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source: addons/HeuristicLab.FitnessLandscapeAnalysis/HeuristicLab.Analysis.FitnessLandscape/Analysis/QualityTrailSummarizer.cs

Last change on this file was 16995, checked in by gkronber, 6 years ago

#2520 Update plugin dependencies and references for HL.FLA for new persistence

File size: 4.8 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2010 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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
22using System.Linq;
23using HeuristicLab.Analysis.FitnessLandscape.DataTables;
24using HeuristicLab.Common;
25using HeuristicLab.Core;
26using HeuristicLab.Operators;
27using HeuristicLab.Optimization.Operators;
28using HeuristicLab.Parameters;
29using System;
30using HEAL.Attic;
31
32namespace HeuristicLab.Analysis.FitnessLandscape.Analysis {
33
34  [StorableType("78C1D578-7752-45B4-9174-DF30D38A7E8A")]
35  public class QualityTrailSummarizer : AlgorithmOperator, IQualityTrailAnalyzer {
36    public bool EnabledByDefault {
37      get { return false; }
38    }
39
40    #region Parameters
41    public LookupParameter<DataTable> QualityTrailParameter {
42      get { return (LookupParameter<DataTable>)Parameters["Quality Trail"]; }
43    }
44    public LookupParameter<QualityTrailSummaryTable> QualityTrailSummaryParameter {
45      get { return (LookupParameter<QualityTrailSummaryTable>)Parameters["QualityTrailSummary"]; }
46    }
47    public LookupParameter<VariableCollection> ResultsParameter {
48      get { return (LookupParameter<VariableCollection>)Parameters["Results"]; }
49    }
50    #endregion
51
52    #region Construction & Cloning
53    [StorableConstructor]
54    protected QualityTrailSummarizer(StorableConstructorFlag _) : base(_) { }
55    protected QualityTrailSummarizer(QualityTrailSummarizer original, Cloner cloner) : base(original, cloner) { }
56
57    public QualityTrailSummarizer() {
58      Parameters.Add(new LookupParameter<DataTable>("Quality Trail", "The quality of the solution"));
59      Parameters.Add(new LookupParameter<QualityTrailSummaryTable>("QualityTrailSummary", "Maximum nr of steps between statistically significantly correlated quality values"));
60      Parameters.Add(new LookupParameter<VariableCollection>("Results", "The collection of all results of this algorithm"));
61
62      var resultsCollector = new ResultsCollector();
63      resultsCollector.CollectedValues.Add(new LookupParameter<DataTable>(QualityTrailSummaryParameter.Name));
64
65      OperatorGraph.InitialOperator = resultsCollector;
66    }
67
68    public override IDeepCloneable Clone(Cloner cloner) {
69      return new QualityTrailSummarizer(this, cloner);
70    }
71    #endregion
72
73    public override IOperation Apply() {
74      QualityTrailSummaryTable qualityTrailSummary = CreateQualitytrailSummaryTable();
75      DataTable qualityTrail = QualityTrailParameter.ActualValue;
76      if (qualityTrail != null && qualityTrail.Rows.Count > 1) {
77        var values = qualityTrail.Rows.First().Values;       
78        DistributionAnalyzer analyzer = new DistributionAnalyzer(values);
79        qualityTrailSummary.Rows["Value Quantiles"].Values.AddRange(new[] { 0, 0.25, 0.5, 0.75, 1 }.Select(q => analyzer[q]));
80        double variance, kurtosis, skewness, mean;
81        for (int i = 0; i < 4; i++) {
82          int minIndex = (int)Math.Round(i*values.Count*0.25);
83          int maxIndex = (int)Math.Round((i+1)*values.Count*0.25);
84          alglib.samplemoments(
85            values.GetRange(minIndex, maxIndex - minIndex).ToArray(),
86            out mean, out variance, out skewness, out kurtosis);
87          qualityTrailSummary.Rows["Epoch Averages"].Values.Add(mean);
88          qualityTrailSummary.Rows["Epoch Variances"].Values.Add(variance);
89          qualityTrailSummary.Rows["Epoch Skewnesses"].Values.Add(skewness);
90          qualityTrailSummary.Rows["Epoch Kurtoses"].Values.Add(kurtosis);
91        }
92      }
93      return base.Apply();
94    }
95
96    private QualityTrailSummaryTable CreateQualitytrailSummaryTable() {
97      QualityTrailSummaryTable qualityTrailSummary = new QualityTrailSummaryTable("Quality Trail Summary");
98      QualityTrailSummaryParameter.ActualValue = qualityTrailSummary;
99      qualityTrailSummary.Rows.Add(new DataRow("Value Quantiles"));
100      qualityTrailSummary.Rows.Add(new DataRow("Epoch Averages"));
101      qualityTrailSummary.Rows.Add(new DataRow("Epoch Variances"));
102      qualityTrailSummary.Rows.Add(new DataRow("Epoch Skewnesses"));
103      qualityTrailSummary.Rows.Add(new DataRow("Epoch Kurtoses"));
104      return qualityTrailSummary;
105    }
106
107  }
108}
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