#region License Information
/* HeuristicLab
* Copyright (C) 2002-2019 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 HeuristicLab.Common;
using HeuristicLab.Core;
using HEAL.Attic;
namespace HeuristicLab.Problems.DataAnalysis {
[StorableType("EF0EF64F-392A-448A-B30F-1AE113C6CC88")]
[Item("DataAnalysisModel", "Base class for data analysis models.")]
public abstract class DataAnalysisModel : NamedItem, IDataAnalysisModel {
[StorableConstructor]
protected DataAnalysisModel(StorableConstructorFlag _) : base(_) { }
protected DataAnalysisModel(DataAnalysisModel original, Cloner cloner)
: base(original, cloner) { }
protected DataAnalysisModel() { }
protected DataAnalysisModel(string name) : base(name) { }
protected DataAnalysisModel(string name, string description) : base(name, description) { }
public abstract IEnumerable VariablesUsedForPrediction { get; }
public virtual bool IsDatasetCompatible(IDataset dataset, out string errorMessage) {
if (dataset == null) throw new ArgumentNullException("dataset", "The provided dataset is null.");
return IsDatasetCompatible(this, dataset, out errorMessage);
}
public abstract bool IsProblemDataCompatible(IDataAnalysisProblemData problemData, out string errorMessage);
public static bool IsDatasetCompatible(IDataAnalysisModel model, IDataset dataset, out string errorMessage) {
if(model == null) throw new ArgumentNullException("model", "The provided model is null.");
if (dataset == null) throw new ArgumentNullException("dataset", "The provided dataset is null.");
errorMessage = string.Empty;
foreach (var variable in model.VariablesUsedForPrediction) {
if (!dataset.ContainsVariable(variable)) {
if (string.IsNullOrEmpty(errorMessage)) {
errorMessage = "The following variables must be present in the dataset for model evaluation:";
}
errorMessage += System.Environment.NewLine + " " + variable;
}
}
return string.IsNullOrEmpty(errorMessage);
}
}
}