[4858] | 1 | #region License Information
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| 2 | /* HeuristicLab
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| 3 | * Copyright (C) 2002-2010 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 HeuristicLab.Common;
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| 23 | using HeuristicLab.Core;
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| 24 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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| 25 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 26 | using HeuristicLab.Random;
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| 27 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Symbols {
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| 28 | [StorableClass]
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| 29 | public class VariableTreeNode : SymbolicExpressionTreeTerminalNode {
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| 30 | public new Variable Symbol {
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| 31 | get { return (Variable)base.Symbol; }
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| 32 | }
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| 33 | [Storable]
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| 34 | private double weight;
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| 35 | public double Weight {
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| 36 | get { return weight; }
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| 37 | set { weight = value; }
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| 38 | }
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| 39 | [Storable]
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| 40 | private string variableName;
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| 41 | public string VariableName {
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| 42 | get { return variableName; }
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| 43 | set { variableName = value; }
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| 44 | }
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| 45 |
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| 46 | [StorableConstructor]
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| 47 | protected VariableTreeNode(bool deserializing) : base(deserializing) { }
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| 48 | protected VariableTreeNode(VariableTreeNode original, Cloner cloner)
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| 49 | : base(original, cloner) {
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| 50 | weight = original.weight;
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| 51 | variableName = original.variableName;
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| 52 | }
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| 53 | protected VariableTreeNode() { }
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| 54 | public VariableTreeNode(Variable variableSymbol) : base(variableSymbol) { }
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| 55 |
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| 56 | public override bool HasLocalParameters {
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| 57 | get {
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| 58 | return true;
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| 59 | }
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| 60 | }
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| 61 |
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| 62 | public override void ResetLocalParameters(IRandom random) {
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| 63 | base.ResetLocalParameters(random);
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| 64 | weight = NormalDistributedRandom.NextDouble(random, Symbol.WeightNu, Symbol.WeightSigma);
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| 65 | variableName = Symbol.VariableNames.SelectRandom(random);
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| 66 | }
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| 67 |
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| 68 | public override void ShakeLocalParameters(IRandom random, double shakingFactor) {
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| 69 | base.ShakeLocalParameters(random, shakingFactor);
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| 70 | double x = NormalDistributedRandom.NextDouble(random, Symbol.WeightManipulatorNu, Symbol.WeightManipulatorSigma);
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| 71 | weight = weight + x * shakingFactor;
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| 72 | variableName = Symbol.VariableNames.SelectRandom(random);
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| 73 | }
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| 74 |
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| 75 | public override IDeepCloneable Clone(Cloner cloner) {
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| 76 | return new VariableTreeNode(this, cloner);
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| 77 | }
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| 78 |
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| 79 | public override string ToString() {
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| 80 | if (weight.IsAlmost(1.0)) return variableName;
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| 81 | else return weight.ToString("E4") + " " + variableName;
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| 82 | }
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| 83 | }
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| 84 | }
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