Free cookie consent management tool by TermsFeed Policy Generator

source: trunk/sources/HeuristicLab.Problems.DataAnalysis.Views/3.4/Classification/DiscriminantFunctionClassificationSolutionEstimatedClassValuesView.cs @ 10217

Last change on this file since 10217 was 9845, checked in by mkommend, 11 years ago

#2094: Adapted estimated values view for discriminant function classification solutions.

File size: 3.9 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2013 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
21using System;
22using System.Linq;
23using System.Windows.Forms;
24using HeuristicLab.Data;
25using HeuristicLab.MainForm;
26using HeuristicLab.MainForm.WindowsForms;
27
28namespace HeuristicLab.Problems.DataAnalysis.Views {
29  [View("Estimated Class Values")]
30  [Content(typeof(IDiscriminantFunctionClassificationSolution))]
31  public partial class DiscriminantFunctionClassificationSolutionEstimatedClassValuesView : ClassificationSolutionEstimatedClassValuesView {
32    private const string TARGETVARIABLE_SERIES_NAME = "TargetVariable";
33    private const string ESTIMATEDVALUES_SERIES_NAME = "Estimated Class Values (all)";
34    private const string ESTIMATEDVALUES_TRAINING_SERIES_NAME = "Estimated Class Values (training)";
35    private const string ESTIMATEDVALUES_TEST_SERIES_NAME = "Estimated Class Values (test)";
36    private const string ESTIMATEDVALUES_DISCRIMINANT_SERIES_NAME = "Discriminant Values (all)";
37
38    public new IDiscriminantFunctionClassificationSolution Content {
39      get { return (IDiscriminantFunctionClassificationSolution)base.Content; }
40      set { base.Content = value; }
41    }
42
43    public DiscriminantFunctionClassificationSolutionEstimatedClassValuesView()
44      : base() {
45      InitializeComponent();
46    }
47
48    protected override void UpdateEstimatedValues() {
49      if (InvokeRequired) Invoke((Action)UpdateEstimatedValues);
50      else {
51        StringMatrix matrix = null;
52        if (Content != null) {
53          string[,] values = new string[Content.ProblemData.Dataset.Rows, 6];
54          double[] target = Content.ProblemData.Dataset.GetDoubleValues(Content.ProblemData.TargetVariable).ToArray();
55          double[] estimatedClassValue = Content.EstimatedClassValues.ToArray();
56          double[] estimatedValues = Content.EstimatedValues.ToArray();
57          for (int row = 0; row < target.Length; row++) {
58            values[row, 0] = row.ToString();
59            values[row, 1] = target[row].ToString();
60            values[row, 2] = estimatedClassValue[row].ToString();
61            values[row, 5] = estimatedValues[row].ToString();
62          }
63
64          var estimatedTraining = Content.EstimatedTrainingClassValues.GetEnumerator();
65          estimatedTraining.MoveNext();
66          foreach (var trainingRow in Content.ProblemData.TrainingIndices) {
67            values[trainingRow, 3] = estimatedTraining.Current.ToString();
68            estimatedTraining.MoveNext();
69          }
70          var estimatedTest = Content.EstimatedTestClassValues.GetEnumerator();
71          estimatedTest.MoveNext();
72          foreach (var testRow in Content.ProblemData.TestIndices) {
73            values[testRow, 4] = estimatedTest.Current.ToString();
74            estimatedTest.MoveNext();
75          }
76
77          matrix = new StringMatrix(values);
78          matrix.ColumnNames = new string[] { "Id", TARGETVARIABLE_SERIES_NAME, ESTIMATEDVALUES_SERIES_NAME, ESTIMATEDVALUES_TRAINING_SERIES_NAME, ESTIMATEDVALUES_TEST_SERIES_NAME, ESTIMATEDVALUES_DISCRIMINANT_SERIES_NAME };
79          matrix.SortableView = true;
80        }
81        matrixView.Content = matrix;
82      }
83    }
84  }
85}
Note: See TracBrowser for help on using the repository browser.