internal static void AddInvokeSymbol(ISymbolicExpressionTreeGrammar grammar, string functionName, int nArgs, CutPoint startCutPoint, IEnumerable<CutPoint> argumentCutPoints) {
if (!grammar.ContainsSymbol(startCutPoint.Child.Symbol)) return;
var invokeSym = new InvokeFunction(functionName);
grammar.AddSymbol(invokeSym);
grammar.SetSubtreeCount(invokeSym, nArgs, nArgs);
//allow invoke symbol everywhere, where the child of the startCutPoint was allowed
SetAllowedParentSymbols(grammar, startCutPoint.Child.Symbol, invokeSym);
if (nArgs > 0) {
//set allowed child symbols of invoke symbol
foreach (ISymbol child in grammar.Symbols) {
if (child.Name == invokeSym.Name) continue;
int i = 0;
foreach (CutPoint argumentCutPoint in argumentCutPoints) {
if (grammar.IsAllowedChildSymbol(argumentCutPoint.Parent.Symbol, child, argumentCutPoint.ChildIndex))
grammar.AddAllowedChildSymbol(invokeSym, child, i);
i++;
}
}
}
}
internal static void AddInvokeSymbol(ISymbolicExpressionTreeGrammar grammar, string functionName, int nArgs, CutPoint startCutPoint, IEnumerable <CutPoint> argumentCutPoints)
{
if (!grammar.ContainsSymbol(startCutPoint.Child.Symbol))
{
return;
}
var invokeSym = new InvokeFunction(functionName);
grammar.AddSymbol(invokeSym);
grammar.SetSubtreeCount(invokeSym, nArgs, nArgs);
//allow invoke symbol everywhere, where the child of the startCutPoint was allowed
SetAllowedParentSymbols(grammar, startCutPoint.Child.Symbol, invokeSym);
if (nArgs > 0)
{
//set allowed child symbols of invoke symbol
foreach (ISymbol child in grammar.Symbols)
{
if (child.Name == invokeSym.Name)
{
continue;
}
int i = 0;
foreach (CutPoint argumentCutPoint in argumentCutPoints)
{
if (grammar.IsAllowedChildSymbol(argumentCutPoint.Parent.Symbol, child, argumentCutPoint.ChildIndex))
{
grammar.AddAllowedChildSymbol(invokeSym, child, i);
}
i++;
}
}
}
}
private static void SelectCrossoverPoint(IRandom random, ISymbolicExpressionTree parent0, double internalNodeProbability, int maxBranchLength, int maxBranchDepth, out CutPoint crossoverPoint)
{
if (internalNodeProbability < 0.0 || internalNodeProbability > 1.0)
{
throw new ArgumentException("internalNodeProbability");
}
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));
}
}
}
);
if (random.NextDouble() < internalNodeProbability)
{
// select from internal node if possible
if (internalCrossoverPoints.Count > 0)
{
// select internal crossover point or leaf
crossoverPoint = internalCrossoverPoints[random.Next(internalCrossoverPoints.Count)];
}
else
{
// otherwise select external node
crossoverPoint = leafCrossoverPoints[random.Next(leafCrossoverPoints.Count)];
}
}
else if (leafCrossoverPoints.Count > 0)
{
// select from leaf crossover point if possible
crossoverPoint = leafCrossoverPoints[random.Next(leafCrossoverPoints.Count)];
}
else
{
// otherwise select internal crossover point
crossoverPoint = internalCrossoverPoints[random.Next(internalCrossoverPoints.Count)];
}
}
private static void SelectCrossoverPoint(IRandom random, ISymbolicExpressionTree parent0, double internalNodeProbability, int maxBranchLength, int maxBranchDepth, out CutPoint crossoverPoint) {
if (internalNodeProbability < 0.0 || internalNodeProbability > 1.0) throw new ArgumentException("internalNodeProbability");
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));
}
}
}
);
if (random.NextDouble() < internalNodeProbability) {
// select from internal node if possible
if (internalCrossoverPoints.Count > 0) {
// select internal crossover point or leaf
crossoverPoint = internalCrossoverPoints[random.Next(internalCrossoverPoints.Count)];
} else {
// otherwise select external node
crossoverPoint = leafCrossoverPoints[random.Next(leafCrossoverPoints.Count)];
}
} else if (leafCrossoverPoints.Count > 0) {
// select from leaf crossover point if possible
crossoverPoint = leafCrossoverPoints[random.Next(leafCrossoverPoints.Count)];
} else {
// otherwise select internal crossover point
crossoverPoint = internalCrossoverPoints[random.Next(internalCrossoverPoints.Count)];
}
}
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();
}
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();
}
