#region License Information /* HeuristicLab * Copyright (C) 2002-2012 Heuristic and Evolutionary Algorithms Laboratory (HEAL) * * This file is part of HeuristicLab. * * HeuristicLab is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * HeuristicLab is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with HeuristicLab. If not, see . */ #endregion using System; using System.Collections.Generic; using System.Globalization; using System.IO; using System.Linq; using System.Text; using HeuristicLab.Problems.DataAnalysis; namespace HeuristicLab.Problems.Instances.DataAnalysis { public class ClassificationCSVInstanceProvider : ClassificationInstanceProvider { public override string Name { get { return "CSV File"; } } public override string Description { get { return ""; } } public override Uri WebLink { get { return new Uri("http://dev.heuristiclab.com/trac/hl/core/wiki/UsersFAQ#DataAnalysisImportFileFormat"); } } public override string ReferencePublication { get { return ""; } } public override IEnumerable GetDataDescriptors() { return new List(); } public override IClassificationProblemData LoadData(IDataDescriptor descriptor) { throw new NotImplementedException(); } public override bool CanImportData { get { return true; } } public override IClassificationProblemData ImportData(string path) { TableFileParser csvFileParser = new TableFileParser(); csvFileParser.Parse(path); Dataset dataset = new Dataset(csvFileParser.VariableNames, csvFileParser.Values); string targetVar = csvFileParser.VariableNames.Where(x => dataset.DoubleVariables.Contains(x)).Last(); IEnumerable allowedInputVars = dataset.DoubleVariables.Where(x => !x.Equals(targetVar)); ClassificationProblemData claData = new ClassificationProblemData(dataset, allowedInputVars, targetVar); int trainingPartEnd = csvFileParser.Rows * 2 / 3; claData.TrainingPartition.Start = 0; claData.TrainingPartition.End = trainingPartEnd; claData.TestPartition.Start = trainingPartEnd; claData.TestPartition.End = csvFileParser.Rows; int pos = path.LastIndexOf('\\'); if (pos < 0) claData.Name = path; else { pos++; claData.Name = path.Substring(pos, path.Length - pos); } return claData; } public override bool CanExportData { get { return true; } } public override void ExportData(IClassificationProblemData instance, string path) { var strBuilder = new StringBuilder(); foreach (var variable in instance.InputVariables) { strBuilder.Append(variable + CultureInfo.CurrentCulture.TextInfo.ListSeparator); } strBuilder.Remove(strBuilder.Length - CultureInfo.CurrentCulture.TextInfo.ListSeparator.Length, CultureInfo.CurrentCulture.TextInfo.ListSeparator.Length); strBuilder.AppendLine(); var dataset = instance.Dataset; for (int i = 0; i < dataset.Rows; i++) { for (int j = 0; j < dataset.Columns; j++) { if (j > 0) strBuilder.Append(CultureInfo.CurrentCulture.TextInfo.ListSeparator); strBuilder.Append(dataset.GetValue(i, j)); } strBuilder.AppendLine(); } using (var writer = new StreamWriter(path)) { writer.Write(strBuilder); } } } }