source: branches/gp-crossover/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Crossovers/SymbolicDataAnalysisExpressionContextAwareCrossover.cs @ 7089

#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2011 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
 *
 * This file is part of HeuristicLab.
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 * HeuristicLab is free software: you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
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 * GNU General Public License for more details.
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 * You should have received a copy of the GNU General Public License
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#endregion

using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
using HeuristicLab.Data;

namespace HeuristicLab.Problems.DataAnalysis.Symbolic {

  [Item("ContextAwareCrossover", "An operator which performs subtree swapping in a deterministic way: it checks all possible cross points in the second parent with the aim of creating the best possible offspring.")]
  public sealed class SymbolicDataAnalysisExpressionContextAwareCrossover<T> : SymbolicDataAnalysisExpressionCrossover<T> where T : class, IDataAnalysisProblemData {
    [StorableConstructor]
    private SymbolicDataAnalysisExpressionContextAwareCrossover(bool deserializing) : base(deserializing) { }
    private SymbolicDataAnalysisExpressionContextAwareCrossover(SymbolicDataAnalysisExpressionContextAwareCrossover<T> original, Cloner cloner)
      : base(original, cloner) {
    }
    public SymbolicDataAnalysisExpressionContextAwareCrossover()
      : base() {
    }
    public override IDeepCloneable Clone(Cloner cloner) {
      return new SymbolicDataAnalysisExpressionContextAwareCrossover<T>(this, cloner);
    }
    protected override ISymbolicExpressionTree Cross(IRandom random, ISymbolicExpressionTree parent0, ISymbolicExpressionTree parent1) {
      if (this.ExecutionContext == null)
        throw new InvalidOperationException("ExecutionContext not set.");
      IEnumerable<int> rows = GenerateRowsToEvaluate();
      T problemData = ProblemDataParameter.ActualValue;
      ISymbolicDataAnalysisSingleObjectiveEvaluator<T> evaluator = EvaluatorParameter.ActualValue;

      return Cross(random, parent0, parent1, this.ExecutionContext, evaluator, problemData, rows, MaximumSymbolicExpressionTreeDepth.Value, MaximumSymbolicExpressionTreeLength.Value);
    }
    /// <summary>
    /// Takes two parent individuals P0 and P1. 
    /// Randomly choose a node i from the first parent, then test all nodes j from the second parent to determine the best child that would be obtained by swapping i for j.
    /// </summary>
    public static ISymbolicExpressionTree Cross(IRandom random, ISymbolicExpressionTree parent0, ISymbolicExpressionTree parent1, IExecutionContext context,
                                                ISymbolicDataAnalysisSingleObjectiveEvaluator<T> evaluator, T problemData, IEnumerable<int> rows, int maxDepth, int maxLength) {
      List<CutPoint> crossoverPoints0 = new List<CutPoint>();
      parent0.Root.ForEachNodePostfix((n) => {
        if (n.Subtrees.Any() && n != parent0.Root)
          foreach (var child in n.Subtrees)
            crossoverPoints0.Add(new CutPoint(n, child));
      });
      CutPoint crossoverPoint0 = crossoverPoints0[random.Next(crossoverPoints0.Count)];
      int level = parent0.Root.GetBranchLevel(crossoverPoint0.Child);
      int length = parent0.Root.GetLength() - crossoverPoint0.Child.GetLength();

      List<ISymbolicExpressionTreeNode> allowedBranches = new List<ISymbolicExpressionTreeNode>();
      parent1.Root.ForEachNodePostfix((n) => {
        if (n.Subtrees.Any() && n != parent1.Root)
          foreach (var child in n.Subtrees)
            if (crossoverPoint0.IsMatchingPointType(child) && (child.GetDepth() + level <= maxDepth) && (child.GetLength() + length <= maxLength))
              allowedBranches.Add(child);
      });

      // check if empty branch is allowed
      if (crossoverPoint0.IsMatchingPointType(null)) allowedBranches.Add(null);

      if (allowedBranches.Count == 0)
        return parent0;

      var dataset = problemData.Dataset;

      // create symbols in order to improvize an ad-hoc tree so that the child can be evaluated
      ISymbolicExpressionTreeNode selectedBranch = null;

      var nodeQualities = new List<Tuple<ISymbolicExpressionTreeNode, double>>();

      foreach (var node in allowedBranches) {
        swap(crossoverPoint0, node);
        double quality = evaluator.Evaluate(context, parent0, problemData, rows);
        nodeQualities.Add(new Tuple<ISymbolicExpressionTreeNode, double>(node, quality));
      }

      nodeQualities.Sort((a, b) => a.Item2.CompareTo(b.Item2)); // assuming this sorts the list in ascending order

      if (evaluator.Maximization)
        selectedBranch = nodeQualities.Last().Item1;
      else
        selectedBranch = nodeQualities.First().Item1;

      // swap the node that would create the best offspring
      swap(crossoverPoint0, selectedBranch);

      return parent0;
    }

    private static void swap(CutPoint crossoverPoint, ISymbolicExpressionTreeNode selectedBranch) {
      if (crossoverPoint.Child != null) {
        // manipulate the tree of parent0 in place
        // replace the branch in tree0 with the selected branch from tree1
        crossoverPoint.Parent.RemoveSubtree(crossoverPoint.ChildIndex);
        if (selectedBranch != null) {
          crossoverPoint.Parent.InsertSubtree(crossoverPoint.ChildIndex, selectedBranch);
        }
      } else {
        // child is null (additional child should be added under the parent)
        if (selectedBranch != null) {
          crossoverPoint.Parent.AddSubtree(selectedBranch);
        }
      }
    }
  }
}