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source: branches/PersistenceOverhaul/HeuristicLab.Problems.NK/3.3/WeightInitializers/LinearWeightsInitializer.cs @ 13368

Last change on this file since 13368 was 13368, checked in by ascheibe, 8 years ago

#2520 added guids to storable classes

File size: 1.8 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2015 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.Collections.Generic;
23using HeuristicLab.Common;
24using HeuristicLab.Core;
25using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
26
27namespace HeuristicLab.Problems.NK {
28  [Item("LinearWeightsInitializer", "Assigns linear increasing weights.")]
29  [StorableClass("733D3565-10B2-4F1D-A83B-65EFF35AE463")]
30  public sealed class LinearWeightsInitializer : ParameterizedNamedItem, IWeightsInitializer {
31    [StorableConstructor]
32    private LinearWeightsInitializer(bool deserializing) : base(deserializing) { }
33    private LinearWeightsInitializer(LinearWeightsInitializer original, Cloner cloner)
34      : base(original, cloner) {
35    }
36    public LinearWeightsInitializer() { }
37    public override IDeepCloneable Clone(Cloner cloner) {
38      return new LinearWeightsInitializer(this, cloner);
39    }
40
41    public IEnumerable<double> GetWeights(int nComponents) {
42      for (int i = 0; i < nComponents; i++)
43        yield return i;
44    }
45  }
46}
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