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source: branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis/3.3/Symbolic/Symbols/Variable.cs @ 5551

Last change on this file since 5551 was 5275, checked in by gkronber, 14 years ago

Merged changes from trunk to data analysis exploration branch and added fractional distance metric evaluator. #1142

File size: 4.0 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 System;
23using System.Collections.Generic;
24using HeuristicLab.Common;
25using HeuristicLab.Core;
26using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
27using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding.Symbols;
28using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
29namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Symbols {
30  [StorableClass]
31  [Item("Variable", "Represents a variable value.")]
32  public class Variable : Symbol {
33    #region Properties
34    [Storable]
35    private double weightMu;
36    public double WeightMu {
37      get { return weightMu; }
38      set {
39        if (value != weightMu) {
40          weightMu = value;
41          OnChanged(EventArgs.Empty);
42        }
43      }
44    }
45    [Storable]
46    private double weightSigma;
47    public double WeightSigma {
48      get { return weightSigma; }
49      set {
50        if (weightSigma < 0.0) throw new ArgumentException("Negative sigma is not allowed.");
51        if (value != weightSigma) {
52          weightSigma = value;
53          OnChanged(EventArgs.Empty);
54        }
55      }
56    }
57    [Storable]
58    private double weightManipulatorMu;
59    public double WeightManipulatorMu {
60      get { return weightManipulatorMu; }
61      set {
62        if (value != weightManipulatorMu) {
63          weightManipulatorMu = value;
64          OnChanged(EventArgs.Empty);
65        }
66      }
67    }
68    [Storable]
69    private double weightManipulatorSigma;
70    public double WeightManipulatorSigma {
71      get { return weightManipulatorSigma; }
72      set {
73        if (weightManipulatorSigma < 0.0) throw new ArgumentException("Negative sigma is not allowed.");
74        if (value != weightManipulatorSigma) {
75          weightManipulatorSigma = value;
76          OnChanged(EventArgs.Empty);
77        }
78      }
79    }
80    private List<string> variableNames;
81    [Storable]
82    public IEnumerable<string> VariableNames {
83      get { return variableNames; }
84      set {
85        if (value == null) throw new ArgumentNullException();
86        variableNames.Clear();
87        variableNames.AddRange(value);
88        OnChanged(EventArgs.Empty);
89      }
90    }
91    #endregion
92    [StorableConstructor]
93    protected Variable(bool deserializing) : base(deserializing) {
94      variableNames = new List<string>();
95    }
96    protected Variable(Variable original, Cloner cloner)
97      : base(original, cloner) {
98      weightMu = original.weightMu;
99      weightSigma = original.weightSigma;
100      variableNames = new List<string>(original.variableNames);
101      weightManipulatorMu = original.weightManipulatorMu;
102      weightManipulatorSigma = original.weightManipulatorSigma;
103    }
104    public Variable() : this("Variable", "Represents a variable value.") { }
105    public Variable(string name, string description)
106      : base(name, description) {
107      weightMu = 1.0;
108      weightSigma = 1.0;
109      weightManipulatorMu = 0.0;
110      weightManipulatorSigma = 1.0;
111      variableNames = new List<string>();
112    }
113
114    public override SymbolicExpressionTreeNode CreateTreeNode() {
115      return new VariableTreeNode(this);
116    }
117
118    public override IDeepCloneable Clone(Cloner cloner) {
119      return new Variable(this, cloner);
120    }
121  }
122}
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