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source: branches/2745_EfficientGlobalOptimization/HeuristicLab.Algorithms.EGO/SamplingMethods/UniformRandomSampling.cs @ 18132

Last change on this file since 18132 was 17332, checked in by bwerth, 5 years ago

#2745 updated persistence to HEAL.Attic

File size: 2.5 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2016 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 HEAL.Attic;
23using HeuristicLab.Common;
24using HeuristicLab.Core;
25using HeuristicLab.Optimization;
26using HeuristicLab.Encodings.RealVectorEncoding;
27
28// ReSharper disable once CheckNamespace
29namespace HeuristicLab.Algorithms.EGO {
30
31    [StorableType("5e725905-0d77-4379-bbb9-8ca6ae392e59")]
32    [Item("UniformRandomSampling", "A uniform random sampling strategy for real valued optimization")]
33  public class UniformRandomSampling : ParameterizedNamedItem, IInitialSampling<RealVector> {
34
35    #region HL-Constructors, Serialization and Cloning
36    [StorableConstructor]
37    protected UniformRandomSampling(StorableConstructorFlag deserializing) : base(deserializing) { }
38    protected UniformRandomSampling(UniformRandomSampling original, Cloner cloner) : base(original, cloner) { }
39    public UniformRandomSampling() {
40    }
41    public override IDeepCloneable Clone(Cloner cloner) {
42      return new UniformRandomSampling(this, cloner);
43    }
44
45    public RealVector[] GetSamples(int noSamples, RealVector[] existingSamples, IEncoding encoding, IRandom random) {
46      var enc = encoding as RealVectorEncoding;
47      var res = new RealVector[noSamples];
48      for (var i = 0; i < noSamples; i++) {
49        var r = new RealVector(enc.Length);
50        res[i] = r;
51        for (var j = 0; j < enc.Length; j++) {
52          var b = j % enc.Bounds.Rows;
53          r[j] = UniformRandom(enc.Bounds[b, 0], enc.Bounds[b, 1], random);
54        }
55      }
56      return res;
57    }
58    private static double UniformRandom(double min, double max, IRandom rand) {
59      return rand.NextDouble() * (max - min) + min;
60    }
61  }
62
63
64
65
66  #endregion
67
68
69}
70
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