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source: branches/DataAnalysis Refactoring/HeuristicLab.Algorithms.DataAnalysis/3.4/Linear/AlglibUtil.cs @ 5658

Last change on this file since 5658 was 5658, checked in by gkronber, 13 years ago

#1418 implemented wrapper for LDA (linear discriminant analysis) implemented in alglib.

File size: 2.0 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2011 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 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<int> allowedRows = CalculateAllowedRows(dataset, variables, rows).ToList();
30
31      double[,] matrix = new double[allowedRows.Count, variables.Count()];
32      for (int row = 0; row < allowedRows.Count; row++) {
33        int col = 0;
34        foreach (string column in variables) {
35          matrix[row, col] = dataset[column, row];
36          col++;
37        }
38      }
39      return matrix;
40    }
41
42    private static IEnumerable<int> CalculateAllowedRows(Dataset dataset, IEnumerable<string> variables, IEnumerable<int> rows) {
43      // return only rows that contain no infinity or NaN values
44      return from row in rows
45             where (from variable in variables
46                    let x = dataset[variable, row]
47                    where double.IsInfinity(x) || double.IsNaN(x)
48                    select 1)
49                    .Any() == false
50             select row;
51    }
52  }
53}
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