/// <summary>
/// Reset the iterator.
/// </summary>
public void Reset()
{
// Store the point count and the distance function.
iPointsRemaining = Math.Min(iMaxPointsReturned, pRoot.Size);
_CurrentDistance = -1;
// Create an interval heap for the points we check.
pEvaluated = new IntervalHeap <T>();
// Create a min heap for the things we need to check.
pPending = new MinHeap <KDNode <T> >();
pPending.Insert(0, pRoot);
}
/// <summary>
/// Construct a new nearest neighbour iterator.
/// </summary>
/// <param name="pRoot">The root of the tree to begin searching from.</param>
/// <param name="tSearchPoint">The point in n-dimensional space to search.</param>
/// <param name="kDistance">The distance function used to evaluate the points.</param>
/// <param name="iMaxPoints">The max number of points which can be returned by this iterator. Capped to max in tree.</param>
/// <param name="fThreshold">Threshold to apply to the search space. Negative numbers indicate that no threshold is applied.</param>
public NearestNeighbour(KDNode <T> pRoot, Vector2 tSearchPoint, IDistanceFunction kDistance, int iMaxPoints, float fThreshold)
{
// Store the search point.
this.tSearchPoint = tSearchPoint;
// Store the point count, distance function and tree root.
iPointsRemaining = Math.Min(iMaxPoints, pRoot.Size);
this.fThreshold = fThreshold;
kDistanceFunction = kDistance;
this.pRoot = pRoot;
iMaxPointsReturned = iMaxPoints;
_CurrentDistance = -1;
// Create an interval heap for the points we check.
pEvaluated = new IntervalHeap <T>();
// Create a min heap for the things we need to check.
pPending = new MinHeap <KDNode <T> >();
pPending.Insert(0, pRoot);
}
