[7186] | 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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[7186] | 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 |
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| 22 | using System;
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| 23 | using System.Collections.Generic;
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[7255] | 24 | using System.Drawing;
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[7186] | 25 | using System.Linq;
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[7255] | 26 | using System.Windows.Forms;
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[7186] | 27 | using System.Windows.Forms.DataVisualization.Charting;
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| 28 | using HeuristicLab.MainForm;
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[7255] | 29 | using HeuristicLab.MainForm.WindowsForms;
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[7186] | 30 |
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[7255] | 31 | namespace HeuristicLab.Problems.DataAnalysis.Views {
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[7186] | 32 | [View("Residual Histogram")]
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| 33 | [Content(typeof(IRegressionSolution))]
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| 34 | public partial class RegressionSolutionResidualHistogram : DataAnalysisSolutionEvaluationView {
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[7485] | 35 |
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| 36 | #region variables
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[7255] | 37 | protected const string ALL_SAMPLES = "All samples";
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| 38 | protected const string TRAINING_SAMPLES = "Training samples";
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| 39 | protected const string TEST_SAMPLES = "Test samples";
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[7485] | 40 | /// <summary>
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| 41 | /// approximate amount of bins
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| 42 | /// </summary>
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[7255] | 43 | protected const double bins = 25;
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[7485] | 44 | #endregion
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[7255] | 45 |
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[7186] | 46 | public new IRegressionSolution Content {
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| 47 | get { return (IRegressionSolution)base.Content; }
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| 48 | set { base.Content = value; }
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| 49 | }
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| 50 |
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[7255] | 51 | public RegressionSolutionResidualHistogram()
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| 52 | : base() {
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[7186] | 53 | InitializeComponent();
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[8104] | 54 | foreach (string series in new List<String>() { ALL_SAMPLES, TRAINING_SAMPLES, TEST_SAMPLES }) {
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[7485] | 55 | chart.Series.Add(series);
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| 56 | chart.Series[series].LegendText = series;
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| 57 | chart.Series[series].ChartType = SeriesChartType.Column;
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| 58 | chart.Series[series]["PointWidth"] = "0.9";
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| 59 | chart.Series[series].BorderWidth = 1;
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| 60 | chart.Series[series].BorderDashStyle = ChartDashStyle.Solid;
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| 61 | chart.Series[series].BorderColor = Color.Black;
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| 62 | chart.Series[series].ToolTip = series + " Y = #VALY from #CUSTOMPROPERTY(from) to #CUSTOMPROPERTY(to)";
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[7255] | 63 | }
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[7186] | 64 | //configure axis
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[7485] | 65 | chart.CustomizeAllChartAreas();
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| 66 | chart.ChartAreas[0].AxisX.Title = "Residuals";
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| 67 | chart.ChartAreas[0].CursorX.IsUserSelectionEnabled = true;
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| 68 | chart.ChartAreas[0].AxisX.ScaleView.Zoomable = true;
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| 69 | chart.ChartAreas[0].CursorX.Interval = 1;
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| 70 | chart.ChartAreas[0].CursorY.Interval = 1;
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| 71 | chart.ChartAreas[0].AxisY.Title = "Relative Frequency";
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| 72 | chart.ChartAreas[0].CursorY.IsUserSelectionEnabled = true;
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| 73 | chart.ChartAreas[0].AxisY.ScaleView.Zoomable = true;
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| 74 | chart.ChartAreas[0].AxisY.IsStartedFromZero = true;
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[7186] | 75 | }
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| 76 |
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| 77 | private void RedrawChart() {
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[8104] | 78 | foreach (Series series in chart.Series) {
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| 79 | series.Points.Clear();
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[7255] | 80 | }
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[7186] | 81 | if (Content != null) {
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[8173] | 82 | List<double> residuals = CalculateResiduals(Content);
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[7186] | 83 |
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[8173] | 84 | double max = 0.0;
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[8104] | 85 | foreach (Series series in chart.Series) {
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[8173] | 86 | CalculateFrequencies(residuals, series);
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| 87 | double seriesMax = series.Points.Select(p => p.YValues.First()).Max();
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| 88 | max = max < seriesMax ? seriesMax : max;
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[7186] | 89 | }
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| 90 |
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[8173] | 91 | // ALL_SAMPLES has to be calculated to know its highest frequency, but it is not shown in the beginning
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[8176] | 92 | chart.Series.First(s => s.Name.Equals(ALL_SAMPLES)).Points.Clear();
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[8173] | 93 |
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| 94 | double roundedMax, intervalWidth;
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| 95 | CalculateResidualParameters(residuals, out roundedMax, out intervalWidth);
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| 96 |
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[7255] | 97 | ChartArea chartArea = chart.ChartAreas[0];
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[14255] | 98 | chartArea.AxisX.Title = string.Format("Residuals ({0})", Content.ProblemData.TargetVariable);
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[7503] | 99 | chartArea.AxisX.Minimum = -roundedMax - intervalWidth;
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| 100 | chartArea.AxisX.Maximum = roundedMax + intervalWidth;
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| 101 | // get the highest frequency of a residual of any series
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[8173] | 102 | chartArea.AxisY.Maximum = max;
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[7503] | 103 | if (chartArea.AxisY.Maximum < 0.1) {
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| 104 | chartArea.AxisY.Interval = 0.01;
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| 105 | chartArea.AxisY.Maximum = Math.Ceiling(chartArea.AxisY.Maximum * 100) / 100;
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| 106 | } else {
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| 107 | chartArea.AxisY.Interval = 0.1;
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| 108 | chartArea.AxisY.Maximum = Math.Ceiling(chartArea.AxisY.Maximum * 10) / 10;
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| 109 | }
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[7255] | 110 | chartArea.AxisX.Interval = intervalWidth;
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[7503] | 111 | int curBins = (int)Math.Round((roundedMax * 2) / intervalWidth);
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[7255] | 112 | //shifts the x axis label so that zero is in the middle
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| 113 | if (curBins % 2 == 0)
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| 114 | chartArea.AxisX.IntervalOffset = intervalWidth;
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| 115 | else
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| 116 | chartArea.AxisX.IntervalOffset = intervalWidth / 2;
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| 117 | }
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| 118 | }
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| 119 |
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[8173] | 120 | private List<double> CalculateResiduals(IRegressionSolution solution) {
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[8104] | 121 | List<double> residuals = new List<double>();
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[7255] | 122 |
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[8173] | 123 | IRegressionProblemData problemdata = solution.ProblemData;
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[7255] | 124 | List<double> targetValues = problemdata.Dataset.GetDoubleValues(Content.ProblemData.TargetVariable).ToList();
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[8173] | 125 | List<double> estimatedValues = solution.EstimatedValues.ToList();
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[7255] | 126 |
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[8173] | 127 | for (int i = 0; i < solution.ProblemData.Dataset.Rows; i++) {
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[15810] | 128 | if (double.IsNaN(estimatedValues[i]) || double.IsInfinity(estimatedValues[i])) continue;
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| 129 | if (double.IsNaN(targetValues[i]) || double.IsInfinity(targetValues[i])) continue;
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[7255] | 130 | double residual = estimatedValues[i] - targetValues[i];
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[8104] | 131 | residuals.Add(residual);
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[7255] | 132 | }
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| 133 | return residuals;
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| 134 | }
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| 135 |
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[8173] | 136 | private void CalculateFrequencies(List<double> residualValues, Series series) {
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| 137 | double roundedMax, intervalWidth;
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| 138 | CalculateResidualParameters(residualValues, out roundedMax, out intervalWidth);
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| 139 |
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[8104] | 140 | IEnumerable<double> relevantResiduals = residualValues;
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| 141 | IRegressionProblemData problemdata = Content.ProblemData;
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[8173] | 142 | if (series.Name.Equals(TRAINING_SAMPLES)) {
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[8104] | 143 | relevantResiduals = residualValues.Skip(problemdata.TrainingPartition.Start).Take(problemdata.TrainingPartition.Size);
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[8173] | 144 | } else if (series.Name.Equals(TEST_SAMPLES)) {
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[8104] | 145 | relevantResiduals = residualValues.Skip(problemdata.TestPartition.Start).Take(problemdata.TestPartition.Size);
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| 146 | }
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| 147 |
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[7255] | 148 | double intervalCenter = intervalWidth / 2.0;
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[8104] | 149 | double sampleCount = relevantResiduals.Count();
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[8173] | 150 | double current = -roundedMax;
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| 151 | DataPointCollection seriesPoints = series.Points;
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[7255] | 152 |
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| 153 | for (int i = 0; i <= bins; i++) {
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[8104] | 154 | IEnumerable<double> help = relevantResiduals.Where(x => x >= (current - intervalCenter) && x < (current + intervalCenter));
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[8173] | 155 | seriesPoints.AddXY(current, help.Count() / sampleCount);
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| 156 | seriesPoints[seriesPoints.Count - 1]["from"] = (current - intervalCenter).ToString();
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| 157 | seriesPoints[seriesPoints.Count - 1]["to"] = (current + intervalCenter).ToString();
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[7255] | 158 | current += intervalWidth;
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| 159 | }
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| 160 | }
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| 161 |
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[8104] | 162 | private void ToggleSeriesData(Series series) {
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| 163 | if (series.Points.Count > 0) { //checks if series is shown
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| 164 | if (chart.Series.Any(s => s != series && s.Points.Count > 0)) {
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| 165 | series.Points.Clear();
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| 166 | }
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| 167 | } else if (Content != null) {
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[8173] | 168 | List<double> residuals = CalculateResiduals(Content);
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| 169 | CalculateFrequencies(residuals, series);
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[8104] | 170 | chart.Legends[series.Legend].ForeColor = Color.Black;
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| 171 | chart.Refresh();
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| 172 | }
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| 173 | }
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| 174 |
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[8173] | 175 | private static void CalculateResidualParameters(List<double> residuals, out double roundedMax, out double intervalWidth) {
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| 176 | double realMax = Math.Max(Math.Abs(residuals.Min()), Math.Abs(residuals.Max()));
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| 177 | roundedMax = HumanRoundMax(realMax);
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| 178 | intervalWidth = (roundedMax * 2.0) / bins;
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| 179 | intervalWidth = HumanRoundMax(intervalWidth);
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| 180 | // sets roundedMax to a value, so that zero will be in the middle of the x axis
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| 181 | double help = realMax / intervalWidth;
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| 182 | help = help % 1 < 0.5 ? (int)help : (int)help + 1;
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| 183 | roundedMax = help * intervalWidth;
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| 184 | }
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| 185 |
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| 186 | private static double HumanRoundMax(double max) {
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[7255] | 187 | double base10;
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| 188 | if (max > 0) base10 = Math.Pow(10.0, Math.Floor(Math.Log10(max)));
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| 189 | else base10 = Math.Pow(10.0, Math.Ceiling(Math.Log10(-max)));
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| 190 | double rounding = (max > 0) ? base10 : -base10;
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| 191 | while (rounding < max) rounding += base10;
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| 192 | return rounding;
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| 193 | }
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| 194 |
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[7186] | 195 | #region events
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| 196 | protected override void RegisterContentEvents() {
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| 197 | base.RegisterContentEvents();
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| 198 | Content.ModelChanged += new EventHandler(Content_ModelChanged);
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| 199 | Content.ProblemDataChanged += new EventHandler(Content_ProblemDataChanged);
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| 200 | }
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| 201 | protected override void DeregisterContentEvents() {
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| 202 | base.DeregisterContentEvents();
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| 203 | Content.ModelChanged -= new EventHandler(Content_ModelChanged);
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| 204 | Content.ProblemDataChanged -= new EventHandler(Content_ProblemDataChanged);
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| 205 | }
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| 206 |
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| 207 | protected override void OnContentChanged() {
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| 208 | base.OnContentChanged();
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| 209 | RedrawChart();
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| 210 | }
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| 211 | private void Content_ProblemDataChanged(object sender, EventArgs e) {
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| 212 | RedrawChart();
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| 213 | }
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| 214 | private void Content_ModelChanged(object sender, EventArgs e) {
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| 215 | RedrawChart();
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| 216 | }
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[7255] | 217 | private void chart_MouseDown(object sender, MouseEventArgs e) {
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| 218 | HitTestResult result = chart.HitTest(e.X, e.Y);
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| 219 | if (result.ChartElementType == ChartElementType.LegendItem) {
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| 220 | ToggleSeriesData(result.Series);
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| 221 | }
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| 222 | }
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| 223 | private void chart_MouseMove(object sender, MouseEventArgs e) {
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| 224 | HitTestResult result = chart.HitTest(e.X, e.Y);
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| 225 | if (result.ChartElementType == ChartElementType.LegendItem)
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| 226 | Cursor = Cursors.Hand;
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| 227 | else
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| 228 | Cursor = Cursors.Default;
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| 229 | }
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| 230 | private void chart_CustomizeLegend(object sender, CustomizeLegendEventArgs e) {
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| 231 | if (chart.Series.Count != 3) return;
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[7485] | 232 | e.LegendItems[0].Cells[1].ForeColor = chart.Series[ALL_SAMPLES].Points.Count == 0 ? Color.Gray : Color.Black;
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| 233 | e.LegendItems[1].Cells[1].ForeColor = chart.Series[TRAINING_SAMPLES].Points.Count == 0 ? Color.Gray : Color.Black;
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| 234 | e.LegendItems[2].Cells[1].ForeColor = chart.Series[TEST_SAMPLES].Points.Count == 0 ? Color.Gray : Color.Black;
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[7255] | 235 | }
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[7186] | 236 | #endregion
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| 237 | }
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| 238 | }
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