source: branches/2974_Constants_Optimization/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/ConstantOptimizationAnalyzer.cs @ 17193

Last change on this file since 17193 was 17193, checked in by mkommend, 12 months ago

#2974: Merged trunk changes into branch.

File size: 8.3 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 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;
23using System.Linq;
24using HeuristicLab.Analysis;
25using HeuristicLab.Common;
26using HeuristicLab.Core;
27using HeuristicLab.Data;
28using HeuristicLab.Optimization;
29using HeuristicLab.Parameters;
30using HEAL.Attic;
31
32namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression {
33  /// <summary>
34  /// An operator that optimizes the constants for the best symbolic expression tress in the current generation.
35  /// </summary>
36  [Item("ConstantOptimizationAnalyzer", "An operator that performs a constant optimization on the best symbolic expression trees.")]
37  [StorableType("9FB87E7B-A9E2-49DD-A92A-78BD9FC17916")]
38  public sealed class ConstantOptimizationAnalyzer : SymbolicDataAnalysisSingleObjectiveAnalyzer, IStatefulItem {
39    private const string PercentageOfBestSolutionsParameterName = "PercentageOfBestSolutions";
40    private const string ConstantOptimizationEvaluatorParameterName = "ConstantOptimizationOperator";
41
42    private const string DataTableNameConstantOptimizationImprovement = "Constant Optimization Improvement";
43    private const string DataRowNameMinimumImprovement = "Minimum improvement";
44    private const string DataRowNameMedianImprovement = "Median improvement";
45    private const string DataRowNameAverageImprovement = "Average improvement";
46    private const string DataRowNameMaximumImprovement = "Maximum improvement";
47
48    #region parameter properties
49    public IFixedValueParameter<PercentValue> PercentageOfBestSolutionsParameter {
50      get { return (IFixedValueParameter<PercentValue>)Parameters[PercentageOfBestSolutionsParameterName]; }
51    }
52
53    public IFixedValueParameter<SymbolicRegressionConstantOptimizationEvaluator> ConstantOptimizationEvaluatorParameter {
54      get { return (IFixedValueParameter<SymbolicRegressionConstantOptimizationEvaluator>)Parameters[ConstantOptimizationEvaluatorParameterName]; }
55    }
56    #endregion
57
58    #region properties
59    public SymbolicRegressionConstantOptimizationEvaluator ConstantOptimizationEvaluator {
60      get { return ConstantOptimizationEvaluatorParameter.Value; }
61    }
62    public double PercentageOfBestSolutions {
63      get { return PercentageOfBestSolutionsParameter.Value.Value; }
64    }
65
66    private DataTable ConstantOptimizationImprovementDataTable {
67      get {
68        IResult result;
69        ResultCollection.TryGetValue(DataTableNameConstantOptimizationImprovement, out result);
70        if (result == null) return null;
71        return (DataTable)result.Value;
72      }
73    }
74    private DataRow MinimumImprovement {
75      get { return ConstantOptimizationImprovementDataTable.Rows[DataRowNameMinimumImprovement]; }
76    }
77    private DataRow MedianImprovement {
78      get { return ConstantOptimizationImprovementDataTable.Rows[DataRowNameMedianImprovement]; }
79    }
80    private DataRow AverageImprovement {
81      get { return ConstantOptimizationImprovementDataTable.Rows[DataRowNameAverageImprovement]; }
82    }
83    private DataRow MaximumImprovement {
84      get { return ConstantOptimizationImprovementDataTable.Rows[DataRowNameMaximumImprovement]; }
85    }
86    #endregion
87
88    [StorableConstructor]
89    private ConstantOptimizationAnalyzer(StorableConstructorFlag _) : base(_) { }
90    private ConstantOptimizationAnalyzer(ConstantOptimizationAnalyzer original, Cloner cloner) : base(original, cloner) { }
91    public override IDeepCloneable Clone(Cloner cloner) { return new ConstantOptimizationAnalyzer(this, cloner); }
92    public ConstantOptimizationAnalyzer()
93      : base() {
94      Parameters.Add(new FixedValueParameter<PercentValue>(PercentageOfBestSolutionsParameterName, "The percentage of the top solutions which should be analyzed.", new PercentValue(0.1)));
95      Parameters.Add(new FixedValueParameter<SymbolicRegressionConstantOptimizationEvaluator>(ConstantOptimizationEvaluatorParameterName, "The operator used to perform the constant optimization"));
96
97      //Changed the ActualName of the EvaluationPartitionParameter so that it matches the parameter name of symbolic regression problems.
98      ConstantOptimizationEvaluator.EvaluationPartitionParameter.ActualName = "FitnessCalculationPartition";
99    }
100
101
102    private double[] qualitiesBeforeCoOp = null;
103    private int[] scopeIndexes = null;
104    void IStatefulItem.InitializeState() {
105      qualitiesBeforeCoOp = null;
106      scopeIndexes = null;
107    }
108    void IStatefulItem.ClearState() {
109      qualitiesBeforeCoOp = null;
110      scopeIndexes = null;
111    }
112
113    public override IOperation Apply() {
114      //code executed in the first call of analyzer
115      if (qualitiesBeforeCoOp == null) {
116        double[] trainingQuality;
117        // sort is ascending and we take the first n% => order so that best solutions are smallest
118        // sort order is determined by maximization parameter
119        if (Maximization.Value) {
120          // largest values must be sorted first
121          trainingQuality = Quality.Select(x => -x.Value).ToArray();
122        } else {
123          // smallest values must be sorted first
124          trainingQuality = Quality.Select(x => x.Value).ToArray();
125        }
126        // sort trees by training qualities
127        int topN = (int)Math.Max(trainingQuality.Length * PercentageOfBestSolutions, 1);
128        scopeIndexes = Enumerable.Range(0, trainingQuality.Length).ToArray();
129        Array.Sort(trainingQuality, scopeIndexes);
130        scopeIndexes = scopeIndexes.Take(topN).ToArray();
131        qualitiesBeforeCoOp = scopeIndexes.Select(x => Quality[x].Value).ToArray();
132
133        OperationCollection operationCollection = new OperationCollection();
134        operationCollection.Parallel = true;
135        foreach (var scopeIndex in scopeIndexes) {
136          var childOperation = ExecutionContext.CreateChildOperation(ConstantOptimizationEvaluator, ExecutionContext.Scope.SubScopes[scopeIndex]);
137          operationCollection.Add(childOperation);
138        }
139
140        return new OperationCollection { operationCollection, ExecutionContext.CreateOperation(this) };
141      }
142
143      //code executed to analyze results of constant optimization
144      double[] qualitiesAfterCoOp = scopeIndexes.Select(x => Quality[x].Value).ToArray();
145      var qualityImprovement = qualitiesBeforeCoOp.Zip(qualitiesAfterCoOp, (b, a) => a - b).ToArray();
146
147      if (!ResultCollection.ContainsKey(DataTableNameConstantOptimizationImprovement)) {
148        var dataTable = new DataTable(DataTableNameConstantOptimizationImprovement);
149        ResultCollection.Add(new Result(DataTableNameConstantOptimizationImprovement, dataTable));
150        dataTable.VisualProperties.YAxisTitle = "R²";
151
152        dataTable.Rows.Add(new DataRow(DataRowNameMinimumImprovement));
153        MinimumImprovement.VisualProperties.StartIndexZero = true;
154
155        dataTable.Rows.Add(new DataRow(DataRowNameMedianImprovement));
156        MedianImprovement.VisualProperties.StartIndexZero = true;
157
158        dataTable.Rows.Add(new DataRow(DataRowNameAverageImprovement));
159        AverageImprovement.VisualProperties.StartIndexZero = true;
160
161        dataTable.Rows.Add(new DataRow(DataRowNameMaximumImprovement));
162        MaximumImprovement.VisualProperties.StartIndexZero = true;
163      }
164
165      MinimumImprovement.Values.Add(qualityImprovement.Min());
166      MedianImprovement.Values.Add(qualityImprovement.Median());
167      AverageImprovement.Values.Add(qualityImprovement.Average());
168      MaximumImprovement.Values.Add(qualityImprovement.Max());
169
170      qualitiesBeforeCoOp = null;
171      scopeIndexes = null;
172      return base.Apply();
173    }
174  }
175}
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