public void Reset()
{
this.iPointsRemaining = Math.Min(this.iMaxPointsReturned, this.pRoot.Size);
this._CurrentDistance = -1;
this.pEvaluated = new IntervalHeap <T>();
this.pPending = new MinHeap <KDNode <T> >();
this.pPending.Insert(0, this.pRoot);
}
public NearestNeighbour(KDNode <T> pRoot, double[] tSearchPoint, DistanceFunctions kDistance, int iMaxPoints, double fThreshold)
{
if ((int)tSearchPoint.Length != pRoot.iDimensions)
{
throw new Exception("Dimensionality of search point and kd-tree are not the same.");
}
this.tSearchPoint = new double[(int)tSearchPoint.Length];
Array.Copy(tSearchPoint, this.tSearchPoint, (int)tSearchPoint.Length);
this.iPointsRemaining = Math.Min(iMaxPoints, pRoot.Size);
this.fThreshold = fThreshold;
this.kDistanceFunction = kDistance;
this.pRoot = pRoot;
this.iMaxPointsReturned = iMaxPoints;
this._CurrentDistance = -1;
this.pEvaluated = new IntervalHeap <T>();
this.pPending = new MinHeap <KDNode <T> >();
this.pPending.Insert(0, pRoot);
}
