// Method ins translated from 352.ins.c of Gonnet & Baeza-Yates
public static KDNode ins(HPoint key, Object val, KDNode t, int lev, int K)
{
if (t == null)
{
t = new KDNode(key, val);
}
else if (key.equals(t.k))
{
// "re-insert"
if (t.deleted)
{
t.deleted = false;
t.v = val;
}
else
{
throw (new KeyDuplicateException());
}
}
else if (key.coord[lev] > t.k.coord[lev])
{
t.right = ins(key, val, t.right, (lev + 1) % K, K);
}
else
{
t.left = ins(key, val, t.left, (lev + 1) % K, K);
}
return(t);
}
public static KDNode delete(HPoint key, KDNode t, int lev, int K, ref bool deleted)
{
if (t == null)
{
return(null);
}
if (!t.deleted && key.equals(t.k))
{
t.deleted = true;
deleted = true;
}
else if (key.coord[lev] > t.k.coord[lev])
{
t.right = delete(key, t.right, (lev + 1) % K, K, ref deleted);
}
else
{
t.left = delete(key, t.left, (lev + 1) % K, K, ref deleted);
}
if (!t.deleted || t.left != null || t.right != null)
{
return(t);
}
else
{
return(null);
}
}
// Method rsearch translated from 352.range.c of Gonnet & Baeza-Yates
public static void rsearch(HPoint lowk, HPoint uppk, KDNode t, int lev,
int K, List <KDNode> v)
{
if (t == null)
{
return;
}
if (lowk.coord[lev] <= t.k.coord[lev])
{
rsearch(lowk, uppk, t.left, (lev + 1) % K, K, v);
}
int j;
for (j = 0; j < K && lowk.coord[j] <= t.k.coord[j] &&
uppk.coord[j] >= t.k.coord[j]; j++)
{
;
}
if (j == K && !t.deleted)
{
v.Add(t);
}
if (uppk.coord[lev] > t.k.coord[lev])
{
rsearch(lowk, uppk, t.right, (lev + 1) % K, K, v);
}
}
/**
* 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 Object[] 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();
}
Object[] nbrs = new Object[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);
}
private static void hpcopy(HPoint hp_src, HPoint hp_dst)
{
for (int i = 0; i < hp_dst.coord.Length; ++i)
{
hp_dst.coord[i] = hp_src.coord[i];
}
}
// constructor is used only by class; other methods are static
private KDNode(HPoint key, Object val)
{
k = key;
v = val;
left = null;
right = null;
deleted = false;
}
public bool equals(HPoint p)
{
// seems faster than java.util.Arrays.equals(), which is not
// currently supported by Matlab anyway
for (int i = 0; i < coord.Length; ++i)
if (coord[i] != p.coord[i])
return false;
return true;
}
public static double sqrdist(HPoint x, HPoint y)
{
double dist = 0;
for (int i = 0; i < x.coord.Length; ++i)
{
double diff = (x.coord[i] - y.coord[i]);
dist += (diff * diff);
}
return(dist);
}
public static double sqrdist(HPoint x, HPoint y)
{
double dist = 0;
for (int i = 0; i < x.coord.Length; ++i)
{
double diff = (x.coord[i] - y.coord[i]);
dist += (diff * diff);
}
return dist;
}
// used in initial conditions of KDTree.nearest()
public static HRect infiniteHRect(int d)
{
HPoint vmin = new HPoint(d);
HPoint vmax = new HPoint(d);
for (int i = 0; i < d; ++i)
{
vmin.coord[i] = Double.NegativeInfinity;
vmax.coord[i] = Double.PositiveInfinity;
}
return new HRect(vmin, vmax);
}
// used in initial conditions of KDTree.nearest()
public static HRect infiniteHRect(int d)
{
HPoint vmin = new HPoint(d);
HPoint vmax = new HPoint(d);
for (int i = 0; i < d; ++i)
{
vmin.coord[i] = Double.NegativeInfinity;
vmax.coord[i] = Double.PositiveInfinity;
}
return(new HRect(vmin, vmax));
}
public bool equals(HPoint p)
{
// seems faster than java.util.Arrays.equals(), which is not
// currently supported by Matlab anyway
for (int i = 0; i < coord.Length; ++i)
{
if (coord[i] != p.coord[i])
{
return(false);
}
}
return(true);
}
// currently unused
protected HRect intersection(HRect r)
{
HPoint newmin = new HPoint(min.coord.Length);
HPoint newmax = new HPoint(min.coord.Length);
for (int i = 0; i < min.coord.Length; ++i)
{
newmin.coord[i] = Math.Max(min.coord[i], r.min.coord[i]);
newmax.coord[i] = Math.Min(max.coord[i], r.max.coord[i]);
if (newmin.coord[i] >= newmax.coord[i])
{
return(null);
}
}
return(new HRect(newmin, newmax));
}
// Method srch translated from 352.srch.c of Gonnet & Baeza-Yates
public static KDNode srch(HPoint key, KDNode t, int K)
{
for (int lev = 0; t != null; lev = (lev + 1) % K)
{
if (!t.deleted && key.equals(t.k))
{
return(t);
}
else if (key.coord[lev] > t.k.coord[lev])
{
t = t.right;
}
else
{
t = t.left;
}
}
return(null);
}
// from Moore's eqn. 6.6
public HPoint closest(HPoint t)
{
HPoint p = new HPoint(t.coord.Length);
for (int i = 0; i < t.coord.Length; ++i)
{
if (t.coord[i] <= min.coord[i])
{
p.coord[i] = min.coord[i];
}
else if (t.coord[i] >= max.coord[i])
{
p.coord[i] = max.coord[i];
}
else
{
p.coord[i] = t.coord[i];
}
}
return(p);
}
// from Moore's eqn. 6.6
public HPoint closest(HPoint t)
{
HPoint p = new HPoint(t.coord.Length);
for (int i = 0; i < t.coord.Length; ++i)
{
if (t.coord[i] <= min.coord[i])
{
p.coord[i] = min.coord[i];
}
else if (t.coord[i] >= max.coord[i])
{
p.coord[i] = max.coord[i];
}
else
{
p.coord[i] = t.coord[i];
}
}
return p;
}
// Method Nearest Neighbor from Andrew Moore's thesis. Numbered
// comments are direct quotes from there. Step "SDL" is added to
// make the algorithm work correctly. NearestNeighborList solution
// courtesy of Bjoern Heckel.
public static void nnbr(KDNode kd, HPoint target, HRect hr,
double max_dist_sqd, int lev, int K,
NearestNeighborList nnl)
{
// 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 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 nearer_kd;
HRect nearer_hr;
KDNode 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
nnbr(nearer_kd, target, nearer_hr, max_dist_sqd, lev + 1, K, nnl);
KDNode nearest = (KDNode)nnl.getHighest();
double dist_sqd;
if (!nnl.isCapacityReached())
{
dist_sqd = Double.MaxValue;
}
else
{
dist_sqd = nnl.getMaxPriority();
}
// 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 sqrt(max-dist-sqd) of
// target. If this is the case then
HPoint closest = further_hr.closest(target);
if (HPoint.eucdist(closest, target) < Math.Sqrt(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)
{
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.getMaxPriority();
}
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
nnbr(further_kd, target, further_hr, max_dist_sqd, lev + 1, K, nnl);
KDNode temp_nearest = (KDNode)nnl.getHighest();
double temp_dist_sqd = nnl.getMaxPriority();
// 10.3 If tmp-dist-sqd < dist-sqd then
if (temp_dist_sqd < dist_sqd)
{
// 10.3.1 nearest := temp_nearest and dist_sqd := temp_dist_sqd
nearest = temp_nearest;
dist_sqd = temp_dist_sqd;
}
}
// SDL: otherwise, current point is nearest
else if (pivot_to_target < max_dist_sqd)
{
nearest = kd;
dist_sqd = pivot_to_target;
}
}
protected HRect(int ndims)
{
min = new HPoint(ndims);
max = new HPoint(ndims);
}
protected HRect(HPoint vmin, HPoint vmax)
{
min = (HPoint)vmin.clone();
max = (HPoint)vmax.clone();
}
protected HRect(int ndims)
{
min = new HPoint(ndims);
max = new HPoint(ndims);
}
protected HRect(HPoint vmin, HPoint vmax)
{
min = (HPoint)vmin.clone();
max = (HPoint)vmax.clone();
}
public static double eucdist(HPoint x, HPoint y)
{
return(Math.Sqrt(sqrdist(x, y)));
}
// currently unused
protected HRect intersection(HRect r)
{
HPoint newmin = new HPoint(min.coord.Length);
HPoint newmax = new HPoint(min.coord.Length);
for (int i = 0; i < min.coord.Length; ++i)
{
newmin.coord[i] = Math.Max(min.coord[i], r.min.coord[i]);
newmax.coord[i] = Math.Min(max.coord[i], r.max.coord[i]);
if (newmin.coord[i] >= newmax.coord[i]) return null;
}
return new HRect(newmin, newmax);
}
public static double eucdist(HPoint x, HPoint y)
{
return Math.Sqrt(sqrdist(x, y));
}