[8473] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[16565] | 3 | * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[8473] | 4 | *
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| 5 | * This file is part of HeuristicLab.
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| 6 | *
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| 7 | * HeuristicLab is free software: you can redistribute it and/or modify
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| 8 | * it under the terms of the GNU General Public License as published by
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| 9 | * the Free Software Foundation, either version 3 of the License, or
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| 10 | * (at your option) any later version.
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| 11 | *
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| 12 | * HeuristicLab is distributed in the hope that it will be useful,
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| 13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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| 14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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| 15 | * GNU General Public License for more details.
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| 16 | *
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| 17 | * You should have received a copy of the GNU General Public License
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| 18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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| 19 | */
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| 20 | #endregion
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| 21 | using System;
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| 22 | using System.Collections.Generic;
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| 23 | using System.Drawing;
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| 24 | using System.Linq;
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| 25 | using System.Windows.Forms;
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| 26 | using System.Windows.Forms.DataVisualization.Charting;
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| 27 | using HeuristicLab.MainForm;
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[13856] | 28 | using HeuristicLab.Problems.DataAnalysis;
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[8473] | 29 | using HeuristicLab.Problems.DataAnalysis.Views;
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[14255] | 30 | using HeuristicLab.Visualization.ChartControlsExtensions;
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[8473] | 31 |
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| 32 | namespace HeuristicLab.Algorithms.DataAnalysis.Views {
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[8678] | 33 | [View("Line Chart (95% confidence interval)")]
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[14099] | 34 | [Content(typeof(IConfidenceRegressionSolution))]
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| 35 | public partial class ConfidenceRegressionSolutionLineChartView : DataAnalysisSolutionEvaluationView {
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[8473] | 36 | private const string TARGETVARIABLE_SERIES_NAME = "Target Variable";
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| 37 | private const string ESTIMATEDVALUES_TRAINING_SERIES_NAME = "Estimated Values (training)";
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| 38 | private const string ESTIMATEDVALUES_TEST_SERIES_NAME = "Estimated Values (test)";
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| 39 | private const string ESTIMATEDVALUES_ALL_SERIES_NAME = "Estimated Values (all samples)";
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| 40 |
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[14099] | 41 | public new IConfidenceRegressionSolution Content {
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| 42 | get { return (IConfidenceRegressionSolution)base.Content; }
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[8473] | 43 | set { base.Content = value; }
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| 44 | }
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| 45 |
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[14099] | 46 | public ConfidenceRegressionSolutionLineChartView()
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[8473] | 47 | : base() {
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| 48 | InitializeComponent();
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| 49 | //configure axis
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| 50 | this.chart.CustomizeAllChartAreas();
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| 51 | this.chart.ChartAreas[0].CursorX.IsUserSelectionEnabled = true;
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| 52 | this.chart.ChartAreas[0].AxisX.ScaleView.Zoomable = true;
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| 53 | this.chart.ChartAreas[0].AxisX.IsStartedFromZero = true;
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| 54 | this.chart.ChartAreas[0].CursorX.Interval = 1;
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| 55 |
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| 56 | this.chart.ChartAreas[0].CursorY.IsUserSelectionEnabled = true;
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| 57 | this.chart.ChartAreas[0].AxisY.ScaleView.Zoomable = true;
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| 58 | this.chart.ChartAreas[0].CursorY.Interval = 0;
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| 59 | }
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| 60 |
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| 61 | private void RedrawChart() {
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| 62 | this.chart.Series.Clear();
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| 63 | if (Content != null) {
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| 64 | this.chart.ChartAreas[0].AxisX.Minimum = 0;
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| 65 | this.chart.ChartAreas[0].AxisX.Maximum = Content.ProblemData.Dataset.Rows - 1;
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| 66 |
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| 67 | // training series
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| 68 | this.chart.Series.Add(ESTIMATEDVALUES_TRAINING_SERIES_NAME);
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| 69 | this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].LegendText = ESTIMATEDVALUES_TRAINING_SERIES_NAME;
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| 70 | this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].ChartType = SeriesChartType.Range;
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| 71 | this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].EmptyPointStyle.Color = this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].Color;
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| 72 | var mean = Content.EstimatedTrainingValues.ToArray();
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[13823] | 73 | var s2 = Content.EstimatedTrainingVariances.ToArray();
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[13121] | 74 | var lower = mean.Zip(s2, GetLowerConfBound).ToArray();
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| 75 | var upper = mean.Zip(s2, GetUpperConfBound).ToArray();
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[8473] | 76 | this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].Points.DataBindXY(Content.ProblemData.TrainingIndices.ToArray(), lower, upper);
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| 77 | this.InsertEmptyPoints(this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME]);
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| 78 | this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].Tag = Content;
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[8475] | 79 |
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[8473] | 80 | // test series
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| 81 | this.chart.Series.Add(ESTIMATEDVALUES_TEST_SERIES_NAME);
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| 82 | this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME].LegendText = ESTIMATEDVALUES_TEST_SERIES_NAME;
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| 83 | this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME].ChartType = SeriesChartType.Range;
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| 84 |
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| 85 | mean = Content.EstimatedTestValues.ToArray();
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[13823] | 86 | s2 = Content.EstimatedTestVariances.ToArray();
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[13121] | 87 | lower = mean.Zip(s2, GetLowerConfBound).ToArray();
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| 88 | upper = mean.Zip(s2, GetUpperConfBound).ToArray();
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[8473] | 89 | this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME].Points.DataBindXY(Content.ProblemData.TestIndices.ToArray(), lower, upper);
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| 90 | this.InsertEmptyPoints(this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME]);
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| 91 | this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME].Tag = Content;
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[8475] | 92 |
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[8473] | 93 | // series of remaining points
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| 94 | int[] allIndices = Enumerable.Range(0, Content.ProblemData.Dataset.Rows).Except(Content.ProblemData.TrainingIndices).Except(Content.ProblemData.TestIndices).ToArray();
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[8484] | 95 | mean = Content.EstimatedValues.ToArray();
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[13823] | 96 | s2 = Content.EstimatedVariances.ToArray();
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[13121] | 97 | lower = mean.Zip(s2, GetLowerConfBound).ToArray();
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| 98 | upper = mean.Zip(s2, GetUpperConfBound).ToArray();
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[8484] | 99 | List<double> allLower = allIndices.Select(index => lower[index]).ToList();
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| 100 | List<double> allUpper = allIndices.Select(index => upper[index]).ToList();
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[8473] | 101 | this.chart.Series.Add(ESTIMATEDVALUES_ALL_SERIES_NAME);
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| 102 | this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME].LegendText = ESTIMATEDVALUES_ALL_SERIES_NAME;
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| 103 | this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME].ChartType = SeriesChartType.Range;
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[8484] | 104 | if (allIndices.Count() > 0) {
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| 105 | this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME].Points.DataBindXY(allIndices, allLower, allUpper);
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| 106 | this.InsertEmptyPoints(this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME]);
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| 107 | }
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[8473] | 108 | this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME].Tag = Content;
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[8475] | 109 |
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| 110 | // target
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| 111 | this.chart.Series.Add(TARGETVARIABLE_SERIES_NAME);
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[14255] | 112 | this.chart.Series[TARGETVARIABLE_SERIES_NAME].LegendText = TARGETVARIABLE_SERIES_NAME;
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[8475] | 113 | this.chart.Series[TARGETVARIABLE_SERIES_NAME].ChartType = SeriesChartType.FastLine;
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| 114 | this.chart.Series[TARGETVARIABLE_SERIES_NAME].Points.DataBindXY(Enumerable.Range(0, Content.ProblemData.Dataset.Rows).ToArray(),
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| 115 | Content.ProblemData.Dataset.GetDoubleValues(Content.ProblemData.TargetVariable).ToArray());
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| 116 |
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[8473] | 117 | this.ToggleSeriesData(this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME]);
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| 118 |
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[8580] | 119 |
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[8562] | 120 | // the series have been added in different order than in the normal line chart
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| 121 | // --> adapt coloring;
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[8580] | 122 | chart.ApplyPaletteColors();
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| 123 | this.chart.Palette = ChartColorPalette.None;
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| 124 | var s0Color = chart.Series[0].Color;
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| 125 | var s1Color = chart.Series[1].Color;
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| 126 | var s2Color = chart.Series[2].Color;
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| 127 | var s3Color = chart.Series[3].Color;
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| 128 | this.chart.PaletteCustomColors = new Color[] { s1Color, s2Color, s3Color, s0Color };
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[8562] | 129 |
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[14255] | 130 | // set the y-axis
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| 131 | var axisY = this.chart.ChartAreas[0].AxisY;
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| 132 | axisY.Title = Content.ProblemData.TargetVariable;
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| 133 | double min = double.MaxValue, max = double.MinValue;
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| 134 | foreach (var point in chart.Series.SelectMany(x => x.Points)) {
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| 135 | if (!point.YValues.Any() || double.IsInfinity(point.YValues[0]) || double.IsNaN(point.YValues[0]))
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| 136 | continue;
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| 137 | var y = point.YValues[0];
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| 138 | if (y < min)
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| 139 | min = y;
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| 140 | if (y > max)
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| 141 | max = y;
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| 142 | }
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| 143 |
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| 144 | double axisMin, axisMax, axisInterval;
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| 145 | ChartUtil.CalculateOptimalAxisInterval(min, max, out axisMin, out axisMax, out axisInterval);
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| 146 | axisY.Minimum = axisMin;
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| 147 | axisY.Maximum = axisMax;
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| 148 | axisY.Interval = axisInterval;
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| 149 |
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[8473] | 150 | UpdateCursorInterval();
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| 151 | this.UpdateStripLines();
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| 152 | }
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| 153 | }
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| 154 |
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| 155 | private void InsertEmptyPoints(Series series) {
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| 156 | int i = 0;
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| 157 | while (i < series.Points.Count - 1) {
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| 158 | if (series.Points[i].IsEmpty) {
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| 159 | ++i;
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| 160 | continue;
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| 161 | }
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| 162 |
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| 163 | var p1 = series.Points[i];
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| 164 | var p2 = series.Points[i + 1];
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| 165 | // check for consecutive indices
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| 166 | if ((int)p2.XValue - (int)p1.XValue != 1) {
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| 167 | // insert an empty point between p1 and p2 so that the line will be invisible (transparent)
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[8484] | 168 | var p = new DataPoint((int)((p1.XValue + p2.XValue) / 2), new double[] { 0.0, 0.0 }) { IsEmpty = true };
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| 169 | // insert
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[8473] | 170 | series.Points.Insert(i + 1, p);
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| 171 | }
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| 172 | ++i;
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| 173 | }
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| 174 | }
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| 175 |
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| 176 | private void UpdateCursorInterval() {
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| 177 | var estimatedValues = this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].Points.Select(x => x.YValues[0]).DefaultIfEmpty(1.0);
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| 178 | var targetValues = this.chart.Series[TARGETVARIABLE_SERIES_NAME].Points.Select(x => x.YValues[0]).DefaultIfEmpty(1.0);
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| 179 | double estimatedValuesRange = estimatedValues.Max() - estimatedValues.Min();
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| 180 | double targetValuesRange = targetValues.Max() - targetValues.Min();
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| 181 | double interestingValuesRange = Math.Min(Math.Max(targetValuesRange, 1.0), Math.Max(estimatedValuesRange, 1.0));
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| 182 | double digits = (int)Math.Log10(interestingValuesRange) - 3;
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| 183 | double yZoomInterval = Math.Max(Math.Pow(10, digits), 10E-5);
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| 184 | this.chart.ChartAreas[0].CursorY.Interval = yZoomInterval;
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| 185 | }
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| 186 |
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| 187 | #region events
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| 188 | protected override void RegisterContentEvents() {
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| 189 | base.RegisterContentEvents();
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| 190 | Content.ModelChanged += new EventHandler(Content_ModelChanged);
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| 191 | Content.ProblemDataChanged += new EventHandler(Content_ProblemDataChanged);
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| 192 | }
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| 193 | protected override void DeregisterContentEvents() {
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| 194 | base.DeregisterContentEvents();
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| 195 | Content.ModelChanged -= new EventHandler(Content_ModelChanged);
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| 196 | Content.ProblemDataChanged -= new EventHandler(Content_ProblemDataChanged);
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| 197 | }
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| 198 |
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| 199 | protected override void OnContentChanged() {
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| 200 | base.OnContentChanged();
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| 201 | RedrawChart();
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| 202 | }
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| 203 | private void Content_ProblemDataChanged(object sender, EventArgs e) {
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| 204 | RedrawChart();
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| 205 | }
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| 206 | private void Content_ModelChanged(object sender, EventArgs e) {
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| 207 | RedrawChart();
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| 208 | }
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| 209 |
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| 210 |
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| 211 |
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| 212 | private void Chart_MouseDoubleClick(object sender, MouseEventArgs e) {
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| 213 | HitTestResult result = chart.HitTest(e.X, e.Y);
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| 214 | if (result.ChartArea != null && (result.ChartElementType == ChartElementType.PlottingArea ||
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| 215 | result.ChartElementType == ChartElementType.Gridlines) ||
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| 216 | result.ChartElementType == ChartElementType.StripLines) {
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| 217 | foreach (var axis in result.ChartArea.Axes)
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| 218 | axis.ScaleView.ZoomReset(int.MaxValue);
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| 219 | }
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| 220 | }
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| 221 | #endregion
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| 222 |
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| 223 | private void UpdateStripLines() {
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| 224 | this.chart.ChartAreas[0].AxisX.StripLines.Clear();
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| 225 |
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| 226 | int[] attr = new int[Content.ProblemData.Dataset.Rows + 1]; // add a virtual last row that is again empty to simplify loop further down
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| 227 | foreach (var row in Content.ProblemData.TrainingIndices) {
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| 228 | attr[row] += 1;
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| 229 | }
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| 230 | foreach (var row in Content.ProblemData.TestIndices) {
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| 231 | attr[row] += 2;
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| 232 | }
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| 233 | int start = 0;
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| 234 | int curAttr = attr[start];
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| 235 | for (int row = 0; row < attr.Length; row++) {
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| 236 | if (attr[row] != curAttr) {
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| 237 | switch (curAttr) {
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| 238 | case 0: break;
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| 239 | case 1:
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| 240 | this.CreateAndAddStripLine("Training", start, row, Color.FromArgb(40, Color.Green), Color.Transparent);
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| 241 | break;
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| 242 | case 2:
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| 243 | this.CreateAndAddStripLine("Test", start, row, Color.FromArgb(40, Color.Red), Color.Transparent);
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| 244 | break;
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| 245 | case 3:
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| 246 | this.CreateAndAddStripLine("Training and Test", start, row, Color.FromArgb(40, Color.Green), Color.FromArgb(40, Color.Red), ChartHatchStyle.WideUpwardDiagonal);
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| 247 | break;
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| 248 | default:
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| 249 | // should not happen
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| 250 | break;
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| 251 | }
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| 252 | curAttr = attr[row];
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| 253 | start = row;
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| 254 | }
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| 255 | }
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| 256 | }
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| 257 |
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| 258 | private void CreateAndAddStripLine(string title, int start, int end, Color color, Color secondColor, ChartHatchStyle hatchStyle = ChartHatchStyle.None) {
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| 259 | StripLine stripLine = new StripLine();
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| 260 | stripLine.BackColor = color;
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| 261 | stripLine.BackSecondaryColor = secondColor;
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| 262 | stripLine.BackHatchStyle = hatchStyle;
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| 263 | stripLine.Text = title;
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| 264 | stripLine.Font = new Font("Times New Roman", 12, FontStyle.Bold);
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| 265 | // strip range is [start .. end] inclusive, but we evaluate [start..end[ (end is exclusive)
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| 266 | // the strip should be by one longer (starting at start - 0.5 and ending at end + 0.5)
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| 267 | stripLine.StripWidth = end - start;
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| 268 | stripLine.IntervalOffset = start - 0.5; // start slightly to the left of the first point to clearly indicate the first point in the partition
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| 269 | this.chart.ChartAreas[0].AxisX.StripLines.Add(stripLine);
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| 270 | }
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| 271 |
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| 272 | private void ToggleSeriesData(Series series) {
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| 273 | if (series.Points.Count > 0) { //checks if series is shown
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| 274 | if (this.chart.Series.Any(s => s != series && s.Points.Count > 0)) {
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| 275 | ClearPointsQuick(series.Points);
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| 276 | }
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| 277 | } else if (Content != null) {
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| 278 |
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| 279 | IEnumerable<int> indices = null;
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| 280 | IEnumerable<double> mean = null;
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| 281 | IEnumerable<double> s2 = null;
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| 282 | double[] lower = null;
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| 283 | double[] upper = null;
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| 284 | switch (series.Name) {
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| 285 | case ESTIMATEDVALUES_ALL_SERIES_NAME:
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| 286 | indices = Enumerable.Range(0, Content.ProblemData.Dataset.Rows).Except(Content.ProblemData.TrainingIndices).Except(Content.ProblemData.TestIndices).ToArray();
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| 287 | mean = Content.EstimatedValues.ToArray();
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[13823] | 288 | s2 = Content.EstimatedVariances.ToArray();
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[13121] | 289 | lower = mean.Zip(s2, GetLowerConfBound).ToArray();
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| 290 | upper = mean.Zip(s2, GetUpperConfBound).ToArray();
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[8473] | 291 | lower = indices.Select(index => lower[index]).ToArray();
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| 292 | upper = indices.Select(index => upper[index]).ToArray();
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| 293 | break;
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| 294 | case ESTIMATEDVALUES_TRAINING_SERIES_NAME:
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| 295 | indices = Content.ProblemData.TrainingIndices.ToArray();
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| 296 | mean = Content.EstimatedTrainingValues.ToArray();
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[13823] | 297 | s2 = Content.EstimatedTrainingVariances.ToArray();
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[13121] | 298 | lower = mean.Zip(s2, GetLowerConfBound).ToArray();
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| 299 | upper = mean.Zip(s2, GetUpperConfBound).ToArray();
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[8473] | 300 | break;
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| 301 | case ESTIMATEDVALUES_TEST_SERIES_NAME:
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| 302 | indices = Content.ProblemData.TestIndices.ToArray();
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| 303 | mean = Content.EstimatedTestValues.ToArray();
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[13823] | 304 | s2 = Content.EstimatedTestVariances.ToArray();
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[13121] | 305 | lower = mean.Zip(s2, GetLowerConfBound).ToArray();
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| 306 | upper = mean.Zip(s2, GetUpperConfBound).ToArray();
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[8473] | 307 | break;
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| 308 | }
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[8484] | 309 | if (indices.Count() > 0) {
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| 310 | series.Points.DataBindXY(indices, lower, upper);
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| 311 | this.InsertEmptyPoints(series);
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| 312 | chart.Legends[series.Legend].ForeColor = Color.Black;
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| 313 | UpdateCursorInterval();
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| 314 | chart.Refresh();
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| 315 | }
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[8473] | 316 | }
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| 317 | }
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| 318 |
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[13121] | 319 | private double GetLowerConfBound(double m, double s) {
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| 320 | return m - 1.96 * Math.Sqrt(s);
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| 321 | }
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| 322 |
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| 323 |
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| 324 | private double GetUpperConfBound(double m, double s) {
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| 325 | return m + 1.96 * Math.Sqrt(s);
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| 326 | }
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| 327 |
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[8473] | 328 | // workaround as per http://stackoverflow.com/questions/5744930/datapointcollection-clear-performance
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| 329 | private static void ClearPointsQuick(DataPointCollection points) {
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| 330 | points.SuspendUpdates();
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| 331 | while (points.Count > 0)
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| 332 | points.RemoveAt(points.Count - 1);
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| 333 | points.ResumeUpdates();
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| 334 | }
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| 335 |
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| 336 | private void chart_MouseMove(object sender, MouseEventArgs e) {
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| 337 | HitTestResult result = chart.HitTest(e.X, e.Y);
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| 338 | if (result.ChartElementType == ChartElementType.LegendItem && result.Series.Name != TARGETVARIABLE_SERIES_NAME)
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| 339 | Cursor = Cursors.Hand;
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| 340 | else
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| 341 | Cursor = Cursors.Default;
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| 342 | }
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| 343 | private void chart_MouseDown(object sender, MouseEventArgs e) {
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| 344 | HitTestResult result = chart.HitTest(e.X, e.Y);
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| 345 | if (result.ChartElementType == ChartElementType.LegendItem && result.Series.Name != TARGETVARIABLE_SERIES_NAME) {
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| 346 | ToggleSeriesData(result.Series);
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| 347 | }
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| 348 | }
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| 349 |
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| 350 | private void chart_CustomizeLegend(object sender, CustomizeLegendEventArgs e) {
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| 351 | if (chart.Series.Count != 4) return;
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[8484] | 352 | e.LegendItems[0].Cells[1].ForeColor = this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].Points.Count == 0 ? Color.Gray : Color.Black;
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| 353 | e.LegendItems[1].Cells[1].ForeColor = this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME].Points.Count == 0 ? Color.Gray : Color.Black;
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| 354 | e.LegendItems[2].Cells[1].ForeColor = this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME].Points.Count == 0 ? Color.Gray : Color.Black;
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| 355 | e.LegendItems[3].Cells[1].ForeColor = this.chart.Series[TARGETVARIABLE_SERIES_NAME].Points.Count == 0 ? Color.Gray : Color.Black;
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[8473] | 356 | }
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| 357 | }
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| 358 | }
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