[18061] | 1 | using System;
|
---|
| 2 | using System.Collections.Generic;
|
---|
| 3 | using System.Linq;
|
---|
| 4 | using System.Text;
|
---|
| 5 | using System.Threading.Tasks;
|
---|
| 6 | using HeuristicLab.Core;
|
---|
| 7 | using HeuristicLab.Optimization;
|
---|
| 8 | using HEAL.Attic;
|
---|
| 9 | using HeuristicLab.Common;
|
---|
| 10 | using HeuristicLab.Problems.Instances;
|
---|
| 11 | using HeuristicLab.Parameters;
|
---|
| 12 | using HeuristicLab.Data;
|
---|
[18062] | 13 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
|
---|
[18061] | 14 |
|
---|
[18063] | 15 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression {
|
---|
[18061] | 16 | [StorableType("7464E84B-65CC-440A-91F0-9FA920D730F9")]
|
---|
[18063] | 17 | [Item(Name = "Structured Symbolic Regression Single Objective Problem (single-objective)", Description = "A problem with a structural definition and unfixed subfunctions.")]
|
---|
| 18 | [Creatable(CreatableAttribute.Categories.GeneticProgrammingProblems, Priority = 150)]
|
---|
[18061] | 19 | public class StructuredSymbolicRegressionSingleObjectiveProblem : SingleObjectiveBasicProblem<MultiEncoding>, IRegressionProblem, IProblemInstanceConsumer<RegressionProblemData> {
|
---|
| 20 |
|
---|
| 21 | #region Constants
|
---|
| 22 | private const string ProblemDataParameterName = "ProblemData";
|
---|
| 23 | private const string StructureDefinitionParameterName = "Structure Definition";
|
---|
[18063] | 24 | private const string StructureTemplateParameterName = "Structure Template";
|
---|
[18072] | 25 |
|
---|
| 26 | private const string StructureTemplateDescriptionText =
|
---|
| 27 | "Enter your expression as string in infix format into the empty input field.\n" +
|
---|
| 28 | "By checking the \"Apply Linear Scaling\" checkbox you can add the relevant scaling terms to your expression.\n" +
|
---|
| 29 | "After entering the expression click parse to build the tree.\n" +
|
---|
| 30 | "To edit the defined sub-functions, click on the coressponding colored node in the tree view.";
|
---|
[18061] | 31 | #endregion
|
---|
| 32 |
|
---|
[18072] | 33 | #region Parameters
|
---|
[18061] | 34 | public IValueParameter<IRegressionProblemData> ProblemDataParameter => (IValueParameter<IRegressionProblemData>)Parameters[ProblemDataParameterName];
|
---|
| 35 | public IFixedValueParameter<StringValue> StructureDefinitionParameter => (IFixedValueParameter<StringValue>)Parameters[StructureDefinitionParameterName];
|
---|
[18063] | 36 | public IFixedValueParameter<StructureTemplate> StructureTemplateParameter => (IFixedValueParameter<StructureTemplate>)Parameters[StructureTemplateParameterName];
|
---|
[18061] | 37 | #endregion
|
---|
| 38 |
|
---|
| 39 | #region Properties
|
---|
| 40 | public IRegressionProblemData ProblemData {
|
---|
| 41 | get => ProblemDataParameter.Value;
|
---|
| 42 | set {
|
---|
| 43 | ProblemDataParameter.Value = value;
|
---|
| 44 | ProblemDataChanged?.Invoke(this, EventArgs.Empty);
|
---|
| 45 | }
|
---|
| 46 | }
|
---|
| 47 |
|
---|
| 48 | public string StructureDefinition {
|
---|
| 49 | get => StructureDefinitionParameter.Value.Value;
|
---|
| 50 | set => StructureDefinitionParameter.Value.Value = value;
|
---|
| 51 | }
|
---|
| 52 |
|
---|
[18063] | 53 | public StructureTemplate StructureTemplate {
|
---|
| 54 | get => StructureTemplateParameter.Value;
|
---|
| 55 | }
|
---|
| 56 |
|
---|
[18071] | 57 | public ISymbolicDataAnalysisExpressionTreeInterpreter Interpreter { get; } = new SymbolicDataAnalysisExpressionTreeInterpreter();
|
---|
| 58 |
|
---|
[18061] | 59 | IParameter IDataAnalysisProblem.ProblemDataParameter => ProblemDataParameter;
|
---|
| 60 | IDataAnalysisProblemData IDataAnalysisProblem.ProblemData => ProblemData;
|
---|
| 61 |
|
---|
[18066] | 62 | public override bool Maximization => true;
|
---|
[18061] | 63 | #endregion
|
---|
| 64 |
|
---|
| 65 | #region EventHandlers
|
---|
| 66 | public event EventHandler ProblemDataChanged;
|
---|
| 67 | #endregion
|
---|
| 68 |
|
---|
| 69 | #region Constructors & Cloning
|
---|
| 70 | public StructuredSymbolicRegressionSingleObjectiveProblem() {
|
---|
[18062] | 71 | var problemData = new ShapeConstrainedRegressionProblemData();
|
---|
| 72 |
|
---|
[18065] | 73 | var structureTemplate = new StructureTemplate();
|
---|
[18066] | 74 | structureTemplate.Changed += OnTemplateChanged;
|
---|
[18065] | 75 |
|
---|
[18066] | 76 | Parameters.Add(new ValueParameter<IRegressionProblemData>(ProblemDataParameterName, problemData));
|
---|
[18072] | 77 | Parameters.Add(new FixedValueParameter<StructureTemplate>(StructureTemplateParameterName,
|
---|
| 78 | StructureTemplateDescriptionText, structureTemplate));
|
---|
[18066] | 79 |
|
---|
[18072] | 80 |
|
---|
[18061] | 81 | }
|
---|
| 82 |
|
---|
[18072] | 83 | public StructuredSymbolicRegressionSingleObjectiveProblem(StructuredSymbolicRegressionSingleObjectiveProblem original,
|
---|
| 84 | Cloner cloner) : base(original, cloner){ }
|
---|
[18061] | 85 |
|
---|
| 86 | [StorableConstructor]
|
---|
[18063] | 87 | protected StructuredSymbolicRegressionSingleObjectiveProblem(StorableConstructorFlag _) : base(_) { }
|
---|
[18065] | 88 | #endregion
|
---|
[18061] | 89 |
|
---|
[18065] | 90 | #region Cloning
|
---|
[18061] | 91 | public override IDeepCloneable Clone(Cloner cloner) =>
|
---|
| 92 | new StructuredSymbolicRegressionSingleObjectiveProblem(this, cloner);
|
---|
| 93 | #endregion
|
---|
| 94 |
|
---|
[18066] | 95 | private void OnTemplateChanged(object sender, EventArgs args) {
|
---|
[18068] | 96 | SetupStructureTemplate();
|
---|
| 97 | }
|
---|
| 98 |
|
---|
| 99 | private void SetupStructureTemplate() {
|
---|
[18066] | 100 | foreach (var e in Encoding.Encodings.ToArray())
|
---|
| 101 | Encoding.Remove(e);
|
---|
| 102 |
|
---|
[18068] | 103 | foreach (var f in StructureTemplate.SubFunctions.Values) {
|
---|
| 104 | SetupVariables(f);
|
---|
| 105 | if(!Encoding.Encodings.Any(x => x.Name == f.Name)) // to prevent the same encoding twice
|
---|
| 106 | Encoding.Add(new SymbolicExpressionTreeEncoding(f.Name, f.Grammar, f.MaximumSymbolicExpressionTreeLength, f.MaximumSymbolicExpressionTreeDepth));
|
---|
[18066] | 107 | }
|
---|
| 108 | }
|
---|
| 109 |
|
---|
| 110 | public override void Analyze(Individual[] individuals, double[] qualities, ResultCollection results, IRandom random) {
|
---|
| 111 | base.Analyze(individuals, qualities, results, random);
|
---|
| 112 |
|
---|
| 113 | int bestIdx = 0;
|
---|
| 114 | double bestQuality = Maximization ? double.MinValue : double.MaxValue;
|
---|
| 115 | for(int idx = 0; idx < qualities.Length; ++idx) {
|
---|
| 116 | if((Maximization && qualities[idx] > bestQuality) ||
|
---|
| 117 | (!Maximization && qualities[idx] < bestQuality)) {
|
---|
| 118 | bestQuality = qualities[idx];
|
---|
| 119 | bestIdx = idx;
|
---|
| 120 | }
|
---|
| 121 | }
|
---|
| 122 |
|
---|
[18071] | 123 | if (results.TryGetValue("Best Tree", out IResult result)) {
|
---|
| 124 | var tree = BuildTree(individuals[bestIdx]);
|
---|
[18072] | 125 | if (StructureTemplate.ApplyLinearScaling)
|
---|
| 126 | AdjustLinearScalingParams(tree, Interpreter);
|
---|
[18071] | 127 | result.Value = tree;
|
---|
| 128 | }
|
---|
| 129 | else {
|
---|
| 130 | var tree = BuildTree(individuals[bestIdx]);
|
---|
[18072] | 131 | if (StructureTemplate.ApplyLinearScaling)
|
---|
| 132 | AdjustLinearScalingParams(tree, Interpreter);
|
---|
[18071] | 133 | results.Add(new Result("Best Tree", tree));
|
---|
| 134 | }
|
---|
| 135 |
|
---|
[18066] | 136 | }
|
---|
| 137 |
|
---|
[18065] | 138 | public override double Evaluate(Individual individual, IRandom random) {
|
---|
[18066] | 139 | var tree = BuildTree(individual);
|
---|
[18071] | 140 |
|
---|
[18072] | 141 | if (StructureTemplate.ApplyLinearScaling)
|
---|
| 142 | AdjustLinearScalingParams(tree, Interpreter);
|
---|
[18066] | 143 | var estimationInterval = ProblemData.VariableRanges.GetInterval(ProblemData.TargetVariable);
|
---|
| 144 | var quality = SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator.Calculate(
|
---|
[18071] | 145 | Interpreter, tree,
|
---|
[18066] | 146 | estimationInterval.LowerBound, estimationInterval.UpperBound,
|
---|
| 147 | ProblemData, ProblemData.TrainingIndices, false);
|
---|
| 148 |
|
---|
| 149 | return quality;
|
---|
| 150 | }
|
---|
| 151 |
|
---|
[18071] | 152 | private void AdjustLinearScalingParams(ISymbolicExpressionTree tree, ISymbolicDataAnalysisExpressionTreeInterpreter interpreter) {
|
---|
| 153 | var offsetNode = tree.Root.GetSubtree(0).GetSubtree(0);
|
---|
| 154 | var scalingNode = offsetNode.Subtrees.Where(x => !(x is ConstantTreeNode)).First();
|
---|
| 155 |
|
---|
| 156 | var offsetConstantNode = (ConstantTreeNode)offsetNode.Subtrees.Where(x => x is ConstantTreeNode).First();
|
---|
| 157 | var scalingConstantNode = (ConstantTreeNode)scalingNode.Subtrees.Where(x => x is ConstantTreeNode).First();
|
---|
| 158 |
|
---|
| 159 | var estimatedValues = interpreter.GetSymbolicExpressionTreeValues(tree, ProblemData.Dataset, ProblemData.TrainingIndices);
|
---|
| 160 | var targetValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices);
|
---|
| 161 |
|
---|
| 162 | OnlineLinearScalingParameterCalculator.Calculate(estimatedValues, targetValues, out double a, out double b, out OnlineCalculatorError error);
|
---|
| 163 | if(error == OnlineCalculatorError.None) {
|
---|
| 164 | offsetConstantNode.Value = a;
|
---|
| 165 | scalingConstantNode.Value = b;
|
---|
| 166 | }
|
---|
| 167 | }
|
---|
| 168 |
|
---|
[18066] | 169 | private ISymbolicExpressionTree BuildTree(Individual individual) {
|
---|
[18065] | 170 | var templateTree = (ISymbolicExpressionTree)StructureTemplate.Tree.Clone();
|
---|
[18066] | 171 |
|
---|
[18065] | 172 | // build main tree
|
---|
| 173 | foreach (var n in templateTree.IterateNodesPrefix()) {
|
---|
[18066] | 174 | if (n.Symbol is SubFunctionSymbol) {
|
---|
| 175 | var subFunctionTreeNode = n as SubFunctionTreeNode;
|
---|
[18068] | 176 | var subFunctionTree = individual.SymbolicExpressionTree(subFunctionTreeNode.Name);
|
---|
[18071] | 177 | //var parent = n.Parent;
|
---|
[18062] | 178 |
|
---|
[18066] | 179 | // remove SubFunctionTreeNode
|
---|
[18071] | 180 | //parent.RemoveSubtree(parent.IndexOfSubtree(subFunctionTreeNode));
|
---|
[18065] | 181 |
|
---|
[18066] | 182 | // add new tree
|
---|
| 183 | var subTree = subFunctionTree.Root.GetSubtree(0) // Start
|
---|
| 184 | .GetSubtree(0); // Offset
|
---|
[18071] | 185 | //parent.AddSubtree(subTree);
|
---|
| 186 | subFunctionTreeNode.AddSubtree(subTree);
|
---|
[18065] | 187 | }
|
---|
| 188 | }
|
---|
[18066] | 189 | return templateTree;
|
---|
[18061] | 190 | }
|
---|
| 191 |
|
---|
[18068] | 192 | private void SetupVariables(SubFunction subFunction) {
|
---|
| 193 | var varSym = (Variable)subFunction.Grammar.GetSymbol("Variable");
|
---|
| 194 | if (varSym == null) {
|
---|
| 195 | varSym = new Variable();
|
---|
| 196 | subFunction.Grammar.AddSymbol(varSym);
|
---|
| 197 | }
|
---|
| 198 |
|
---|
| 199 | var allVariables = ProblemData.InputVariables.Select(x => x.Value);
|
---|
| 200 | var allInputs = allVariables.Where(x => x != ProblemData.TargetVariable);
|
---|
| 201 |
|
---|
| 202 | // set all variables
|
---|
| 203 | varSym.AllVariableNames = allVariables;
|
---|
| 204 |
|
---|
| 205 | // set all allowed variables
|
---|
| 206 | if (subFunction.Arguments.Contains("_")) {
|
---|
| 207 | varSym.VariableNames = allInputs;
|
---|
| 208 | } else {
|
---|
| 209 | var vars = new List<string>();
|
---|
| 210 | var exceptions = new List<Exception>();
|
---|
| 211 | foreach (var arg in subFunction.Arguments) {
|
---|
| 212 | if (allInputs.Contains(arg))
|
---|
| 213 | vars.Add(arg);
|
---|
| 214 | else
|
---|
| 215 | exceptions.Add(new ArgumentException($"The argument '{arg}' for sub-function '{subFunction.Name}' is not a valid variable."));
|
---|
| 216 | }
|
---|
| 217 | if (exceptions.Any())
|
---|
| 218 | throw new AggregateException(exceptions);
|
---|
| 219 | varSym.VariableNames = vars;
|
---|
| 220 | }
|
---|
| 221 |
|
---|
| 222 | varSym.Enabled = true;
|
---|
| 223 | }
|
---|
| 224 |
|
---|
[18061] | 225 | public void Load(RegressionProblemData data) {
|
---|
| 226 | ProblemData = data;
|
---|
[18068] | 227 | SetupStructureTemplate();
|
---|
[18061] | 228 | }
|
---|
| 229 | }
|
---|
| 230 | }
|
---|