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source: branches/crossvalidation-2434/HeuristicLab.Algorithms.DataAnalysis.Views/3.4/GaussianProcessModelView.cs @ 13371

Last change on this file since 13371 was 12012, checked in by ascheibe, 10 years ago

#2212 merged r12008, r12009, r12010 back into trunk

File size: 2.2 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2015 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.Windows.Forms;
23using HeuristicLab.Data;
24using HeuristicLab.MainForm;
25using HeuristicLab.MainForm.WindowsForms;
26using HeuristicLab.Optimization;
27
28namespace HeuristicLab.Algorithms.DataAnalysis.Views {
29  [View("Gaussian Process Model")]
30  [Content(typeof(IGaussianProcessModel), true)]
31  public partial class GaussianProcessModelView : AsynchronousContentView {
32
33    public new IGaussianProcessModel Content {
34      get { return (IGaussianProcessModel)base.Content; }
35      set {
36        base.Content = value;
37      }
38    }
39
40    public GaussianProcessModelView()
41      : base() {
42      InitializeComponent();
43    }
44
45    protected override void OnContentChanged() {
46      base.OnContentChanged();
47      if (Content == null) {
48        // clear
49        resultCollectionView.Content = null;
50      } else {
51        resultCollectionView.Content = CreateResultCollection(Content);
52      }
53    }
54
55    private ResultCollection CreateResultCollection(IGaussianProcessModel gaussianProcessModel) {
56      var res = new ResultCollection();
57      res.Add(new Result("Mean Function", gaussianProcessModel.MeanFunction));
58      res.Add(new Result("Covariance Function", gaussianProcessModel.CovarianceFunction));
59      res.Add(new Result("Noise sigma", new DoubleValue(gaussianProcessModel.SigmaNoise)));
60      return res;
61    }
62  }
63}
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