private static void SelectCrossoverPoint(IRandom random, ISymbolicExpressionTree parent0, int maxBranchLength, int maxBranchDepth, out CutPoint crossoverPoint, PercentMatrix probabilities)
{
List <CutPoint> internalCrossoverPoints = new List <CutPoint>();
List <CutPoint> leafCrossoverPoints = new List <CutPoint>();
parent0.Root.ForEachNodePostfix((n) => {
if (n.SubtreeCount > 0 && n != parent0.Root)
{
//avoid linq to reduce memory pressure
for (int i = 0; i < n.SubtreeCount; i++)
{
var child = n.GetSubtree(i);
if (child.GetLength() <= maxBranchLength &&
child.GetDepth() <= maxBranchDepth)
{
if (child.SubtreeCount > 0)
{
internalCrossoverPoints.Add(new CutPoint(n, child));
}
else
{
leafCrossoverPoints.Add(new CutPoint(n, child));
}
}
}
// add one additional extension point if the number of sub trees for the symbol is not full
if (n.SubtreeCount < n.Grammar.GetMaximumSubtreeCount(n.Symbol))
{
// empty extension point
internalCrossoverPoints.Add(new CutPoint(n, n.SubtreeCount));
}
}
}
);
List <CutPoint> allCrossoverPoints = new List <CutPoint>();
allCrossoverPoints.AddRange(internalCrossoverPoints);
allCrossoverPoints.AddRange(leafCrossoverPoints);
var weights = allCrossoverPoints.Select(x => probabilities[probabilities.RowNames.ToList().IndexOf(x.Child.Symbol.Name), 0]);
crossoverPoint = allCrossoverPoints.SampleProportional(random, 1, weights).First();
}
public ISymbolicExpressionTree Cross(IRandom random,
ISymbolicExpressionTree parent0, ISymbolicExpressionTree parent1,
int maxTreeLength, int maxTreeDepth, PercentMatrix probabilities)
{
// select a random crossover point in the first parent
CutPoint crossoverPoint0;
SelectCrossoverPoint(random, parent0, maxTreeLength, maxTreeDepth, out crossoverPoint0, probabilities);
int childLength = crossoverPoint0.Child != null?crossoverPoint0.Child.GetLength() : 0;
// calculate the max length and depth that the inserted branch can have
int maxInsertedBranchLength = maxTreeLength - (parent0.Length - childLength);
int maxInsertedBranchDepth = maxTreeDepth - parent0.Root.GetBranchLevel(crossoverPoint0.Parent);
List <ISymbolicExpressionTreeNode> allowedBranches = new List <ISymbolicExpressionTreeNode>();
parent1.Root.ForEachNodePostfix((n) => {
if (n.GetLength() <= maxInsertedBranchLength &&
n.GetDepth() <= maxInsertedBranchDepth && crossoverPoint0.IsMatchingPointType(n))
{
allowedBranches.Add(n);
}
});
// empty branch
if (crossoverPoint0.IsMatchingPointType(null))
{
allowedBranches.Add(null);
}
if (allowedBranches.Count == 0)
{
return(parent0);
}
else
{
CutPointSymbolParameter.ActualValue = (ISymbol)crossoverPoint0.Parent.Symbol.Clone();
var selectedBranch = SelectRandomBranch(random, allowedBranches);
if (crossoverPoint0.Child != null)
{
// manipulate the tree of parent0 in place
// replace the branch in tree0 with the selected branch from tree1
crossoverPoint0.Parent.RemoveSubtree(crossoverPoint0.ChildIndex);
RemovedBranchParameter.ActualValue = new SymbolicExpressionTree((ISymbolicExpressionTreeNode)crossoverPoint0.Child.Clone());
if (selectedBranch != null)
{
crossoverPoint0.Parent.InsertSubtree(crossoverPoint0.ChildIndex, selectedBranch);
AddedBranchParameter.ActualValue = new SymbolicExpressionTree((ISymbolicExpressionTreeNode)selectedBranch.Clone());
}
}
else
{
// child is null (additional child should be added under the parent)
if (selectedBranch != null)
{
crossoverPoint0.Parent.AddSubtree(selectedBranch);
AddedBranchParameter.ActualValue = new SymbolicExpressionTree((ISymbolicExpressionTreeNode)selectedBranch.Clone());
}
}
return(parent0);
}
}
