source: branches/2971_named_intervals/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective/PearsonRSquaredAverageSimilarityEvaluator.cs @ 17144

Last change on this file since 17144 was 17144, checked in by mkommend, 2 months ago

#2971: Merged trunk changes into branch.

File size: 6.3 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2019 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.Collections.Generic;
24using HEAL.Attic;
25using HeuristicLab.Common;
26using HeuristicLab.Core;
27using HeuristicLab.Data;
28using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
29using HeuristicLab.Parameters;
30
31namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression {
32  [Item("Pearson R² & Average Similarity Evaluator", "Calculates the Pearson R² and the average similarity of a symbolic regression solution candidate.")]
33  [StorableType("FE514989-E619-48B8-AC8E-9A2202708F65")]
34  public class PearsonRSquaredAverageSimilarityEvaluator : SymbolicRegressionMultiObjectiveEvaluator {
35    private const string StrictSimilarityParameterName = "StrictSimilarity";
36    private const string AverageSimilarityParameterName = "AverageSimilarity";
37
38    private readonly object locker = new object();
39
40    private readonly SymbolicDataAnalysisExpressionTreeAverageSimilarityCalculator SimilarityCalculator = new SymbolicDataAnalysisExpressionTreeAverageSimilarityCalculator();
41
42    public IFixedValueParameter<BoolValue> StrictSimilarityParameter {
43      get { return (IFixedValueParameter<BoolValue>)Parameters[StrictSimilarityParameterName]; }
44    }
45
46    public ILookupParameter<DoubleValue> AverageSimilarityParameter {
47      get { return (ILookupParameter<DoubleValue>)Parameters[AverageSimilarityParameterName]; }
48    }
49
50    public bool StrictSimilarity {
51      get { return StrictSimilarityParameter.Value.Value; }
52    }
53
54    [StorableConstructor]
55    protected PearsonRSquaredAverageSimilarityEvaluator(StorableConstructorFlag _) : base(_) { }
56    protected PearsonRSquaredAverageSimilarityEvaluator(PearsonRSquaredAverageSimilarityEvaluator original, Cloner cloner)
57      : base(original, cloner) {
58    }
59    public override IDeepCloneable Clone(Cloner cloner) {
60      return new PearsonRSquaredAverageSimilarityEvaluator(this, cloner);
61    }
62
63    public PearsonRSquaredAverageSimilarityEvaluator() : base() {
64      Parameters.Add(new FixedValueParameter<BoolValue>(StrictSimilarityParameterName, "Use strict similarity calculation.", new BoolValue(false)));
65      Parameters.Add(new LookupParameter<DoubleValue>(AverageSimilarityParameterName));
66    }
67
68    public override IEnumerable<bool> Maximization { get { return new bool[2] { true, false }; } } // maximize R² and minimize average similarity
69
70    public override IOperation InstrumentedApply() {
71      IEnumerable<int> rows = GenerateRowsToEvaluate();
72      var solution = SymbolicExpressionTreeParameter.ActualValue;
73      var problemData = ProblemDataParameter.ActualValue;
74      var interpreter = SymbolicDataAnalysisTreeInterpreterParameter.ActualValue;
75      var estimationLimits = EstimationLimitsParameter.ActualValue;
76      var applyLinearScaling = ApplyLinearScalingParameter.ActualValue.Value;
77
78      if (UseConstantOptimization) {
79        SymbolicRegressionConstantOptimizationEvaluator.OptimizeConstants(interpreter, solution, problemData, rows, applyLinearScaling, ConstantOptimizationIterations, updateVariableWeights: ConstantOptimizationUpdateVariableWeights, lowerEstimationLimit: estimationLimits.Lower, upperEstimationLimit: estimationLimits.Upper);
80      }
81
82      double r2 = SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator.Calculate(interpreter, solution, estimationLimits.Lower, estimationLimits.Upper, problemData, rows, applyLinearScaling);
83
84      if (DecimalPlaces >= 0)
85        r2 = Math.Round(r2, DecimalPlaces);
86
87      lock (locker) {
88        if (AverageSimilarityParameter.ActualValue == null) {
89          var context = new ExecutionContext(null, SimilarityCalculator, ExecutionContext.Scope.Parent);
90          SimilarityCalculator.StrictSimilarity = StrictSimilarity;
91          SimilarityCalculator.Execute(context, CancellationToken);
92        }
93      }
94      var avgSimilarity = AverageSimilarityParameter.ActualValue.Value;
95
96      QualitiesParameter.ActualValue = new DoubleArray(new[] { r2, avgSimilarity });
97      return base.InstrumentedApply();
98    }
99
100    public override double[] Evaluate(IExecutionContext context, ISymbolicExpressionTree tree, IRegressionProblemData problemData, IEnumerable<int> rows) {
101      SymbolicDataAnalysisTreeInterpreterParameter.ExecutionContext = context;
102      AverageSimilarityParameter.ExecutionContext = context;
103      EstimationLimitsParameter.ExecutionContext = context;
104      ApplyLinearScalingParameter.ExecutionContext = context;
105
106      var estimationLimits = EstimationLimitsParameter.ActualValue;
107      var applyLinearScaling = ApplyLinearScalingParameter.ActualValue.Value;
108
109      double r2 = SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator.Calculate(SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, tree, estimationLimits.Lower, estimationLimits.Upper, problemData, rows, applyLinearScaling);
110
111      lock (locker) {
112        if (AverageSimilarityParameter.ActualValue == null) {
113          var ctx = new ExecutionContext(null, SimilarityCalculator, context.Scope.Parent);
114          SimilarityCalculator.StrictSimilarity = StrictSimilarity;
115          SimilarityCalculator.Execute(context, CancellationToken);
116        }
117      }
118      var avgSimilarity = AverageSimilarityParameter.ActualValue.Value;
119
120      SymbolicDataAnalysisTreeInterpreterParameter.ExecutionContext = null;
121      EstimationLimitsParameter.ExecutionContext = null;
122      ApplyLinearScalingParameter.ExecutionContext = null;
123
124      return new[] { r2, avgSimilarity };
125    }
126  }
127}
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