1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2019 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 HEAL.Attic;
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23 | using HeuristicLab.Common;
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24 | using HeuristicLab.Core;
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25 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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26 | using HeuristicLab.Random;
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27 | using System.Linq;
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28 |
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29 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
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30 | [StorableType("44B25E73-6C4D-404C-93E5-42B7D2807CF7")]
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31 | public sealed class TreeModelTreeNode : SymbolicExpressionTreeTerminalNode {
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32 | public new TreeModel Symbol {
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33 | get { return (TreeModel)base.Symbol; }
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34 | }
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35 | [Storable]
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36 | ISymbolicExpressionTree tree;
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37 | public ISymbolicExpressionTree Tree {
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38 | get { return tree; }
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39 | set { tree = value; }
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40 | }
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41 | int clusterNumer = -10;
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42 | int treeNumber = 0;
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43 | public int ClusterNumer {
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44 | get { return clusterNumer; }
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45 | set { clusterNumer = value; }
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46 | }
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47 | public int TreeNumber {
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48 | get { return treeNumber; }
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49 | set { treeNumber = value; }
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50 | }
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51 |
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52 | [StorableConstructor]
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53 | private TreeModelTreeNode(StorableConstructorFlag _) : base(_) {
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54 | ClusterNumer = -10;
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55 | }
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56 |
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57 | private TreeModelTreeNode(TreeModelTreeNode original, Cloner cloner)
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58 | : base(original, cloner) {
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59 | tree = (ISymbolicExpressionTree)original.tree.Clone(cloner);
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60 | ClusterNumer = original.ClusterNumer;
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61 | TreeNumber = original.TreeNumber;
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62 | }
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63 |
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64 | private TreeModelTreeNode() : base() { }
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65 | public TreeModelTreeNode(TreeModel treeModelSymbol) : base(treeModelSymbol) {
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66 | ClusterNumer = -10;
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67 | }
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68 |
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69 | public override bool HasLocalParameters {
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70 | get { return true; }
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71 | }
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72 | public override void ShakeLocalParameters(IRandom random, double shakingFactor) {
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73 | base.ShakeLocalParameters(random, shakingFactor);
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74 | var parametricNodes = Tree.IterateNodesPrefix().Where(x => x.HasLocalParameters).ToList();
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75 | if (parametricNodes.Any()) {
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76 | var selectedPoint = parametricNodes.SampleRandom(random);
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77 | if (selectedPoint is VariableTreeNode variableTreeNode) {
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78 | var symbol = variableTreeNode.Symbol;
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79 | variableTreeNode.Weight = NormalDistributedRandom.NextDouble(random, symbol.WeightManipulatorMu, symbol.WeightManipulatorSigma);
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80 | } else {
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81 | selectedPoint.ShakeLocalParameters(random, shakingFactor);
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82 | }
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83 |
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84 | }
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85 | }
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86 | public void SetLocalParameters(IRandom random, double shakingFactor) {
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87 | foreach (var node in Tree.IterateNodesPrefix().Where(x => x.HasLocalParameters)) {
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88 | if (node is VariableTreeNode variableTreeNode) {
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89 | var symbol = variableTreeNode.Symbol;
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90 | variableTreeNode.Weight = NormalDistributedRandom.NextDouble(random, symbol.WeightManipulatorMu, symbol.WeightManipulatorSigma);
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91 | } else {
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92 | node.ResetLocalParameters(random);
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93 | }
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94 | }
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95 | }
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96 | public override IDeepCloneable Clone(Cloner cloner) {
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97 | return new TreeModelTreeNode(this, cloner);
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98 | }
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99 |
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100 | public override string ToString() {
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101 |
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102 | string s = "model" + " " + TreeNumber.ToString() + "\n " + new InfixExpressionFormatter().Format(tree);
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103 | return s;
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104 | }
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105 | }
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106 | }
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107 |
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108 |
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