| 1 | #region License Information
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| 2 | /* HeuristicLab
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| 3 | * Copyright (C) 2002-2010 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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| 4 | *
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| 5 | * This file is part of HeuristicLab.
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| 6 | *
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| 7 | * HeuristicLab is free software: you can redistribute it and/or modify
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| 8 | * it under the terms of the GNU General Public License as published by
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| 9 | * the Free Software Foundation, either version 3 of the License, or
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| 10 | * (at your option) any later version.
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| 11 | *
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| 12 | * HeuristicLab is distributed in the hope that it will be useful,
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| 13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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| 14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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| 15 | * GNU General Public License for more details.
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| 16 | *
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| 17 | * You should have received a copy of the GNU General Public License
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| 18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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| 19 | */
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| 20 | #endregion
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| 21 |
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| 22 | using System.Linq;
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| 23 | using HeuristicLab.Common;
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| 24 | using HeuristicLab.Core;
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| 25 | using HeuristicLab.Data;
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| 26 | using HeuristicLab.Operators;
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| 27 | using HeuristicLab.Optimization;
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| 28 | using HeuristicLab.Parameters;
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| 29 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 30 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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| 31 |
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| 32 | namespace HeuristicLab.Problems.ArtificialAnt.Analyzers {
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| 33 | /// <summary>
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| 34 | /// An operator for analyzing the best ant trail of an artificial ant problem.
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| 35 | /// </summary>
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| 36 | [Item("BestAntTrailAnalyzer", "An operator for analyzing the best ant trail of an artificial ant problem.")]
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| 37 | [StorableClass]
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| 38 | public sealed class BestAntTrailAnalyzer : SingleSuccessorOperator, IAntTrailAnalyzer {
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| 39 | public ILookupParameter<BoolMatrix> WorldParameter {
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| 40 | get { return (ILookupParameter<BoolMatrix>)Parameters["World"]; }
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| 41 | }
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| 42 | public ScopeTreeLookupParameter<SymbolicExpressionTree> SymbolicExpressionTreeParameter {
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| 43 | get { return (ScopeTreeLookupParameter<SymbolicExpressionTree>)Parameters["SymbolicExpressionTree"]; }
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| 44 | }
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| 45 | public ScopeTreeLookupParameter<DoubleValue> QualityParameter {
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| 46 | get { return (ScopeTreeLookupParameter<DoubleValue>)Parameters["Quality"]; }
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| 47 | }
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| 48 | public ILookupParameter<IntValue> MaxTimeStepsParameter {
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| 49 | get { return (ILookupParameter<IntValue>)Parameters["MaxTimeSteps"]; }
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| 50 | }
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| 51 | public ILookupParameter<AntTrail> BestSolutionParameter {
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| 52 | get { return (ILookupParameter<AntTrail>)Parameters["BestSolution"]; }
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| 53 | }
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| 54 | public ValueLookupParameter<ResultCollection> ResultsParameter {
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| 55 | get { return (ValueLookupParameter<ResultCollection>)Parameters["Results"]; }
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| 56 | }
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| 57 |
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| 58 | public BestAntTrailAnalyzer()
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| 59 | : base() {
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| 60 | Parameters.Add(new LookupParameter<BoolMatrix>("World", "The world with food items for the artificial ant."));
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| 61 | Parameters.Add(new ScopeTreeLookupParameter<SymbolicExpressionTree>("SymbolicExpressionTree", "The artificial ant solutions from which the best solution should be visualized."));
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| 62 | Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", "The qualities of the artificial ant solutions which should be visualized."));
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| 63 | Parameters.Add(new LookupParameter<AntTrail>("BestSolution", "The visual representation of the best ant trail."));
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| 64 | Parameters.Add(new LookupParameter<IntValue>("MaxTimeSteps", "The maximal time steps that the artificial ant has available to collect all food items."));
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| 65 | Parameters.Add(new ValueLookupParameter<ResultCollection>("Results", "The result collection where the best artificial ant solution should be stored."));
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| 66 | }
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| 67 |
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| 68 | public override IOperation Apply() {
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| 69 | ItemArray<SymbolicExpressionTree> expressions = SymbolicExpressionTreeParameter.ActualValue;
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| 70 | ItemArray<DoubleValue> qualities = QualityParameter.ActualValue;
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| 71 | BoolMatrix world = WorldParameter.ActualValue;
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| 72 | IntValue maxTimeSteps = MaxTimeStepsParameter.ActualValue;
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| 73 | ResultCollection results = ResultsParameter.ActualValue;
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| 74 |
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| 75 | int i = qualities.Select((x, index) => new { index, x.Value }).OrderBy(x => -x.Value).First().index;
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| 76 |
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| 77 | AntTrail antTrail = BestSolutionParameter.ActualValue;
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| 78 | if (antTrail == null) {
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| 79 | var bestAntTrail = new AntTrail(world, expressions[i], maxTimeSteps);
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| 80 | BestSolutionParameter.ActualValue = bestAntTrail;
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| 81 | results.Add(new Result("Best Artificial Ant Solution", bestAntTrail));
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| 82 | } else {
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| 83 | antTrail.World = world;
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| 84 | antTrail.SymbolicExpressionTree = expressions[i];
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| 85 | antTrail.MaxTimeSteps = maxTimeSteps;
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| 86 | results["Best Artificial Ant Solution"].Value = antTrail;
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| 87 | }
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| 88 | return base.Apply();
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| 89 | }
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| 90 | }
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| 91 | }
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