source: trunk/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionResidualAnalysisView.cs @ 17539

Last change on this file since 17539 was 17539, checked in by mkommend, 2 months ago

#3038: Removed filtering of variables with only one distinct value in ResidualAnalysisView.

File size: 6.1 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) Heuristic and Evolutionary Algorithms Laboratory (HEAL)
4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21using System;
22using System.Collections.Generic;
23using System.Drawing;
24using System.Linq;
25using HeuristicLab.Data;
26using HeuristicLab.MainForm;
27using HeuristicLab.Optimization;
28
29namespace HeuristicLab.Problems.DataAnalysis.Views {
30  [View("Residual Analysis")]
31  [Content(typeof(IRegressionSolution))]
32  public sealed partial class RegressionSolutionResidualAnalysisView : DataAnalysisSolutionEvaluationView {
33
34    // names should be relatively save to prevent collisions with variable names in the dataset
35    private const string TargetLabel = "> Target";
36    private const string PredictionLabel = "> Prediction";
37    private const string ResidualLabel = "> Residual";
38    private const string AbsResidualLabel = "> Residual (abs.)";
39    private const string RelativeErrorLabel = "> Relative Error";
40    private const string AbsRelativeErrorLabel = "> Relative Error (abs.)";
41    private const string PartitionLabel = "> Partition";
42
43    public new IRegressionSolution Content {
44      get { return (IRegressionSolution)base.Content; }
45      set { base.Content = value; }
46    }
47
48    public RegressionSolutionResidualAnalysisView() : base() {
49      InitializeComponent();
50    }
51
52    #region events
53    protected override void RegisterContentEvents() {
54      base.RegisterContentEvents();
55      Content.ModelChanged += new EventHandler(Content_ModelChanged);
56      Content.ProblemDataChanged += new EventHandler(Content_ProblemDataChanged);
57    }
58
59    protected override void DeregisterContentEvents() {
60      base.DeregisterContentEvents();
61      Content.ModelChanged -= new EventHandler(Content_ModelChanged);
62      Content.ProblemDataChanged -= new EventHandler(Content_ProblemDataChanged);
63    }
64
65    private void Content_ProblemDataChanged(object sender, EventArgs e) {
66      OnContentChanged();
67    }
68
69    private void Content_ModelChanged(object sender, EventArgs e) {
70      OnContentChanged();
71    }
72
73    protected override void OnContentChanged() {
74      base.OnContentChanged();
75      if (Content == null) {
76        bubbleChartView.Content = null;
77      } else {
78        UpdateBubbleChart();
79      }
80    }
81
82    private void UpdateBubbleChart() {
83      if (Content == null) return;
84      var selectedXAxis = bubbleChartView.SelectedXAxis;
85      var selectedYAxis = bubbleChartView.SelectedYAxis;
86
87      var problemData = Content.ProblemData;
88      var ds = problemData.Dataset;
89      var runs = new RunCollection();
90
91      var doubleVars = ds.DoubleVariables.ToArray();
92      var stringVars = ds.StringVariables.ToArray();
93      var dateTimeVars = ds.DateTimeVariables.ToArray();
94
95      var predictedValues = Content.EstimatedValues.ToArray();
96      var targetValues = ds.GetReadOnlyDoubleValues(problemData.TargetVariable);
97
98      foreach (var i in problemData.AllIndices) {
99        var run = CreateRunForIdx(i, problemData, doubleVars, stringVars, dateTimeVars);
100        AddErrors(run, predictedValues[i], targetValues[i]);
101
102        if (problemData.IsTrainingSample(i) && problemData.IsTestSample(i)) {
103          run.Results.Add(PartitionLabel, new StringValue("Training + Test"));
104          run.Color = Color.Orange;
105        } else if (problemData.IsTrainingSample(i)) {
106          run.Results.Add(PartitionLabel, new StringValue("Training"));
107          run.Color = Color.Gold;
108        } else if (problemData.IsTestSample(i)) {
109          run.Results.Add(PartitionLabel, new StringValue("Test"));
110          run.Color = Color.Red;
111        } else {
112          run.Results.Add(PartitionLabel, new StringValue("Additional Data"));
113          run.Color = Color.Black;
114        }
115        runs.Add(run);
116      }
117
118      if (string.IsNullOrEmpty(selectedXAxis))
119        selectedXAxis = "Index";
120      if (string.IsNullOrEmpty(selectedYAxis))
121        selectedYAxis = "Residual";
122
123      bubbleChartView.Content = runs;
124      bubbleChartView.SelectedXAxis = selectedXAxis;
125      bubbleChartView.SelectedYAxis = selectedYAxis;
126    }
127
128    private static void AddErrors(IRun run, double pred, double target) {
129      var residual = target - pred;
130      var relError = residual / target;
131      run.Results.Add(TargetLabel, new DoubleValue(target));
132      run.Results.Add(PredictionLabel, new DoubleValue(pred));
133      run.Results.Add(ResidualLabel, new DoubleValue(residual));
134      run.Results.Add(AbsResidualLabel, new DoubleValue(Math.Abs(residual)));
135      run.Results.Add(RelativeErrorLabel, new DoubleValue(relError));
136      run.Results.Add(AbsRelativeErrorLabel, new DoubleValue(Math.Abs(relError)));
137    }
138
139    private static IRun CreateRunForIdx(int i, IRegressionProblemData problemData, IEnumerable<string> doubleVars, IEnumerable<string> stringVars, IEnumerable<string> dateTimeVars) {
140      var ds = problemData.Dataset;
141      var run = new Run();
142      foreach (var variableName in doubleVars) {
143        run.Results.Add(variableName, new DoubleValue(ds.GetDoubleValue(variableName, i)));
144      }
145      foreach (var variableName in stringVars) {
146        run.Results.Add(variableName, new StringValue(ds.GetStringValue(variableName, i)));
147      }
148      foreach (var variableName in dateTimeVars) {
149        run.Results.Add(variableName, new DateTimeValue(ds.GetDateTimeValue(variableName, i)));
150      }
151      return run;
152    }
153    #endregion
154
155  }
156}
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