#region License Information
/* HeuristicLab
* Copyright (C) 2002-2008 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 System.Text;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Operators;
using HeuristicLab.Functions;
using HeuristicLab.DataAnalysis;
namespace HeuristicLab.StructureIdentification {
public abstract class GPEvaluatorBase : OperatorBase {
protected double maximumPunishment;
public GPEvaluatorBase()
: base() {
AddVariableInfo(new VariableInfo("OperatorTree", "The function tree that should be evaluated", typeof(IFunction), VariableKind.In));
AddVariableInfo(new VariableInfo("Dataset", "Dataset with all samples on which to apply the function", typeof(Dataset), VariableKind.In));
AddVariableInfo(new VariableInfo("TargetVariable", "Index of the column of the dataset that holds the target variable", typeof(IntData), VariableKind.In));
AddVariableInfo(new VariableInfo("PunishmentFactor", "Punishment factor for invalid estimations", typeof(DoubleData), VariableKind.In));
AddVariableInfo(new VariableInfo("Quality", "The evaluated quality of the model", typeof(DoubleData), VariableKind.New));
}
public override IOperation Apply(IScope scope) {
int targetVariable = GetVariableValue("TargetVariable", scope, true).Data;
Dataset dataset = GetVariableValue("Dataset", scope, true);
IFunction function = GetVariableValue("OperatorTree", scope, true);
this.maximumPunishment = GetVariableValue("PunishmentFactor", scope, true).Data * dataset.GetRange(targetVariable);
double result = Evaluate(scope, function, targetVariable, dataset);
scope.AddVariable(new HeuristicLab.Core.Variable(scope.TranslateName("Quality"), new DoubleData(result)));
return null;
}
public abstract double Evaluate(IScope scope, IFunction function, int targetVariable, Dataset dataset);
}
}