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source: trunk/HeuristicLab.Problems.NK/3.3/WeightInitializers/LinearWeightsInitializer.cs @ 17180

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

#2875: Removed years in copyrights

File size: 1.7 KB
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[12566]1#region License Information
2/* HeuristicLab
[17180]3 * Copyright (C) Heuristic and Evolutionary Algorithms Laboratory (HEAL)
[12566]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
[7128]22using System.Collections.Generic;
[12566]23using HeuristicLab.Common;
[7128]24using HeuristicLab.Core;
[16565]25using HEAL.Attic;
[7128]26
[12582]27namespace HeuristicLab.Problems.NK {
[12569]28  [Item("LinearWeightsInitializer", "Assigns linear increasing weights.")]
[16565]29  [StorableType("355BD81C-E35B-4260-91DD-2B1729682E61")]
[12592]30  public sealed class LinearWeightsInitializer : ParameterizedNamedItem, IWeightsInitializer {
[7128]31    [StorableConstructor]
[16565]32    private LinearWeightsInitializer(StorableConstructorFlag _) : base(_) { }
[12582]33    private LinearWeightsInitializer(LinearWeightsInitializer original, Cloner cloner)
[7128]34      : base(original, cloner) {
35    }
[12582]36    public LinearWeightsInitializer() { }
[7128]37    public override IDeepCloneable Clone(Cloner cloner) {
38      return new LinearWeightsInitializer(this, cloner);
39    }
40
41    public IEnumerable<double> GetWeights(int nComponents) {
[12566]42      for (int i = 0; i < nComponents; i++)
[7128]43        yield return i;
44    }
45  }
46}
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