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source: branches/DataAnalysis SolutionEnsembles/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Symbols/Variable.cs @ 5991

Last change on this file since 5991 was 5809, checked in by mkommend, 14 years ago

#1418: Reintegrated branch into trunk.

File size: 4.6 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2011 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.Persistence.Default.CompositeSerializers.Storable;
28namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
29  [StorableClass]
30  [Item("Variable", "Represents a variable value.")]
31  public class Variable : Symbol {
32    #region Properties
33    [Storable]
34    private double weightMu;
35    public double WeightMu {
36      get { return weightMu; }
37      set {
38        if (value != weightMu) {
39          weightMu = value;
40          OnChanged(EventArgs.Empty);
41        }
42      }
43    }
44    [Storable]
45    private double weightSigma;
46    public double WeightSigma {
47      get { return weightSigma; }
48      set {
49        if (weightSigma < 0.0) throw new ArgumentException("Negative sigma is not allowed.");
50        if (value != weightSigma) {
51          weightSigma = value;
52          OnChanged(EventArgs.Empty);
53        }
54      }
55    }
56    [Storable]
57    private double weightManipulatorMu;
58    public double WeightManipulatorMu {
59      get { return weightManipulatorMu; }
60      set {
61        if (value != weightManipulatorMu) {
62          weightManipulatorMu = value;
63          OnChanged(EventArgs.Empty);
64        }
65      }
66    }
67    [Storable]
68    private double weightManipulatorSigma;
69    public double WeightManipulatorSigma {
70      get { return weightManipulatorSigma; }
71      set {
72        if (weightManipulatorSigma < 0.0) throw new ArgumentException("Negative sigma is not allowed.");
73        if (value != weightManipulatorSigma) {
74          weightManipulatorSigma = value;
75          OnChanged(EventArgs.Empty);
76        }
77      }
78    }
79    [Storable(DefaultValue = 0.0)]
80    private double multiplicativeWeightManipulatorSigma;
81    public double MultiplicativeWeightManipulatorSigma {
82      get { return multiplicativeWeightManipulatorSigma; }
83      set {
84        if (multiplicativeWeightManipulatorSigma < 0.0) throw new ArgumentException("Negative sigma is not allowed.");
85        if (value != multiplicativeWeightManipulatorSigma) {
86          multiplicativeWeightManipulatorSigma = value;
87          OnChanged(EventArgs.Empty);
88        }
89      }
90    }
91    private List<string> variableNames;
92    [Storable]
93    public IEnumerable<string> VariableNames {
94      get { return variableNames; }
95      set {
96        if (value == null) throw new ArgumentNullException();
97        variableNames.Clear();
98        variableNames.AddRange(value);
99        OnChanged(EventArgs.Empty);
100      }
101    }
102    #endregion
103    [StorableConstructor]
104    protected Variable(bool deserializing)
105      : base(deserializing) {
106      variableNames = new List<string>();
107    }
108    protected Variable(Variable original, Cloner cloner)
109      : base(original, cloner) {
110      weightMu = original.weightMu;
111      weightSigma = original.weightSigma;
112      variableNames = new List<string>(original.variableNames);
113      weightManipulatorMu = original.weightManipulatorMu;
114      weightManipulatorSigma = original.weightManipulatorSigma;
115      multiplicativeWeightManipulatorSigma = original.multiplicativeWeightManipulatorSigma;
116    }
117    public Variable() : this("Variable", "Represents a variable value.") { }
118    public Variable(string name, string description)
119      : base(name, description) {
120      weightMu = 1.0;
121      weightSigma = 1.0;
122      weightManipulatorMu = 0.0;
123      weightManipulatorSigma = 0.05;
124      multiplicativeWeightManipulatorSigma = 0.03;
125      variableNames = new List<string>();
126    }
127
128    public override ISymbolicExpressionTreeNode CreateTreeNode() {
129      return new VariableTreeNode(this);
130    }
131
132    public override IDeepCloneable Clone(Cloner cloner) {
133      return new Variable(this, cloner);
134    }
135  }
136}
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