#region License Information /* HeuristicLab * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL) * * This file is part of HeuristicLab. * * HeuristicLab is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * HeuristicLab is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with HeuristicLab. If not, see . */ #endregion using System.Linq; using HeuristicLab.Common; using HeuristicLab.Core; using HeuristicLab.Encodings.RealVectorEncoding; using HeuristicLab.Optimization; using HeuristicLab.Parameters; using HeuristicLab.Persistence.Default.CompositeSerializers.Storable; namespace HeuristicLab.Problems.TestFunctions.MultiObjective { [StorableClass] [Item("ScatterPlotAnalyzer", "Creates a Scatterplot for the current and the best known front (see Multi-Objective Performance Metrics - Shodhganga for more information)")] public class ScatterPlotAnalyzer : MOTFAnalyzer { public IScopeTreeLookupParameter IndividualsParameter { get { return (IScopeTreeLookupParameter)Parameters["Individuals"]; } } public IResultParameter ScatterPlotResultParameter { get { return (IResultParameter)Parameters["Scatterplot"]; } } [StorableConstructor] protected ScatterPlotAnalyzer(bool deserializing) : base(deserializing) { } protected ScatterPlotAnalyzer(ScatterPlotAnalyzer original, Cloner cloner) : base(original, cloner) { } public override IDeepCloneable Clone(Cloner cloner) { return new ScatterPlotAnalyzer(this, cloner); } public ScatterPlotAnalyzer() { Parameters.Add(new ScopeTreeLookupParameter("Individuals", "The individual solutions to the problem")); Parameters.Add(new ResultParameter("Scatterplot", "The scatterplot for the current and optimal (if known front)")); } public override IOperation Apply() { var qualities = QualitiesParameter.ActualValue; var individuals = IndividualsParameter.ActualValue; var testFunction = TestFunctionParameter.ActualValue; int objectives = qualities[0].Length; int problemSize = individuals[0].Length; double[][] optimalFront = new double[0][]; var front = testFunction.OptimalParetoFront(objectives); if (front != null) optimalFront = front.ToArray(); var qualityClones = qualities.Select(s => s.ToArray()).ToArray(); var solutionClones = individuals.Select(s => s.ToArray()).ToArray(); ScatterPlotResultParameter.ActualValue = new ParetoFrontScatterPlot(qualityClones, solutionClones, optimalFront, objectives, problemSize); return base.Apply(); } } }