1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2008 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 |
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24 | namespace HeuristicLab.GP.StructureIdentification {
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25 | /// <summary>
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26 | /// Evaluates FunctionTrees recursively by interpretation of the function symbols in each node with HL2 semantics.
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27 | /// Not thread-safe!
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28 | /// </summary>
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29 | public class HL2TreeEvaluator : TreeEvaluatorBase {
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30 | public HL2TreeEvaluator() : base() { } // for persistence
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31 | public HL2TreeEvaluator(double minValue, double maxValue) : base(minValue, maxValue) { }
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32 |
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33 | [Obsolete]
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34 | protected override double EvaluateBakedCode() {
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35 | Instr currInstr = codeArr[PC++];
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36 | switch (currInstr.symbol) {
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37 | case EvaluatorSymbolTable.VARIABLE: {
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38 | int row = sampleIndex + currInstr.i_arg1;
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39 | if (row < 0 || row >= dataset.Rows) return double.NaN;
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40 | else return currInstr.d_arg0 * dataset.GetValue(row, currInstr.i_arg0);
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41 | }
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42 | case EvaluatorSymbolTable.CONSTANT: {
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43 | return currInstr.d_arg0;
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44 | }
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45 | case EvaluatorSymbolTable.DIFFERENTIAL: {
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46 | int row = sampleIndex + currInstr.i_arg1;
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47 | if (row < 1 || row >= dataset.Rows) return double.NaN;
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48 | else {
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49 | double prevValue = dataset.GetValue(row - 1, currInstr.i_arg0);
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50 | return currInstr.d_arg0 * (dataset.GetValue(row, currInstr.i_arg0) - prevValue);
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51 | }
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52 | }
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53 | case EvaluatorSymbolTable.MULTIPLICATION: {
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54 | double result = EvaluateBakedCode();
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55 | for (int i = 1; i < currInstr.arity; i++) {
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56 | result *= EvaluateBakedCode();
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57 | }
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58 | return result;
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59 | }
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60 | case EvaluatorSymbolTable.ADDITION: {
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61 | double sum = EvaluateBakedCode();
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62 | for (int i = 1; i < currInstr.arity; i++) {
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63 | sum += EvaluateBakedCode();
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64 | }
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65 | return sum;
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66 | }
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67 | case EvaluatorSymbolTable.SUBTRACTION: {
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68 | return EvaluateBakedCode() - EvaluateBakedCode();
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69 | }
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70 | case EvaluatorSymbolTable.DIVISION: {
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71 | double arg0 = EvaluateBakedCode();
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72 | double arg1 = EvaluateBakedCode();
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73 | if (double.IsNaN(arg0) || double.IsNaN(arg1)) return double.NaN;
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74 | if (Math.Abs(arg1) < (10e-20)) return 0.0; else return (arg0 / arg1);
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75 | }
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76 | case EvaluatorSymbolTable.COSINUS: {
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77 | return Math.Cos(EvaluateBakedCode());
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78 | }
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79 | case EvaluatorSymbolTable.SINUS: {
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80 | return Math.Sin(EvaluateBakedCode());
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81 | }
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82 | case EvaluatorSymbolTable.EXP: {
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83 | return Math.Exp(EvaluateBakedCode());
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84 | }
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85 | case EvaluatorSymbolTable.LOG: {
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86 | return Math.Log(EvaluateBakedCode());
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87 | }
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88 | case EvaluatorSymbolTable.POWER: {
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89 | double x = EvaluateBakedCode();
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90 | double p = EvaluateBakedCode();
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91 | return Math.Pow(x, p);
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92 | }
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93 | case EvaluatorSymbolTable.SIGNUM: {
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94 | double value = EvaluateBakedCode();
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95 | if (double.IsNaN(value)) return double.NaN;
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96 | if (value < 0.0) return -1.0;
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97 | if (value > 0.0) return 1.0;
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98 | return 0.0;
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99 | }
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100 | case EvaluatorSymbolTable.SQRT: {
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101 | return Math.Sqrt(EvaluateBakedCode());
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102 | }
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103 | case EvaluatorSymbolTable.TANGENS: {
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104 | return Math.Tan(EvaluateBakedCode());
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105 | }
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106 | case EvaluatorSymbolTable.AND: { // only defined for inputs 1 and 0
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107 | double result = EvaluateBakedCode();
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108 | bool hasNaNBranch = false;
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109 | for (int i = 1; i < currInstr.arity; i++) {
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110 | if (result < 0.5 || double.IsNaN(result)) hasNaNBranch |= double.IsNaN(EvaluateBakedCode());
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111 | else {
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112 | result = EvaluateBakedCode();
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113 | }
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114 | }
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115 | if (hasNaNBranch || double.IsNaN(result)) return double.NaN;
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116 | if (result < 0.5) return 0.0;
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117 | return 1.0;
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118 | }
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119 | case EvaluatorSymbolTable.EQU: {
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120 | double x = EvaluateBakedCode();
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121 | double y = EvaluateBakedCode();
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122 | if (double.IsNaN(x) || double.IsNaN(y)) return double.NaN;
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123 | // direct comparison of double values is most likely incorrect but
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124 | // that's the way how it is implemented in the standard HL2 function library
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125 | if (x == y) return 1.0; else return 0.0;
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126 | }
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127 | case EvaluatorSymbolTable.GT: {
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128 | double x = EvaluateBakedCode();
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129 | double y = EvaluateBakedCode();
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130 | if (double.IsNaN(x) || double.IsNaN(y)) return double.NaN;
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131 | if (x > y) return 1.0;
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132 | return 0.0;
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133 | }
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134 | case EvaluatorSymbolTable.IFTE: { // only defined for condition 0 or 1
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135 | double condition = EvaluateBakedCode();
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136 | double result;
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137 | bool hasNaNBranch = false;
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138 | if (double.IsNaN(condition)) return double.NaN;
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139 | if (condition > 0.5) {
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140 | result = EvaluateBakedCode(); hasNaNBranch = double.IsNaN(EvaluateBakedCode());
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141 | } else {
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142 | hasNaNBranch = double.IsNaN(EvaluateBakedCode()); result = EvaluateBakedCode();
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143 | }
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144 | if (hasNaNBranch) return double.NaN;
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145 | return result;
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146 | }
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147 | case EvaluatorSymbolTable.LT: {
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148 | double x = EvaluateBakedCode();
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149 | double y = EvaluateBakedCode();
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150 | if (double.IsNaN(x) || double.IsNaN(y)) return double.NaN;
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151 | if (x < y) return 1.0;
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152 | return 0.0;
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153 | }
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154 | case EvaluatorSymbolTable.NOT: { // only defined for inputs 0 or 1
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155 | double result = EvaluateBakedCode();
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156 | if (double.IsNaN(result)) return double.NaN;
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157 | if (result < 0.5) return 1.0;
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158 | return 0.0;
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159 | }
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160 | case EvaluatorSymbolTable.OR: { // only defined for inputs 0 or 1
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161 | double result = EvaluateBakedCode();
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162 | bool hasNaNBranch = false;
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163 | for (int i = 1; i < currInstr.arity; i++) {
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164 | if (double.IsNaN(result) || result > 0.5) hasNaNBranch |= double.IsNaN(EvaluateBakedCode());
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165 | else
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166 | result = EvaluateBakedCode();
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167 | }
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168 | if (hasNaNBranch || double.IsNaN(result)) return double.NaN;
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169 | if (result > 0.5) return 1.0;
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170 | return 0.0;
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171 | }
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172 | default: {
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173 | throw new NotImplementedException();
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174 | }
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175 | }
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176 | }
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177 | }
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178 | }
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