1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2012 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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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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24 | using System.Drawing;
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25 | using System.Linq;
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26 | using System.Windows.Forms;
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27 | using System.Windows.Forms.DataVisualization.Charting;
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28 | using HeuristicLab.MainForm;
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29 | using HeuristicLab.MainForm.WindowsForms;
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30 |
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31 | namespace HeuristicLab.Problems.DataAnalysis.Views {
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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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35 |
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36 | #region variables
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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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40 | /// <summary>
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41 | /// approximate amount of bins
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42 | /// </summary>
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43 | protected const double bins = 25;
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44 | #endregion
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45 |
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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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51 | public RegressionSolutionResidualHistogram()
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52 | : base() {
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53 | InitializeComponent();
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54 | foreach (string series in new List<String>() { ALL_SAMPLES, TRAINING_SAMPLES, TEST_SAMPLES }) {
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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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63 | }
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64 | //configure axis
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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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75 | }
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76 |
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77 | private void RedrawChart() {
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78 | foreach (Series series in chart.Series) {
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79 | series.Points.Clear();
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80 | }
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81 | if (Content != null) {
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82 | List<double> residuals = CalculateResiduals(Content);
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83 |
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84 | double max = 0.0;
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85 | foreach (Series series in chart.Series) {
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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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89 | }
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90 |
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91 | // ALL_SAMPLES has to be calculated to know its highest frequency, but it is not shown in the beginning
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92 | chart.Series.Where(s => s.Name.Equals(ALL_SAMPLES)).First().Points.Clear();
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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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97 | ChartArea chartArea = chart.ChartAreas[0];
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98 | chartArea.AxisX.Minimum = -roundedMax - intervalWidth;
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99 | chartArea.AxisX.Maximum = roundedMax + intervalWidth;
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100 | // get the highest frequency of a residual of any series
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101 | chartArea.AxisY.Maximum = max;
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102 | if (chartArea.AxisY.Maximum < 0.1) {
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103 | chartArea.AxisY.Interval = 0.01;
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104 | chartArea.AxisY.Maximum = Math.Ceiling(chartArea.AxisY.Maximum * 100) / 100;
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105 | } else {
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106 | chartArea.AxisY.Interval = 0.1;
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107 | chartArea.AxisY.Maximum = Math.Ceiling(chartArea.AxisY.Maximum * 10) / 10;
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108 | }
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109 | chartArea.AxisX.Interval = intervalWidth;
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110 | int curBins = (int)Math.Round((roundedMax * 2) / intervalWidth);
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111 | //shifts the x axis label so that zero is in the middle
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112 | if (curBins % 2 == 0)
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113 | chartArea.AxisX.IntervalOffset = intervalWidth;
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114 | else
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115 | chartArea.AxisX.IntervalOffset = intervalWidth / 2;
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116 | }
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117 | }
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118 |
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119 | private List<double> CalculateResiduals(IRegressionSolution solution) {
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120 | List<double> residuals = new List<double>();
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121 |
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122 | IRegressionProblemData problemdata = solution.ProblemData;
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123 | List<double> targetValues = problemdata.Dataset.GetDoubleValues(Content.ProblemData.TargetVariable).ToList();
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124 | List<double> estimatedValues = solution.EstimatedValues.ToList();
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125 |
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126 | for (int i = 0; i < solution.ProblemData.Dataset.Rows; i++) {
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127 | double residual = estimatedValues[i] - targetValues[i];
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128 | residuals.Add(residual);
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129 | }
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130 | return residuals;
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131 | }
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132 |
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133 | private void CalculateFrequencies(List<double> residualValues, Series series) {
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134 | double roundedMax, intervalWidth;
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135 | CalculateResidualParameters(residualValues, out roundedMax, out intervalWidth);
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136 |
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137 | IEnumerable<double> relevantResiduals = residualValues;
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138 | IRegressionProblemData problemdata = Content.ProblemData;
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139 | if (series.Name.Equals(TRAINING_SAMPLES)) {
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140 | relevantResiduals = residualValues.Skip(problemdata.TrainingPartition.Start).Take(problemdata.TrainingPartition.Size);
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141 | } else if (series.Name.Equals(TEST_SAMPLES)) {
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142 | relevantResiduals = residualValues.Skip(problemdata.TestPartition.Start).Take(problemdata.TestPartition.Size);
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143 | }
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144 |
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145 | double intervalCenter = intervalWidth / 2.0;
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146 | double sampleCount = relevantResiduals.Count();
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147 | double current = -roundedMax;
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148 | DataPointCollection seriesPoints = series.Points;
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149 |
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150 | for (int i = 0; i <= bins; i++) {
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151 | IEnumerable<double> help = relevantResiduals.Where(x => x >= (current - intervalCenter) && x < (current + intervalCenter));
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152 | seriesPoints.AddXY(current, help.Count() / sampleCount);
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153 | seriesPoints[seriesPoints.Count - 1]["from"] = (current - intervalCenter).ToString();
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154 | seriesPoints[seriesPoints.Count - 1]["to"] = (current + intervalCenter).ToString();
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155 | current += intervalWidth;
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156 | }
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157 | }
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158 |
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159 | private void ToggleSeriesData(Series series) {
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160 | if (series.Points.Count > 0) { //checks if series is shown
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161 | if (chart.Series.Any(s => s != series && s.Points.Count > 0)) {
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162 | series.Points.Clear();
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163 | }
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164 | } else if (Content != null) {
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165 | List<double> residuals = CalculateResiduals(Content);
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166 | CalculateFrequencies(residuals, series);
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167 | chart.Legends[series.Legend].ForeColor = Color.Black;
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168 | chart.Refresh();
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169 | }
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170 | }
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171 |
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172 | private static void CalculateResidualParameters(List<double> residuals, out double roundedMax, out double intervalWidth) {
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173 | double realMax = Math.Max(Math.Abs(residuals.Min()), Math.Abs(residuals.Max()));
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174 | roundedMax = HumanRoundMax(realMax);
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175 | intervalWidth = (roundedMax * 2.0) / bins;
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176 | intervalWidth = HumanRoundMax(intervalWidth);
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177 | // sets roundedMax to a value, so that zero will be in the middle of the x axis
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178 | double help = realMax / intervalWidth;
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179 | help = help % 1 < 0.5 ? (int)help : (int)help + 1;
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180 | roundedMax = help * intervalWidth;
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181 | }
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182 |
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183 | private static double HumanRoundMax(double max) {
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184 | double base10;
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185 | if (max > 0) base10 = Math.Pow(10.0, Math.Floor(Math.Log10(max)));
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186 | else base10 = Math.Pow(10.0, Math.Ceiling(Math.Log10(-max)));
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187 | double rounding = (max > 0) ? base10 : -base10;
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188 | while (rounding < max) rounding += base10;
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189 | return rounding;
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190 | }
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191 |
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192 | #region events
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193 | protected override void RegisterContentEvents() {
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194 | base.RegisterContentEvents();
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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 | protected override void DeregisterContentEvents() {
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199 | base.DeregisterContentEvents();
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200 | Content.ModelChanged -= new EventHandler(Content_ModelChanged);
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201 | Content.ProblemDataChanged -= new EventHandler(Content_ProblemDataChanged);
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202 | }
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203 |
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204 | protected override void OnContentChanged() {
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205 | base.OnContentChanged();
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206 | RedrawChart();
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207 | }
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208 | private void Content_ProblemDataChanged(object sender, EventArgs e) {
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209 | RedrawChart();
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210 | }
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211 | private void Content_ModelChanged(object sender, EventArgs e) {
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212 | RedrawChart();
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213 | }
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214 | private void chart_MouseDown(object sender, MouseEventArgs e) {
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215 | HitTestResult result = chart.HitTest(e.X, e.Y);
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216 | if (result.ChartElementType == ChartElementType.LegendItem) {
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217 | ToggleSeriesData(result.Series);
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218 | }
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219 | }
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220 | private void chart_MouseMove(object sender, MouseEventArgs e) {
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221 | HitTestResult result = chart.HitTest(e.X, e.Y);
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222 | if (result.ChartElementType == ChartElementType.LegendItem)
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223 | Cursor = Cursors.Hand;
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224 | else
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225 | Cursor = Cursors.Default;
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226 | }
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227 | private void chart_CustomizeLegend(object sender, CustomizeLegendEventArgs e) {
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228 | if (chart.Series.Count != 3) return;
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229 | e.LegendItems[0].Cells[1].ForeColor = chart.Series[ALL_SAMPLES].Points.Count == 0 ? Color.Gray : Color.Black;
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230 | e.LegendItems[1].Cells[1].ForeColor = chart.Series[TRAINING_SAMPLES].Points.Count == 0 ? Color.Gray : Color.Black;
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231 | e.LegendItems[2].Cells[1].ForeColor = chart.Series[TEST_SAMPLES].Points.Count == 0 ? Color.Gray : Color.Black;
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232 | }
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233 | #endregion
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234 | }
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235 | }
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