1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 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;
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24 | using System.Collections.Generic;
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25 | using System.Collections.ObjectModel;
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26 | using System.Diagnostics;
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27 | using System.Globalization;
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28 | using System.IO;
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29 | using System.IO.Compression;
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30 | using System.Linq;
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31 | using HeuristicLab.Problems.DataAnalysis;
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32 |
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33 | namespace HeuristicLab.Problems.Instances.DataAnalysis {
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34 | public abstract class TimeSeriesInstanceProvider : ResourceClassificationInstanceProvider {
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35 | //public override string Name {
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36 | // get { return "TimeSeries (Univariate) Problems"; }
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37 | //}
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38 | public override string Description {
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39 | get { return "UEA & UCR TimeSeries Problems"; }
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40 | }
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41 | public override Uri WebLink {
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42 | get { return new Uri("http://www.timeseriesclassification.com/"); }
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43 | }
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44 | public override string ReferencePublication {
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45 | get { return "Anthony Bagnall, Jason Lines, William Vickers and Eamonn Keogh, The UEA & UCR Time Series Classification Repository, www.timeseriesclassification.com"; }
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46 | }
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47 |
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48 | public override IClassificationProblemData LoadData(IDataDescriptor id) {
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49 | var descriptor = (TimeSeriesDataDescriptor)id;
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50 | using (var instancesZipFile = OpenZipArchive()) {
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51 | var trainingEntry = instancesZipFile.GetEntry(descriptor.TrainingEntryName);
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52 | var testEntry = instancesZipFile.GetEntry(descriptor.TestEntryName);
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53 |
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54 | if (trainingEntry == null || testEntry == null) {
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55 | throw new InvalidOperationException("The training or test entry could not be found in the archive.");
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56 | }
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57 |
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58 | using (var trainingReader = new StreamReader(trainingEntry.Open()))
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59 | using (var testReader = new StreamReader(testEntry.Open())) {
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60 | ParseMetadata(trainingReader, out var inputVariables, out string targetVariable);
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61 | ParseMetadata(testReader, out _, out _); // ignore outputs
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62 |
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63 | // Read data
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64 | var inputsData = new List<DoubleVector>[inputVariables.Count];
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65 | for (int i = 0; i < inputsData.Length; i++) inputsData[i] = new List<DoubleVector>();
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66 | var targetData = new List<double>();
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67 | ReadData(trainingReader, inputsData, targetData, out int numTrainingRows);
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68 | ReadData(testReader, inputsData, targetData, out int numTestRows);
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69 |
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70 | // Build dataset
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71 | var dataset = new Dataset(
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72 | inputVariables.Concat(new[] { targetVariable }),
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73 | inputsData.Cast<IList>().Concat(new[] { targetData })
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74 | );
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75 | Debug.Assert(dataset.Rows == numTrainingRows + numTestRows);
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76 | Debug.Assert(dataset.Columns == inputVariables.Count + 1);
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77 |
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78 | // Build problem data
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79 | var problemData = new ClassificationProblemData(dataset, inputVariables, targetVariable) {
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80 | Name = descriptor.Name
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81 | };
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82 | problemData.TrainingPartition.Start = 0;
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83 | problemData.TrainingPartition.End = numTrainingRows;
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84 | problemData.TestPartition.Start = numTrainingRows;
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85 | problemData.TestPartition.End = numTrainingRows + numTestRows;
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86 |
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87 | return problemData;
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88 | }
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89 | }
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90 | }
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91 |
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92 | private static void ParseMetadata(StreamReader reader, out List<string> inputVariables, out string targetVariable) {
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93 | int nrOfInputs = 0;
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94 | bool dataStart = false;
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95 | while (!reader.EndOfStream && !dataStart) {
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96 | var line = reader.ReadLine();
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97 | if (line.StartsWith("#")) {
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98 | // Comment
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99 | } else if (line.StartsWith("@")) {
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100 | var splits = line.Split(' ');
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101 | var type = splits.First();
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102 | var arguments = splits.Skip(1).ToList();
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103 | switch (type.ToLowerInvariant()) {
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104 | case "@univariate":
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105 | bool univariate = bool.Parse(arguments[0]);
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106 | if (univariate)
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107 | nrOfInputs = 1;
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108 | break;
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109 | case "@dimensions":
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110 | int dimensions = int.Parse(arguments[0]);
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111 | nrOfInputs = dimensions;
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112 | break;
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113 | case "@data":
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114 | dataStart = true;
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115 | break;
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116 | }
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117 | } else {
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118 | throw new InvalidOperationException("A data section already occurred within metadata section.");
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119 | }
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120 | }
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121 |
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122 | int digits = Math.Max((int)Math.Log10(nrOfInputs - 1) + 1, 1);
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123 | inputVariables = Enumerable.Range(0, nrOfInputs)
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124 | .Select(i => "X" + i.ToString("D" + digits))
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125 | .ToList();
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126 |
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127 | targetVariable = "Y";
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128 | }
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129 |
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130 | private static void ReadData(StreamReader reader, List<DoubleVector>[] inputsData, List<double> targetData, out int count) {
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131 | count = 0;
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132 | while (!reader.EndOfStream) {
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133 | var line = reader.ReadLine();
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134 | var variables = line.Split(':');
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135 |
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136 | // parse all except last, which is the non-vector target
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137 | for (int i = 0; i < variables.Length - 1; i++) {
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138 | var variable = variables[i];
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139 | var numbers = variable
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140 | .Split(',')
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141 | .Select(d => double.Parse(d, CultureInfo.InvariantCulture))
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142 | .ToList();
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143 | inputsData[i].Add(new DoubleVector(numbers));
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144 | }
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145 |
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146 | var target = double.Parse(variables[variables.Length - 1], CultureInfo.InvariantCulture);
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147 | targetData.Add(target);
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148 |
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149 | count++;
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150 | }
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151 | }
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152 |
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153 | public override IEnumerable<IDataDescriptor> GetDataDescriptors() {
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154 | using (var instancesZipFile = OpenZipArchive()) {
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155 | var instances = GroupEntriesByInstance(instancesZipFile.Entries);
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156 | var descriptors = instances.Select(instance => CreateDescriptor(instance.Key, instance.Value));
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157 |
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158 | return descriptors.ToList();
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159 | }
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160 | }
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161 |
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162 | private ZipArchive OpenZipArchive() {
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163 | var instanceArchiveName = GetResourceName(FileName + @"\.zip");
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164 | return new ZipArchive(GetType().Assembly.GetManifestResourceStream(instanceArchiveName), ZipArchiveMode.Read);
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165 | }
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166 |
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167 | private static IDictionary<string, List<ZipArchiveEntry>> GroupEntriesByInstance(ReadOnlyCollection<ZipArchiveEntry> entries) {
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168 | var topLevelEntries = entries.Where(entry => string.IsNullOrEmpty(entry.Name)).ToList();
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169 |
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170 | return topLevelEntries.ToDictionary(
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171 | entry => Path.GetDirectoryName(entry.FullName),
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172 | entry => entries.Except(topLevelEntries).Where(subEntry => subEntry.FullName.StartsWith(entry.FullName)).ToList());
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173 | }
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174 |
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175 | private static TimeSeriesDataDescriptor CreateDescriptor(string name, List<ZipArchiveEntry> subEntries) {
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176 | var trainingEntry = subEntries.Single(entry => entry.Name.EndsWith("_TRAIN.ts"));
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177 | var testEntry = subEntries.Single(entry => entry.Name.EndsWith("_TEST.ts"));
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178 | return new TimeSeriesDataDescriptor(name, trainingEntry.FullName, testEntry.FullName);
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179 | }
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180 | }
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181 | }
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