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source: branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Analyzers/SymbolicDataAnalysisVariableFrequencyAnalyzer.cs @ 5651

Last change on this file since 5651 was 5556, checked in by gkronber, 14 years ago

#1418 renamed analyzers

File size: 8.6 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2011 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.Collections.Generic;
23using System.Linq;
24using HeuristicLab.Common;
25using HeuristicLab.Core;
26using HeuristicLab.Data;
27using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
28using HeuristicLab.Operators;
29using HeuristicLab.Optimization;
30using HeuristicLab.Parameters;
31using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
32using HeuristicLab.Analysis;
33
34namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
35  /// <summary>
36  /// Calculates the accumulated frequencies of variable-symbols over all trees in the population.
37  /// </summary>
38  [Item("SymbolicDataAnalysisVariableFrequencyAnalyzer", "Calculates the accumulated frequencies of variable-symbols over all trees in the population.")]
39  [StorableClass]
40  public sealed class SymbolicDataAnalysisVariableFrequencyAnalyzer : SymbolicDataAnalysisAnalyzer {
41    private const string VariableFrequenciesParameterName = "VariableFrequencies";
42    private const string AggregateLaggedVariablesParameterName = "AggregateLaggedVariables";
43
44    #region parameter properties
45    public ILookupParameter<DataTable> VariableFrequenciesParameter {
46      get { return (ILookupParameter<DataTable>)Parameters[VariableFrequenciesParameterName]; }
47    }
48    public IValueLookupParameter<BoolValue> AggregateLaggedVariablesParameter {
49      get { return (IValueLookupParameter<BoolValue>)Parameters[AggregateLaggedVariablesParameterName]; }
50    }
51    #endregion
52    #region properties
53    public DataTable VariableFrequencies {
54      get { return VariableFrequenciesParameter.ActualValue; }
55      set { VariableFrequenciesParameter.ActualValue = value; }
56    }
57    public BoolValue AggregateLaggedVariables {
58      get { return AggregateLaggedVariablesParameter.ActualValue; }
59    }
60    #endregion
61    [StorableConstructor]
62    private SymbolicDataAnalysisVariableFrequencyAnalyzer(bool deserializing) : base(deserializing) { }
63    private SymbolicDataAnalysisVariableFrequencyAnalyzer(SymbolicDataAnalysisVariableFrequencyAnalyzer original, Cloner cloner)
64      : base(original, cloner) {
65    }
66    public SymbolicDataAnalysisVariableFrequencyAnalyzer()
67      : base() {
68      Parameters.Add(new LookupParameter<DataTable>(VariableFrequenciesParameterName, "The relative variable reference frequencies aggregated over all trees in the population."));
69      Parameters.Add(new ValueLookupParameter<BoolValue>(AggregateLaggedVariablesParameterName, "Switch that determines whether all references to a variable should be aggregated regardless of time-offsets. Turn off to analyze all variable references with different time offsets separately.", new BoolValue(true)));
70    }
71    public override IDeepCloneable Clone(Cloner cloner) {
72      return new SymbolicDataAnalysisVariableFrequencyAnalyzer(this, cloner);
73    }
74
75
76    public override IOperation Apply() {
77      ItemArray<ISymbolicExpressionTree> expressions = SymbolicExpressionTreeParameter.ActualValue;
78      ResultCollection results = ResultCollection;
79
80      if (VariableFrequencies == null) {
81        VariableFrequencies = new DataTable("Variable frequencies", "Relative frequency of variable references aggregated over the whole population.");
82        VariableFrequencies.VisualProperties.XAxisTitle = "Generation";
83        VariableFrequencies.VisualProperties.YAxisTitle = "Relative Variable Frequency";
84        results.Add(new Result("Variable frequencies", VariableFrequencies));
85      }
86
87      // all rows must have the same number of values so we can just take the first
88      int numberOfValues = VariableFrequencies.Rows.Select(r => r.Values.Count).DefaultIfEmpty().First();
89
90      foreach (var pair in SymbolicDataAnalysisVariableFrequencyAnalyzer.CalculateVariableFrequencies(expressions, AggregateLaggedVariables.Value)) {
91        if (!VariableFrequencies.Rows.ContainsKey(pair.Key)) {
92          // initialize a new row for the variable and pad with zeros
93          DataRow row = new DataRow(pair.Key, "", Enumerable.Repeat(0.0, numberOfValues));
94          row.VisualProperties.StartIndexZero = true;
95          VariableFrequencies.Rows.Add(row);
96        }
97        VariableFrequencies.Rows[pair.Key].Values.Add(pair.Value);
98      }
99
100      // add a zero for each data row that was not modified in the previous loop
101      foreach (var row in VariableFrequencies.Rows.Where(r => r.Values.Count != numberOfValues + 1))
102        row.Values.Add(0.0);
103
104      return base.Apply();
105    }
106
107    public static IEnumerable<KeyValuePair<string, double>> CalculateVariableFrequencies(IEnumerable<ISymbolicExpressionTree> trees, bool aggregateLaggedVariables = true) {
108      Dictionary<string, double> variableFrequencies = new Dictionary<string, double>();
109      int totalNumberOfSymbols = 0;
110
111      foreach (var tree in trees) {
112        var variableReferences = GetVariableReferences(tree, aggregateLaggedVariables);
113        foreach (var pair in variableReferences) {
114          totalNumberOfSymbols += pair.Value;
115        }
116      }
117
118      foreach (var pair in variableFrequencies)
119        yield return new KeyValuePair<string, double>(pair.Key, pair.Value / totalNumberOfSymbols);
120    }
121
122    private static IEnumerable<KeyValuePair<string, int>> GetVariableReferences(ISymbolicExpressionTree tree, bool aggregateLaggedVariables = true) {
123      Dictionary<string, int> references = new Dictionary<string, int>();
124      if (aggregateLaggedVariables) {
125        tree.Root.ForEachNodePrefix(node => {
126          if (node.Symbol is Variable) {
127            var varNode = node as VariableTreeNode;
128            IncReferenceCount(references, varNode.VariableName);
129          } else if (node.Symbol is VariableCondition) {
130            var varCondNode = node as VariableConditionTreeNode;
131            IncReferenceCount(references, varCondNode.VariableName);
132          }
133        });
134      } else {
135        GetVariableReferences(references, tree.Root, 0);
136      }
137      return references;
138    }
139
140    private static void GetVariableReferences(Dictionary<string, int> references, ISymbolicExpressionTreeNode node, int currentLag) {
141      if (node.Symbol is LaggedVariable) {
142        var laggedVarNode = node as LaggedVariableTreeNode;
143        IncReferenceCount(references, laggedVarNode.VariableName, currentLag + laggedVarNode.Lag);
144      } else if (node.Symbol is Variable) {
145        var varNode = node as VariableTreeNode;
146        IncReferenceCount(references, varNode.VariableName, currentLag);
147      } else if (node.Symbol is VariableCondition) {
148        var varCondNode = node as VariableConditionTreeNode;
149        IncReferenceCount(references, varCondNode.VariableName, currentLag);
150        GetVariableReferences(references, node.GetSubTree(0), currentLag);
151        GetVariableReferences(references, node.GetSubTree(1), currentLag);
152      } else if (node.Symbol is Integral) {
153        var laggedNode = node as LaggedTreeNode;
154        for (int l = laggedNode.Lag; l <= 0; l++) {
155          GetVariableReferences(references, node.GetSubTree(0), currentLag + l);
156        }
157      } else if (node.Symbol is Derivative) {
158        var laggedNode = node as LaggedTreeNode;
159        for (int l = laggedNode.Lag; l <= 0; l++) {
160          GetVariableReferences(references, node.GetSubTree(0), currentLag + l);
161        }
162      } else if (node.Symbol is TimeLag) {
163        var laggedNode = node as LaggedTreeNode;
164        GetVariableReferences(references, node.GetSubTree(0), currentLag + laggedNode.Lag);
165      }
166    }
167
168    private static void IncReferenceCount(Dictionary<string, int> references, string variableName, int timeLag = 0) {
169      string referenceId = variableName +
170        (timeLag == 0 ? "" : timeLag < 0 ? "(t" + timeLag + ")" : "(t+" + timeLag + ")");
171      if (references.ContainsKey(referenceId)) {
172        references[referenceId]++;
173      } else {
174        references[referenceId] = 1;
175      }
176    }
177  }
178}
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