#region License Information
/* HeuristicLab
* Copyright (C) 2002-2018 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.IO;
using System.Linq;
using HeuristicLab.Common;
using HeuristicLab.Problems.Instances;
using HeuristicLab.Problems.Instances.DataAnalysis;
namespace HeuristicLab.Problems.DataAnalysis.Trading {
public class CsvProblemInstanceProvider : ProblemInstanceProvider {
public override string Name {
get { return "CSV File"; }
}
public override string Description {
get {
return "Comma separated values file importer";
}
}
public override Uri WebLink {
get { return new Uri("http://dev.heuristiclab.com/trac.fcgi/wiki/Documentation/FAQ#DataAnalysisImportFileFormat"); }
}
public override string ReferencePublication {
get { return ""; }
}
public override IEnumerable GetDataDescriptors() {
return new List();
}
public override IProblemData LoadData(IDataDescriptor descriptor) {
throw new NotImplementedException();
}
public override bool CanImportData {
get { return true; }
}
public override IProblemData ImportData(string path) {
TableFileParser csvFileParser = new TableFileParser();
csvFileParser.Parse(path, csvFileParser.AreColumnNamesInFirstLine(path));
Dataset dataset = new Dataset(csvFileParser.VariableNames, csvFileParser.Values);
string targetVar = (from v in dataset.DoubleVariables
where dataset.GetReadOnlyDoubleValues(v).Min() <= 0
where dataset.GetReadOnlyDoubleValues(v).Max() >= 0
select v).LastOrDefault();
if (targetVar == null) throw new ArgumentException("The target variable must contain changes (deltas) of the asset price over time.");
// turn off input variables that are constant in the training partition
var allowedInputVars = new List();
var trainingIndizes = Enumerable.Range(0, (csvFileParser.Rows * 2) / 3);
if (trainingIndizes.Count() >= 2) {
foreach (var variableName in dataset.DoubleVariables) {
if (dataset.GetDoubleValues(variableName, trainingIndizes).Range() > 0)
allowedInputVars.Add(variableName);
}
} else {
allowedInputVars.AddRange(dataset.DoubleVariables);
}
IProblemData problemData = new ProblemData(dataset, allowedInputVars, targetVar);
var trainingPartEnd = trainingIndizes.Last();
problemData.TrainingPartition.Start = trainingIndizes.First();
problemData.TrainingPartition.End = trainingPartEnd;
problemData.TestPartition.Start = trainingPartEnd;
problemData.TestPartition.End = csvFileParser.Rows;
problemData.Name = Path.GetFileName(path);
return problemData;
}
}
}