pyinterp.RTree.query#
- RTree.query(coordinates: ndarray, k: Optional[int] = 4, within: Optional[bool] = True, num_threads: Optional[int] = 0) Tuple[ndarray, ndarray] [source]#
Search for the nearest K nearest neighbors of a given point.
- Parameters:
coordinates – a matrix
(n, ndims)
wheren
is the number of observations andndims
is the number of coordinates in order: longitude and latitude in degrees, altitude in meters and then the other coordinates defined in Euclidean space ifdims
> 3. If the shape of the matrix is(n, ndims)
then the method considers the altitude constant and equal to zero.k – The number of nearest neighbors to be searched. Defaults to
4
.within – If true, the method ensures that the neighbors found are located within the point of interest. Defaults to
false
.num_threads – The number of threads to use for the computation. If 0 all CPUs are used. If 1 is given, no parallel computing code is used at all, which is useful for debugging. Defaults to
0
.
- Returns:
A tuple containing a matrix describing for each provided position, the distance, in meters, between the provided position and the found neighbors and a matrix containing the value of the different neighbors found for all provided positions. If no neighbors are found, the distance and the value are set to
-1
.