Free cookie consent management tool by TermsFeed Policy Generator

source: trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/CSV/RegressionCSVInstanceProvider.cs @ 8601

Last change on this file since 8601 was 8601, checked in by sforsten, 11 years ago

#1942: training has now at least one sample

File size: 5.8 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;
24using System.Collections.Generic;
25using System.Globalization;
26using System.IO;
27using System.Linq;
28using System.Text;
29using HeuristicLab.Common;
30using HeuristicLab.Problems.DataAnalysis;
31
32namespace HeuristicLab.Problems.Instances.DataAnalysis {
33  public class RegressionCSVInstanceProvider : RegressionInstanceProvider {
34    public override string Name {
35      get { return "CSV File"; }
36    }
37    public override string Description {
38      get {
39        return "";
40      }
41    }
42    public override Uri WebLink {
43      get { return new Uri("http://dev.heuristiclab.com/trac/hl/core/wiki/UsersFAQ#DataAnalysisImportFileFormat"); }
44    }
45    public override string ReferencePublication {
46      get { return ""; }
47    }
48
49    public override IEnumerable<IDataDescriptor> GetDataDescriptors() {
50      return new List<IDataDescriptor>();
51    }
52    public override IRegressionProblemData LoadData(IDataDescriptor descriptor) {
53      throw new NotImplementedException();
54    }
55
56    public override bool CanImportData {
57      get { return true; }
58    }
59    public override IRegressionProblemData ImportData(string path) {
60      TableFileParser csvFileParser = new TableFileParser();
61      csvFileParser.Parse(path);
62
63      Dataset dataset = new Dataset(csvFileParser.VariableNames, csvFileParser.Values);
64      string targetVar = dataset.DoubleVariables.Last();
65
66      // turn of input variables that are constant in the training partition
67      var allowedInputVars = new List<string>();
68      var trainingIndizes = Enumerable.Range(0, (csvFileParser.Rows * 2) / 3);
69      foreach (var variableName in dataset.DoubleVariables) {
70        if (trainingIndizes.Count() >= 2 && dataset.GetDoubleValues(variableName, trainingIndizes).Range() > 0 &&
71          variableName != targetVar)
72          allowedInputVars.Add(variableName);
73      }
74
75      IRegressionProblemData regressionData = new RegressionProblemData(dataset, allowedInputVars, targetVar);
76
77      var trainingPartEnd = trainingIndizes.Last();
78      regressionData.TrainingPartition.Start = trainingIndizes.First();
79      regressionData.TrainingPartition.End = trainingPartEnd;
80      regressionData.TestPartition.Start = trainingPartEnd;
81      regressionData.TestPartition.End = csvFileParser.Rows;
82
83      regressionData.Name = Path.GetFileName(path);
84
85      return regressionData;
86    }
87
88    public override IRegressionProblemData ImportData(string path, DataAnalysisImportType type) {
89      TableFileParser csvFileParser = new TableFileParser();
90      csvFileParser.Parse(path);
91
92      List<IList> values = csvFileParser.Values;
93      if (type.Shuffle) {
94        values = Shuffle(values);
95      }
96      Dataset dataset = new Dataset(csvFileParser.VariableNames, values);
97      string targetVar = dataset.DoubleVariables.Last();
98
99      // turn of input variables that are constant in the training partition
100      var allowedInputVars = new List<string>();
101      int trainingPartEnd = (csvFileParser.Rows * type.Training) / 100;
102      trainingPartEnd = trainingPartEnd > 0 ? trainingPartEnd : 1;
103      var trainingIndizes = Enumerable.Range(0, trainingPartEnd);
104      if (trainingIndizes.Count() >= 2) {
105        foreach (var variableName in dataset.DoubleVariables) {
106          if (dataset.GetDoubleValues(variableName, trainingIndizes).Range() > 0 &&
107            variableName != targetVar)
108            allowedInputVars.Add(variableName);
109        }
110      } else {
111        allowedInputVars.AddRange(dataset.DoubleVariables.Where(x => x.Equals(targetVar)));
112      }
113
114      RegressionProblemData regressionData = new RegressionProblemData(dataset, allowedInputVars, targetVar);
115
116      regressionData.TrainingPartition.Start = 0;
117      regressionData.TrainingPartition.End = trainingPartEnd;
118      regressionData.TestPartition.Start = trainingPartEnd;
119      regressionData.TestPartition.End = csvFileParser.Rows;
120
121      regressionData.Name = Path.GetFileName(path);
122
123      return regressionData;
124    }
125
126    public override bool CanExportData {
127      get { return true; }
128    }
129    public override void ExportData(IRegressionProblemData instance, string path) {
130      var strBuilder = new StringBuilder();
131
132      foreach (var variable in instance.InputVariables) {
133        strBuilder.Append(variable + CultureInfo.CurrentCulture.TextInfo.ListSeparator);
134      }
135      strBuilder.Remove(strBuilder.Length - CultureInfo.CurrentCulture.TextInfo.ListSeparator.Length, CultureInfo.CurrentCulture.TextInfo.ListSeparator.Length);
136      strBuilder.AppendLine();
137
138      var dataset = instance.Dataset;
139
140      for (int i = 0; i < dataset.Rows; i++) {
141        for (int j = 0; j < dataset.Columns; j++) {
142          if (j > 0) strBuilder.Append(CultureInfo.CurrentCulture.TextInfo.ListSeparator);
143          strBuilder.Append(dataset.GetValue(i, j));
144        }
145        strBuilder.AppendLine();
146      }
147
148      using (var writer = new StreamWriter(path)) {
149        writer.Write(strBuilder);
150      }
151    }
152  }
153}
Note: See TracBrowser for help on using the repository browser.