#region License Information /* HeuristicLab * Copyright (C) 2002-2019 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 . * * Author: Sabine Winkler */ #endregion using System; using System.Drawing; using System.Linq; using HeuristicLab.Common; using HeuristicLab.Common.Resources; using HeuristicLab.Core; using HeuristicLab.Data; using HeuristicLab.Encodings.IntegerVectorEncoding; using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding; using HeuristicLab.Optimization; using HeuristicLab.Parameters; using HEAL.Attic; using HeuristicLab.PluginInfrastructure; using HeuristicLab.Problems.DataAnalysis; using HeuristicLab.Problems.DataAnalysis.Symbolic; using HeuristicLab.Problems.GrammaticalEvolution.Mappers; using HeuristicLab.Problems.Instances; namespace HeuristicLab.Problems.GrammaticalEvolution { [StorableType("E31AC1E8-590D-4D65-883F-3113544B6C91")] public abstract class GESymbolicDataAnalysisProblem : HeuristicOptimizationProblem, IDataAnalysisProblem, IGESymbolicDataAnalysisProblem, IStorableContent, IProblemInstanceConsumer, IProblemInstanceExporter where T : class, IDataAnalysisProblemData where U : class, IGESymbolicDataAnalysisEvaluator where V : class, IIntegerVectorCreator { #region parameter names & descriptions private const string ProblemDataParameterName = "ProblemData"; private const string SymbolicExpressionTreeGrammarParameterName = "SymbolicExpressionTreeGrammar"; private const string SymbolicExpressionTreeInterpreterParameterName = "SymbolicExpressionTreeInterpreter"; private const string MaximumSymbolicExpressionTreeLengthParameterName = "MaximumSymbolicExpressionTreeLength"; private const string RelativeNumberOfEvaluatedSamplesParameterName = "RelativeNumberOfEvaluatedSamples"; private const string FitnessCalculationPartitionParameterName = "FitnessCalculationPartition"; private const string ValidationPartitionParameterName = "ValidationPartition"; private const string ApplyLinearScalingParameterName = "ApplyLinearScaling"; private const string BoundsParameterName = "Bounds"; private const string GenotypeToPhenotypeMapperParameterName = "GenotypeToPhenotypeMapper"; private const string ProblemDataParameterDescription = ""; private const string SymbolicExpressionTreeGrammarParameterDescription = "The grammar that should be used for symbolic expression tree."; private const string SymbolicExpressionTreeInterpreterParameterDescription = "The interpreter that should be used to evaluate the symbolic expression tree."; private const string MaximumSymbolicExpressionTreeLengthParameterDescription = "Maximal length of the symbolic expression."; private const string RelativeNumberOfEvaluatedSamplesParameterDescription = "The relative number of samples of the dataset partition, which should be randomly chosen for evaluation."; private const string FitnessCalculationPartitionParameterDescription = "The partition of the problem data training partition, that should be used to calculate the fitness of an individual."; private const string ValidationPartitionParameterDescription = "The partition of the problem data training partition, that should be used to select the best model from (optional)."; private const string ApplyLinearScalingParameterDescription = "Flag that indicates if the individual should be linearly scaled before evaluating."; private const string BoundsParameterDescription = "The integer number range in which the single genomes of a genotype are created."; private const string GenotypeToPhenotypeMapperParameterDescription = "Maps the genotype (an integer vector) to the phenotype (a symbolic expression tree)."; #endregion #region parameter properties IParameter IDataAnalysisProblem.ProblemDataParameter { get { return ProblemDataParameter; } } public IValueParameter ProblemDataParameter { get { return (IValueParameter)Parameters[ProblemDataParameterName]; } } public IValueParameter SymbolicExpressionTreeGrammarParameter { get { return (IValueParameter)Parameters[SymbolicExpressionTreeGrammarParameterName]; } } public IValueParameter SymbolicExpressionTreeInterpreterParameter { get { return (IValueParameter)Parameters[SymbolicExpressionTreeInterpreterParameterName]; } } public IFixedValueParameter MaximumSymbolicExpressionTreeLengthParameter { get { return (IFixedValueParameter)Parameters[MaximumSymbolicExpressionTreeLengthParameterName]; } } public IFixedValueParameter RelativeNumberOfEvaluatedSamplesParameter { get { return (IFixedValueParameter)Parameters[RelativeNumberOfEvaluatedSamplesParameterName]; } } public IFixedValueParameter FitnessCalculationPartitionParameter { get { return (IFixedValueParameter)Parameters[FitnessCalculationPartitionParameterName]; } } public IFixedValueParameter ValidationPartitionParameter { get { return (IFixedValueParameter)Parameters[ValidationPartitionParameterName]; } } public IFixedValueParameter ApplyLinearScalingParameter { get { return (IFixedValueParameter)Parameters[ApplyLinearScalingParameterName]; } } public IValueParameter BoundsParameter { get { return (IValueParameter)Parameters[BoundsParameterName]; } } public IValueParameter GenotypeToPhenotypeMapperParameter { get { return (IValueParameter)Parameters[GenotypeToPhenotypeMapperParameterName]; } } #endregion #region properties public string Filename { get; set; } public static new Image StaticItemImage { get { return VSImageLibrary.Type; } } IDataAnalysisProblemData IDataAnalysisProblem.ProblemData { get { return ProblemData; } } public T ProblemData { get { return ProblemDataParameter.Value; } set { ProblemDataParameter.Value = value; } } public ISymbolicDataAnalysisGrammar SymbolicExpressionTreeGrammar { get { return SymbolicExpressionTreeGrammarParameter.Value; } set { SymbolicExpressionTreeGrammarParameter.Value = value; } } public ISymbolicDataAnalysisExpressionTreeInterpreter SymbolicExpressionTreeInterpreter { get { return SymbolicExpressionTreeInterpreterParameter.Value; } set { SymbolicExpressionTreeInterpreterParameter.Value = value; } } public IntValue MaximumSymbolicExpressionTreeLength { get { return MaximumSymbolicExpressionTreeLengthParameter.Value; } } public PercentValue RelativeNumberOfEvaluatedSamples { get { return RelativeNumberOfEvaluatedSamplesParameter.Value; } } public IntRange FitnessCalculationPartition { get { return FitnessCalculationPartitionParameter.Value; } } public IntRange ValidationPartition { get { return ValidationPartitionParameter.Value; } } public BoolValue ApplyLinearScaling { get { return ApplyLinearScalingParameter.Value; } } #endregion [StorableConstructor] protected GESymbolicDataAnalysisProblem(StorableConstructorFlag _) : base(_) { } [StorableHook(HookType.AfterDeserialization)] private void AfterDeserialization() { RegisterEventHandlers(); } protected GESymbolicDataAnalysisProblem(GESymbolicDataAnalysisProblem original, Cloner cloner) : base(original, cloner) { RegisterEventHandlers(); } protected GESymbolicDataAnalysisProblem(T problemData, U evaluator, V solutionCreator) : base(evaluator, solutionCreator) { Parameters.Add(new ValueParameter(ProblemDataParameterName, ProblemDataParameterDescription, problemData)); Parameters.Add(new ValueParameter(SymbolicExpressionTreeGrammarParameterName, SymbolicExpressionTreeGrammarParameterDescription)); Parameters.Add(new ValueParameter(SymbolicExpressionTreeInterpreterParameterName, SymbolicExpressionTreeInterpreterParameterDescription)); Parameters.Add(new FixedValueParameter(MaximumSymbolicExpressionTreeLengthParameterName, MaximumSymbolicExpressionTreeLengthParameterDescription)); Parameters.Add(new FixedValueParameter(FitnessCalculationPartitionParameterName, FitnessCalculationPartitionParameterDescription)); Parameters.Add(new FixedValueParameter(ValidationPartitionParameterName, ValidationPartitionParameterDescription)); Parameters.Add(new FixedValueParameter(RelativeNumberOfEvaluatedSamplesParameterName, RelativeNumberOfEvaluatedSamplesParameterDescription, new PercentValue(1))); Parameters.Add(new FixedValueParameter(ApplyLinearScalingParameterName, ApplyLinearScalingParameterDescription, new BoolValue(false))); IntMatrix m = new IntMatrix(new int[,] { { 0, 100 } }); Parameters.Add(new ValueParameter(BoundsParameterName, BoundsParameterDescription, m)); Parameters.Add(new ValueParameter(GenotypeToPhenotypeMapperParameterName, GenotypeToPhenotypeMapperParameterDescription, new DepthFirstMapper())); SymbolicExpressionTreeInterpreterParameter.Hidden = true; ApplyLinearScalingParameter.Hidden = true; if (problemData.AllowedInputVariables.Any(name => !problemData.Dataset.VariableHasType(name))) throw new NotSupportedException("Categorical variables are not supported"); SymbolicExpressionTreeGrammar = new GESymbolicExpressionGrammar(problemData.AllowedInputVariables, problemData.AllowedInputVariables.Count() * 3); SymbolicExpressionTreeInterpreter = new SymbolicDataAnalysisExpressionTreeLinearInterpreter(); FitnessCalculationPartition.Start = ProblemData.TrainingPartition.Start; FitnessCalculationPartition.End = ProblemData.TrainingPartition.End; InitializeOperators(); UpdateGrammar(); RegisterEventHandlers(); } private void DeregisterGrammarHandler() { SymbolicExpressionTreeGrammarParameter.ValueChanged -= SymbolicExpressionTreeGrammarParameter_ValueChanged; } private void RegisterGrammarHandler() { SymbolicExpressionTreeGrammarParameter.ValueChanged += SymbolicExpressionTreeGrammarParameter_ValueChanged; } private void UpdateGrammar() { DeregisterGrammarHandler(); // create a new grammar instance with the correct allowed input variables SymbolicExpressionTreeGrammarParameter.Value = new GESymbolicExpressionGrammar(ProblemData.AllowedInputVariables, ProblemData.AllowedInputVariables.Count() * 3); RegisterGrammarHandler(); } private void InitializeOperators() { Operators.AddRange(ApplicationManager.Manager.GetInstances()); Operators.Add(new SymbolicExpressionSymbolFrequencyAnalyzer()); Operators.Add(new SymbolicDataAnalysisVariableFrequencyAnalyzer()); Operators.Add(new MinAverageMaxSymbolicExpressionTreeLengthAnalyzer()); Operators.Add(new SymbolicExpressionTreeLengthAnalyzer()); ParameterizeOperators(); } #region events private void RegisterEventHandlers() { ProblemDataParameter.ValueChanged += new EventHandler(ProblemDataParameter_ValueChanged); ProblemDataParameter.Value.Changed += (object sender, EventArgs e) => OnProblemDataChanged(); RegisterGrammarHandler(); } private void ProblemDataParameter_ValueChanged(object sender, EventArgs e) { ValidationPartition.Start = 0; ValidationPartition.End = 0; ProblemDataParameter.Value.Changed += (object s, EventArgs args) => OnProblemDataChanged(); OnProblemDataChanged(); } private void SymbolicExpressionTreeGrammarParameter_ValueChanged(object sender, EventArgs e) { UpdateGrammar(); } protected override void OnEvaluatorChanged() { base.OnEvaluatorChanged(); Evaluator.SymbolicExpressionTreeParameter.ActualNameChanged += new EventHandler(Evaluator_SymbolicExpressionTreeParameter_ActualNameChanged); ParameterizeOperators(); } private void Evaluator_SymbolicExpressionTreeParameter_ActualNameChanged(object sender, EventArgs e) { ParameterizeOperators(); } public event EventHandler ProblemDataChanged; protected virtual void OnProblemDataChanged() { FitnessCalculationPartition.Start = ProblemData.TrainingPartition.Start; FitnessCalculationPartition.End = ProblemData.TrainingPartition.End; UpdateGrammar(); ParameterizeOperators(); var handler = ProblemDataChanged; if (handler != null) handler(this, EventArgs.Empty); OnReset(); } #endregion protected virtual void ParameterizeOperators() { var operators = Parameters.OfType().Select(p => p.Value).OfType().Union(Operators).ToList(); foreach (var op in operators.OfType()) { op.SymbolicExpressionTreeGrammarParameter.ActualName = SymbolicExpressionTreeGrammarParameter.Name; } foreach (var op in operators.OfType>()) { op.ProblemDataParameter.ActualName = ProblemDataParameterName; op.SymbolicExpressionTreeParameter.ActualName = Evaluator.SymbolicExpressionTreeParameter.ActualName; op.EvaluationPartitionParameter.ActualName = FitnessCalculationPartitionParameter.Name; op.RelativeNumberOfEvaluatedSamplesParameter.ActualName = RelativeNumberOfEvaluatedSamplesParameter.Name; op.ApplyLinearScalingParameter.ActualName = ApplyLinearScalingParameter.Name; op.IntegerVectorParameter.ActualName = SolutionCreator.IntegerVectorParameter.Name; op.GenotypeToPhenotypeMapperParameter.ActualName = GenotypeToPhenotypeMapperParameter.Name; op.SymbolicExpressionTreeGrammarParameter.ActualName = SymbolicExpressionTreeGrammarParameter.Name; } foreach (var op in operators.OfType()) { op.ParentsParameter.ActualName = SolutionCreator.IntegerVectorParameter.ActualName; op.ChildParameter.ActualName = SolutionCreator.IntegerVectorParameter.ActualName; } foreach (var op in operators.OfType()) { op.IntegerVectorParameter.ActualName = SolutionCreator.IntegerVectorParameter.ActualName; } foreach (var op in operators.OfType()) { op.BoundsParameter.ActualName = BoundsParameter.Name; op.LengthParameter.ActualName = MaximumSymbolicExpressionTreeLengthParameter.Name; } foreach (var op in operators.OfType()) { op.SymbolicExpressionTreeParameter.ActualName = Evaluator.SymbolicExpressionTreeParameter.ActualName; } foreach (var op in operators.OfType()) { op.ApplyLinearScalingParameter.ActualName = ApplyLinearScalingParameter.Name; } foreach (var op in operators.OfType()) { op.ApplyLinearScalingParameter.ActualName = ApplyLinearScalingParameter.Name; } foreach (var op in operators.OfType()) { op.SymbolicExpressionTreeParameter.ActualName = Evaluator.SymbolicExpressionTreeParameter.ActualName; } foreach (var op in operators.OfType>()) { op.RelativeNumberOfEvaluatedSamplesParameter.ActualName = RelativeNumberOfEvaluatedSamplesParameter.Name; op.ValidationPartitionParameter.ActualName = ValidationPartitionParameter.Name; } foreach (var op in operators.OfType()) { op.SymbolicDataAnalysisTreeInterpreterParameter.ActualName = SymbolicExpressionTreeInterpreterParameter.Name; } } #region Import & Export public virtual void Load(T data) { Name = data.Name; Description = data.Description; ProblemData = data; } public virtual T Export() { return ProblemData; } #endregion } }