[Numpy-discussion] How to apply a function to an ndarray over a given dimension

[Jorge Scandaliaris]

Hi,
First, excuse me if I am over-optimizing, but I am curious if there exist a way
to apply a function to an ndarray over a given dimension. In case I don't make
myself clear, I have an array of shape( n,2,2) where each row represents a 2 by
2 covariance matrix, and I want to perform the eigenvalue decomposition of each
row. Right now I do it with list comprehensions:

import numpy as np
import scipy as sp

C = np.arange(10*2*2).reshape(10,2,2)
ed = [sp.linalg.eig(r) for r in C[:]]

Is there a better way, along the lines of vectorize, of doing this?


Cheers,

Jorge