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source: trunk/sources/HeuristicLab.DataPreprocessing/3.4/Implementations/HistogramContent.cs @ 12663

Last change on this file since 12663 was 12012, checked in by ascheibe, 10 years ago

#2212 merged r12008, r12009, r12010 back into trunk

File size: 2.6 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.Collections.Generic;
23using System.Drawing;
24using System.Linq;
25using HeuristicLab.Common;
26using HeuristicLab.Core;
27using HeuristicLab.DataPreprocessing.Interfaces;
28
29namespace HeuristicLab.DataPreprocessing {
30  [Item("Histogram", "Represents the histogram grid.")]
31  public class HistogramContent : PreprocessingChartContent {
32
33    public static new Image StaticItemImage {
34      get { return HeuristicLab.Common.Resources.VSImageLibrary.Statistics; }
35    }
36    private const int MAX_DISTINCT_VALUES_FOR_CLASSIFCATION = 20;
37
38    private int classifierVariableIndex = 0;
39
40    public int ClassifierVariableIndex {
41      get { return this.classifierVariableIndex; }
42      set { this.classifierVariableIndex = value; }
43    }
44
45
46    public HistogramContent(IFilteredPreprocessingData preprocessingData)
47      : base(preprocessingData) {
48      AllInOneMode = false;
49    }
50
51    public HistogramContent(HistogramContent content, Cloner cloner)
52      : base(content, cloner) {
53    }
54    public override IDeepCloneable Clone(Cloner cloner) {
55      return new HistogramContent(this, cloner);
56    }
57
58    public IEnumerable<string> GetVariableNamesForHistogramClassification() {
59      List<string> doubleVariableNames = new List<string>();
60
61      //only return variable names from type double
62      for (int i = 0; i < PreprocessingData.Columns; ++i) {
63        if (PreprocessingData.VariableHasType<double>(i)) {
64          double distinctValueCount = PreprocessingData.GetValues<double>(i).GroupBy(x => x).Count();
65          bool distinctValuesOk = distinctValueCount <= MAX_DISTINCT_VALUES_FOR_CLASSIFCATION;
66          if (distinctValuesOk)
67            doubleVariableNames.Add(PreprocessingData.GetVariableName(i));
68        }
69      }
70      return doubleVariableNames;
71    }
72
73  }
74}
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