1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2018 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.Common;
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26 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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27 | using static HeuristicLab.Problems.DataAnalysis.Symbolic.TreeToAutoDiffTermConverter;
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28 |
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29 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic.ConstantsOptimization {
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30 | public static class Util {
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31 |
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32 | public static double[,] ExtractData(IDataset dataset, IEnumerable<DataForVariable> variables, IEnumerable<int> rows) {
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33 | var x = new double[rows.Count(), variables.Count()];
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34 |
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35 | int row = 0;
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36 | foreach (var r in rows) {
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37 | int col = 0;
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38 | foreach (var variable in variables) {
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39 | if (dataset.VariableHasType<double>(variable.variableName)) {
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40 | x[row, col] = dataset.GetDoubleValue(variable.variableName, r + variable.lag);
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41 | } else if (dataset.VariableHasType<string>(variable.variableName)) {
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42 | x[row, col] = dataset.GetStringValue(variable.variableName, r) == variable.variableValue ? 1 : 0;
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43 | } else throw new InvalidProgramException("found a variable of unknown type");
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44 | col++;
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45 | }
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46 | row++;
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47 | }
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48 | return x;
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49 | }
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50 |
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51 | public static List<DataForVariable> GenerateVariables(IDataset dataset) {
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52 | var variables = new List<DataForVariable>();
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53 | foreach (var doubleVariable in dataset.DoubleVariables) {
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54 | var data = new DataForVariable(doubleVariable, string.Empty, 0);
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55 | variables.Add(data);
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56 | }
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57 |
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58 | foreach (var stringVariable in dataset.StringVariables) {
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59 | foreach (var stringValue in dataset.GetStringValues(stringVariable).Distinct()) {
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60 | var data = new DataForVariable(stringVariable, stringValue, 0);
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61 | variables.Add(data);
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62 | }
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63 | }
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64 | return variables;
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65 | }
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66 |
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67 | public static List<DataForVariable> ExtractLaggedVariables(ISymbolicExpressionTree tree) {
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68 | var variables = new HashSet<DataForVariable>();
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69 | foreach (var laggedNode in tree.IterateNodesPrefix().OfType<ILaggedTreeNode>()) {
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70 | var laggedVariableTreeNode = laggedNode as LaggedVariableTreeNode;
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71 | if (laggedVariableTreeNode != null) {
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72 | var data = new DataForVariable(laggedVariableTreeNode.VariableName, string.Empty, laggedVariableTreeNode.Lag);
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73 | if (!variables.Contains(data)) variables.Add(data);
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74 | }
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75 | }
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76 | return variables.ToList();
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77 | }
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78 |
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79 | public static double[] ExtractConstants(ISymbolicExpressionTree tree) {
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80 | var constants = new List<double>();
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81 | foreach (var node in tree.IterateNodesPrefix().OfType<SymbolicExpressionTreeTerminalNode>()) {
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82 | ConstantTreeNode constantTreeNode = node as ConstantTreeNode;
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83 | VariableTreeNodeBase variableTreeNodeBase = node as VariableTreeNodeBase;
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84 | FactorVariableTreeNode factorVarTreeNode = node as FactorVariableTreeNode;
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85 | if (constantTreeNode != null)
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86 | constants.Add(constantTreeNode.Value);
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87 | else if (variableTreeNodeBase != null)
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88 | constants.Add(variableTreeNodeBase.Weight);
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89 | else if (factorVarTreeNode != null) {
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90 | for (int j = 0; j < factorVarTreeNode.Weights.Length; j++)
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91 | constants.Add(factorVarTreeNode.Weights[j]);
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92 | } else throw new NotSupportedException(string.Format("Terminal nodes of type {0} are not supported.", node.GetType().GetPrettyName()));
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93 | }
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94 | return constants.ToArray();
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95 | }
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96 |
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97 | public static void UpdateConstants(ISymbolicExpressionTree tree, double[] constants) {
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98 | int i = 0;
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99 | foreach (var node in tree.Root.IterateNodesPrefix().OfType<SymbolicExpressionTreeTerminalNode>()) {
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100 | ConstantTreeNode constantTreeNode = node as ConstantTreeNode;
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101 | VariableTreeNodeBase variableTreeNodeBase = node as VariableTreeNodeBase;
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102 | FactorVariableTreeNode factorVarTreeNode = node as FactorVariableTreeNode;
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103 | if (constantTreeNode != null)
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104 | constantTreeNode.Value = constants[i++];
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105 | else if (variableTreeNodeBase != null)
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106 | variableTreeNodeBase.Weight = constants[i++];
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107 | else if (factorVarTreeNode != null) {
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108 | for (int j = 0; j < factorVarTreeNode.Weights.Length; j++)
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109 | factorVarTreeNode.Weights[j] = constants[i++];
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110 | } else throw new NotSupportedException(string.Format("Terminal nodes of type {0} are not supported.", node.GetType().GetPrettyName()));
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111 | }
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112 | }
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113 | }
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114 | }
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