[3408] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[5445] | 3 | * Copyright (C) 2002-2011 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[3408] | 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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[6760] | 22 | using System.Collections.Generic;
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[3408] | 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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[4068] | 26 | using System.Windows.Forms.DataVisualization.Charting;
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[3408] | 27 | using HeuristicLab.MainForm;
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| 28 | using HeuristicLab.MainForm.WindowsForms;
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| 29 |
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[3442] | 30 | namespace HeuristicLab.Problems.DataAnalysis.Views {
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[5975] | 31 | [View("Line Chart")]
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[5663] | 32 | [Content(typeof(IRegressionSolution))]
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[6760] | 33 | public partial class RegressionSolutionLineChartView : DataAnalysisSolutionEvaluationView {
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| 34 | private const string TARGETVARIABLE_SERIES_NAME = "Target Variable";
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| 35 | private const string ESTIMATEDVALUES_TRAINING_SERIES_NAME = "Estimated Values (training)";
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| 36 | private const string ESTIMATEDVALUES_TEST_SERIES_NAME = "Estimated Values (test)";
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| 37 | private const string ESTIMATEDVALUES_ALL_SERIES_NAME = "Estimated Values (all samples)";
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[3442] | 38 |
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[5663] | 39 | public new IRegressionSolution Content {
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| 40 | get { return (IRegressionSolution)base.Content; }
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[3916] | 41 | set { base.Content = value; }
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[3442] | 42 | }
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| 43 |
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[5663] | 44 | public RegressionSolutionLineChartView()
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[3408] | 45 | : base() {
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| 46 | InitializeComponent();
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| 47 | //configure axis
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[4651] | 48 | this.chart.CustomizeAllChartAreas();
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[3408] | 49 | this.chart.ChartAreas[0].CursorX.IsUserSelectionEnabled = true;
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| 50 | this.chart.ChartAreas[0].AxisX.ScaleView.Zoomable = true;
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[6760] | 51 | this.chart.ChartAreas[0].AxisX.IsStartedFromZero = true;
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[3707] | 52 | this.chart.ChartAreas[0].CursorX.Interval = 1;
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[3408] | 53 |
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| 54 | this.chart.ChartAreas[0].CursorY.IsUserSelectionEnabled = true;
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| 55 | this.chart.ChartAreas[0].AxisY.ScaleView.Zoomable = true;
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[3442] | 56 | this.chart.ChartAreas[0].CursorY.Interval = 0;
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[3408] | 57 | }
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| 58 |
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[3462] | 59 | private void RedrawChart() {
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[3442] | 60 | this.chart.Series.Clear();
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[4011] | 61 | if (Content != null) {
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[6760] | 62 | this.chart.ChartAreas[0].AxisX.Minimum = 0;
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| 63 | this.chart.ChartAreas[0].AxisX.Maximum = Content.ProblemData.Dataset.Rows - 1;
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| 64 |
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[4011] | 65 | this.chart.Series.Add(TARGETVARIABLE_SERIES_NAME);
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[5663] | 66 | this.chart.Series[TARGETVARIABLE_SERIES_NAME].LegendText = Content.ProblemData.TargetVariable;
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[4011] | 67 | this.chart.Series[TARGETVARIABLE_SERIES_NAME].ChartType = SeriesChartType.FastLine;
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[6760] | 68 | this.chart.Series[TARGETVARIABLE_SERIES_NAME].Points.DataBindXY(Enumerable.Range(0, Content.ProblemData.Dataset.Rows).ToArray(),
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| 69 | Content.ProblemData.Dataset.GetDoubleValues(Content.ProblemData.TargetVariable).ToArray());
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[3462] | 70 |
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[6760] | 71 | this.chart.Series.Add(ESTIMATEDVALUES_TRAINING_SERIES_NAME);
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| 72 | this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].LegendText = ESTIMATEDVALUES_TRAINING_SERIES_NAME;
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| 73 | this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].ChartType = SeriesChartType.FastLine;
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| 74 | this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].Points.DataBindXY(Content.ProblemData.TrainingIndizes.ToArray(), Content.EstimatedTrainingValues.ToArray());
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| 75 | this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].Tag = Content;
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| 76 | this.chart.DataManipulator.InsertEmptyPoints(1, IntervalType.Number, ESTIMATEDVALUES_TRAINING_SERIES_NAME);
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| 77 | this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].EmptyPointStyle.BorderWidth = 0;
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| 78 | this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].EmptyPointStyle.MarkerStyle = MarkerStyle.None;
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| 79 |
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| 80 |
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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.FastLine;
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| 84 | this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME].Points.DataBindXY(Content.ProblemData.TestIndizes.ToArray(), Content.EstimatedTestValues.ToArray());
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| 85 | this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME].Tag = Content;
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| 86 |
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| 87 |
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| 88 | int[] allIndizes = Enumerable.Range(0, Content.ProblemData.Dataset.Rows).Except(Content.ProblemData.TrainingIndizes).Except(Content.ProblemData.TestIndizes).ToArray();
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| 89 | var estimatedValues = Content.EstimatedValues.ToArray();
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| 90 | List<double> allEstimatedValues = allIndizes.Select(index => estimatedValues[index]).ToList();
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| 91 |
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| 92 | this.chart.Series.Add(ESTIMATEDVALUES_ALL_SERIES_NAME);
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| 93 | this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME].LegendText = ESTIMATEDVALUES_ALL_SERIES_NAME;
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| 94 | this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME].ChartType = SeriesChartType.FastLine;
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| 95 | this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME].Points.DataBindXY(allIndizes, allEstimatedValues);
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| 96 | this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME].Tag = Content;
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| 97 | this.chart.DataManipulator.InsertEmptyPoints(1, IntervalType.Number, ESTIMATEDVALUES_ALL_SERIES_NAME);
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| 98 | this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].EmptyPointStyle.BorderWidth = 0;
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| 99 | this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].EmptyPointStyle.MarkerStyle = MarkerStyle.None;
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| 100 | this.ToggleSeriesData(this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME]);
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| 101 |
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[4011] | 102 | UpdateCursorInterval();
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[6760] | 103 | this.UpdateStripLines();
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[4011] | 104 | }
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[3408] | 105 | }
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| 106 |
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[3707] | 107 | private void UpdateCursorInterval() {
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[6760] | 108 | var estimatedValues = this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].Points.Select(x => x.YValues[0]).DefaultIfEmpty(1.0);
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[3707] | 109 | var targetValues = this.chart.Series[TARGETVARIABLE_SERIES_NAME].Points.Select(x => x.YValues[0]).DefaultIfEmpty(1.0);
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| 110 | double estimatedValuesRange = estimatedValues.Max() - estimatedValues.Min();
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| 111 | double targetValuesRange = targetValues.Max() - targetValues.Min();
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| 112 | double interestingValuesRange = Math.Min(Math.Max(targetValuesRange, 1.0), Math.Max(estimatedValuesRange, 1.0));
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| 113 | double digits = (int)Math.Log10(interestingValuesRange) - 3;
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| 114 | double yZoomInterval = Math.Max(Math.Pow(10, digits), 10E-5);
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| 115 | this.chart.ChartAreas[0].CursorY.Interval = yZoomInterval;
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| 116 | }
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| 117 |
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[3442] | 118 | #region events
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| 119 | protected override void RegisterContentEvents() {
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| 120 | base.RegisterContentEvents();
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[5663] | 121 | Content.ModelChanged += new EventHandler(Content_ModelChanged);
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[3442] | 122 | Content.ProblemDataChanged += new EventHandler(Content_ProblemDataChanged);
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[3408] | 123 | }
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[3442] | 124 | protected override void DeregisterContentEvents() {
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| 125 | base.DeregisterContentEvents();
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[5663] | 126 | Content.ModelChanged -= new EventHandler(Content_ModelChanged);
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[3442] | 127 | Content.ProblemDataChanged -= new EventHandler(Content_ProblemDataChanged);
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[3408] | 128 | }
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| 129 |
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[6760] | 130 | protected override void OnContentChanged() {
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| 131 | base.OnContentChanged();
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| 132 | RedrawChart();
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| 133 | }
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[3916] | 134 | private void Content_ProblemDataChanged(object sender, EventArgs e) {
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[3462] | 135 | RedrawChart();
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[3408] | 136 | }
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[5663] | 137 | private void Content_ModelChanged(object sender, EventArgs e) {
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[3462] | 138 | RedrawChart();
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[3442] | 139 | }
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| 140 |
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[5006] | 141 |
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[6760] | 142 |
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[5006] | 143 | private void Chart_MouseDoubleClick(object sender, MouseEventArgs e) {
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| 144 | HitTestResult result = chart.HitTest(e.X, e.Y);
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| 145 | if (result.ChartArea != null && (result.ChartElementType == ChartElementType.PlottingArea ||
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| 146 | result.ChartElementType == ChartElementType.Gridlines) ||
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| 147 | result.ChartElementType == ChartElementType.StripLines) {
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| 148 | foreach (var axis in result.ChartArea.Axes)
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| 149 | axis.ScaleView.ZoomReset(int.MaxValue);
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| 150 | }
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| 151 | }
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[3442] | 152 | #endregion
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[3408] | 153 |
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| 154 | private void UpdateStripLines() {
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| 155 | this.chart.ChartAreas[0].AxisX.StripLines.Clear();
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[6760] | 156 |
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| 157 | 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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| 158 | foreach (var row in Content.ProblemData.TrainingIndizes) {
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| 159 | attr[row] += 1;
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| 160 | }
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| 161 | foreach (var row in Content.ProblemData.TestIndizes) {
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| 162 | attr[row] += 2;
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| 163 | }
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| 164 | int start = 0;
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| 165 | int curAttr = attr[start];
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| 166 | for (int row = 0; row < attr.Length; row++) {
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| 167 | if (attr[row] != curAttr) {
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| 168 | switch (curAttr) {
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| 169 | case 0: break;
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| 170 | case 1:
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| 171 | this.CreateAndAddStripLine("Training", start, row, Color.FromArgb(40, Color.Green), Color.Transparent);
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| 172 | break;
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| 173 | case 2:
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| 174 | this.CreateAndAddStripLine("Test", start, row, Color.FromArgb(40, Color.Red), Color.Transparent);
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| 175 | break;
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| 176 | case 3:
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| 177 | this.CreateAndAddStripLine("Training and Test", start, row, Color.FromArgb(40, Color.Green), Color.FromArgb(40, Color.Red), ChartHatchStyle.WideUpwardDiagonal);
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| 178 | break;
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| 179 | default:
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| 180 | // should not happen
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| 181 | break;
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| 182 | }
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| 183 | curAttr = attr[row];
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| 184 | start = row;
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| 185 | }
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| 186 | }
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[3408] | 187 | }
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| 188 |
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[6760] | 189 | private void CreateAndAddStripLine(string title, int start, int end, Color color, Color secondColor, ChartHatchStyle hatchStyle = ChartHatchStyle.None) {
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[3408] | 190 | StripLine stripLine = new StripLine();
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[6760] | 191 | stripLine.BackColor = color;
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| 192 | stripLine.BackSecondaryColor = secondColor;
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| 193 | stripLine.BackHatchStyle = hatchStyle;
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[3408] | 194 | stripLine.Text = title;
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| 195 | stripLine.Font = new Font("Times New Roman", 12, FontStyle.Bold);
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[6760] | 196 | // strip range is [start .. end] inclusive, but we evaluate [start..end[ (end is exclusive)
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| 197 | // the strip should be by one longer (starting at start - 0.5 and ending at end + 0.5)
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[3408] | 198 | stripLine.StripWidth = end - start;
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[6760] | 199 | 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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[3408] | 200 | this.chart.ChartAreas[0].AxisX.StripLines.Add(stripLine);
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| 201 | }
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[6760] | 202 |
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| 203 | private void ToggleSeriesData(Series series) {
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| 204 | if (series.Points.Count > 0) { //checks if series is shown
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| 205 | if (this.chart.Series.Any(s => s != series && s.Points.Count > 0)) {
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| 206 | series.Points.Clear();
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| 207 | }
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| 208 | } else if (Content != null) {
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| 209 | string targetVariableName = Content.ProblemData.TargetVariable;
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| 210 |
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| 211 | IEnumerable<int> indizes = null;
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| 212 | IEnumerable<double> predictedValues = null;
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| 213 | switch (series.Name) {
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| 214 | case ESTIMATEDVALUES_ALL_SERIES_NAME:
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| 215 | indizes = Enumerable.Range(0, Content.ProblemData.Dataset.Rows).Except(Content.ProblemData.TrainingIndizes).Except(Content.ProblemData.TestIndizes).ToArray();
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| 216 | var estimatedValues = Content.EstimatedValues.ToArray();
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| 217 | predictedValues = indizes.Select(index => estimatedValues[index]).ToList();
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| 218 | break;
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| 219 | case ESTIMATEDVALUES_TRAINING_SERIES_NAME:
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| 220 | indizes = Content.ProblemData.TrainingIndizes.ToArray();
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| 221 | predictedValues = Content.EstimatedTrainingValues.ToArray();
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| 222 | break;
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| 223 | case ESTIMATEDVALUES_TEST_SERIES_NAME:
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| 224 | indizes = Content.ProblemData.TestIndizes.ToArray();
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| 225 | predictedValues = Content.EstimatedTestValues.ToArray();
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| 226 | break;
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| 227 | }
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| 228 | series.Points.DataBindXY(indizes, predictedValues);
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| 229 | chart.DataManipulator.InsertEmptyPoints(1, IntervalType.Number, series.Name);
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| 230 | chart.Legends[series.Legend].ForeColor = Color.Black;
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| 231 | UpdateCursorInterval();
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| 232 | }
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| 233 | }
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| 234 |
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| 235 | private void chart_MouseMove(object sender, MouseEventArgs e) {
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| 236 | HitTestResult result = chart.HitTest(e.X, e.Y);
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| 237 | if (result.ChartElementType == ChartElementType.LegendItem && result.Series.Name != TARGETVARIABLE_SERIES_NAME)
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| 238 | Cursor = Cursors.Hand;
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| 239 | else
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| 240 | Cursor = Cursors.Default;
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| 241 | }
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| 242 | private void chart_MouseDown(object sender, MouseEventArgs e) {
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| 243 | HitTestResult result = chart.HitTest(e.X, e.Y);
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| 244 | if (result.ChartElementType == ChartElementType.LegendItem && result.Series.Name != TARGETVARIABLE_SERIES_NAME) {
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| 245 | ToggleSeriesData(result.Series);
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| 246 | }
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| 247 | }
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| 248 |
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| 249 | private void chart_CustomizeLegend(object sender, CustomizeLegendEventArgs e) {
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| 250 | if (chart.Series.Count != 4) return;
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| 251 | e.LegendItems[0].Cells[1].ForeColor = this.chart.Series[TARGETVARIABLE_SERIES_NAME].Points.Count == 0 ? Color.Gray : Color.Black;
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| 252 | e.LegendItems[1].Cells[1].ForeColor = this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].Points.Count == 0 ? Color.Gray : Color.Black;
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| 253 | e.LegendItems[2].Cells[1].ForeColor = this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME].Points.Count == 0 ? Color.Gray : Color.Black;
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| 254 | e.LegendItems[3].Cells[1].ForeColor = this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME].Points.Count == 0 ? Color.Gray : Color.Black;
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| 255 | }
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[3408] | 256 | }
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| 257 | }
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