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source: trunk/sources/HeuristicLab.Random/3.3/NormalRandomizer.cs @ 3289

Last change on this file since 3289 was 3269, checked in by gkronber, 15 years ago

Implemented initialization of Variable and Constant terminal nodes. #938 (Data types and operators for regression problems)

File size: 3.6 KB
RevLine 
[2]1#region License Information
2/* HeuristicLab
[3269]3 * Copyright (C) 2002-2010 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
[2]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 System.Text;
25using HeuristicLab.Core;
26using HeuristicLab.Data;
[1853]27using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
[3269]28using HeuristicLab.Operators;
29using HeuristicLab.Parameters;
[2]30
31namespace HeuristicLab.Random {
[1153]32  /// <summary>
33  /// Normally distributed random number generator.
34  /// </summary>
[3269]35  [StorableClass]
36  [Item("NormalRandomizer", "Initializes the value of variable 'Value' to a random value normally distributed with parameters 'Mu' and 'Sigma'")]
37  public class NormalRandomizer : SingleSuccessorOperator {
38    #region parameter properties
39    public ILookupParameter<IRandom> RandomParameter {
40      get { return (ILookupParameter<IRandom>)Parameters["Random"]; }
[2]41    }
[3269]42    public IValueLookupParameter<DoubleValue> MuParameter {
43      get { return (IValueLookupParameter<DoubleValue>)Parameters["Mu"]; }
[426]44    }
[3269]45    public IValueLookupParameter<DoubleValue> SigmaParameter {
46      get { return (IValueLookupParameter<DoubleValue>)Parameters["Sigma"]; }
[426]47    }
[3269]48    public ILookupParameter<DoubleValue> ValueParameter {
49      get { return (ILookupParameter<DoubleValue>)Parameters["Value"]; }
50    }
51    #endregion
52    #region Properties
53    public DoubleValue Mu {
54      get { return MuParameter.ActualValue; }
55      set { MuParameter.ActualValue = value; }
56    }
57    public DoubleValue Max {
58      get { return SigmaParameter.ActualValue; }
59      set { SigmaParameter.ActualValue = value; }
60    }
61    #endregion
[1153]62    /// <summary>
63    /// Initializes a new instance of <see cref="NormalRandomizer"/> with four variable infos
64    /// (<c>Mu</c>, <c>Sigma</c>, <c>Value</c> and <c>Random</c>).
65    /// </summary>
[2]66    public NormalRandomizer() {
[3269]67      Parameters.Add(new LookupParameter<IRandom>("Random", "A random generator that supplies uniformly distributed values."));
68      Parameters.Add(new ValueLookupParameter<DoubleValue>("Mu", "Mu parameter of the normal distribution (N(mu,sigma))."));
69      Parameters.Add(new ValueLookupParameter<DoubleValue>("Sigma", "Sigma parameter of the normal distribution (N(mu,sigma))."));
70      Parameters.Add(new LookupParameter<DoubleValue>("Value", "The value that should be set to a random value."));
[2]71    }
72
[1153]73    /// <summary>
[3269]74    /// Generates a new normally distributed random variable and assigns it to the specified variable.
[1153]75    /// </summary>
[3269]76    public override IOperation Apply() {
77      IRandom random = RandomParameter.ActualValue;
78      double mu = MuParameter.ActualValue.Value;
79      double sigma = SigmaParameter.ActualValue.Value;
[2]80
[3269]81      NormalDistributedRandom normalRandom = new NormalDistributedRandom(random, mu, sigma);
82      ValueParameter.ActualValue = new DoubleValue(normalRandom.NextDouble());
[2]83      return null;
84    }
85  }
86}
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