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source: trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/Util.cs @ 8491

Last change on this file since 8491 was 8491, checked in by gkronber, 12 years ago

#1902 fixed test cases, improved performance

File size: 2.5 KB
Line 
1#region License Information
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
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;
24
25namespace HeuristicLab.Algorithms.DataAnalysis {
26  public static class Util {
27    public static double ScalarProd(IEnumerable<double> v, IEnumerable<double> u) {
28      return v.Zip(u, (vi, ui) => vi * ui).Sum();
29    }
30
31    public static double SqrDist(double x, double y) {
32      double d = x - y;
33      return d * d;
34    }
35
36    public static double SqrDist(IEnumerable<double> x, IEnumerable<double> y) {
37      return x.Zip(y, (a, b) => (a - b) * (a - b)).Sum();
38    }
39
40    public static double SqrDist(double[,] x, int i, int j, double scale = 1.0) {
41      return SqrDist(x, i, x, j, scale);
42    }
43
44    public static double SqrDist(double[,] x, int i, double[,] xt, int j, double scale = 1.0) {
45      double ss = 0.0;
46      for (int k = 0; k < x.GetLength(1); k++) {
47        double d = x[i, k] - xt[j, k];
48        ss += d * d;
49      }
50      return scale * scale * ss;
51    }
52    public static double SqrDist(double[,] x, int i, int j, double[] scale) {
53      return SqrDist(x, i, x, j, scale);
54    }
55
56    public static double SqrDist(double[,] x, int i, double[,] xt, int j, double[] scale) {
57      double ss = 0.0;
58      for (int k = 0; k < x.GetLength(1); k++) {
59        double d = x[i, k] - xt[j, k];
60        ss += d * d * scale[k] * scale[k];
61      }
62      return ss;
63    }
64
65    public static IEnumerable<double> GetRow(double[,] x, int r) {
66      int cols = x.GetLength(1);
67      return Enumerable.Range(0, cols).Select(c => x[r, c]);
68    }
69    public static IEnumerable<double> GetCol(double[,] x, int c) {
70      int rows = x.GetLength(0);
71      return Enumerable.Range(0, rows).Select(r => x[r, c]);
72    }
73  }
74}
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