[10268] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[15584] | 3 | * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[10268] | 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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[10968] | 19 | *
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| 20 | * Author: Sabine Winkler
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[10268] | 21 | */
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[10968] | 22 |
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[10268] | 23 | #endregion
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| 24 |
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| 25 | using System.Collections.Generic;
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| 26 | using System.Linq;
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| 27 | using HeuristicLab.Common;
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| 28 | using HeuristicLab.Core;
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| 29 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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| 30 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 31 | using HeuristicLab.Problems.DataAnalysis.Symbolic;
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| 32 | using HeuristicLab.Random;
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| 33 |
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| 34 | namespace HeuristicLab.Problems.GrammaticalEvolution {
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| 35 | [StorableClass]
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| 36 | [Item("GESymbolicExpressionGrammar", "Represents a grammar for functional expressions for grammatical evolution.")]
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| 37 | public class GESymbolicExpressionGrammar : SymbolicExpressionGrammar, ISymbolicDataAnalysisGrammar {
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| 38 | [StorableConstructor]
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| 39 | protected GESymbolicExpressionGrammar(bool deserializing) : base(deserializing) { }
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| 40 | protected GESymbolicExpressionGrammar(GESymbolicExpressionGrammar original, Cloner cloner) : base(original, cloner) { }
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| 41 | public GESymbolicExpressionGrammar()
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| 42 | : base(ItemAttribute.GetName(typeof(GESymbolicExpressionGrammar)), ItemAttribute.GetDescription(typeof(GESymbolicExpressionGrammar))) {
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| 43 | // empty ctor is necessary to allow creation of new GEGrammars from the GUI.
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| 44 | // the problem creates a new correctly configured grammar when the grammar is set
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| 45 | }
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| 46 | internal GESymbolicExpressionGrammar(IEnumerable<string> variableNames, int nConstants)
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| 47 | : base(ItemAttribute.GetName(typeof(GESymbolicExpressionGrammar)), ItemAttribute.GetDescription(typeof(GESymbolicExpressionGrammar))) {
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| 48 | // this ctor is called by the problem as only the problem knows the allowed input variables
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| 49 | Initialize(variableNames, nConstants);
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| 50 | }
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| 51 | public override IDeepCloneable Clone(Cloner cloner) {
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| 52 | return new GESymbolicExpressionGrammar(this, cloner);
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| 53 | }
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| 54 |
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| 55 | private void Initialize(IEnumerable<string> variableNames, int nConstants) {
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| 56 | #region symbol declaration
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| 57 | var add = new Addition();
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| 58 | var sub = new Subtraction();
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| 59 | var mul = new Multiplication();
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| 60 | var div = new Division();
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| 61 | var mean = new Average();
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| 62 | var log = new Logarithm();
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| 63 | var pow = new Power();
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| 64 | var square = new Square();
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| 65 | var root = new Root();
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| 66 | var sqrt = new SquareRoot();
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| 67 | var exp = new Exponential();
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| 68 |
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| 69 | // we use our own random number generator here because we assume
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| 70 | // that grammars are only initialized once when setting the grammar in the problem.
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| 71 | // This means everytime the grammar parameter in the problem is changed
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| 72 | // we initialize the constants to new values
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| 73 | var rand = new MersenneTwister();
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| 74 | // warm up
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| 75 | for (int i = 0; i < 1000; i++) rand.NextDouble();
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| 76 |
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| 77 | var constants = new List<Constant>(nConstants);
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| 78 | for (int i = 0; i < nConstants; i++) {
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| 79 | var constant = new Constant();
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[10984] | 80 | do {
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| 81 | var constVal = rand.NextDouble() * 20.0 - 10.0;
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| 82 | constant.Name = string.Format("{0:0.000}", constVal);
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| 83 | constant.MinValue = constVal;
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| 84 | constant.MaxValue = constVal;
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| 85 | constant.ManipulatorSigma = 0.0;
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| 86 | constant.ManipulatorMu = 0.0;
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| 87 | constant.MultiplicativeManipulatorSigma = 0.0;
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| 88 | } while (constants.Any(c => c.Name == constant.Name)); // unlikely, but it could happen that the same constant value is sampled twice. so we resample if necessary.
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[10268] | 89 | constants.Add(constant);
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| 90 | }
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| 91 |
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| 92 | var variables = new List<HeuristicLab.Problems.DataAnalysis.Symbolic.Variable>();
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| 93 | foreach (var variableName in variableNames) {
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| 94 | var variableSymbol = new HeuristicLab.Problems.DataAnalysis.Symbolic.Variable();
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| 95 | variableSymbol.Name = variableName;
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| 96 | variableSymbol.WeightManipulatorMu = 0.0;
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| 97 | variableSymbol.WeightManipulatorSigma = 0.0;
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| 98 | variableSymbol.WeightMu = 1.0;
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| 99 | variableSymbol.WeightSigma = 0.0;
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| 100 | variableSymbol.MultiplicativeWeightManipulatorSigma = 0.0;
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| 101 | variableSymbol.AllVariableNames = new[] { variableName };
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| 102 | variableSymbol.VariableNames = new[] { variableName };
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| 103 | variables.Add(variableSymbol);
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| 104 | }
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| 105 |
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| 106 | #endregion
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| 107 |
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| 108 | AddSymbol(add);
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| 109 | AddSymbol(sub);
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| 110 | AddSymbol(mul);
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| 111 | AddSymbol(div);
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| 112 | AddSymbol(mean);
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| 113 | AddSymbol(log);
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| 114 | AddSymbol(pow);
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| 115 | AddSymbol(square);
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| 116 | AddSymbol(root);
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| 117 | AddSymbol(sqrt);
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| 118 | AddSymbol(exp);
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| 119 | constants.ForEach(AddSymbol);
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| 120 | variables.ForEach(AddSymbol);
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| 121 |
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| 122 | #region subtree count configuration
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| 123 | SetSubtreeCount(add, 2, 2);
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| 124 | SetSubtreeCount(sub, 2, 2);
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| 125 | SetSubtreeCount(mul, 2, 2);
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| 126 | SetSubtreeCount(div, 2, 2);
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| 127 | SetSubtreeCount(mean, 2, 2);
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| 128 | SetSubtreeCount(log, 1, 1);
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| 129 | SetSubtreeCount(pow, 2, 2);
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| 130 | SetSubtreeCount(square, 1, 1);
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| 131 | SetSubtreeCount(root, 2, 2);
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| 132 | SetSubtreeCount(sqrt, 1, 1);
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| 133 | SetSubtreeCount(exp, 1, 1);
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| 134 | constants.ForEach((c) => SetSubtreeCount(c, 0, 0));
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| 135 | variables.ForEach((v) => SetSubtreeCount(v, 0, 0));
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| 136 | #endregion
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| 137 |
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| 138 | var functions = new ISymbol[] { add, sub, mul, div, mean, log, pow, root, square, sqrt };
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| 139 | var terminalSymbols = variables.Concat<ISymbol>(constants);
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| 140 | var allSymbols = functions.Concat(terminalSymbols);
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| 141 |
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| 142 | #region allowed child symbols configuration
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| 143 | foreach (var s in allSymbols) {
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| 144 | AddAllowedChildSymbol(StartSymbol, s);
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| 145 | }
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| 146 | foreach (var parentSymb in functions)
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| 147 | foreach (var childSymb in allSymbols) {
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| 148 | AddAllowedChildSymbol(parentSymb, childSymb);
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| 149 | }
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| 150 |
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| 151 | #endregion
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| 152 | }
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| 153 | }
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| 154 | }
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