#region License Information /* HeuristicLab * Copyright (C) 2002-2010 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.Linq; using HeuristicLab.Common; using HeuristicLab.Core; using HeuristicLab.Data; using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding; using HeuristicLab.Operators; using HeuristicLab.Optimization; using HeuristicLab.Parameters; using HeuristicLab.Persistence.Default.CompositeSerializers.Storable; namespace HeuristicLab.Problems.ArtificialAnt.Analyzers { /// /// An operator for analyzing the best ant trail of an artificial ant problem. /// [Item("BestAntTrailAnalyzer", "An operator for analyzing the best ant trail of an artificial ant problem.")] [StorableClass] public sealed class BestAntTrailAnalyzer : SingleSuccessorOperator, IAntTrailAnalyzer { public ILookupParameter WorldParameter { get { return (ILookupParameter)Parameters["World"]; } } public ScopeTreeLookupParameter SymbolicExpressionTreeParameter { get { return (ScopeTreeLookupParameter)Parameters["SymbolicExpressionTree"]; } } public ScopeTreeLookupParameter QualityParameter { get { return (ScopeTreeLookupParameter)Parameters["Quality"]; } } public ILookupParameter MaxTimeStepsParameter { get { return (ILookupParameter)Parameters["MaxTimeSteps"]; } } public ILookupParameter BestSolutionParameter { get { return (ILookupParameter)Parameters["BestSolution"]; } } public ValueLookupParameter ResultsParameter { get { return (ValueLookupParameter)Parameters["Results"]; } } public BestAntTrailAnalyzer() : base() { Parameters.Add(new LookupParameter("World", "The world with food items for the artificial ant.")); Parameters.Add(new ScopeTreeLookupParameter("SymbolicExpressionTree", "The artificial ant solutions from which the best solution should be visualized.")); Parameters.Add(new ScopeTreeLookupParameter("Quality", "The qualities of the artificial ant solutions which should be visualized.")); Parameters.Add(new LookupParameter("BestSolution", "The visual representation of the best ant trail.")); Parameters.Add(new LookupParameter("MaxTimeSteps", "The maximal time steps that the artificial ant has available to collect all food items.")); Parameters.Add(new ValueLookupParameter("Results", "The result collection where the best artificial ant solution should be stored.")); } [StorableConstructor] private BestAntTrailAnalyzer(bool deserializing) : base(deserializing) { } private BestAntTrailAnalyzer(BestAntTrailAnalyzer original, Cloner cloner) : base(original, cloner) { } public override IDeepCloneable Clone(Cloner cloner) { return new BestAntTrailAnalyzer(this, cloner); } public override IOperation Apply() { ItemArray expressions = SymbolicExpressionTreeParameter.ActualValue; ItemArray qualities = QualityParameter.ActualValue; BoolMatrix world = WorldParameter.ActualValue; IntValue maxTimeSteps = MaxTimeStepsParameter.ActualValue; ResultCollection results = ResultsParameter.ActualValue; int i = qualities.Select((x, index) => new { index, x.Value }).OrderBy(x => -x.Value).First().index; AntTrail antTrail = BestSolutionParameter.ActualValue; if (antTrail == null) { var bestAntTrail = new AntTrail(world, expressions[i], maxTimeSteps); BestSolutionParameter.ActualValue = bestAntTrail; results.Add(new Result("Best Artificial Ant Solution", bestAntTrail)); } else { antTrail.World = world; antTrail.SymbolicExpressionTree = expressions[i]; antTrail.MaxTimeSteps = maxTimeSteps; results["Best Artificial Ant Solution"].Value = antTrail; } return base.Apply(); } } }