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source: branches/DatasetFeatureCorrelation/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/ExtendedHeatMap.cs @ 8318

Last change on this file since 8318 was 8318, checked in by sforsten, 12 years ago

#1292:

  • added cloning method and constructor to ExtendedHeatMap
  • renamed a variable in ExtendedHeatMapView
  • added backwards compatibility code in DataAnalysisProblemData
File size: 8.2 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2012 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
21#endregion
22
23using System;
24using System.Collections.Generic;
25using System.ComponentModel;
26using System.Linq;
27using HeuristicLab.Analysis;
28using HeuristicLab.Common;
29using HeuristicLab.Core;
30using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
31using HeuristicLab.PluginInfrastructure;
32
33namespace HeuristicLab.Problems.DataAnalysis {
34  [StorableClass]
35  [Item("HeatMap", "Represents a heat map of double values.")]
36  public class ExtendedHeatMap : HeatMap {
37
38    private const string PrearsonsRSquared = "Pearsons R Squared";
39    private const string HoeffdingsDependence = "Hoeffdings Dependence";
40    private const string SpearmansRank = "Spearmans Rank";
41    public IEnumerable<string> CorrelationCalculators {
42      get { return new List<string>() { PrearsonsRSquared, HoeffdingsDependence, SpearmansRank }; }
43    }
44
45    private const string AllSamples = "All Samples";
46    private const string TrainingSamples = "Training Samples";
47    private const string TestSamples = "Test Samples";
48    public IEnumerable<string> Partitions {
49      get { return new List<string>() { AllSamples, TrainingSamples, TestSamples }; }
50    }
51
52    private IDataAnalysisProblemData problemData;
53    public IDataAnalysisProblemData ProblemData {
54      get { return problemData; }
55      set {
56        if (problemData != value) {
57          problemData = value;
58          columnNames = value.Dataset.DoubleVariables.ToList();
59          rowNames = value.Dataset.DoubleVariables.ToList();
60          OnProblemDataChanged();
61        }
62      }
63    }
64
65    private BackgroundWorker bw;
66
67    public ExtendedHeatMap()
68      : base() {
69      this.Title = "Feature Correlation";
70      this.columnNames = Enumerable.Range(1, 2).Select(x => x.ToString()).ToList();
71      this.rowNames = Enumerable.Range(1, 2).Select(x => x.ToString()).ToList();
72    }
73
74    public ExtendedHeatMap(IDataAnalysisProblemData problemData) {
75      this.problemData = problemData;
76      this.Title = "Feature Correlation";
77      this.columnNames = problemData.Dataset.DoubleVariables.ToList();
78      this.rowNames = problemData.Dataset.DoubleVariables.ToList();
79
80      CalculateElements(problemData.Dataset);
81    }
82    protected ExtendedHeatMap(ExtendedHeatMap original, Cloner cloner)
83      : base(original, cloner) {
84      this.Title = "Feature Correlation";
85      this.problemData = original.problemData;
86      this.columnNames = original.problemData.Dataset.DoubleVariables.ToList();
87      this.rowNames = original.problemData.Dataset.DoubleVariables.ToList();
88    }
89    public override IDeepCloneable Clone(Cloner cloner) {
90      return new ExtendedHeatMap(this, cloner);
91    }
92
93    public void Recalculate(string calc, string partition) {
94      CalculateElements(problemData.Dataset, calc, partition);
95    }
96
97    private void CalculateElements(Dataset dataset) {
98      CalculateElements(dataset, CorrelationCalculators.First(), Partitions.First());
99    }
100
101    private void CalculateElements(Dataset dataset, string calc, string partition) {
102      if (bw == null || bw.IsBusy) {
103        if (bw != null) {
104          bw.CancelAsync();
105        }
106        bw = new BackgroundWorker();
107        bw.WorkerReportsProgress = true;
108        bw.WorkerSupportsCancellation = true;
109        bw.DoWork += new DoWorkEventHandler(bw_DoWork);
110        bw.ProgressChanged += new ProgressChangedEventHandler(bw_ProgressChanged);
111        bw.RunWorkerCompleted += new RunWorkerCompletedEventHandler(bw_RunWorkerCompleted);
112      }
113      bw.RunWorkerAsync(new BackgroundWorkerInfo { Dataset = dataset, Calculator = calc, Partition = partition });
114    }
115
116    private void bw_DoWork(object sender, DoWorkEventArgs e) {
117      BackgroundWorker worker = sender as BackgroundWorker;
118
119      BackgroundWorkerInfo bwInfo = (BackgroundWorkerInfo)e.Argument;
120      Dataset dataset = bwInfo.Dataset;
121      string partition = bwInfo.Partition;
122      string calc = bwInfo.Calculator;
123
124      IList<string> doubleVariableNames = dataset.DoubleVariables.ToList();
125      OnlineCalculatorError error;
126      int length = doubleVariableNames.Count;
127      double[,] elements = new double[length, length];
128
129      double calculations = (Math.Pow(length, 2) + length) / 2;
130
131      for (int i = 0; i < length; i++) {
132        for (int j = 0; j < i + 1; j++) {
133          if (worker.CancellationPending) {
134            e.Cancel = true;
135            return;
136          }
137
138          IEnumerable<double> var1 = dataset.GetDoubleValues(doubleVariableNames[i]);
139          IEnumerable<double> var2 = dataset.GetDoubleValues(doubleVariableNames[j]);
140          if (partition.Equals(TrainingSamples)) {
141            var1 = var1.Skip(problemData.TrainingPartition.Start).Take(problemData.TrainingPartition.End - problemData.TrainingPartition.Start);
142            var2 = var2.Skip(problemData.TrainingPartition.Start).Take(problemData.TrainingPartition.End - problemData.TrainingPartition.Start);
143          } else if (partition.Equals(TestSamples)) {
144            var1 = var1.Skip(problemData.TestPartition.Start).Take(problemData.TestPartition.End - problemData.TestPartition.Start);
145            var2 = var2.Skip(problemData.TestPartition.Start).Take(problemData.TestPartition.End - problemData.TestPartition.Start);
146          }
147
148          if (calc.Equals(HoeffdingsDependence)) {
149            elements[i, j] = HoeffdingsDependenceCalculator.Calculate(var1, var2, out error);
150          } else if (calc.Equals(SpearmansRank)) {
151            elements[i, j] = SpearmansRankCorrelationCoefficientCalculator.Calculate(var1, var2, out error);
152          } else {
153            elements[i, j] = OnlinePearsonsRSquaredCalculator.Calculate(var1, var2, out error);
154          }
155          elements[j, i] = elements[i, j];
156          if (!error.Equals(OnlineCalculatorError.None)) {
157            throw new ArgumentException("Calculator returned " + error);
158          }
159          worker.ReportProgress((int)Math.Round((((Math.Pow(i, 2) + i) / 2 + j + 1.0) / calculations) * 100));
160        }
161      }
162      e.Result = elements;
163    }
164
165    private void bw_RunWorkerCompleted(object sender, RunWorkerCompletedEventArgs e) {
166      BackgroundWorker worker = sender as BackgroundWorker;
167      if (!e.Cancelled && !worker.CancellationPending) {
168        if (!(e.Error == null)) {
169          ErrorHandling.ShowErrorDialog(e.Error);
170        } else {
171          matrix = (double[,])e.Result;
172          OnReset();
173        }
174      } else {
175        Console.WriteLine("Backgroundworker canceled");
176      }
177    }
178
179    #region events
180    public delegate void ProgressCalculationHandler(object sender, ProgressChangedEventArgs e);
181    public event ProgressCalculationHandler ProgressCalculation;
182    protected void bw_ProgressChanged(object sender, ProgressChangedEventArgs e) {
183      BackgroundWorker worker = sender as BackgroundWorker;
184      if (!worker.CancellationPending && ProgressCalculation != null) {
185        ProgressCalculation(sender, e);
186      }
187    }
188
189    public event EventHandler ProblemDataChanged;
190    protected virtual void OnProblemDataChanged() {
191      var handler = ProblemDataChanged;
192      if (handler != null) handler(this, EventArgs.Empty);
193    }
194    #endregion
195
196    protected class BackgroundWorkerInfo {
197      public Dataset Dataset { get; set; }
198      public string Calculator { get; set; }
199      public string Partition { get; set; }
200    }
201  }
202}
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