source: branches/3027-NormalDistribution/HeuristicLab.Random/3.3/NormalRandomizer.cs @ 17244

Last change on this file since 17244 was 17244, checked in by gkronber, 11 months ago

#3027: added class to generate normally distributed numbers using the polar method.

File size: 3.9 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 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.Data;
25using HeuristicLab.Operators;
26using HeuristicLab.Parameters;
27using HEAL.Attic;
28using System;
29
30namespace HeuristicLab.Random {
31  /// <summary>
32  /// Normally distributed random number generator.
33  /// </summary>
34  [StorableType("0EAF4184-6C98-4C9D-80A1-09A42E03450E")]
35  [Item("NormalRandomizer", "Initializes the value of variable 'Value' to a random value normally distributed with parameters 'Mu' and 'Sigma'")]
36  [Obsolete("Use NormalRandomizerPolar instead.")]
37  public class NormalRandomizer : SingleSuccessorOperator {
38    #region Parameter Properties
39    public ILookupParameter<IRandom> RandomParameter {
40      get { return (ILookupParameter<IRandom>)Parameters["Random"]; }
41    }
42    public IValueLookupParameter<DoubleValue> MuParameter {
43      get { return (IValueLookupParameter<DoubleValue>)Parameters["Mu"]; }
44    }
45    public IValueLookupParameter<DoubleValue> SigmaParameter {
46      get { return (IValueLookupParameter<DoubleValue>)Parameters["Sigma"]; }
47    }
48    public ILookupParameter<DoubleValue> ValueParameter {
49      get { return (ILookupParameter<DoubleValue>)Parameters["Value"]; }
50    }
51    #endregion
52
53    #region Properties
54    public DoubleValue Mu {
55      get { return MuParameter.ActualValue; }
56      set { MuParameter.ActualValue = value; }
57    }
58    public DoubleValue Max {
59      get { return SigmaParameter.ActualValue; }
60      set { SigmaParameter.ActualValue = value; }
61    }
62    #endregion
63
64    [StorableConstructor]
65    protected NormalRandomizer(StorableConstructorFlag _) : base(_) { }
66    protected NormalRandomizer(NormalRandomizer original, Cloner cloner) : base(original, cloner) { }
67    /// <summary>
68    /// Initializes a new instance of <see cref="NormalRandomizer"/> with four variable infos
69    /// (<c>Mu</c>, <c>Sigma</c>, <c>Value</c> and <c>Random</c>).
70    /// </summary>
71    public NormalRandomizer() {
72      Parameters.Add(new LookupParameter<IRandom>("Random", "A random generator that supplies uniformly distributed values."));
73      Parameters.Add(new ValueLookupParameter<DoubleValue>("Mu", "Mu parameter of the normal distribution (N(mu,sigma))."));
74      Parameters.Add(new ValueLookupParameter<DoubleValue>("Sigma", "Sigma parameter of the normal distribution (N(mu,sigma))."));
75      Parameters.Add(new LookupParameter<DoubleValue>("Value", "The value that should be set to a random value."));
76    }
77
78    public override IDeepCloneable Clone(Cloner cloner) {
79      return new NormalRandomizer(this, cloner);
80    }
81
82    /// <summary>
83    /// Generates a new normally distributed random variable and assigns it to the specified variable.
84    /// </summary>
85    public override IOperation Apply() {
86      IRandom random = RandomParameter.ActualValue;
87      double mu = MuParameter.ActualValue.Value;
88      double sigma = SigmaParameter.ActualValue.Value;
89
90      NormalDistributedRandom normalRandom = new NormalDistributedRandom(random, mu, sigma);
91      ValueParameter.ActualValue = new DoubleValue(normalRandom.NextDouble());
92      return base.Apply();
93    }
94  }
95}
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