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 System;
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23 | using System.Linq;
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24 | using HeuristicLab.Common;
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25 | using HeuristicLab.Core;
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26 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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27 | using HEAL.Attic;
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28 | using HeuristicLab.Random;
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29 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
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30 | [StorableType("A968620F-339E-4C96-B39A-8FC8E42D6509")]
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31 | public sealed class FactorVariableTreeNode : SymbolicExpressionTreeTerminalNode, IVariableTreeNode {
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32 | public new FactorVariable Symbol {
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33 | get { return (FactorVariable)base.Symbol; }
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34 | }
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35 | [Storable]
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36 | private double[] weights;
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37 | public double[] Weights {
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38 | get { return weights; }
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39 | set { weights = value; }
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40 | }
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41 | [Storable]
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42 | private string variableName;
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43 | public string VariableName {
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44 | get { return variableName; }
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45 | set { variableName = value; }
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46 | }
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47 |
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48 | [StorableConstructor]
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49 | private FactorVariableTreeNode(StorableConstructorFlag _) : base(_) { }
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50 | private FactorVariableTreeNode(FactorVariableTreeNode original, Cloner cloner)
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51 | : base(original, cloner) {
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52 | variableName = original.variableName;
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53 | if (original.weights != null) {
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54 | this.weights = new double[original.Weights.Length];
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55 | Array.Copy(original.Weights, weights, weights.Length);
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56 | }
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57 | }
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58 |
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59 | public FactorVariableTreeNode(FactorVariable variableSymbol)
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60 | : base(variableSymbol) {
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61 | }
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62 |
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63 | public override bool HasLocalParameters {
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64 | get { return true; }
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65 | }
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66 |
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67 | public override void ResetLocalParameters(IRandom random) {
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68 | base.ResetLocalParameters(random);
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69 | variableName = Symbol.VariableNames.SampleRandom(random);
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70 | weights =
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71 | Symbol.GetVariableValues(variableName)
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72 | .Select(_ => NormalDistributedRandom.NextDouble(random, 0, 1)).ToArray();
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73 | }
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74 |
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75 | public override void ShakeLocalParameters(IRandom random, double shakingFactor) {
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76 | // mutate only one randomly selected weight
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77 | var idx = random.Next(weights.Length);
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78 | // 50% additive & 50% multiplicative
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79 | if (random.NextDouble() < 0.5) {
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80 | double x = NormalDistributedRandom.NextDouble(random, Symbol.WeightManipulatorMu,
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81 | Symbol.WeightManipulatorSigma);
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82 | weights[idx] = weights[idx] + x * shakingFactor;
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83 | } else {
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84 | double x = NormalDistributedRandom.NextDouble(random, 1.0, Symbol.MultiplicativeWeightManipulatorSigma);
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85 | weights[idx] = weights[idx] * x;
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86 | }
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87 | if (random.NextDouble() < Symbol.VariableChangeProbability) {
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88 | VariableName = Symbol.VariableNames.SampleRandom(random);
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89 | if (weights.Length != Symbol.GetVariableValues(VariableName).Count()) {
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90 | // if the length of the weight array does not match => re-initialize weights
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91 | weights =
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92 | Symbol.GetVariableValues(variableName)
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93 | .Select(_ => NormalDistributedRandom.NextDouble(random, 0, 1))
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94 | .ToArray();
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95 | }
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96 | }
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97 | }
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98 |
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99 | public override IDeepCloneable Clone(Cloner cloner) {
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100 | return new FactorVariableTreeNode(this, cloner);
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101 | }
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102 |
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103 | public double GetValue(string cat) {
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104 | return weights[Symbol.GetIndexForValue(VariableName, cat)];
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105 | }
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106 |
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107 | public override string ToString() {
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108 | var weightStr = string.Join("; ",
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109 | Symbol.GetVariableValues(VariableName).Select(value => value + ": " + GetValue(value).ToString("E4")));
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110 | return VariableName + " (factor) "
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111 | + "[" + weightStr + "]";
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112 | }
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113 | }
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114 | }
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115 |
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