/**
* Find KD-tree nodes whose keys are <I>n</I> nearest neighbors to
* key. Uses algorithm above. Neighbors are returned in ascending
* order of distance to key.
*
* @param key key for KD-tree node
* @param n how many neighbors to find
*
* @return objects at node nearest to key, or null on failure
*
* @throws KeySizeException if key.length mismatches K
* @throws IllegalArgumentException if <I>n</I> is negative or
* exceeds tree size
*/
public TYPE[] nearest(double[] key, int n)
{
if (n < 0 || n > m_count)
{
throw new ArgumentException("Number of neighbors cannot be negative or greater than number of nodes");
}
if (key.Length != m_K)
{
throw new KeySizeException();
}
TYPE[] nbrs = new TYPE[n];
NearestNeighborList nnl = new NearestNeighborList(n);
// initial call is with infinite hyper-rectangle and max distance
HRect hr = HRect.infiniteHRect(key.Length);
double max_dist_sqd = Double.MaxValue;
HPoint keyp = new HPoint(key);
KDNode.nnbr(m_root, keyp, hr, max_dist_sqd, 0, m_K, nnl);
for (int i = 0; i < n; ++i)
{
KDNode kd = (KDNode)nnl.removeHighest();
nbrs[n - i - 1] = kd.v;
}
return(nbrs);
}
