Package | Description |
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Jcg.rangesearch |
Modifier and Type | Field and Description |
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private PointCloud_KdTree |
MedianWithSorting.N |
PointCloud_KdTree |
PointCloud_KdTree.next |
private PointCloud_KdTree |
KdTree.points |
Modifier and Type | Method and Description |
---|---|
PointCloud_KdTree |
FastRangeSearch.NN(X q,
double sqRad)
Main search procedure (for Range search queries)
|
PointCloud_KdTree |
RangeSearch.OrthogonalRangeSearch(X q,
double sqRad)
Range search: return the list of nearest points to a given query point q.
|
PointCloud_KdTree |
FastRangeSearch.OrthogonalRangeSearch(X q,
double sqRad)
Perform range search using KdTrees
|
PointCloud_KdTree |
KdTree.OrthogonalRangeSearch(X q,
double sqRad)
Range search: return the list of nearest point to a given query point q.
|
static PointCloud_KdTree |
PointCloud_KdTree.randomPoints(int n,
int dim)
return a point cloud of n random points (in the unit hyper-square in dimension dim)
|
static PointCloud_KdTree |
PointCloud_KdTree.randomPointsOnCircle(int n,
int dim)
return a point cloud of n random points sampled on a circle
(according to normal distribution)
|
static PointCloud_KdTree[] |
KdTree.split(PointCloud_KdTree N,
double cutValue,
int cutDim)
Split a point cloud into two sub-point clouds (lower an upper point clouds)
|
Modifier and Type | Method and Description |
---|---|
static double[] |
PointCloud_KdTree.boundingBox(PointCloud_KdTree N) |
static <X extends Point_> |
KdTree.constructDataStructure(PointCloud_KdTree N,
int pDim)
Construct a Kd-Tree from a point cloud (in dimension pDim)
|
static Point_d[] |
PointCloud_KdTree.copy(PointCloud_KdTree N,
int size) |
static Point_d |
PointCloud_KdTree.mean(PointCloud_KdTree N) |
static int |
PointCloud_KdTree.size(PointCloud_KdTree N)
return the size (number of points)
|
static PointCloud_KdTree[] |
KdTree.split(PointCloud_KdTree N,
double cutValue,
int cutDim)
Split a point cloud into two sub-point clouds (lower an upper point clouds)
|
Constructor and Description |
---|
FastRangeSearch(PointCloud_KdTree N)
Construct the data structure for range search
|
KdTree(PointCloud_KdTree N,
int pDim,
int cutDim)
Constructor -- builds the entire Kd-tree at once recursively
|
MedianWithSorting(PointCloud_KdTree points) |
PointCloud_KdTree(Point_d p,
PointCloud_KdTree n,
boolean copy)
Constructor: add a new point to the cloud (copying or not)
|