private TKey DistanceSquaredBetweenPoints(TKey[] a, TKey[] b)
{
TKey distance = typeMath.Zero;
// Return the absolute distance bewteen 2 hyper points
for (var dimension = 0; dimension < dimensions; dimension++)
{
TKey distOnThisAxis = typeMath.Subtract(a[dimension], b[dimension]);
TKey distOnThisAxisSquared = typeMath.Multiply(distOnThisAxis, distOnThisAxis);
distance = typeMath.Add(distance, distOnThisAxisSquared);
}
return(distance);
}
private KdTreeNode <TKey, TValue>[] RadialSearch(TKey[] center, TKey radius, NearestNeighbourList <KdTreeNode <TKey, TValue>, TKey> nearestNeighbours)
{
AddNearestNeighbours(
root,
center,
HyperRect <TKey> .Infinite(dimensions, typeMath),
0,
nearestNeighbours,
typeMath.Multiply(radius, radius));
var count = nearestNeighbours.Count;
var neighbourArray = new KdTreeNode <TKey, TValue> [count];
for (var index = 0; index < count; index++)
{
neighbourArray[count - index - 1] = nearestNeighbours.RemoveFurtherest();
}
return(neighbourArray);
}
public KDTreeNode <TKey, TValue>[] RangeQuery(TKey[] center, TKey radius, int count)
{
var nearestNeighbours = new NearestNeighbourList <KDTreeNode <TKey, TValue>, TKey>(count, typeMath);
AddNearestNeighbours(
root,
center,
KDTreeHyperRect <TKey> .Infinite(dimensions, typeMath),
0,
nearestNeighbours,
typeMath.Multiply(radius, radius));
count = nearestNeighbours.Count;
var neighbourArray = new KDTreeNode <TKey, TValue> [count];
for (var index = 0; index < count; index++)
{
neighbourArray[count - index - 1] = nearestNeighbours.RemoveFurtherest();
}
return(neighbourArray);
}
