#region License Information
/* HeuristicLab
* Copyright (C) 2002-2013 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.Linq;
using HeuristicLab.Problems.DataAnalysis.Transformations;
namespace HeuristicLab.DataPreprocessing {
public class PreprocessingTransformator {
private readonly ITransactionalPreprocessingData preprocessingData;
public PreprocessingTransformator(IPreprocessingData preprocessingData) {
this.preprocessingData = (ITransactionalPreprocessingData)preprocessingData;
}
public bool ApplyTransformations(IEnumerable transformations, out string errorMsg) {
bool success;
preprocessingData.BeginTransaction(DataPreprocessingChangedEventType.Transformation);
try {
var doubleTransformations = transformations.OfType>().ToList();
ApplyDoubleTranformations(doubleTransformations, out success, out errorMsg);
} finally {
preprocessingData.EndTransaction();
//if (!success)
//preprocessingData.Undo();
}
return success;
}
private void ApplyDoubleTranformations(IEnumerable> transformations, out bool success, out string errorMsg) {
errorMsg = string.Empty;
success = true;
foreach (var transformation in transformations) {
int colIndex = preprocessingData.GetColumnIndex(transformation.Column);
var originalData = preprocessingData.GetValues(colIndex);
string errorMsgPart;
bool successPart;
var transformedData = ApplyDoubleTransformation(transformation, originalData, out successPart, out errorMsgPart);
errorMsg += errorMsgPart + Environment.NewLine;
//if (!success) return;
if (!successPart) success = false;
preprocessingData.SetValues(colIndex, transformedData.ToList());
preprocessingData.Transformations.Add(transformation);
}
}
private IEnumerable ApplyDoubleTransformation(Transformation transformation, IEnumerable data, out bool success, out string errorMsg) {
success = transformation.Check(data, out errorMsg);
return transformation.Apply(data);
}
}
}