#region License Information
/* HeuristicLab
* Copyright (C) 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 HEAL.Attic;
namespace HeuristicLab.Problems.TestFunctions.MultiObjective {
[StorableType("720E2726-7F31-4425-B478-327D24BA2FF3")]
[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(StorableConstructorFlag _) : base(_) { }
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();
}
}
}