#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); } }