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source: trunk/sources/HeuristicLab.GP.StructureIdentification/3.3/HL3TreeEvaluator.cs @ 2332

Last change on this file since 2332 was 2328, checked in by gkronber, 15 years ago

this is the remaining part of changeset r2327.
Applied changes in modeling plugins that are necessary for the new model analyzer (#722)

  • predictor has properties for the lower and upper limit of the predicted value
  • added views for predictors that show the limits (also added a new view for GeneticProgrammingModel that shows the size and height of the model)
  • Reintroduced TreeEvaluatorInjectors that read a PunishmentFactor and calculate the lower and upper limits for estimated values (limits are set in the tree evaluators)
  • Added operators to create Predictors. Changed modeling algorithms to use the predictors for the calculation of final model qualities and variable impacts (to be compatible with the new model analyzer the predictors use a very large PunishmentFactor)
  • replaced all private implementations of double.IsAlmost and use HL.Commons instead (see #733 r2324)
  • Implemented operator SolutionExtractor and moved BestSolutionStorer from HL.Logging to HL.Modeling (fixes #734)
File size: 7.1 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2008 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;
23using System.Diagnostics;
24using HeuristicLab.Common; // double.IsAlmost extension
25
26namespace HeuristicLab.GP.StructureIdentification {
27  /// <summary>
28  /// Evaluates FunctionTrees recursively by interpretation of the function symbols in each node.
29  /// Not thread-safe!
30  /// </summary>
31  public class HL3TreeEvaluator : TreeEvaluatorBase {
32    public HL3TreeEvaluator() : base() { } // for persistence
33    public HL3TreeEvaluator(double minValue, double maxValue) : base(minValue, maxValue) { }
34
35    protected override double EvaluateBakedCode() {
36      Instr currInstr = codeArr[PC++];
37      switch (currInstr.symbol) {
38        case EvaluatorSymbolTable.VARIABLE: {
39            int row = sampleIndex + currInstr.i_arg1;
40            if (row < 0 || row >= dataset.Rows) throw new InvalidOperationException("Out of range access to dataset row: " + row);
41            else return currInstr.d_arg0 * dataset.GetValue(row, currInstr.i_arg0);
42          }
43        case EvaluatorSymbolTable.CONSTANT: {
44            return currInstr.d_arg0;
45          }
46        case EvaluatorSymbolTable.DIFFERENTIAL: {
47            int row = sampleIndex + currInstr.i_arg1;
48            if (row < 0 || row >= dataset.Rows) throw new InvalidOperationException("Out of range access to dataset row: " + row);
49            else if (row < 1) return 0.0;
50            else {
51              double prevValue = dataset.GetValue(row - 1, currInstr.i_arg0);
52              if (double.IsNaN(prevValue) || double.IsInfinity(prevValue)) return 0.0;
53              else return currInstr.d_arg0 * (dataset.GetValue(row, currInstr.i_arg0) - prevValue);
54            }
55          }
56        case EvaluatorSymbolTable.MULTIPLICATION: {
57            double result = EvaluateBakedCode();
58            for (int i = 1; i < currInstr.arity; i++) {
59              result *= EvaluateBakedCode();
60            }
61            return result;
62          }
63        case EvaluatorSymbolTable.ADDITION: {
64            double sum = EvaluateBakedCode();
65            for (int i = 1; i < currInstr.arity; i++) {
66              sum += EvaluateBakedCode();
67            }
68            return sum;
69          }
70        case EvaluatorSymbolTable.SUBTRACTION: {
71            double result = EvaluateBakedCode();
72            for (int i = 1; i < currInstr.arity; i++) {
73              result -= EvaluateBakedCode();
74            }
75            return result;
76          }
77        case EvaluatorSymbolTable.DIVISION: {
78            double result;
79            result = EvaluateBakedCode();
80            for (int i = 1; i < currInstr.arity; i++) {
81              result /= EvaluateBakedCode();
82            }
83            if (double.IsInfinity(result)) return 0.0;
84            else return result;
85          }
86        case EvaluatorSymbolTable.AVERAGE: {
87            double sum = EvaluateBakedCode();
88            for (int i = 1; i < currInstr.arity; i++) {
89              sum += EvaluateBakedCode();
90            }
91            return sum / currInstr.arity;
92          }
93        case EvaluatorSymbolTable.COSINUS: {
94            return Math.Cos(EvaluateBakedCode());
95          }
96        case EvaluatorSymbolTable.SINUS: {
97            return Math.Sin(EvaluateBakedCode());
98          }
99        case EvaluatorSymbolTable.EXP: {
100            return Math.Exp(EvaluateBakedCode());
101          }
102        case EvaluatorSymbolTable.LOG: {
103            return Math.Log(EvaluateBakedCode());
104          }
105        case EvaluatorSymbolTable.POWER: {
106            double x = EvaluateBakedCode();
107            double p = EvaluateBakedCode();
108            return Math.Pow(x, p);
109          }
110        case EvaluatorSymbolTable.SIGNUM: {
111            double value = EvaluateBakedCode();
112            if (double.IsNaN(value)) return double.NaN;
113            else return Math.Sign(value);
114          }
115        case EvaluatorSymbolTable.SQRT: {
116            return Math.Sqrt(EvaluateBakedCode());
117          }
118        case EvaluatorSymbolTable.TANGENS: {
119            return Math.Tan(EvaluateBakedCode());
120          }
121        case EvaluatorSymbolTable.AND: {
122            double result = EvaluateBakedCode();
123            for (int i = 1; i < currInstr.arity; i++) {
124              if (result < 0.0) SkipBakedCode();
125              else {
126                result = EvaluateBakedCode();
127              }
128            }
129            return Math.Sign(result);
130          }
131        case EvaluatorSymbolTable.EQU: {
132            double x = EvaluateBakedCode();
133            double y = EvaluateBakedCode();
134            if (x.IsAlmost(y)) return 1.0; else return -1.0;
135          }
136        case EvaluatorSymbolTable.GT: {
137            double x = EvaluateBakedCode();
138            double y = EvaluateBakedCode();
139            if (x > y) return 1.0;
140            else return -1.0;
141          }
142        case EvaluatorSymbolTable.IFTE: {
143            double condition = EvaluateBakedCode();
144            double result;
145            if (condition < 0.0) {
146              result = EvaluateBakedCode(); SkipBakedCode();
147            } else {
148              SkipBakedCode(); result = EvaluateBakedCode();
149            }
150            return result;
151          }
152        case EvaluatorSymbolTable.LT: {
153            double x = EvaluateBakedCode();
154            double y = EvaluateBakedCode();
155            if (x < y) return 1.0;
156            else return -1.0;
157          }
158        case EvaluatorSymbolTable.NOT: {
159            return -EvaluateBakedCode();
160          }
161        case EvaluatorSymbolTable.OR: {
162            double result = EvaluateBakedCode();
163            for (int i = 1; i < currInstr.arity; i++) {
164              if (result >= 0.0) SkipBakedCode();
165              else {
166                result = EvaluateBakedCode();
167              }
168            }
169            return Math.Sign(result);
170          }
171        case EvaluatorSymbolTable.XOR: {
172            double x = EvaluateBakedCode();
173            double y = EvaluateBakedCode();
174            if (x > y) {
175              double tmp = x;
176              x = y;
177              y = tmp;
178            }
179            // invariant y >= x
180            if (y < 0.0 || x > 0.0) return -1.0;
181            else return 1.0;
182          }
183        default: {
184            throw new NotImplementedException();
185          }
186      }
187    }
188  }
189}
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