/// <summary>
/// This method was written by Ted Dunsford by restructuring the nearest neighbor
/// algorithm presented by Andrew and Bjoern
/// </summary>
/// <param name="kd">Since this is recursive, this represents the current node</param>
/// <param name="target">The target is the HPoint that we are trying to calculate the farthest distance from</param>
/// <param name="hr">In this case, the hr is the hyper rectangle bounding the region that must contain the furthest point.</param>
/// <param name="maxDistSqd">The maximum distance that we have calculated thus far, and will therefore be testing against.</param>
/// <param name="lev">The integer based level of that we have recursed to in the tree</param>
/// <param name="k">The dimensionality of the kd tree</param>
/// <param name="fnl">A list to contain the output, prioritized by distance</param>
public static void FarthestNeighbor(KdNode kd, HPoint target, HRect hr,
double maxDistSqd, int lev, int k,
FarthestNeighborList fnl)
{
// 1. if kd is empty then set dist-sqd to infinity and exit.
if (kd == null)
{
return;
}
// 2. s := split field of kd
int s = lev % k;
// 3. pivot := dom-elt field of kd
HPoint pivot = kd._k;
double pivotToTarget = HPoint.SquareDistance(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 leftHr = hr; // optimize by not cloning
HRect rightHr = hr.Copy();
leftHr._max[s] = pivot[s];
rightHr._min[s] = pivot[s];
// 5. target-in-left := target_s <= pivot_s
bool targetInLeft = target[s] < pivot[s];
KdNode nearerKd;
HRect nearerHr;
KdNode furtherKd;
HRect furtherHr;
// 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 (targetInLeft)
{
nearerKd = kd._left;
nearerHr = leftHr;
furtherKd = kd._right;
furtherHr = rightHr;
}
//
// 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
{
nearerKd = kd._right;
nearerHr = rightHr;
furtherKd = kd._left;
furtherHr = leftHr;
}
// 8. Recursively call Nearest Neighbor with paramters
// (nearer-kd, target, nearer-hr, max-dist-sqd), storing the
// results in nearest and dist-sqd
//FarthestNeighbor(nearer_kd, target, nearer_hr, max_dist_sqd, lev + 1, K, nnl);
// This line changed by Ted Dunsford to attempt to find the farther point
FarthestNeighbor(furtherKd, target, furtherHr, maxDistSqd, lev + 1, k, fnl);
//KDNode nearest = (KDNode)nnl.Highest;
double distSqd;
if (!fnl.IsCapacityReached)
{
//dist_sqd = 1.79769e+30;// Double.MaxValue;
distSqd = 0;
}
else
{
distSqd = fnl.MinimumPriority;
}
// 9. max-dist-sqd := minimum of max-dist-sqd and dist-sqd
//max_dist_sqd = Math.Min(max_dist_sqd, dist_sqd);
maxDistSqd = Math.Max(maxDistSqd, distSqd);
// 10. A nearer point could only lie in further-kd if there were some
// part of further-hr within distance sqrt(max-dist-sqd) of
// target. If this is the case then
// HPoint closest = further_hr.Closest(target);
HPoint furthest = nearerHr.Farthest(target);
//if (HPoint.EuclideanDistance(closest, target) < Math.Sqrt(max_dist_sqd))
if(HPoint.EuclideanDistance(furthest, target) > Math.Sqrt(maxDistSqd))
{
// 10.1 if (pivot-target)^2 < dist-sqd then
if (pivotToTarget > distSqd)
{
// 10.1.1 nearest := (pivot, range-elt field of kd)
//nearest = kd;
// 10.1.2 dist-sqd = (pivot-target)^2
distSqd = pivotToTarget;
// add to nnl
if (!kd.IsDeleted)
{
fnl.Insert(kd, distSqd);
}
// 10.1.3 max-dist-sqd = dist-sqd
// max_dist_sqd = dist_sqd;
if (fnl.IsCapacityReached)
{
maxDistSqd = fnl.MinimumPriority;
}
else
{
// max_dist_sqd = 1.79769e+30;//Double.MaxValue;
maxDistSqd = 0;
}
}
// 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
FarthestNeighbor(nearerKd, target, nearerHr, maxDistSqd, lev + 1, k, fnl);
KdNode tempFarthest = (KdNode)fnl.Farthest;
double tempDistSqd = fnl.MinimumPriority;
// 10.3 If tmp-dist-sqd < dist-sqd then
if (tempDistSqd > distSqd)
{
// 10.3.1 nearest := temp_nearest and dist_sqd := temp_dist_sqd
distSqd = tempDistSqd;
}
}
// SDL: otherwise, current point is nearest
else if (pivotToTarget < maxDistSqd)
{
distSqd = pivotToTarget;
}
}
/// <summary>
/// Find KD-tree nodes whose keys are <I>n</I> farthest neighbors from
/// key. Neighbors are returned in descending order of distance to key.
/// </summary>
/// <param name="key">key for KD-tree node</param>
/// <param name="numNeighbors">The Integer showing how many neighbors to find</param>
/// <returns>An array of objects at the node nearest to the key</returns>
/// <exception cref="KeySizeException">Mismatch if key length doesn't match the dimension for the tree</exception>
/// <exception cref="NeighborsOutOfRangeException">if <I>n</I> is negative or exceeds tree size </exception>
public object[] Farthest(double[] key, int numNeighbors)
{
if (numNeighbors < 0 || numNeighbors > _count) throw new NeighborsOutOfRangeException();
if (key.Length != _k) throw new KeySizeException();
object[] neighbors = new object[numNeighbors];
FarthestNeighborList fnl = new FarthestNeighborList(numNeighbors);
// initial call is with infinite hyper-rectangle and max distance
HRect hr = HRect.InfiniteHRect(key.Length);
//double max_dist_sqd = 1.79769e+30;//Double.MaxValue;
HPoint keyp = new HPoint(key);
KdNode.FarthestNeighbor(_root, keyp, hr, 0, 0, _k, fnl);
//KDNode.nnbr(_root, keyp, hr, max_dist_sqd, 0, _k, nnl);
for (int i = 0; i < numNeighbors; ++i)
{
KdNode kd = (KdNode)fnl.RemoveFarthest();
neighbors[numNeighbors - i - 1] = kd._v;
}
return neighbors;
}