numpy: Efficiently avoid 0s when taking log(matrix)

Question

from numpy import *

m = array([[1,0],
           [2,3]])

I would like to compute the element-wise log2(m), but only in the places whe

Answer 1

The masked array solution and the solution that disables the warning are both fine. For variety, here's another that uses scipy.special.xlogy. np.sign(m) is given as the x argument, so xlogy returns 0 wherever np.sign(m) is 0. The result is divided by np.log(2) to give the base-2 logarithm.

In [4]: from scipy.special import xlogy

In [5]: m = np.array([[1, 0], [2, 3]])

In [6]: xlogy(np.sign(m), m) / np.log(2)
Out[6]: 
array([[ 0.       ,  0.       ],
       [ 1.       ,  1.5849625]])