#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; using System.Linq; using HEAL.Attic; using HeuristicLab.Common; using HeuristicLab.Core; using HeuristicLab.Data; using HeuristicLab.Operators; using HeuristicLab.Optimization; using HeuristicLab.Optimization.Operators; using HeuristicLab.Parameters; using HeuristicLab.Random; namespace HeuristicLab.Analysis.FitnessLandscape { [Item("Local Analysis", "A local analysis algorithm.")] [StorableType("2D91C41A-81F8-4EDC-8FD9-F9AE8F4BDA1D")] public abstract class LocalAnalysis : HeuristicOptimizationEngineAlgorithm, IStorableContent where T : class, IOperator, new() { public string Filename { get; set; } #region Problem Properties public override Type ProblemType { get { return typeof(ISingleObjectiveHeuristicOptimizationProblem); } } public new ISingleObjectiveHeuristicOptimizationProblem Problem { get { return (ISingleObjectiveHeuristicOptimizationProblem)base.Problem; } set { base.Problem = value; } } #endregion #region Parameter Properties public IFixedValueParameter SeedParameter { get { return (IFixedValueParameter)Parameters["Seed"]; } } public IFixedValueParameter SetSeedRandomlyParameter { get { return (IFixedValueParameter)Parameters["SetSeedRandomly"]; } } public IConstrainedValueParameter MutatorParameter { get { return (IConstrainedValueParameter)Parameters["Mutator"]; } } public IFixedValueParameter MaximumIterationsParameter { get { return (IFixedValueParameter)Parameters["MaximumIterations"]; } } public IFixedValueParameter RepetitionsParameter { get { return (IFixedValueParameter)Parameters["Repetitions"]; } } public IValueParameter AnalyzerParameter { get { return (IValueParameter)Parameters["Analyzer"]; } } public IFixedValueParameter SelectorParameter { get { return (IFixedValueParameter)Parameters["Selector"]; } } #endregion #region Properties protected RandomCreator GlobalRandomCreator { get { return (RandomCreator)OperatorGraph.InitialOperator; } } protected UniformSubScopesProcessor FirstUniformSubScopesProcessor { get { return (UniformSubScopesProcessor)((SubScopesCreator)GlobalRandomCreator.Successor).Successor; } } protected LocalRandomCreator IteratedRandomCreator { get { return (LocalRandomCreator)FirstUniformSubScopesProcessor.Operator; } } protected VariableCreator VariableCreator { get { return (VariableCreator)IteratedRandomCreator.Successor; } } protected UniformSubScopesProcessor SecondUniformSubScopesProcessor { get { return (UniformSubScopesProcessor)FirstUniformSubScopesProcessor.Successor; } } protected SolutionsCreator SolutionsCreator { get { return (SolutionsCreator)SecondUniformSubScopesProcessor.Operator; } } protected LocalAnalysisMainLoop MainLoop { get { return (LocalAnalysisMainLoop)SolutionsCreator.Successor; } } [Storable] private QualityTrailMultiAnalyzer qualityTrailAnalyzer; #endregion [StorableConstructor] protected LocalAnalysis(StorableConstructorFlag _) : base(_) { } protected LocalAnalysis(LocalAnalysis original, Cloner cloner) : base(original, cloner) { qualityTrailAnalyzer = cloner.Clone(original.qualityTrailAnalyzer); RegisterEventHandlers(); } protected LocalAnalysis(T selector) : base() { Parameters.Add(new FixedValueParameter("Seed", "The random seed used to initialize the new pseudo random number generator.", new IntValue(0))); Parameters.Add(new FixedValueParameter("SetSeedRandomly", "True if the random seed should be set to a random value, otherwise false.", new BoolValue(true))); Parameters.Add(new ConstrainedValueParameter("Mutator", "Mutation operator.")); Parameters.Add(new FixedValueParameter("MaximumIterations", "The maximum number of generations which should be processed.", new IntValue(100))); Parameters.Add(new FixedValueParameter("Repetitions", "The number of repetitions that should be performed.", new IntValue(10))); Parameters.Add(new ValueParameter("Analyzer", "The operator used to analyze the solution and moves.", new MultiAnalyzer())); Parameters.Add(new FixedValueParameter("Selector", "Selection operator.", selector)); RandomCreator randomCreator = new RandomCreator(); SubScopesCreator ssc = new SubScopesCreator(); UniformSubScopesProcessor ussp1 = new UniformSubScopesProcessor(); UniformSubScopesProcessor ussp2 = new UniformSubScopesProcessor(); LocalRandomCreator lrc = new LocalRandomCreator(); VariableCreator variableCreator = new VariableCreator(); SolutionsCreator solutionsCreator = new SolutionsCreator(); LocalAnalysisMainLoop laMainLoop = new LocalAnalysisMainLoop(); ResultsCollector collector = new ResultsCollector(); OperatorGraph.InitialOperator = randomCreator; randomCreator.RandomParameter.ActualName = "Random"; randomCreator.SeedParameter.ActualName = SeedParameter.Name; randomCreator.SeedParameter.Value = null; randomCreator.SetSeedRandomlyParameter.ActualName = SetSeedRandomlyParameter.Name; randomCreator.SetSeedRandomlyParameter.Value = null; randomCreator.Successor = ssc; ssc.NumberOfSubScopesParameter.Value = null; ssc.NumberOfSubScopesParameter.ActualName = RepetitionsParameter.Name; ssc.Successor = ussp1; ussp1.Depth = new IntValue(1); ussp1.Parallel = new BoolValue(false); ussp1.Operator = lrc; ussp1.Successor = ussp2; lrc.GlobalRandomParameter.ActualName = randomCreator.RandomParameter.ActualName; lrc.LocalRandomParameter.ActualName = "IteratedRandom"; lrc.Successor = variableCreator; var iterResults = new ValueParameter("IteratedResults", new ResultCollection()); variableCreator.CollectedValues.Add(iterResults); variableCreator.Successor = null; ussp2.Depth = new IntValue(1); ussp2.Parallel = new BoolValue(true); ussp2.Operator = solutionsCreator; ussp2.Successor = collector; solutionsCreator.NumberOfSolutions = new IntValue(1); solutionsCreator.Successor = laMainLoop; laMainLoop.MutatorParameter.ActualName = MutatorParameter.Name; laMainLoop.SelectorParameter.ActualName = SelectorParameter.Name; laMainLoop.MaximumIterationsParameter.ActualName = MaximumIterationsParameter.Name; laMainLoop.RandomParameter.ActualName = lrc.LocalRandomParameter.ActualName; laMainLoop.ResultsParameter.ActualName = iterResults.Name; laMainLoop.AnalyzerParameter.ActualName = AnalyzerParameter.Name; qualityTrailAnalyzer = new QualityTrailMultiAnalyzer(); qualityTrailAnalyzer.UpdateIntervalParameter.Value = null; qualityTrailAnalyzer.UpdateIntervalParameter.ActualName = MaximumIterationsParameter.Name; AnalyzerParameter.Value.Operators.Add(qualityTrailAnalyzer, true); collector.CollectedValues.Add(new ScopeTreeLookupParameter("IteratedResults", 1)); collector.ResultsParameter.ActualName = "Results"; collector.CopyValue = new BoolValue(false); collector.Successor = null; RegisterEventHandlers(); } public override void Prepare() { if (Problem != null) base.Prepare(); } protected override void OnStopped() { var iteratedResults = Results.SingleOrDefault(x => x.Name == "IteratedResults"); if (iteratedResults != null) { var rc = iteratedResults.Value as ItemArray; if (rc != null) { var results = rc.FirstOrDefault(); if (results != null) { var toAvg = results.Select(x => x.Name).ToDictionary(x => x, x => 0.0); foreach (var r in rc) { foreach (var v in r) { if (!toAvg.ContainsKey(v.Name)) continue; var value = v.Value as IntValue; if (value != null) toAvg[v.Name] += value.Value; else { var doubleValue = v.Value as DoubleValue; if (doubleValue != null) toAvg[v.Name] += doubleValue.Value; } } } foreach (var r in toAvg.Keys.OrderBy(x => x)) { Results.Add(new Result(r, new DoubleValue(toAvg[r] / RepetitionsParameter.Value.Value))); } } } } base.OnStopped(); } #region Events protected override void OnProblemChanged() { base.OnProblemChanged(); UpdateMutators(); Parameterize(); Problem.Evaluator.QualityParameter.ActualNameChanged += Evaluator_QualityParameter_ActualNameChanged; } protected override void Problem_SolutionCreatorChanged(object sender, EventArgs e) { base.Problem_SolutionCreatorChanged(sender, e); Parameterize(); } protected override void Problem_EvaluatorChanged(object sender, EventArgs e) { base.Problem_EvaluatorChanged(sender, e); Parameterize(); Problem.Evaluator.QualityParameter.ActualNameChanged += Evaluator_QualityParameter_ActualNameChanged; } protected override void Problem_OperatorsChanged(object sender, EventArgs e) { UpdateMutators(); Parameterize(); base.Problem_OperatorsChanged(sender, e); } private void Evaluator_QualityParameter_ActualNameChanged(object sender, EventArgs e) { Parameterize(); } #endregion #region Helpers private void RegisterEventHandlers() { if (Problem != null) { Problem.Evaluator.QualityParameter.ActualNameChanged += Evaluator_QualityParameter_ActualNameChanged; } } private void UpdateMutators() { var selected = MutatorParameter.Value; MutatorParameter.ValidValues.Clear(); foreach (var m in Problem.Operators.OfType()) { MutatorParameter.ValidValues.Add(m); if (selected != null && selected.GetType() == m.GetType()) MutatorParameter.Value = m; } } protected virtual void Parameterize() { if (Problem == null) return; MainLoop.BestKnownQualityParameter.ActualName = Problem.BestKnownQualityParameter.Name; MainLoop.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name; MainLoop.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName; foreach (var sOp in Problem.Operators.OfType()) { sOp.RandomParameter.ActualName = IteratedRandomCreator.LocalRandomParameter.ActualName; } foreach (var iOp in Problem.Operators.OfType()) { iOp.IterationsParameter.ActualName = "Iterations"; iOp.MaximumIterationsParameter.ActualName = MaximumIterationsParameter.Name; } var sEval = Problem.Evaluator as IStochasticOperator; if (sEval != null) sEval.RandomParameter.ActualName = IteratedRandomCreator.LocalRandomParameter.ActualName; var sCrea = Problem.SolutionCreator as IStochasticOperator; if (sCrea != null) sCrea.RandomParameter.ActualName = IteratedRandomCreator.LocalRandomParameter.ActualName; var sSel = SelectorParameter.Value as IStochasticOperator; if (sSel != null) sSel.RandomParameter.ActualName = IteratedRandomCreator.LocalRandomParameter.ActualName; var sel = SelectorParameter.Value as ISelector; if (sel != null) { sel.NumberOfSelectedSubScopesParameter.Value = new IntValue(1); sel.CopySelected = new BoolValue(false); var sos = sel as ISingleObjectiveSelector; if (sos != null) { sos.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name; sos.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName; } } foreach (var op in Problem.Operators.OfType()) { var resultsParam = op.Parameters.SingleOrDefault(x => x.Name == "Results"); var lookupParam = resultsParam as ILookupParameter; if (lookupParam == null) continue; lookupParam.ActualName = "IteratedResults"; } } #endregion } }