#region License Information /* HeuristicLab * Copyright (C) 2002-2014 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; } } }