1 | #region License Information
|
---|
2 |
|
---|
3 | /* HeuristicLab
|
---|
4 | * Copyright (C) 2002-2014 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
|
---|
5 | *
|
---|
6 | * This file is part of HeuristicLab.
|
---|
7 | *
|
---|
8 | * HeuristicLab is free software: you can redistribute it and/or modify
|
---|
9 | * it under the terms of the GNU General Public License as published by
|
---|
10 | * the Free Software Foundation, either version 3 of the License, or
|
---|
11 | * (at your option) any later version.
|
---|
12 | *
|
---|
13 | * HeuristicLab is distributed in the hope that it will be useful,
|
---|
14 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
|
---|
15 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
---|
16 | * GNU General Public License for more details.
|
---|
17 | *
|
---|
18 | * You should have received a copy of the GNU General Public License
|
---|
19 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
|
---|
20 | */
|
---|
21 |
|
---|
22 | #endregion
|
---|
23 |
|
---|
24 | using System.Linq;
|
---|
25 | using HeuristicLab.Common;
|
---|
26 | using HeuristicLab.Core;
|
---|
27 | using HeuristicLab.Data;
|
---|
28 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
|
---|
29 | using HeuristicLab.Operators;
|
---|
30 | using HeuristicLab.Parameters;
|
---|
31 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
|
---|
32 |
|
---|
33 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
|
---|
34 | [StorableClass]
|
---|
35 | [Item("SymbolicExpressionTreePruningOperator", "An operator that replaces introns with constant values in a symbolic expression tree.")]
|
---|
36 | public class SymbolicDataAnalysisExpressionPruningOperator : SingleSuccessorOperator {
|
---|
37 | private const string NumberOfPrunedSubtreesParameterName = "PrunedSubtrees";
|
---|
38 | private const string NumberOfPrunedTreesParameterName = "PrunedTrees";
|
---|
39 | #region parameter properties
|
---|
40 | public ILookupParameter<DoubleValue> NumberOfPrunedSubtreesParameter {
|
---|
41 | get { return (ILookupParameter<DoubleValue>)Parameters[NumberOfPrunedSubtreesParameterName]; }
|
---|
42 | }
|
---|
43 | public ILookupParameter<DoubleValue> NumberOfPrunedTreesParameter {
|
---|
44 | get { return (ILookupParameter<DoubleValue>)Parameters[NumberOfPrunedTreesParameterName]; }
|
---|
45 | }
|
---|
46 | #endregion
|
---|
47 | #region properties
|
---|
48 | private DoubleValue PrunedSubtrees { get { return NumberOfPrunedSubtreesParameter.ActualValue; } }
|
---|
49 | private DoubleValue PrunedTrees { get { return NumberOfPrunedTreesParameter.ActualValue; } }
|
---|
50 | #endregion
|
---|
51 | public override IDeepCloneable Clone(Cloner cloner) {
|
---|
52 | return new SymbolicDataAnalysisExpressionPruningOperator(this, cloner);
|
---|
53 | }
|
---|
54 | private SymbolicDataAnalysisExpressionPruningOperator(SymbolicDataAnalysisExpressionPruningOperator original, Cloner cloner)
|
---|
55 | : base(original, cloner) {
|
---|
56 | }
|
---|
57 |
|
---|
58 | public SymbolicDataAnalysisExpressionPruningOperator() {
|
---|
59 | Parameters.Add(new LookupParameter<DoubleValue>(NumberOfPrunedSubtreesParameterName));
|
---|
60 | Parameters.Add(new LookupParameter<DoubleValue>(NumberOfPrunedTreesParameterName));
|
---|
61 | }
|
---|
62 |
|
---|
63 | public ISymbolicDataAnalysisModel Model { get; set; }
|
---|
64 | public IDataAnalysisProblemData ProblemData { get; set; }
|
---|
65 | public ISymbolicDataAnalysisSolutionImpactValuesCalculator ImpactsCalculator { get; set; }
|
---|
66 |
|
---|
67 | public IntRange FitnessCalculationPartition { get; set; }
|
---|
68 | public IRandom Random { get; set; }
|
---|
69 |
|
---|
70 | public bool PruneOnlyZeroImpactNodes { get; set; }
|
---|
71 | public double NodeImpactThreshold { get; set; }
|
---|
72 |
|
---|
73 | public override IOperation Apply() {
|
---|
74 | int prunedSubtrees = 0;
|
---|
75 |
|
---|
76 | var nodes = Model.SymbolicExpressionTree.Root.GetSubtree(0).GetSubtree(0).IterateNodesPrefix().ToList();
|
---|
77 | var rows = Enumerable.Range(FitnessCalculationPartition.Start, FitnessCalculationPartition.Size).ToList();
|
---|
78 |
|
---|
79 | for (int j = 0; j < nodes.Count; ++j) {
|
---|
80 | var node = nodes[j];
|
---|
81 | if (node is ConstantTreeNode) continue;
|
---|
82 |
|
---|
83 | var impact = ImpactsCalculator.CalculateImpactValue(Model, node, ProblemData, rows);
|
---|
84 |
|
---|
85 | if (PruneOnlyZeroImpactNodes) {
|
---|
86 | if (!impact.IsAlmost(0.0)) continue;
|
---|
87 | } else {
|
---|
88 | if (NodeImpactThreshold < impact) continue;
|
---|
89 | }
|
---|
90 |
|
---|
91 | var replacementValue = ImpactsCalculator.CalculateReplacementValue(Model, node, ProblemData, rows);
|
---|
92 | var constantNode = new ConstantTreeNode(new Constant()) { Value = replacementValue };
|
---|
93 | ReplaceWithConstant(node, constantNode);
|
---|
94 | j += node.GetLength() - 1; // skip subtrees under the node that was folded
|
---|
95 |
|
---|
96 | prunedSubtrees++;
|
---|
97 | }
|
---|
98 |
|
---|
99 | if (prunedSubtrees > 0) {
|
---|
100 | lock (PrunedSubtrees) { PrunedSubtrees.Value += prunedSubtrees; }
|
---|
101 | lock (PrunedTrees) { PrunedTrees.Value += 1; }
|
---|
102 | }
|
---|
103 | return base.Apply();
|
---|
104 | }
|
---|
105 | private static void ReplaceWithConstant(ISymbolicExpressionTreeNode original, ISymbolicExpressionTreeNode replacement) {
|
---|
106 | var parent = original.Parent;
|
---|
107 | var i = parent.IndexOfSubtree(original);
|
---|
108 | parent.RemoveSubtree(i);
|
---|
109 | parent.InsertSubtree(i, replacement);
|
---|
110 | }
|
---|
111 | }
|
---|
112 | }
|
---|