#region License Information /* HeuristicLab * Copyright (C) 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 HeuristicLab.Encodings.SymbolicExpressionTreeEncoding; using HEAL.Attic; namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression { /// /// Represents a symbolic regression model /// [StorableType("2739C33E-4DDB-4285-9DFB-C056D900B2F2")] [Item(Name = "Symbolic Regression Model", Description = "Represents a symbolic regression model.")] public class SymbolicRegressionModel : SymbolicDataAnalysisModel, ISymbolicRegressionModel { [Storable] private string targetVariable; public string TargetVariable { get { return targetVariable; } set { if (string.IsNullOrEmpty(value) || targetVariable == value) return; targetVariable = value; OnTargetVariableChanged(this, EventArgs.Empty); } } [StorableConstructor] protected SymbolicRegressionModel(StorableConstructorFlag _) : base(_) { targetVariable = string.Empty; } protected SymbolicRegressionModel(SymbolicRegressionModel original, Cloner cloner) : base(original, cloner) { this.targetVariable = original.targetVariable; } public SymbolicRegressionModel(string targetVariable, ISymbolicExpressionTree tree, ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, double lowerEstimationLimit = double.MinValue, double upperEstimationLimit = double.MaxValue) : base(tree, interpreter, lowerEstimationLimit, upperEstimationLimit) { this.targetVariable = targetVariable; } public override IDeepCloneable Clone(Cloner cloner) { return new SymbolicRegressionModel(this, cloner); } public IEnumerable GetEstimatedValues(IDataset dataset, IEnumerable rows) { return Interpreter.GetSymbolicExpressionTreeValues(SymbolicExpressionTree, dataset, rows) .LimitToRange(LowerEstimationLimit, UpperEstimationLimit); } public ISymbolicRegressionSolution CreateRegressionSolution(IRegressionProblemData problemData) { return new SymbolicRegressionSolution(this, new RegressionProblemData(problemData)); } IRegressionSolution IRegressionModel.CreateRegressionSolution(IRegressionProblemData problemData) { return CreateRegressionSolution(problemData); } public void Scale(IRegressionProblemData problemData) { Scale(problemData, problemData.TargetVariable); } public virtual bool IsProblemDataCompatible(IRegressionProblemData problemData, out string errorMessage) { return RegressionModel.IsProblemDataCompatible(this, problemData, out errorMessage); } public override bool IsProblemDataCompatible(IDataAnalysisProblemData problemData, out string errorMessage) { if (problemData == null) throw new ArgumentNullException("problemData", "The provided problemData is null."); var regressionProblemData = problemData as IRegressionProblemData; if (regressionProblemData == null) throw new ArgumentException("The problem data is not compatible with this symbolic regression model. Instead a " + problemData.GetType().GetPrettyName() + " was provided.", "problemData"); return IsProblemDataCompatible(regressionProblemData, out errorMessage); } #region events public event EventHandler TargetVariableChanged; private void OnTargetVariableChanged(object sender, EventArgs args) { var changed = TargetVariableChanged; if (changed != null) changed(sender, args); } #endregion } }