#region License Information
/* HeuristicLab
* Copyright (C) 2002-2011 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.Collections.Generic;
using System.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
using HeuristicLab.Operators;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Optimization;
using System;
namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Classification {
///
/// Represents a symbolic classification solution (model + data) and attributes of the solution like accuracy and complexity
///
[StorableClass]
[Item(Name = "SymbolicClassificationSolution", Description = "Represents a symbolic classification solution (model + data) and attributes of the solution like accuracy and complexity.")]
public sealed class SymbolicClassificationSolution : ClassificationSolution, ISymbolicClassificationSolution {
private const string ModelLengthResultName = "ModelLength";
private const string ModelDepthResultName = "ModelDepth";
public new ISymbolicClassificationModel Model {
get { return (ISymbolicClassificationModel)base.Model; }
set { base.Model = value; }
}
ISymbolicDataAnalysisModel ISymbolicDataAnalysisSolution.Model {
get { return (ISymbolicDataAnalysisModel)base.Model; }
}
public int ModelLength {
get { return ((IntValue)this[ModelLengthResultName].Value).Value; }
private set { ((IntValue)this[ModelLengthResultName].Value).Value = value; }
}
public int ModelDepth {
get { return ((IntValue)this[ModelDepthResultName].Value).Value; }
private set { ((IntValue)this[ModelDepthResultName].Value).Value = value; }
}
[StorableConstructor]
private SymbolicClassificationSolution(bool deserializing) : base(deserializing) { }
private SymbolicClassificationSolution(SymbolicClassificationSolution original, Cloner cloner)
: base(original, cloner) {
}
public SymbolicClassificationSolution(ISymbolicClassificationModel model, IClassificationProblemData problemData)
: base(model, problemData) {
Add(new Result(ModelLengthResultName, "Length of the symbolic classification model.", new IntValue()));
Add(new Result(ModelDepthResultName, "Depth of the symbolic classification model.", new IntValue()));
RecalculateResults();
}
public override IDeepCloneable Clone(Cloner cloner) {
return new SymbolicClassificationSolution(this, cloner);
}
protected override void OnModelChanged(EventArgs e) {
base.OnModelChanged(e);
RecalculateResults();
}
private new void RecalculateResults() {
ModelLength = Model.SymbolicExpressionTree.Length;
ModelDepth = Model.SymbolicExpressionTree.Depth;
}
}
}