/// <summary>
/// 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.
/// </summary>
/// <param name="key">key for KD-tree node</param>
/// <param name="n">how many neighbors to find</param>
/// <param name="checker">an optional object to filter matches</param>
/// <returns>objects at node nearest to key, or null on failure</returns>
/// <exception cref="KeySizeException">if key.Length mismatches K</exception>
public List <T> Nearest(double[] key, int n, Predicate <T> checker)
{
if (n <= 0)
{
return(new List <T>());
}
NearestNeighborList <KDNode <T> > nnl = this.getNbrs(key, n, checker);
n = nnl.Count;
List <T> nbrs = new List <T>();
for (int i = 0; i < n; ++i)
{
KDNode <T> kd = nnl.RemoveHighest();
nbrs.Add(kd.Value);
}
//nbrs.Reverse();
return(nbrs);
}
private NearestNeighborList <KDNode <T> > getNbrs(double[] key, int n, Predicate <T> checker)
{
if (key.Length != this.m_K)
{
throw new KeySizeException();
}
NearestNeighborList <KDNode <T> > nnl = new NearestNeighborList <KDNode <T> >(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);
if (this.m_count > 0)
{
long timeout = (this.m_timeout > 0) ? (CurrentTimeMillis() + this.m_timeout) : 0;
KDNode <T> .NearestNeighbors(this.m_root, keyp, hr, max_dist_sqd, 0, this.m_K, nnl, checker, timeout);
}
return(nnl);
}
private List <T> nearestDistance(double[] key, double dist, DistanceMetric metric)
{
NearestNeighborList <KDNode <T> > nnl = this.getNbrs(key);
int n = nnl.Count;
List <T> nbrs = new List <T>();
for (int i = 0; i < n; ++i)
{
KDNode <T> kd = nnl.RemoveHighest();
HPoint p = kd.Key;
//HACK metric.Distance(kd.Key.Coord, key) < dist changed to - metric.Distance(kd.Key.Coord, key) <= dist
if (metric.Distance(kd.Key.Coord, key) <= dist)
{
nbrs.Add(kd.Value);
}
}
//HACK Verificar se o reverse é necessario
//nbrs.Reverse();
return(nbrs);
}
// Method Nearest Neighbor from Andrew Moore's thesis. Numbered
// comments are direct quotes from there. NearestNeighborList solution
// courtesy of Bjoern Heckel.
public static void NearestNeighbors <T>(KDNode <T> kd, HPoint target, HRect hr, double max_dist_sqd, int lev,
int K, NearestNeighborList <KDNode <T> > nnl, Predicate <T> checker,
long timeout)
{
// 1. if kd is empty then set dist-sqd to infinity and exit.
if (kd == null)
{
return;
}
if ((timeout > 0) && (timeout < DateTime.Now.TimeOfDay.TotalMilliseconds))
{
return;
}
// 2. s := split field of kd
int s = lev % K;
// 3. pivot := dom-elt field of kd
HPoint pivot = kd.key;
double pivot_to_target = HPoint.SqrDist(pivot, target);
// 4. Cut hr into to sub-hyperrectangles left-hr and right-hr.
// The cut plane is through pivot and perpendicular to the s
// dimension.
HRect left_hr = hr; // optimize by not cloning
HRect right_hr = (HRect)hr.Clone();
left_hr.Max.Coord[s] = pivot.Coord[s];
right_hr.Min.Coord[s] = pivot.Coord[s];
// 5. target-in-left := target_s <= pivot_s
bool target_in_left = target.Coord[s] < pivot.Coord[s];
KDNode <T> nearer_kd;
HRect nearer_hr;
KDNode <T> further_kd;
HRect further_hr;
// 6. if target-in-left then
// 6.1. nearer-kd := left field of kd and nearer-hr := left-hr
// 6.2. further-kd := right field of kd and further-hr := right-hr
if (target_in_left)
{
nearer_kd = kd.left;
nearer_hr = left_hr;
further_kd = kd.right;
further_hr = right_hr;
}
//
// 7. if not target-in-left then
// 7.1. nearer-kd := right field of kd and nearer-hr := right-hr
// 7.2. further-kd := left field of kd and further-hr := left-hr
else
{
nearer_kd = kd.right;
nearer_hr = right_hr;
further_kd = kd.left;
further_hr = left_hr;
}
// 8. Recursively call Nearest Neighbor with paramters
// (nearer-kd, target, nearer-hr, max-dist-sqd), storing the
// results in nearest and dist-sqd
NearestNeighbors(nearer_kd, target, nearer_hr, max_dist_sqd, lev + 1, K, nnl, checker, timeout);
// KDNode<T> nearest = nnl.getHighest();
double dist_sqd;
if (!nnl.IsCapacityReached())
{
dist_sqd = Double.MaxValue;
}
else
{
dist_sqd = nnl.MaxPriority;
}
// 9. max-dist-sqd := minimum of max-dist-sqd and dist-sqd
max_dist_sqd = Math.Min(max_dist_sqd, dist_sqd);
// 10. A nearer point could only lie in further-kd if there were some
// part of further-hr within distance max-dist-sqd of
// target.
HPoint closest = further_hr.Closest(target);
if (HPoint.SqrDist(closest, target) < max_dist_sqd)
{
// 10.1 if (pivot-target)^2 < dist-sqd then
if (pivot_to_target < dist_sqd)
{
// 10.1.1 nearest := (pivot, range-elt field of kd)
// nearest = kd;
// 10.1.2 dist-sqd = (pivot-target)^2
dist_sqd = pivot_to_target;
// add to nnl
if (!kd.deleted && ((checker == null) || checker.Invoke(kd.value)))
{
nnl.Insert(kd, dist_sqd);
}
// 10.1.3 max-dist-sqd = dist-sqd
// max_dist_sqd = dist_sqd;
if (nnl.IsCapacityReached())
{
max_dist_sqd = nnl.MaxPriority;
}
else
{
max_dist_sqd = Double.MaxValue;
}
}
// 10.2 Recursively call Nearest Neighbor with parameters
// (further-kd, target, further-hr, max-dist_sqd),
// storing results in temp-nearest and temp-dist-sqd
NearestNeighbors(further_kd, target, further_hr, max_dist_sqd, lev + 1, K, nnl, checker, timeout);
}
}