inverse elements except for zero in a numpy vector

Question

In python, I'm trying to inverse a numpy vector except for these elements with zero values.

I used vectorize function, but always got a wrong answer when the first element is zero, (the code works well when zeros are not in the first position ).

active_N=np.array([0,1,3,5])
f=np.vectorize(lambda x:x if x==0 else 1./x)
active_N_inverse=f(active_N)

Run the code then I get

array([0, 0, 0, 0])

What was wrong with the codes above? Is there any other method to solve this problem with high efficiency?

Instead of vectorizing a function, you might consider this: https://stackoverflow.com/questions/70014001/make-elements-with-value-division-by-zero-equal-to-zero-in-a-2d-numpy-array — Mark, Jan 17 '23 at 04:44

score 0 · Accepted Answer · answered Jan 17 '23 at 04:45

0

Use np.divide with a where clause:

np.divide(1, active_N, where=active_N!=0)

Optionally combined with round:

np.divide(1, active_N, where=active_N!=0).round(100)

Output:

array([0.        , 1.        , 0.33333333, 0.2       ])

answered Jan 17 '23 at 04:45

mozway

1 Answers1