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source: trunk/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Grammars/LinearScalingGrammar.cs @ 18220

Last change on this file since 18220 was 18132, checked in by gkronber, 3 years ago

#3140: merged r18091:18131 from branch to trunk

File size: 4.8 KB
RevLine 
[17902]1#region License Information
2
3/* HeuristicLab
4 * Copyright (C) Heuristic and Evolutionary Algorithms Laboratory (HEAL)
5 *
6 * This file is part of HeuristicLab.
7 *
8 * HeuristicLab is free software: you can redistribute it and/or modify
9 * it under the terms of the GNU General Public License as published by
10 * the Free Software Foundation, either version 3 of the License, or
11 * (at your option) any later version.
12 *
13 * HeuristicLab is distributed in the hope that it will be useful,
14 * but WITHOUT ANY WARRANTY; without even the implied warranty of
15 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
16 * GNU General Public License for more details.
17 *
18 * You should have received a copy of the GNU General Public License
19 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
20 */
21
22#endregion
23using System.Collections.Generic;
[17650]24using System.Linq;
[17628]25using HEAL.Attic;
26using HeuristicLab.Common;
27using HeuristicLab.Core;
28using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
29
30namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
31  [StorableType("5A2300A0-D0FC-4F2D-B910-F86384FE9052")]
[17958]32  [Item("LinearScalingGrammar", "Represents a grammar which includes linear scaling parts implicitly.")]
33  public class LinearScalingGrammar : DataAnalysisGrammar, ISymbolicDataAnalysisGrammar {
34    public LinearScalingGrammar() : base(ItemAttribute.GetName(typeof(LinearScalingGrammar)),
35      ItemAttribute.GetDescription(typeof(LinearScalingGrammar))) {
[17628]36      Initialize();
37    }
38
39    [StorableConstructor]
[17958]40    public LinearScalingGrammar(StorableConstructorFlag _) : base(_) { }
[17628]41
[17958]42    protected LinearScalingGrammar(LinearScalingGrammar original, Cloner cloner) : base(original, cloner) { }
43    public LinearScalingGrammar(string name, string description) : base(name, description) { }
[17628]44
45    public override IDeepCloneable Clone(Cloner cloner) {
[17958]46      return new LinearScalingGrammar(this, cloner);
[17628]47    }
48
49    private void Initialize() {
50      #region Symbols
51
[17880]52      var add = new Addition();
53      var sub = new Subtraction();
54      var mul = new Multiplication();
55      var div = new Division();
56      var sin = new Sine();
57      var cos = new Cosine();
58      var tan = new Tangent();
[17902]59      var tanh = new HyperbolicTangent();
[17880]60      var log = new Logarithm();
[17902]61      var exp = new Exponential();
[17880]62      var square = new Square();
63      var sqrt = new SquareRoot();
[17902]64      var cube = new Cube();
65      var cbrt = new CubeRoot();
66      var abs = new Absolute();
67      var aq = new AnalyticQuotient();
[18132]68      var number = new Number();
69      number.MinValue = -20;
70      number.MaxValue = 20;
[17628]71      var constant = new Constant();
[18132]72      constant.Enabled = false;
[17628]73      var variableSymbol = new Variable();
74
75      #endregion
76
77      //Special symbols
[17902]78      var offset = new Addition { Name = "Offset" };
79      var scaling = new Multiplication { Name = "Scaling" };
[17628]80      //all other symbols
81      var allSymbols = new List<Symbol> {
[18132]82        add, sub, mul, div, number, constant, variableSymbol, sin, cos, tan, log, square, sqrt, cube, cbrt, exp,
[17902]83        tanh, aq, abs
[17628]84      };
85
[17902]86      var bivariateFuncs = new List<Symbol> { add, sub, mul, div, aq };
87      var univariateFuncs = new List<Symbol> { sin, cos, tan, tanh, exp, log, abs, square, cube, sqrt, cbrt };
88      var realValueSymbols = new List<Symbol> {
89         add, sub, mul, div, sin, cos, tan, tanh, exp, log, aq, abs, square, cube, sqrt, cbrt,
[18132]90         variableSymbol, number, constant
[17902]91        };
[17628]92
93
94      //Add special symbols
95      AddSymbol(offset);
96      AddSymbol(scaling);
97      //Add all other symbols
98      foreach (var symb in allSymbols) AddSymbol(symb);
99
100      #region define subtree count for special symbols
101
[17902]102      foreach (var symb in bivariateFuncs) SetSubtreeCount(symb, 2, 2);
[17628]103
[17902]104      foreach (var symb in univariateFuncs) SetSubtreeCount(symb, 1, 1);
[17628]105
106      SetSubtreeCount(offset, 2, 2);
107      SetSubtreeCount(scaling, 2, 2);
108
109      #endregion
110
111      #region child symbols config
112
113      AddAllowedChildSymbol(StartSymbol, offset);
114
115      //Define childs for offset
116      AddAllowedChildSymbol(offset, scaling, 0);
[18132]117      AddAllowedChildSymbol(offset, number, 1);
[17628]118
119      //Define childs for scaling
120      foreach (var symb in allSymbols) AddAllowedChildSymbol(scaling, symb, 0);
[18132]121      AddAllowedChildSymbol(scaling, number, 1);
[17628]122
123      //Define childs for realvalue symbols
124      foreach (var symb in realValueSymbols) {
125        foreach (var c in realValueSymbols) AddAllowedChildSymbol(symb, c);
126      }
127
128      #endregion
[17650]129
[17902]130      Symbols.First(s => s is Cube).Enabled = false;
131      Symbols.First(s => s is CubeRoot).Enabled = false;
132      Symbols.First(s => s is Absolute).Enabled = false;
[18132]133      Symbols.First(s => s is Constant).Enabled = false;
[17628]134    }
135  }
136}
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