linalg.norm not taking axis argument

Question

I am using Python 3 within Pyzo. Please could you tell me why the linalg.norm function does not recognise the axis argument.

This code:

c = np.array([[ 1, 2, 3],[-1, 1, 4]])
d=linalg.norm(c, axis=1)

returns the error:

TypeError: norm() got an unexpected keyword argument 'axis'

Answer 1

linalg.norm does not accept an axis argument. You can get around that with:

np.apply_along_axis(np.linalg.norm, 1, c)
# array([ 3.74165739,  4.24264069])

Or to be faster, implement it yourself with:

np.sqrt(np.einsum('ij,ij->i',c,c))
# array([ 3.74165739,  4.24264069])

For timing:

timeit np.apply_along_axis(np.linalg.norm, 1, c)
10000 loops, best of 3: 170 µs per loop

timeit np.sqrt(np.einsum('ij,ij->i',c,c))
100000 loops, best of 3: 10.7 µs per loop

Answer 2

On numpy versions below 1.8 linalg.norm does not take axis argument, you can use np.apply_along_axis to get your desired outcome, as pointed out by Warren Weckesser in the comment to the question.

import numpy as np
from numpy import linalg

c = np.array([[ 1, 2, 3],[-1, 1, 4]])

d = np.apply_along_axis(linalg.norm, 1, c)

Result:

>>> d
array([ 3.74165739,  4.24264069])