source: trunk/sources/HeuristicLab.Problems.DataAnalysis.Views/3.4/FeatureCorrelation/TimeframeFeatureCorrelationView.cs @ 13938

Last change on this file since 13938 was 13938, checked in by mkommend, 5 years ago

#2619:

  • Refactored and separated the different feature correlation calculations.
  • Added a checkbox to ignore missing values in the calculation.
File size: 7.3 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2015 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
21
22using System;
23using System.Collections.Generic;
24using System.Linq;
25using System.Windows.Forms;
26using HeuristicLab.Data;
27using HeuristicLab.MainForm;
28using HeuristicLab.PluginInfrastructure;
29
30namespace HeuristicLab.Problems.DataAnalysis.Views {
31  [View("Timeframe Feature Correlation View")]
32  [Content(typeof(DataAnalysisProblemData), false)]
33  public partial class TimeframeFeatureCorrelationView : AbstractFeatureCorrelationView {
34
35    private FeatureCorrelationTimeframeCache correlationTimeframCache;
36    private string lastFramesValue;
37
38    private new TimeframeFeatureCorrelationCalculator CorrelationCalculator {
39      get { return (TimeframeFeatureCorrelationCalculator)base.CorrelationCalculator; }
40      set { base.CorrelationCalculator = value; }
41    }
42
43
44    public TimeframeFeatureCorrelationView() {
45      InitializeComponent();
46      CorrelationCalculator = new TimeframeFeatureCorrelationCalculator();
47      correlationTimeframCache = new FeatureCorrelationTimeframeCache();
48      errorProvider.SetIconAlignment(timeframeTextbox, ErrorIconAlignment.MiddleRight);
49      errorProvider.SetIconPadding(timeframeTextbox, 2);
50      lastFramesValue = timeframeTextbox.Text;
51    }
52
53    protected override void OnContentChanged() {
54      correlationTimeframCache.Reset();
55      if (Content != null) {
56        dataView.RowVisibility = SetInitialVariableVisibility();
57        SetVariableSelectionComboBox();
58      }
59      base.OnContentChanged();
60    }
61
62    protected virtual void SetVariableSelectionComboBox() {
63      variableSelectionComboBox.DataSource = Content.Dataset.DoubleVariables.ToList();
64    }
65
66    private void VariableSelectionComboBox_SelectedChangeCommitted(object sender, EventArgs e) {
67      CalculateCorrelation();
68    }
69    private void TimeframeTextbox_KeyDown(object sender, System.Windows.Forms.KeyEventArgs e) {
70      if (e.KeyCode == Keys.Enter || e.KeyCode == Keys.Return) {
71        timeFrameLabel.Select();  // select label to validate data
72      }
73
74      if (e.KeyCode == Keys.Escape) {
75        timeframeTextbox.Text = lastFramesValue;
76        timeFrameLabel.Select();  // select label to validate data
77      }
78    }
79    private void TimeframeTextbox_Validated(object sender, System.EventArgs e) {
80      lastFramesValue = timeframeTextbox.Text;
81      errorProvider.SetError(timeframeTextbox, string.Empty);
82      CalculateCorrelation();
83    }
84    private void TimeframeTextbox_Validating(object sender, System.ComponentModel.CancelEventArgs e) {
85      int help;
86      if (!int.TryParse(timeframeTextbox.Text, out help)) {
87        errorProvider.SetError(timeframeTextbox, "Timeframe couldn't be parsed. Enter a valid integer value.");
88        e.Cancel = true;
89      } else {
90        if (help > 50) {
91          DialogResult dr = MessageBox.Show("The entered value is bigger than 50. Are you sure you want to calculate? " +
92                                            "The calculation could take some time.", "Huge Value Warning", MessageBoxButtons.YesNo);
93          e.Cancel = !dr.Equals(DialogResult.Yes);
94        } else if (help < 0) {
95          errorProvider.SetError(timeframeTextbox, "The entered value can't be negative!");
96          e.Cancel = true;
97        }
98      }
99    }
100
101    protected override void CalculateCorrelation() {
102      if (correlationCalcComboBox.SelectedItem == null) return;
103      if (partitionComboBox.SelectedItem == null) return;
104      if (variableSelectionComboBox.SelectedItem == null) return;
105
106      string variable = (string)variableSelectionComboBox.SelectedItem;
107      IDependencyCalculator calc = (IDependencyCalculator)correlationCalcComboBox.SelectedValue;
108      string partition = (string)partitionComboBox.SelectedValue;
109      int frames;
110      int.TryParse(timeframeTextbox.Text, out frames);
111      dataView.Enabled = false;
112      double[,] corr = correlationTimeframCache.GetTimeframeCorrelation(calc, partition, variable);
113      if (corr == null) {
114        CorrelationCalculator.CalculateTimeframeElements(Content, calc, partition, variable, frames);
115      } else if (corr.GetLength(1) <= frames) {
116        CorrelationCalculator.CalculateTimeframeElements(Content, calc, partition, variable, frames, corr);
117      } else {
118        CorrelationCalculator.TryCancelCalculation();
119        var columnNames = Enumerable.Range(0, corr.GetLength(1)).Select(x => x.ToString());
120        var correlation = new DoubleMatrix(corr, columnNames, Content.Dataset.DoubleVariables);
121        ((IStringConvertibleMatrix)correlation).Columns = frames + 1;
122        UpdateDataView(correlation);
123      }
124    }
125
126    protected override void FeatureCorrelation_CalculationFinished(object sender, AbstractFeatureCorrelationCalculator.CorrelationCalculationFinishedArgs e) {
127      if (InvokeRequired) {
128        Invoke(new AbstractFeatureCorrelationCalculator.CorrelationCalculationFinishedHandler(FeatureCorrelation_CalculationFinished), sender, e);
129      } else {
130        correlationTimeframCache.SetTimeframeCorrelation(e.Calculcator, e.Partition, e.Variable, e.Correlation);
131        var columnNames = Enumerable.Range(0, e.Correlation.GetLength(1)).Select(x => x.ToString());
132        var correlation = new DoubleMatrix(e.Correlation, columnNames, Content.Dataset.DoubleVariables);
133        UpdateDataView(correlation);
134      }
135    }
136
137    [NonDiscoverableType]
138    private class FeatureCorrelationTimeframeCache : Object {
139      private Dictionary<Tuple<IDependencyCalculator, string, string>, double[,]> timeFrameCorrelationsCache;
140
141      public FeatureCorrelationTimeframeCache()
142        : base() {
143        InitializeCaches();
144      }
145
146      private void InitializeCaches() {
147        timeFrameCorrelationsCache = new Dictionary<Tuple<IDependencyCalculator, string, string>, double[,]>();
148      }
149
150      public void Reset() {
151        InitializeCaches();
152      }
153
154      public double[,] GetTimeframeCorrelation(IDependencyCalculator calc, string partition, string variable) {
155        double[,] corr;
156        var key = new Tuple<IDependencyCalculator, string, string>(calc, partition, variable);
157        timeFrameCorrelationsCache.TryGetValue(key, out corr);
158        return corr;
159      }
160
161      public void SetTimeframeCorrelation(IDependencyCalculator calc, string partition, string variable, double[,] correlation) {
162        var key = new Tuple<IDependencyCalculator, string, string>(calc, partition, variable);
163        timeFrameCorrelationsCache[key] = correlation;
164      }
165    }
166  }
167}
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