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.Linq;
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25 | using System.Windows.Forms;
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26 | using HeuristicLab.Data;
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27 | using HeuristicLab.MainForm;
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28 | using HeuristicLab.PluginInfrastructure;
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29 |
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30 | namespace HeuristicLab.Problems.DataAnalysis.Views {
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31 | [View("Timeframe Feature Correlation View")]
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32 | [Content(typeof(DataAnalysisProblemData), false)]
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33 | public partial class TimeframeFeatureCorrelationView : AbstractFeatureCorrelationView {
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34 |
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35 | private FeatureCorrelationTimeframeCache correlationTimeframCache;
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36 |
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37 | public TimeframeFeatureCorrelationView() {
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38 | InitializeComponent();
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39 | correlationTimeframCache = new FeatureCorrelationTimeframeCache();
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40 | }
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41 |
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42 | protected override void OnContentChanged() {
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43 | correlationTimeframCache.Reset();
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44 | if (Content != null) {
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45 | dataView.RowVisibility = SetInitialVariableVisibility();
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46 | VariableSelectionComboBox.DataSource = Content.Dataset.DoubleVariables.ToList();
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47 | }
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48 | base.OnContentChanged();
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49 | }
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50 |
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51 | private void VariableSelectionComboBox_SelectedChangeCommitted(object sender, EventArgs e) {
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52 | CalculateCorrelation();
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53 | }
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54 |
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55 | private void TimeframeTextbox_KeyDown(object sender, System.Windows.Forms.KeyEventArgs e) {
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56 | if (e.KeyCode == Keys.Enter) {
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57 | CalculateCorrelation();
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58 | }
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59 | }
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60 |
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61 | protected override void CalculateCorrelation() {
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62 | if (CorrelationCalcComboBox.SelectedItem != null && PartitionComboBox.SelectedItem != null
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63 | && VariableSelectionComboBox.SelectedItem != null && ValidateTimeframeTextbox()) {
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64 | string variable = (string)VariableSelectionComboBox.SelectedItem;
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65 | IDependencyCalculator calc = (IDependencyCalculator)CorrelationCalcComboBox.SelectedValue;
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66 | string partition = (string)PartitionComboBox.SelectedValue;
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67 | int frames;
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68 | int.TryParse(TimeframeTextbox.Text, out frames);
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69 | dataView.Enabled = false;
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70 | double[,] corr = correlationTimeframCache.GetTimeframeCorrelation(calc, partition, variable);
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71 | if (corr == null) {
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72 | fcc.CalculateTimeframeElements(calc, partition, variable, frames);
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73 | } else if (corr.GetLength(1) <= frames) {
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74 | fcc.CalculateTimeframeElements(calc, partition, variable, frames, corr);
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75 | } else {
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76 | fcc.TryCancelCalculation();
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77 | var columnNames = Enumerable.Range(0, corr.GetLength(1)).Select(x => x.ToString());
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78 | var correlation = new DoubleMatrix(corr, columnNames, Content.Dataset.DoubleVariables);
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79 | ((IStringConvertibleMatrix)correlation).Columns = frames + 1;
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80 | UpdateDataView(correlation);
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81 | }
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82 | }
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83 | }
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84 |
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85 | private bool ValidateTimeframeTextbox() {
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86 | int help;
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87 | if (!int.TryParse(TimeframeTextbox.Text, out help)) {
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88 | MessageBox.Show("Timeframe couldn't be parsed. Enter a valid integer value.", "Parse Error", MessageBoxButtons.OK);
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89 | return false;
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90 | } else {
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91 | if (help > 50) {
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92 | DialogResult dr = MessageBox.Show("The entered value is bigger than 50. Are you sure you want to calculate? " +
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93 | "The calculation could take some time.", "Huge Value Warning", MessageBoxButtons.YesNo);
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94 | return dr.Equals(DialogResult.Yes);
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95 | }
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96 | }
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97 | return true;
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98 | }
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99 |
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100 |
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101 | protected override void Content_CorrelationCalculationFinished(object sender, FeatureCorrelationCalculator.CorrelationCalculationFinishedArgs e) {
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102 | if (InvokeRequired) {
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103 | Invoke(new FeatureCorrelationCalculator.CorrelationCalculationFinishedHandler(Content_CorrelationCalculationFinished), sender, e);
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104 | } else {
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105 | correlationTimeframCache.SetTimeframeCorrelation(e.Calculcator, e.Partition, e.Variable, e.Correlation);
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106 | var columnNames = Enumerable.Range(0, e.Correlation.GetLength(1)).Select(x => x.ToString());
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107 | var correlation = new DoubleMatrix(e.Correlation, columnNames, Content.Dataset.DoubleVariables);
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108 | UpdateDataView(correlation);
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109 | }
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110 | }
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111 |
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112 | [NonDiscoverableType]
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113 | private class FeatureCorrelationTimeframeCache : Object {
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114 | private Dictionary<Tuple<IDependencyCalculator, string, string>, double[,]> timeFrameCorrelationsCache;
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115 |
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116 | public FeatureCorrelationTimeframeCache()
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117 | : base() {
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118 | InitializeCaches();
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119 | }
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120 |
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121 | private void InitializeCaches() {
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122 | timeFrameCorrelationsCache = new Dictionary<Tuple<IDependencyCalculator, string, string>, double[,]>();
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123 | }
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124 |
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125 | public void Reset() {
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126 | InitializeCaches();
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127 | }
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128 |
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129 | public double[,] GetTimeframeCorrelation(IDependencyCalculator calc, string partition, string variable) {
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130 | double[,] corr;
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131 | var key = new Tuple<IDependencyCalculator, string, string>(calc, partition, variable);
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132 | timeFrameCorrelationsCache.TryGetValue(key, out corr);
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133 | return corr;
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134 | }
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135 |
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136 | public void SetTimeframeCorrelation(IDependencyCalculator calc, string partition, string variable, double[,] correlation) {
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137 | var key = new Tuple<IDependencyCalculator, string, string>(calc, partition, variable);
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138 | timeFrameCorrelationsCache[key] = correlation;
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139 | }
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140 | }
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141 | }
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142 | } |
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