source: trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Classification/CSV/ClassifiactionCSVInstanceProvider.cs @ 8566

Last change on this file since 8566 was 8566, checked in by gkronber, 7 years ago

#1927 implemented check to deactivate input variables that are constant in the training partition in the CSV problem instance providers for regression, classification and clustering.

File size: 4.2 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#endregion
21
22using System;
23using System.Collections.Generic;
24using System.Globalization;
25using System.IO;
26using System.Linq;
27using System.Text;
28using HeuristicLab.Common;
29using HeuristicLab.Problems.DataAnalysis;
30
31namespace HeuristicLab.Problems.Instances.DataAnalysis {
32  public class ClassificationCSVInstanceProvider : ClassificationInstanceProvider {
33    public override string Name {
34      get { return "CSV File"; }
35    }
36    public override string Description {
37      get {
38        return "";
39      }
40    }
41    public override Uri WebLink {
42      get { return new Uri("http://dev.heuristiclab.com/trac/hl/core/wiki/UsersFAQ#DataAnalysisImportFileFormat"); }
43    }
44    public override string ReferencePublication {
45      get { return ""; }
46    }
47
48    public override IEnumerable<IDataDescriptor> GetDataDescriptors() {
49      return new List<IDataDescriptor>();
50    }
51
52    public override IClassificationProblemData LoadData(IDataDescriptor descriptor) {
53      throw new NotImplementedException();
54    }
55
56    public override bool CanImportData {
57      get { return true; }
58    }
59    public override IClassificationProblemData ImportData(string path) {
60      TableFileParser csvFileParser = new TableFileParser();
61
62      csvFileParser.Parse(path);
63
64      Dataset dataset = new Dataset(csvFileParser.VariableNames, csvFileParser.Values);
65      string targetVar = dataset.DoubleVariables.Last();
66
67      // turn of input variables that are constant in the training partition
68      var allowedInputVars = new List<string>();
69      var trainingIndizes = Enumerable.Range(0, (csvFileParser.Rows * 2) / 3);
70      foreach (var variableName in dataset.DoubleVariables) {
71        if (dataset.GetDoubleValues(variableName, trainingIndizes).Range() > 0 &&
72          variableName != targetVar)
73          allowedInputVars.Add(variableName);
74      }
75
76      ClassificationProblemData classificationData = new ClassificationProblemData(dataset, allowedInputVars, targetVar);
77
78      int trainingPartEnd = trainingIndizes.Last();
79      classificationData.TrainingPartition.Start = trainingIndizes.First();
80      classificationData.TrainingPartition.End = trainingPartEnd;
81      classificationData.TestPartition.Start = trainingPartEnd;
82      classificationData.TestPartition.End = csvFileParser.Rows;
83
84      classificationData.Name = Path.GetFileName(path);
85
86      return classificationData;
87    }
88
89    public override bool CanExportData {
90      get { return true; }
91    }
92    public override void ExportData(IClassificationProblemData instance, string path) {
93      var strBuilder = new StringBuilder();
94
95      foreach (var variable in instance.InputVariables) {
96        strBuilder.Append(variable + CultureInfo.CurrentCulture.TextInfo.ListSeparator);
97      }
98      strBuilder.Remove(strBuilder.Length - CultureInfo.CurrentCulture.TextInfo.ListSeparator.Length, CultureInfo.CurrentCulture.TextInfo.ListSeparator.Length);
99      strBuilder.AppendLine();
100
101      var dataset = instance.Dataset;
102
103      for (int i = 0; i < dataset.Rows; i++) {
104        for (int j = 0; j < dataset.Columns; j++) {
105          if (j > 0) strBuilder.Append(CultureInfo.CurrentCulture.TextInfo.ListSeparator);
106          strBuilder.Append(dataset.GetValue(i, j));
107        }
108        strBuilder.AppendLine();
109      }
110
111      using (var writer = new StreamWriter(path)) {
112        writer.Write(strBuilder);
113      }
114    }
115  }
116}
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