source: branches/2913_MatlabScriptProblemInstanceProvider/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Matlab/RegressionMatlabInstanceProvider.cs @ 17717

#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 <http://www.gnu.org/licenses/>.
 */
#endregion

using System;
using System.Collections.Generic;
using System.IO;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
using HeuristicLab.Common;
using HeuristicLab.Problems.DataAnalysis;
using HeuristicLab.Problems.Instances.DataAnalysis.Regression.Matlab.Api.Types;
using HeuristicLab.Random;

namespace HeuristicLab.Problems.Instances.DataAnalysis.Regression.Matlab {
  /// <summary>
  /// This is a RegressionInstanceProvider which imports data for a regression problem from a matlab script.
  /// </summary>
  public class RegressionMatlabInstanceProvider : RegressionInstanceProvider {
    public override string Name {
      get {
        return "Matlab Script";
      }
    }

    public override string Description {
      get { return ""; }
    }

    public override Uri WebLink {
      get { return new Uri("http://dev.heuristiclab.com"); }
    }

    public override string ReferencePublication {
      get { return ""; }
    }

    public override IEnumerable<IDataDescriptor> GetDataDescriptors() {
      return new List<IDataDescriptor>();
    }

    public override IRegressionProblemData LoadData(IDataDescriptor descriptor) {
      throw new NotImplementedException();
    }

    public override bool CanImportData {
      get { return true; }
    }


    private Dataset GetValues(RegressionMatlabImportType type) {
      if (type.Shuffle) {
        type.Values = type.Values.Shuffle(new MersenneTwister());
      }
      return type.Values;
    }

    public IRegressionProblemData ImportData(string path, RegressionMatlabImportType type, IEnumerable<MLVariableInfo> variableNames) {
      var dataset = GetValues(type);
      var targetVar = type.TargetVariable;

      // turn off input variables that are constant in the training partition
      var rows = dataset.Rows;
      var allowedInputVars = new List<string>();
      int trainingPartEnd = (rows * type.TrainingPercentage) / 100;
      trainingPartEnd = trainingPartEnd > 0 ? trainingPartEnd : 1;

      var trainingIndizes = Enumerable.Range(0, trainingPartEnd);
      if (trainingIndizes.Count() >= 2) {
        foreach (var variableName in dataset.DoubleVariables) {
          if (dataset.GetDoubleValues(variableName, trainingIndizes).Range() > 0 && variableName != type.TargetVariable) {
            allowedInputVars.Add(variableName);
          }
        }
      } else {
        allowedInputVars.AddRange(dataset.DoubleVariables.Where(x => !x.Equals(type.TargetVariable)));
      }

      IRegressionProblemData regressionData = new RegressionProblemData(dataset, allowedInputVars, targetVar);

      regressionData.TrainingPartition.Start = trainingIndizes.First();
      regressionData.TrainingPartition.End = trainingPartEnd;
      regressionData.TestPartition.Start = trainingPartEnd;
      regressionData.TestPartition.End = rows;

      regressionData.Name = Path.GetFileName(path);

      return regressionData;
    }
  }
}