1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2013 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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4 | *
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5 | * This file is part of HeuristicLab.
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6 | *
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7 | * HeuristicLab is free software: you can redistribute it and/or modify
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8 | * it under the terms of the GNU General Public License as published by
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9 | * the Free Software Foundation, either version 3 of the License, or
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10 | * (at your option) any later version.
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11 | *
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12 | * HeuristicLab is distributed in the hope that it will be useful,
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13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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15 | * GNU General Public License for more details.
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16 | *
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17 | * You should have received a copy of the GNU General Public License
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18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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19 | */
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20 | #endregion
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21 |
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22 | using System;
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23 | using System.Collections.Generic;
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24 | using System.Linq;
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25 | using HeuristicLab.Analysis;
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26 | using HeuristicLab.Common;
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27 | using HeuristicLab.Core;
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28 | using HeuristicLab.Data;
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29 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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30 | using HeuristicLab.Optimization;
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31 | using HeuristicLab.Parameters;
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32 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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33 |
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34 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
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35 | /// <summary>
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36 | /// Calculates the accumulated frequencies of variable-symbols over all trees in the population.
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37 | /// </summary>
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38 | [Item("SymbolicDataAnalysisVariableFrequencyAnalyzer", "Calculates the accumulated frequencies of variable-symbols over all trees in the population.")]
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39 | [StorableClass]
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40 | public sealed class SymbolicDataAnalysisVariableFrequencyAnalyzer : SymbolicDataAnalysisAnalyzer {
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41 | private const string VariableFrequenciesParameterName = "VariableFrequencies";
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42 | private const string AggregateLaggedVariablesParameterName = "AggregateLaggedVariables";
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43 | private const string VariableImpactsParameterName = "VariableImpacts";
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44 |
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45 | #region parameter properties
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46 | public ILookupParameter<DataTable> VariableFrequenciesParameter {
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47 | get { return (ILookupParameter<DataTable>)Parameters[VariableFrequenciesParameterName]; }
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48 | }
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49 | public ILookupParameter<DoubleMatrix> VariableImpactsParameter {
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50 | get { return (ILookupParameter<DoubleMatrix>)Parameters[VariableImpactsParameterName]; }
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51 | }
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52 | public IValueLookupParameter<BoolValue> AggregateLaggedVariablesParameter {
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53 | get { return (IValueLookupParameter<BoolValue>)Parameters[AggregateLaggedVariablesParameterName]; }
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54 | }
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55 | #endregion
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56 | #region properties
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57 | public BoolValue AggregateLaggedVariables {
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58 | get { return AggregateLaggedVariablesParameter.ActualValue; }
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59 | set { AggregateLaggedVariablesParameter.Value = value; }
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60 | }
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61 | #endregion
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62 | [StorableConstructor]
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63 | private SymbolicDataAnalysisVariableFrequencyAnalyzer(bool deserializing) : base(deserializing) { }
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64 | private SymbolicDataAnalysisVariableFrequencyAnalyzer(SymbolicDataAnalysisVariableFrequencyAnalyzer original, Cloner cloner)
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65 | : base(original, cloner) {
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66 | }
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67 | public SymbolicDataAnalysisVariableFrequencyAnalyzer()
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68 | : base() {
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69 | Parameters.Add(new LookupParameter<DataTable>(VariableFrequenciesParameterName, "The relative variable reference frequencies aggregated over all trees in the population."));
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70 | Parameters.Add(new LookupParameter<DoubleMatrix>(VariableImpactsParameterName, "The relative variable relevance calculated as the average relative variable frequency over the whole run."));
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71 | 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)));
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72 | }
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73 |
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74 | public override IDeepCloneable Clone(Cloner cloner) {
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75 | return new SymbolicDataAnalysisVariableFrequencyAnalyzer(this, cloner);
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76 | }
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77 |
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78 | public override IOperation Apply() {
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79 | ItemArray<ISymbolicExpressionTree> expressions = SymbolicExpressionTreeParameter.ActualValue;
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80 | ResultCollection results = ResultCollection;
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81 | DataTable datatable;
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82 | if (VariableFrequenciesParameter.ActualValue == null) {
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83 | datatable = new DataTable("Variable frequencies", "Relative frequency of variable references aggregated over the whole population.");
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84 | datatable.VisualProperties.XAxisTitle = "Generation";
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85 | datatable.VisualProperties.YAxisTitle = "Relative Variable Frequency";
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86 | VariableFrequenciesParameter.ActualValue = datatable;
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87 | results.Add(new Result("Variable frequencies", "Relative frequency of variable references aggregated over the whole population.", datatable));
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88 | results.Add(new Result("Variable impacts", "The relative variable relevance calculated as the average relative variable frequency over the whole run.", new DoubleMatrix()));
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89 | }
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90 |
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91 | datatable = VariableFrequenciesParameter.ActualValue;
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92 | // all rows must have the same number of values so we can just take the first
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93 | int numberOfValues = datatable.Rows.Select(r => r.Values.Count).DefaultIfEmpty().First();
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94 |
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95 | foreach (var pair in SymbolicDataAnalysisVariableFrequencyAnalyzer.CalculateVariableFrequencies(expressions, AggregateLaggedVariables.Value)) {
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96 | if (!datatable.Rows.ContainsKey(pair.Key)) {
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97 | // initialize a new row for the variable and pad with zeros
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98 | DataRow row = new DataRow(pair.Key, "", Enumerable.Repeat(0.0, numberOfValues));
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99 | row.VisualProperties.StartIndexZero = true;
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100 | datatable.Rows.Add(row);
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101 | }
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102 | datatable.Rows[pair.Key].Values.Add(Math.Round(pair.Value, 3));
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103 | }
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104 |
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105 | // add a zero for each data row that was not modified in the previous loop
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106 | foreach (var row in datatable.Rows.Where(r => r.Values.Count != numberOfValues + 1))
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107 | row.Values.Add(0.0);
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108 |
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109 | // update variable impacts matrix
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110 | var orderedImpacts = (from row in datatable.Rows
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111 | select new { Name = row.Name, Impact = Math.Round(datatable.Rows[row.Name].Values.Average(), 3) })
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112 | .OrderByDescending(p => p.Impact)
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113 | .ToList();
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114 | var impacts = new DoubleMatrix();
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115 | var matrix = impacts as IStringConvertibleMatrix;
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116 | matrix.Rows = orderedImpacts.Count;
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117 | matrix.RowNames = orderedImpacts.Select(x => x.Name);
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118 | matrix.Columns = 1;
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119 | matrix.ColumnNames = new string[] { "Relative variable relevance" };
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120 | int i = 0;
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121 | foreach (var p in orderedImpacts) {
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122 | matrix.SetValue(p.Impact.ToString(), i++, 0);
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123 | }
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124 |
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125 | VariableImpactsParameter.ActualValue = impacts;
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126 | results["Variable impacts"].Value = impacts;
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127 | return base.Apply();
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128 | }
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129 |
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130 | public static IEnumerable<KeyValuePair<string, double>> CalculateVariableFrequencies(IEnumerable<ISymbolicExpressionTree> trees, bool aggregateLaggedVariables = true) {
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131 |
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132 | var variableFrequencies = trees
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133 | .SelectMany(t => GetVariableReferences(t, aggregateLaggedVariables))
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134 | .GroupBy(pair => pair.Key, pair => pair.Value)
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135 | .ToDictionary(g => g.Key, g => (double)g.Sum());
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136 |
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137 | double totalNumberOfSymbols = variableFrequencies.Values.Sum();
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138 |
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139 | foreach (var pair in variableFrequencies.OrderBy(p => p.Key, new NaturalStringComparer()))
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140 | yield return new KeyValuePair<string, double>(pair.Key, pair.Value / totalNumberOfSymbols);
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141 | }
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142 |
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143 | private static IEnumerable<KeyValuePair<string, int>> GetVariableReferences(ISymbolicExpressionTree tree, bool aggregateLaggedVariables = true) {
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144 | Dictionary<string, int> references = new Dictionary<string, int>();
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145 | if (aggregateLaggedVariables) {
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146 | tree.Root.ForEachNodePrefix(node => {
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147 | if (node.Symbol is Variable) {
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148 | var varNode = node as VariableTreeNode;
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149 | IncReferenceCount(references, varNode.VariableName);
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150 | } else if (node.Symbol is VariableCondition) {
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151 | var varCondNode = node as VariableConditionTreeNode;
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152 | IncReferenceCount(references, varCondNode.VariableName);
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153 | }
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154 | });
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155 | } else {
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156 | GetVariableReferences(references, tree.Root, 0);
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157 | }
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158 | return references;
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159 | }
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160 |
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161 | private static void GetVariableReferences(Dictionary<string, int> references, ISymbolicExpressionTreeNode node, int currentLag) {
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162 | if (node.Symbol is LaggedVariable) {
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163 | var laggedVarNode = node as LaggedVariableTreeNode;
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164 | IncReferenceCount(references, laggedVarNode.VariableName, currentLag + laggedVarNode.Lag);
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165 | } else if (node.Symbol is Variable) {
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166 | var varNode = node as VariableTreeNode;
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167 | IncReferenceCount(references, varNode.VariableName, currentLag);
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168 | } else if (node.Symbol is VariableCondition) {
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169 | var varCondNode = node as VariableConditionTreeNode;
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170 | IncReferenceCount(references, varCondNode.VariableName, currentLag);
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171 | GetVariableReferences(references, node.GetSubtree(0), currentLag);
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172 | GetVariableReferences(references, node.GetSubtree(1), currentLag);
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173 | } else if (node.Symbol is Integral) {
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174 | var laggedNode = node as LaggedTreeNode;
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175 | for (int l = laggedNode.Lag; l <= 0; l++) {
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176 | GetVariableReferences(references, node.GetSubtree(0), currentLag + l);
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177 | }
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178 | } else if (node.Symbol is Derivative) {
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179 | for (int l = -4; l <= 0; l++) {
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180 | GetVariableReferences(references, node.GetSubtree(0), currentLag + l);
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181 | }
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182 | } else if (node.Symbol is TimeLag) {
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183 | var laggedNode = node as LaggedTreeNode;
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184 | GetVariableReferences(references, node.GetSubtree(0), currentLag + laggedNode.Lag);
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185 | } else {
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186 | foreach (var subtree in node.Subtrees) {
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187 | GetVariableReferences(references, subtree, currentLag);
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188 | }
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189 | }
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190 | }
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191 |
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192 | private static void IncReferenceCount(Dictionary<string, int> references, string variableName, int timeLag = 0) {
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193 | string referenceId = variableName +
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194 | (timeLag == 0 ? "" : timeLag < 0 ? "(t" + timeLag + ")" : "(t+" + timeLag + ")");
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195 | if (references.ContainsKey(referenceId)) {
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196 | references[referenceId]++;
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197 | } else {
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198 | references[referenceId] = 1;
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199 | }
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200 | }
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201 | }
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202 | }
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