I have a numpy array, filtered__rows, comprised of LAS data [x, y, z, intensity, classification]. I have created a cKDTree of points
Do you know how that translates for multi-dimensional arrays?
It can be expanded to multi dimensional arrays by giving a 1d array for every index so for a 2d array
filter_indices=np.array([[1,0],[0,1]])
array=np.array([[0,1],[1,2]])
print(array[filter_indices[:,0],filter_indices[:,1])
will give you : [1,1]
Scipy has an explanation on what will happen if you call:
print(array[filter_indices])
https://docs.scipy.org/doc/numpy-1.13.0/user/basics.indexing.html