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source: trunk/sources/HeuristicLab.Random/3.3/NormalRandomizer.cs @ 13741

Last change on this file since 13741 was 12012, checked in by ascheibe, 10 years ago

#2212 merged r12008, r12009, r12010 back into trunk

File size: 3.9 KB
RevLine 
[2]1#region License Information
2/* HeuristicLab
[12012]3 * Copyright (C) 2002-2015 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
[4722]22using HeuristicLab.Common;
[2]23using HeuristicLab.Core;
24using HeuristicLab.Data;
[3269]25using HeuristicLab.Operators;
26using HeuristicLab.Parameters;
[4068]27using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
[2]28
29namespace HeuristicLab.Random {
[1153]30  /// <summary>
31  /// Normally distributed random number generator.
32  /// </summary>
[3269]33  [StorableClass]
34  [Item("NormalRandomizer", "Initializes the value of variable 'Value' to a random value normally distributed with parameters 'Mu' and 'Sigma'")]
35  public class NormalRandomizer : SingleSuccessorOperator {
[4722]36    #region Parameter Properties
[3269]37    public ILookupParameter<IRandom> RandomParameter {
38      get { return (ILookupParameter<IRandom>)Parameters["Random"]; }
[2]39    }
[3269]40    public IValueLookupParameter<DoubleValue> MuParameter {
41      get { return (IValueLookupParameter<DoubleValue>)Parameters["Mu"]; }
[426]42    }
[3269]43    public IValueLookupParameter<DoubleValue> SigmaParameter {
44      get { return (IValueLookupParameter<DoubleValue>)Parameters["Sigma"]; }
[426]45    }
[3269]46    public ILookupParameter<DoubleValue> ValueParameter {
47      get { return (ILookupParameter<DoubleValue>)Parameters["Value"]; }
48    }
49    #endregion
[4722]50
[3269]51    #region Properties
52    public DoubleValue Mu {
53      get { return MuParameter.ActualValue; }
54      set { MuParameter.ActualValue = value; }
55    }
56    public DoubleValue Max {
57      get { return SigmaParameter.ActualValue; }
58      set { SigmaParameter.ActualValue = value; }
59    }
60    #endregion
[4722]61
62    [StorableConstructor]
63    protected NormalRandomizer(bool deserializing) : base(deserializing) { }
64    protected NormalRandomizer(NormalRandomizer original, Cloner cloner) : base(original, cloner) { }
[1153]65    /// <summary>
66    /// Initializes a new instance of <see cref="NormalRandomizer"/> with four variable infos
67    /// (<c>Mu</c>, <c>Sigma</c>, <c>Value</c> and <c>Random</c>).
68    /// </summary>
[2]69    public NormalRandomizer() {
[3269]70      Parameters.Add(new LookupParameter<IRandom>("Random", "A random generator that supplies uniformly distributed values."));
71      Parameters.Add(new ValueLookupParameter<DoubleValue>("Mu", "Mu parameter of the normal distribution (N(mu,sigma))."));
72      Parameters.Add(new ValueLookupParameter<DoubleValue>("Sigma", "Sigma parameter of the normal distribution (N(mu,sigma))."));
73      Parameters.Add(new LookupParameter<DoubleValue>("Value", "The value that should be set to a random value."));
[2]74    }
75
[4722]76    public override IDeepCloneable Clone(Cloner cloner) {
77      return new NormalRandomizer(this, cloner);
78    }
79
[1153]80    /// <summary>
[3269]81    /// Generates a new normally distributed random variable and assigns it to the specified variable.
[1153]82    /// </summary>
[3269]83    public override IOperation Apply() {
84      IRandom random = RandomParameter.ActualValue;
85      double mu = MuParameter.ActualValue.Value;
86      double sigma = SigmaParameter.ActualValue.Value;
[2]87
[3269]88      NormalDistributedRandom normalRandom = new NormalDistributedRandom(random, mu, sigma);
89      ValueParameter.ActualValue = new DoubleValue(normalRandom.NextDouble());
[7644]90      return base.Apply();
[2]91    }
92  }
93}
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