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source: branches/DataAnalysis.Extensions/HeuristicLab.Problems.DataAnalysis/3.3/Symbolic/Symbols/VariableTreeNode.cs @ 9760

Last change on this file since 9760 was 4858, checked in by swinkler, 14 years ago

Removed obsolete project for symbolic expression tree formatters; (re-)added DataAnalysis project in branch DataAnalysis.Extensions. (#1270)

File size: 3.0 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2010 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21
22using HeuristicLab.Common;
23using HeuristicLab.Core;
24using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
25using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
26using HeuristicLab.Random;
27namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Symbols {
28  [StorableClass]
29  public class VariableTreeNode : SymbolicExpressionTreeTerminalNode {
30    public new Variable Symbol {
31      get { return (Variable)base.Symbol; }
32    }
33    [Storable]
34    private double weight;
35    public double Weight {
36      get { return weight; }
37      set { weight = value; }
38    }
39    [Storable]
40    private string variableName;
41    public string VariableName {
42      get { return variableName; }
43      set { variableName = value; }
44    }
45
46    [StorableConstructor]
47    protected VariableTreeNode(bool deserializing) : base(deserializing) { }
48    protected VariableTreeNode(VariableTreeNode original, Cloner cloner)
49      : base(original, cloner) {
50      weight = original.weight;
51      variableName = original.variableName;
52    }
53    protected VariableTreeNode() { }
54    public VariableTreeNode(Variable variableSymbol) : base(variableSymbol) { }
55
56    public override bool HasLocalParameters {
57      get {
58        return true;
59      }
60    }
61
62    public override void ResetLocalParameters(IRandom random) {
63      base.ResetLocalParameters(random);
64      weight = NormalDistributedRandom.NextDouble(random, Symbol.WeightNu, Symbol.WeightSigma);
65      variableName = Symbol.VariableNames.SelectRandom(random);
66    }
67
68    public override void ShakeLocalParameters(IRandom random, double shakingFactor) {
69      base.ShakeLocalParameters(random, shakingFactor);
70      double x = NormalDistributedRandom.NextDouble(random, Symbol.WeightManipulatorNu, Symbol.WeightManipulatorSigma);
71      weight = weight + x * shakingFactor;
72      variableName = Symbol.VariableNames.SelectRandom(random);
73    }
74
75    public override IDeepCloneable Clone(Cloner cloner) {
76      return new VariableTreeNode(this, cloner);
77    }
78
79    public override string ToString() {
80      if (weight.IsAlmost(1.0)) return variableName;
81      else return weight.ToString("E4") + " " + variableName;
82    }
83  }
84}
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