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# source:trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/Linear/AlglibUtil.cs@8929

Last change on this file since 8929 was 8323, checked in by gkronber, 12 years ago

#1902 initial import of Gaussian process regression algorithm

File size: 2.3 KB
Line
2/* HeuristicLab
3 * Copyright (C) 2002-2012 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
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 System.Linq;
24using HeuristicLab.Problems.DataAnalysis;
25
26namespace HeuristicLab.Algorithms.DataAnalysis {
27  public static class AlglibUtil {
28    public static double[,] PrepareInputMatrix(Dataset dataset, IEnumerable<string> variables, IEnumerable<int> rows) {
29      List<string> variablesList = variables.ToList();
30      List<int> rowsList = rows.ToList();
31
32      double[,] matrix = new double[rowsList.Count, variablesList.Count];
33
34      int col = 0;
35      foreach (string column in variables) {
36        var values = dataset.GetDoubleValues(column, rows);
37        int row = 0;
38        foreach (var value in values) {
39          matrix[row, col] = value;
40          row++;
41        }
42        col++;
43      }
44
45      return matrix;
46    }
47    public static double[,] PrepareAndScaleInputMatrix(Dataset dataset, IEnumerable<string> variables, IEnumerable<int> rows, Scaling scaling) {
48      List<string> variablesList = variables.ToList();
49      List<int> rowsList = rows.ToList();
50
51      double[,] matrix = new double[rowsList.Count, variablesList.Count];
52
53      int col = 0;
54      foreach (string column in variables) {
55        var values = scaling.GetScaledValues(dataset, column, rows);
56        int row = 0;
57        foreach (var value in values) {
58          matrix[row, col] = value;
59          row++;
60        }
61        col++;
62      }
63
64      return matrix;
65    }
66  }
67}
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