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source: branches/3043-Regression-Instances-For-Scaling/HeuristicLab.Problems.NK/3.3/WeightInitializers/ReverseLinearWeightsInitializer.cs @ 17578

Last change on this file since 17578 was 17180, checked in by swagner, 5 years ago

#2875: Removed years in copyrights

File size: 1.8 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 System.Collections.Generic;
23using HeuristicLab.Common;
24using HeuristicLab.Core;
25using HEAL.Attic;
26
27namespace HeuristicLab.Problems.NK {
28  [Item("ReverseLinearWeightsInitializer", "Assigns exponentially decreasing weights.")]
29  [StorableType("E63DE1AE-FBA4-4430-9C22-631ADDFD3976")]
30  public sealed class ReverseLinearWeightsInitializer : ParameterizedNamedItem, IWeightsInitializer {
31    [StorableConstructor]
32    private ReverseLinearWeightsInitializer(StorableConstructorFlag _) : base(_) { }
33    private ReverseLinearWeightsInitializer(ReverseLinearWeightsInitializer original, Cloner cloner)
34      : base(original, cloner) {
35    }
36    public ReverseLinearWeightsInitializer() { }
37    public override IDeepCloneable Clone(Cloner cloner) {
38      return new ReverseLinearWeightsInitializer(this, cloner);
39    }
40
41    public IEnumerable<double> GetWeights(int nComponents) {
42      for (int i = nComponents - 1; i >= 0; i--)
43        yield return i;
44    }
45  }
46}
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