#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.Collections.Generic; using HeuristicLab.Common; using HeuristicLab.Core; using HeuristicLab.Optimization; using HEAL.Attic; namespace HeuristicLab.Problems.Programmable { [Item("Single-objective Problem Definition Script", "Script that defines the parameter vector and evaluates the solution for a programmable problem.")] [StorableType("D0B2A649-EDDE-4A6E-A3B5-F40F5FD1B2C0")] public sealed class SingleObjectiveProblemDefinitionScript : ProblemDefinitionScript, ISingleObjectiveProblemDefinition, IStorableContent { public string Filename { get; set; } private new ISingleObjectiveProblemDefinition CompiledProblemDefinition { get { return (ISingleObjectiveProblemDefinition)base.CompiledProblemDefinition; } } [StorableConstructor] private SingleObjectiveProblemDefinitionScript(StorableConstructorFlag _) : base(_) { } private SingleObjectiveProblemDefinitionScript(SingleObjectiveProblemDefinitionScript original, Cloner cloner) : base(original, cloner) { } public SingleObjectiveProblemDefinitionScript() : base(ScriptTemplates.CompiledSingleObjectiveProblemDefinition) { } public override IDeepCloneable Clone(Cloner cloner) { return new SingleObjectiveProblemDefinitionScript(this, cloner); } bool ISingleObjectiveProblemDefinition.Maximization { get { return CompiledProblemDefinition.Maximization; } } double ISingleObjectiveProblemDefinition.Evaluate(Individual individual, IRandom random) { return CompiledProblemDefinition.Evaluate(individual, random); } void ISingleObjectiveProblemDefinition.Analyze(Individual[] individuals, double[] qualities, ResultCollection results, IRandom random) { CompiledProblemDefinition.Analyze(individuals, qualities, results, random); } IEnumerable ISingleObjectiveProblemDefinition.GetNeighbors(Individual individual, IRandom random) { return CompiledProblemDefinition.GetNeighbors(individual, random); } } }