1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2011 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 | protected const string ALL_SAMPLES = "All samples";
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36 | protected const string TRAINING_SAMPLES = "Training samples";
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37 | protected const string TEST_SAMPLES = "Test samples";
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38 |
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39 | //to reduce code duplication
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40 | protected static string[] ALL_SERIES = new string[] { ALL_SAMPLES, TRAINING_SAMPLES, TEST_SAMPLES };
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41 |
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42 | //approximate amount of bins
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43 | protected const double bins = 25;
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44 |
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45 | /*
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46 | * keeps for all series a list for all bins with the position of the bin, the relative frequency of the
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47 | * residuals and the beginning and the end of the interval of the bin
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48 | */
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49 | protected Dictionary<string, List<List<double>>> relativeFrequencies;
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50 |
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51 | public new IRegressionSolution Content {
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52 | get { return (IRegressionSolution)base.Content; }
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53 | set { base.Content = value; }
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54 | }
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55 |
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56 | public RegressionSolutionResidualHistogram()
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57 | : base() {
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58 | InitializeComponent();
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59 |
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60 | relativeFrequencies = new Dictionary<string, List<List<double>>>();
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61 |
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62 | foreach (string series in ALL_SERIES) {
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63 | this.chart.Series.Add(series);
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64 | this.chart.Series[series].LegendText = series;
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65 | this.chart.Series[series].ChartType = SeriesChartType.Column;
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66 | this.chart.Series[series]["PointWidth"] = "0.9";
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67 | this.chart.Series[series].BorderWidth = 1;
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68 | this.chart.Series[series].BorderDashStyle = ChartDashStyle.Solid;
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69 | this.chart.Series[series].BorderColor = Color.Black;
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70 | this.chart.Series[series].ToolTip = series + " Y = #VALY from #CUSTOMPROPERTY(from) to #CUSTOMPROPERTY(to)";
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71 |
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72 | relativeFrequencies[series] = new List<List<double>>();
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73 | }
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74 |
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75 | //configure axis
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76 | this.chart.CustomizeAllChartAreas();
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77 | this.chart.ChartAreas[0].AxisX.Title = "Residuals";
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78 | this.chart.ChartAreas[0].CursorX.IsUserSelectionEnabled = true;
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79 | this.chart.ChartAreas[0].AxisX.ScaleView.Zoomable = true;
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80 | this.chart.ChartAreas[0].CursorX.Interval = 1;
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81 | this.chart.ChartAreas[0].CursorY.Interval = 1;
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82 |
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83 | this.chart.ChartAreas[0].AxisY.Title = "Relative Frequency";
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84 | this.chart.ChartAreas[0].CursorY.IsUserSelectionEnabled = true;
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85 | this.chart.ChartAreas[0].AxisY.ScaleView.Zoomable = true;
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86 | this.chart.ChartAreas[0].AxisY.IsStartedFromZero = true;
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87 | }
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88 |
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89 | private void RedrawChart() {
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90 |
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91 | foreach (string series in ALL_SERIES) {
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92 | this.chart.Series[series].Points.Clear();
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93 | this.relativeFrequencies[series].Clear();
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94 | }
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95 |
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96 | if (Content != null) {
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97 |
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98 | Dictionary<string, List<double>> residuals = CalculateResiduals();
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99 |
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100 | double max = Math.Max(Math.Abs(residuals[ALL_SAMPLES].Min()), Math.Abs(residuals[ALL_SAMPLES].Max()));
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101 | double intervalWidth = (max * 2.0) / bins;
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102 |
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103 | max = HumanRoundMax(max);
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104 | intervalWidth = HumanRoundMax(intervalWidth);
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105 |
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106 | foreach (string series in ALL_SERIES) {
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107 | CalculateFrequencies(residuals[series], series, max, intervalWidth);
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108 | }
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109 |
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110 | ChartArea chartArea = chart.ChartAreas[0];
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111 |
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112 | chartArea.AxisX.Minimum = -max - intervalWidth;
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113 | chartArea.AxisX.Maximum = max + intervalWidth;
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114 | chartArea.AxisY.Maximum = relativeFrequencies[ALL_SAMPLES].Select(x => x.ElementAt(1)).Max() + 0.02;
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115 | chartArea.AxisY.Interval = 0.1;
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116 |
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117 | chartArea.AxisX.Interval = intervalWidth;
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118 | int curBins = (int)Math.Round(max / intervalWidth);
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119 | //shifts the x axis label so that zero is in the middle
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120 | if (curBins % 2 == 0)
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121 | chartArea.AxisX.IntervalOffset = intervalWidth;
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122 | else
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123 | chartArea.AxisX.IntervalOffset = intervalWidth / 2;
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124 | }
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125 | }
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126 |
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127 | private Dictionary<string, List<double>> CalculateResiduals() {
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128 | Dictionary<string, List<double>> residuals = new Dictionary<string, List<double>>();
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129 |
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130 | foreach (string series in ALL_SERIES) {
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131 | residuals[series] = new List<double>();
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132 | }
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133 |
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134 | IRegressionProblemData problemdata = Content.ProblemData;
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135 | List<double> targetValues = problemdata.Dataset.GetDoubleValues(Content.ProblemData.TargetVariable).ToList();
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136 | List<double> estimatedValues = Content.EstimatedValues.ToList();
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137 |
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138 | for (int i = 0; i < Content.ProblemData.Dataset.Rows; i++) {
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139 | double residual = estimatedValues[i] - targetValues[i];
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140 | residuals[ALL_SAMPLES].Add(residual);
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141 | if (i >= problemdata.TrainingPartition.Start && i < problemdata.TrainingPartition.End)
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142 | residuals[TRAINING_SAMPLES].Add(residual);
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143 | if (i >= problemdata.TestPartition.Start && i < problemdata.TestPartition.End)
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144 | residuals[TEST_SAMPLES].Add(residual);
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145 | }
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146 |
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147 | return residuals;
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148 | }
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149 |
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150 | private void CalculateFrequencies(List<double> residualValues, string series, double max, double intervalWidth) {
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151 | Series residualSeries = this.chart.Series[series];
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152 |
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153 | double intervalCenter = intervalWidth / 2.0;
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154 | double sampleCount = residualValues.Count();
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155 | double current = -max;
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156 |
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157 | for (int i = 0; i <= bins; i++) {
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158 | IEnumerable<double> help = residualValues.Where(x => x >= (current - intervalCenter) && x < (current + intervalCenter));
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159 | relativeFrequencies[series].Add(new List<double>() { current, help.Count() / sampleCount, current - intervalCenter, current + intervalCenter });
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160 | current += intervalWidth;
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161 | }
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162 |
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163 | ShowValues(residualSeries, relativeFrequencies[series]);
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164 | }
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165 |
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166 | private void ToggleSeriesData(Series series) {
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167 | if (series.Points.Count > 0) { //checks if series is shown
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168 | if (this.chart.Series.Any(s => s != series && s.Points.Count > 0)) {
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169 | series.Points.Clear();
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170 | }
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171 | } else if (Content != null) {
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172 | ShowValues(series, relativeFrequencies[series.Name]);
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173 | chart.Legends[series.Legend].ForeColor = Color.Black;
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174 | chart.Refresh();
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175 | }
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176 | }
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177 |
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178 | private void ShowValues(Series series, List<List<double>> relativeSeriesFrequencies) {
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179 | DataPointCollection seriesPoints = series.Points;
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180 |
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181 | foreach (var valueList in relativeSeriesFrequencies) {
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182 | seriesPoints.AddXY(valueList[0], valueList[1]);
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183 | seriesPoints[seriesPoints.Count - 1]["from"] = valueList[2].ToString();
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184 | seriesPoints[seriesPoints.Count - 1]["to"] = valueList[3].ToString();
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185 | }
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186 | }
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187 |
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188 | private double HumanRoundMax(double max) {
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189 | double base10;
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190 | if (max > 0) base10 = Math.Pow(10.0, Math.Floor(Math.Log10(max)));
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191 | else base10 = Math.Pow(10.0, Math.Ceiling(Math.Log10(-max)));
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192 | double rounding = (max > 0) ? base10 : -base10;
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193 | while (rounding < max) rounding += base10;
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194 | return rounding;
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195 | }
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196 |
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197 | #region events
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198 | protected override void RegisterContentEvents() {
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199 | base.RegisterContentEvents();
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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 | protected override void DeregisterContentEvents() {
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204 | base.DeregisterContentEvents();
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205 | Content.ModelChanged -= new EventHandler(Content_ModelChanged);
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206 | Content.ProblemDataChanged -= new EventHandler(Content_ProblemDataChanged);
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207 | }
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208 |
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209 | protected override void OnContentChanged() {
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210 | base.OnContentChanged();
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211 | RedrawChart();
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212 | }
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213 | private void Content_ProblemDataChanged(object sender, EventArgs e) {
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214 | RedrawChart();
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215 | }
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216 | private void Content_ModelChanged(object sender, EventArgs e) {
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217 | RedrawChart();
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218 | }
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219 |
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220 | private void chart_MouseDown(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 | ToggleSeriesData(result.Series);
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224 | }
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225 | }
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226 | private void chart_MouseMove(object sender, MouseEventArgs e) {
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227 | HitTestResult result = chart.HitTest(e.X, e.Y);
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228 | if (result.ChartElementType == ChartElementType.LegendItem)
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229 | Cursor = Cursors.Hand;
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230 | else
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231 | Cursor = Cursors.Default;
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232 | }
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233 | private void chart_CustomizeLegend(object sender, CustomizeLegendEventArgs e) {
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234 | if (chart.Series.Count != 3) return;
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235 | e.LegendItems[0].Cells[1].ForeColor = this.chart.Series[ALL_SAMPLES].Points.Count == 0 ? Color.Gray : Color.Black;
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236 | e.LegendItems[1].Cells[1].ForeColor = this.chart.Series[TRAINING_SAMPLES].Points.Count == 0 ? Color.Gray : Color.Black;
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237 | e.LegendItems[2].Cells[1].ForeColor = this.chart.Series[TEST_SAMPLES].Points.Count == 0 ? Color.Gray : Color.Black;
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238 | }
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239 | #endregion
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240 | }
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241 | }
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