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source: branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis/3.3/RandomEnumerable.cs @ 4501

Last change on this file since 4501 was 4244, checked in by gkronber, 14 years ago

Use FastRandom instead of Mersenne twister for partial evaluation of training samples. #1082

File size: 2.0 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2010 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;
23using System.Collections.Generic;
24using HeuristicLab.Random;
25
26namespace HeuristicLab.Problems.DataAnalysis {
27  public class RandomEnumerable {
28    public static IEnumerable<int> SampleRandomNumbers(int maxElement, int count) {
29      return SampleRandomNumbers(Environment.TickCount, 0, maxElement, count);
30    }
31
32    public static IEnumerable<int> SampleRandomNumbers(int start, int end, int count) {
33      return SampleRandomNumbers(Environment.TickCount, start, end, count);
34    }
35
36    //algorithm taken from progamming pearls page 127
37    //IMPORTANT because IEnumerables with yield are used the seed must best be specified to return always
38    //the same sequence of numbers without caching the values.
39    public static IEnumerable<int> SampleRandomNumbers(int seed, int start, int end, int count) {
40      int remaining = end - start;
41      var mt = new FastRandom(seed);
42      for (int i = start; i < end && count > 0; i++) {
43        double probability = mt.NextDouble();
44        if (probability < ((double)count) / remaining) {
45          count--;
46          yield return i;
47        }
48        remaining--;
49      }
50    }
51  }
52}
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