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source: branches/2520_PersistenceReintegration/HeuristicLab.Algorithms.DataAnalysis/3.4/Nca/Initialization/RandomInitializer.cs @ 16453

Last change on this file since 16453 was 16453, checked in by jkarder, 5 years ago

#2520: updated year of copyrights

File size: 2.3 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2019 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.Linq;
23using HeuristicLab.Common;
24using HeuristicLab.Core;
25using HeuristicLab.Optimization;
26using HeuristicLab.Parameters;
27using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
28using HeuristicLab.Problems.DataAnalysis;
29
30namespace HeuristicLab.Algorithms.DataAnalysis {
31  [Item("Random", "Initializes the matrix randomly.")]
32  [StorableClass]
33  public sealed class RandomInitializer : NcaInitializer, IStochasticOperator {
34    public ILookupParameter<IRandom> RandomParameter {
35      get { return (ILookupParameter<IRandom>)Parameters["Random"]; }
36    }
37
38    [StorableConstructor]
39    private RandomInitializer(bool deserializing) : base(deserializing) { }
40    private RandomInitializer(RandomInitializer original, Cloner cloner) : base(original, cloner) { }
41    public RandomInitializer()
42      : base() {
43      Parameters.Add(new LookupParameter<IRandom>("Random", "The random number generator to use."));
44    }
45
46    public override IDeepCloneable Clone(Cloner cloner) {
47      return new RandomInitializer(this, cloner);
48    }
49
50    public override double[,] Initialize(IClassificationProblemData data, int dimensions) {
51      var attributes = data.AllowedInputVariables.Count();
52
53      var random = RandomParameter.ActualValue;
54      var matrix = new double[attributes, dimensions];
55      for (int i = 0; i < attributes; i++)
56        for (int j = 0; j < dimensions; j++)
57          matrix[i, j] = random.NextDouble();
58
59      return matrix;
60    }
61  }
62}
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