[3253] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[12012] | 3 | * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[3253] | 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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[4722] | 22 | using HeuristicLab.Common;
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[4068] | 23 | using HeuristicLab.Core;
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[3253] | 24 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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| 25 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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[3269] | 26 | using HeuristicLab.Random;
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[5532] | 27 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
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[3253] | 28 | [StorableClass]
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[4022] | 29 | public class VariableTreeNode : SymbolicExpressionTreeTerminalNode {
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[3269] | 30 | public new Variable Symbol {
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| 31 | get { return (Variable)base.Symbol; }
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| 32 | }
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[3485] | 33 | [Storable]
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[3253] | 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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[3485] | 39 | [Storable]
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[3253] | 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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[4722] | 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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[3253] | 50 | weight = original.weight;
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| 51 | variableName = original.variableName;
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| 52 | }
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[4722] | 53 | protected VariableTreeNode() { }
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[3253] | 54 | public VariableTreeNode(Variable variableSymbol) : base(variableSymbol) { }
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| 55 |
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[3442] | 56 | public override bool HasLocalParameters {
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[5467] | 57 | get { return true; }
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[3442] | 58 | }
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| 59 |
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[3269] | 60 | public override void ResetLocalParameters(IRandom random) {
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| 61 | base.ResetLocalParameters(random);
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[4989] | 62 | weight = NormalDistributedRandom.NextDouble(random, Symbol.WeightMu, Symbol.WeightSigma);
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[12422] | 63 |
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| 64 | #pragma warning disable 612, 618
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[3512] | 65 | variableName = Symbol.VariableNames.SelectRandom(random);
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[12422] | 66 | #pragma warning restore 612, 618
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[3269] | 67 | }
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| 68 |
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[3512] | 69 | public override void ShakeLocalParameters(IRandom random, double shakingFactor) {
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| 70 | base.ShakeLocalParameters(random, shakingFactor);
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[5326] | 71 | // 50% additive & 50% multiplicative
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| 72 | if (random.NextDouble() < 0) {
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| 73 | double x = NormalDistributedRandom.NextDouble(random, Symbol.WeightManipulatorMu, Symbol.WeightManipulatorSigma);
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| 74 | weight = weight + x * shakingFactor;
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[12422] | 75 | } else {
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[5326] | 76 | double x = NormalDistributedRandom.NextDouble(random, 1.0, Symbol.MultiplicativeWeightManipulatorSigma);
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| 77 | weight = weight * x;
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| 78 | }
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[12422] | 79 | #pragma warning disable 612, 618
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[3512] | 80 | variableName = Symbol.VariableNames.SelectRandom(random);
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[12422] | 81 | #pragma warning restore 612, 618
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[3512] | 82 | }
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| 83 |
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[4722] | 84 | public override IDeepCloneable Clone(Cloner cloner) {
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| 85 | return new VariableTreeNode(this, cloner);
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[3253] | 86 | }
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[3442] | 87 |
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| 88 | public override string ToString() {
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[4239] | 89 | if (weight.IsAlmost(1.0)) return variableName;
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| 90 | else return weight.ToString("E4") + " " + variableName;
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[3442] | 91 | }
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[3253] | 92 | }
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| 93 | }
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