#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.Collections.Generic; using System.Linq; using HeuristicLab.Common; using HeuristicLab.Core; using HeuristicLab.Data; using HeuristicLab.Optimization; using HeuristicLab.Parameters; using HeuristicLab.Persistence.Default.CompositeSerializers.Storable; namespace HeuristicLab.Analysis { [Item("RankBasedParetoFrontAnalyzer", "Uses the rank value that is computed by e.g. the NSGA2's fast non dominated sort operator to collect all solutions and their qualities of front 0 (the current Pareto front).")] [StorableClass] public class RankBasedParetoFrontAnalyzer : ParetoFrontAnalyzer { public IScopeTreeLookupParameter RankParameter { get { return (IScopeTreeLookupParameter)Parameters["Rank"]; } } [StorableConstructor] protected RankBasedParetoFrontAnalyzer(bool deserializing) : base(deserializing) { } protected RankBasedParetoFrontAnalyzer(RankBasedParetoFrontAnalyzer original, Cloner cloner) : base(original, cloner) { } public RankBasedParetoFrontAnalyzer() { Parameters.Add(new ScopeTreeLookupParameter("Rank", "The rank of solution [0..N] describes to which front it belongs.")); } protected override void Analyze(ItemArray qualities, ResultCollection results) { ItemArray ranks = RankParameter.ActualValue; bool populationLevel = RankParameter.Depth == 1; int objectives = qualities[0].Length; int frontSize = ranks.Count(x => x.Value == 0); ItemArray paretoArchive = null; if (populationLevel) paretoArchive = new ItemArray(frontSize); DoubleMatrix front = new DoubleMatrix(frontSize, objectives); int counter = 0; for (int i = 0; i < ranks.Length; i++) { if (ranks[i].Value == 0) { for (int k = 0; k < objectives; k++) front[counter, k] = qualities[i][k]; if (populationLevel) { paretoArchive[counter] = (IScope)ExecutionContext.Scope.SubScopes[i].Clone(); } counter++; } } front.RowNames = GetRowNames(front); front.ColumnNames = GetColumnNames(front); if (results.ContainsKey("Pareto Front")) results["Pareto Front"].Value = front; else results.Add(new Result("Pareto Front", front)); if (populationLevel) { if (results.ContainsKey("Pareto Archive")) results["Pareto Archive"].Value = paretoArchive; else results.Add(new Result("Pareto Archive", paretoArchive)); } } private IEnumerable GetRowNames(DoubleMatrix front) { for (int i = 1; i <= front.Rows; i++) yield return "Solution " + i.ToString(); } private IEnumerable GetColumnNames(DoubleMatrix front) { for (int i = 1; i <= front.Columns; i++) yield return "Objective " + i.ToString(); } public override IDeepCloneable Clone(Cloner cloner) { return new RankBasedParetoFrontAnalyzer(this, cloner); } } }