Fast way of computing covariance matrix of nonstationary kernel in Python
I still would apply numpy's covaranice function using numpy.apply_along_axis 

import numpy as np

x = np.array([[0, 2], [1, 1], [2, 0]]).T
np.apply_along_axis(func1d=np.cov, arr=x, axis=0)