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source: trunk/sources/HeuristicLab.Selection/3.3/ProportionalSelector.cs @ 4618

Last change on this file since 4618 was 4477, checked in by gkronber, 14 years ago

Merged r4458, r4459,r4462,r4464 from data analysis exploration branch into trunk. #1142

File size: 4.0 KB
RevLine 
[2]1#region License Information
2/* HeuristicLab
[2817]3 * Copyright (C) 2002-2010 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
[2]4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21
[2818]22using System;
23using System.Collections.Generic;
[2817]24using System.Linq;
[2]25using HeuristicLab.Core;
26using HeuristicLab.Data;
[3138]27using HeuristicLab.Optimization;
[2817]28using HeuristicLab.Parameters;
29using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
[2]30
31namespace HeuristicLab.Selection {
[817]32  /// <summary>
[2817]33  /// A quality proportional selection operator which considers a single double quality value for selection.
[817]34  /// </summary>
[2817]35  [Item("ProportionalSelector", "A quality proportional selection operator which considers a single double quality value for selection.")]
[3017]36  [StorableClass]
[3138]37  public sealed class ProportionalSelector : StochasticSingleObjectiveSelector, ISingleObjectiveSelector {
[3048]38    private ValueParameter<BoolValue> WindowingParameter {
39      get { return (ValueParameter<BoolValue>)Parameters["Windowing"]; }
[2]40    }
41
[3048]42    public BoolValue Windowing {
[2817]43      get { return WindowingParameter.Value; }
44      set { WindowingParameter.Value = value; }
[2]45    }
46
[2817]47    public ProportionalSelector()
48      : base() {
[3048]49      Parameters.Add(new ValueParameter<BoolValue>("Windowing", "Apply windowing strategy (selection probability is proportional to the quality differences and not to the total quality).", new BoolValue(true)));
[2817]50    }
[2]51
[2830]52    protected override IScope[] Select(List<IScope> scopes) {
[2817]53      int count = NumberOfSelectedSubScopesParameter.ActualValue.Value;
54      bool copy = CopySelectedParameter.Value.Value;
55      IRandom random = RandomParameter.ActualValue;
56      bool maximization = MaximizationParameter.ActualValue.Value;
57      bool windowing = WindowingParameter.Value.Value;
[2830]58      IScope[] selected = new IScope[count];
[2]59
[2817]60      // prepare qualities for proportional selection
[2818]61      var qualities = QualityParameter.ActualValue.Select(x => x.Value);
62      double minQuality = qualities.Min();
63      double maxQuality = qualities.Max();
[2817]64      if (minQuality == maxQuality) {  // all quality values are equal
[2818]65        qualities = qualities.Select(x => 1.0);
[2817]66      } else {
67        if (windowing) {
68          if (maximization)
[2818]69            qualities = qualities.Select(x => x - minQuality);
[2817]70          else
[2818]71            qualities = qualities.Select(x => maxQuality - x);
[2817]72        } else {
73          if (minQuality < 0.0) throw new InvalidOperationException("Proportional selection without windowing does not work with quality values < 0.");
74          if (!maximization) {
75            double limit = Math.Min(maxQuality * 2, double.MaxValue);
[2818]76            qualities = qualities.Select(x => limit - x);
[2817]77          }
[2]78        }
79      }
80
[2818]81      List<double> list = qualities.ToList();
82      double qualitySum = qualities.Sum();
[2817]83      for (int i = 0; i < count; i++) {
84        double selectedQuality = random.NextDouble() * qualitySum;
85        int index = 0;
[2818]86        double currentQuality = list[index];
[2817]87        while (currentQuality < selectedQuality) {
88          index++;
[2818]89          currentQuality += list[index];
[2]90        }
[2817]91        if (copy)
[2830]92          selected[i] = (IScope)scopes[index].Clone();
[2817]93        else {
[2830]94          selected[i] = scopes[index];
[2817]95          scopes.RemoveAt(index);
[2818]96          qualitySum -= list[index];
97          list.RemoveAt(index);
[2]98        }
99      }
[2817]100      return selected;
[2]101    }
102  }
103}
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