#region License Information
/* HeuristicLab
* Copyright (C) 2002-2016 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);
}
}
}