0][];
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| 65 | var front = testFunction.OptimalParetoFront(objectives);
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| 66 | if (front != null) optimalFront = front.ToArray();
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| 67 |
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| 68 | var qualityClones = qualities.Select(s => s.ToArray()).ToArray();
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| 69 | var solutionClones = individuals.Select(s => s.ToArray()).ToArray();
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| 70 |
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[15203] | 71 | ScatterPlotResultParameter.ActualValue = new ParetoFrontScatterPlot(qualityClones, solutionClones, optimalFront, objectives, problemSize);
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[14044] | 72 |
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| 73 | return base.Apply();
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[13672] | 74 | }
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| 75 | }
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| 76 | }
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