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source: trunk/sources/HeuristicLab.GP.Tests/SymbolicExpressionImporter.cs @ 2447

Last change on this file since 2447 was 2447, checked in by gkronber, 14 years ago

Added until test project for HeuristicLab.GP plugins. #791 (Tests for GP operators and structure identification evaluators)

File size: 5.0 KB
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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.Collections.Generic;
24using System.Linq;
25using System.Text;
26using HeuristicLab.GP.Interfaces;
27using System.IO;
28using System.Diagnostics;
29using HeuristicLab.GP.StructureIdentification;
30
31namespace HeuristicLab.GP.Test {
32  class SymbolicExpressionImporter {
33    private const string DIFFSTART = "dif";
34    private const string VARSTART = "var";
35    private Dictionary<string, IFunction> knownFunctions = new Dictionary<string, IFunction>()
36      {
37        {"+", new Addition()},
38        {"and", new And()},
39        {"mean", new Average()},
40        {"cos", new Cosinus()},
41        {"/", new Division()},
42        {"equ", new Equal()},
43        {"exp", new Exponential()},
44        {">", new GreaterThan()},
45        {"if", new IfThenElse()},
46        {"<", new LessThan()},
47        {"log", new Logarithm()},
48        {"*", new Multiplication()},
49        {"not", new Not()},
50        {"or", new Or()},
51        {"expt", new Power()},
52        {"sign", new Signum()},
53        {"sin",new Sinus()},
54        {"sqrt", new Sqrt()},
55        {"-", new Subtraction()},
56        {"tan", new Tangens()},
57        {"xor", new Xor()}
58      };
59    Constant constant = new Constant();
60    HeuristicLab.GP.StructureIdentification.Variable variable = new HeuristicLab.GP.StructureIdentification.Variable();
61    Differential differential = new Differential();
62
63    public SymbolicExpressionImporter() {
64    }
65
66    internal IFunctionTree Import(string str) {
67      str = str.Replace("(", " ( ").Replace(")", " ) ");
68      return ParseSexp(new Queue<Token>(GetTokenStream(str)));
69    }
70
71    private IEnumerable<Token> GetTokenStream(string str) {
72      return
73             from strToken in str.Split(new string[] { " " }, StringSplitOptions.RemoveEmptyEntries).AsEnumerable()
74             let t = Token.Parse(strToken)
75             where t != null
76             select t;
77    }
78
79    private HeuristicLab.GP.Interfaces.IFunctionTree ParseSexp(Queue<Token> tokens) {
80      if (tokens.Peek().Symbol == TokenSymbol.LPAR) {
81        IFunctionTree tree;
82        Expect(Token.LPAR, tokens);
83        if (tokens.Peek().StringValue.StartsWith(VARSTART)) {
84          tree = ParseVariable(tokens);
85        } else if (tokens.Peek().StringValue.StartsWith(DIFFSTART)) {
86          tree = ParseDifferential(tokens);
87        } else {
88          Token curToken = tokens.Dequeue();
89          tree = CreateTree(curToken);
90          while (!tokens.Peek().Equals(Token.RPAR)) {
91            tree.AddSubTree(ParseSexp(tokens));
92          }
93        }
94        Expect(Token.RPAR, tokens);
95        return tree;
96      } else if (tokens.Peek().Symbol == TokenSymbol.NUMBER) {
97        ConstantFunctionTree t = (ConstantFunctionTree)constant.GetTreeNode();
98        t.Value = tokens.Dequeue().DoubleValue;
99        return t;
100      } else throw new FormatException("Expected function or constant symbol");
101    }
102
103    private IFunctionTree ParseDifferential(Queue<Token> tokens) {
104      Token diffTok = tokens.Dequeue();
105      Debug.Assert(diffTok.StringValue == "differential");
106      VariableFunctionTree t = (VariableFunctionTree)differential.GetTreeNode();
107      t.Weight = tokens.Dequeue().DoubleValue;
108      t.VariableName = tokens.Dequeue().StringValue;
109      t.SampleOffset = (int)tokens.Dequeue().DoubleValue;
110      return t;
111    }
112
113    private IFunctionTree ParseVariable(Queue<Token> tokens) {
114      Token varTok = tokens.Dequeue();
115      Debug.Assert(varTok.StringValue == "variable");
116      VariableFunctionTree t = (VariableFunctionTree)variable.GetTreeNode();
117      t.Weight = tokens.Dequeue().DoubleValue;
118      t.VariableName = tokens.Dequeue().StringValue;
119      t.SampleOffset = (int)tokens.Dequeue().DoubleValue;
120      return t;
121    }
122
123    private IFunctionTree CreateTree(Token token) {
124      if (token.Symbol != TokenSymbol.SYMB) throw new FormatException("Expected function symbol, but got: " + token.StringValue);
125      return knownFunctions[token.StringValue].GetTreeNode();
126    }
127
128    private void Expect(Token token, Queue<Token> tokens) {
129      Token cur = tokens.Dequeue();
130      if (!token.Equals(cur)) throw new FormatException("Expected: " + token.StringValue + ", but got found: " + cur.StringValue);
131    }
132  }
133}
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