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source: trunk/sources/HeuristicLab.DataPreprocessing/3.4/Content/ScatterPlotContent.cs @ 13508

Last change on this file since 13508 was 13508, checked in by pfleck, 8 years ago

#2559

  • Enabled type selection for creating/importing/exporting/applying.
  • Deleted unnecessary interfaces.
  • Reorganized source files of DataPreprocessing.
File size: 3.8 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.Analysis;
26using HeuristicLab.Common;
27using HeuristicLab.Core;
28
29namespace HeuristicLab.DataPreprocessing {
30
31  [Item("ScatterPlot", "Represents a scatter plot.")]
32  public class ScatterPlotContent : PreprocessingChartContent {
33
34    public string SelectedXVariable { get; set; }
35    public string SelectedYVariable { get; set; }
36    public string SelectedColorVariable { get; set; }
37
38    public ScatterPlotContent(IFilteredPreprocessingData preprocessingData)
39      : base(preprocessingData) {
40    }
41
42    public ScatterPlotContent(ScatterPlotContent content, Cloner cloner)
43      : base(content, cloner) {
44      this.SelectedXVariable = content.SelectedXVariable;
45      this.SelectedYVariable = content.SelectedYVariable;
46      this.SelectedColorVariable = content.SelectedColorVariable;
47    }
48
49    public static new Image StaticItemImage {
50      get { return HeuristicLab.Common.Resources.VSImageLibrary.Performance; }
51    }
52
53    public override IDeepCloneable Clone(Cloner cloner) {
54      return new ScatterPlotContent(this, cloner);
55    }
56
57    public ScatterPlot CreateScatterPlot(string variableNameX, string variableNameY, string variableNameColor = "-") {
58      ScatterPlot scatterPlot = new ScatterPlot();
59
60      IList<double> xValues = PreprocessingData.GetValues<double>(PreprocessingData.GetColumnIndex(variableNameX));
61      IList<double> yValues = PreprocessingData.GetValues<double>(PreprocessingData.GetColumnIndex(variableNameY));
62      if (variableNameColor == null || variableNameColor == "-") {
63        List<Point2D<double>> points = new List<Point2D<double>>();
64
65        for (int i = 0; i < xValues.Count; i++) {
66          Point2D<double> point = new Point2D<double>(xValues[i], yValues[i]);
67          points.Add(point);
68        }
69
70        ScatterPlotDataRow scdr = new ScatterPlotDataRow(variableNameX + " - " + variableNameY, "", points);
71        scatterPlot.Rows.Add(scdr);
72
73      } else {
74        var colorValues = PreprocessingData.GetValues<double>(PreprocessingData.GetColumnIndex(variableNameColor));
75        var data = xValues.Zip(yValues, (x, y) => new { x, y }).Zip(colorValues, (v, c) => new { v.x, v.y, c }).ToList();
76        var gradients = ColorGradient.Colors;
77        int curGradient = 0;
78        int numColors = colorValues.Distinct().Count();
79        foreach (var colorValue in colorValues.Distinct()) {
80          var values = data.Where(x => x.c == colorValue);
81          var row = new ScatterPlotDataRow(
82            variableNameX + " - " + variableNameY + " (" + colorValue + ")",
83            "",
84            values.Select(v => new Point2D<double>(v.x, v.y)),
85            new ScatterPlotDataRowVisualProperties() { Color = gradients[curGradient] });
86          curGradient += gradients.Count / numColors;
87          scatterPlot.Rows.Add(row);
88        }
89      }
90      return scatterPlot;
91    }
92  }
93}
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