Numpy apply function to array

Question

For example, I have function:

f1 = lambda x: x % 2

If I want to modify array = np.linspace(0, 5, 6) I can do f1(array) . Everything works as expected:

[0. 1. 0. 1. 0. 1.]

If I change function to:

f2 = lambda x: 0
print(f2(array))

gives me 0 while I expected [0. 0. 0. 0. 0. 0.] [0. 0. 0. 0. 0. 0.] . How to achieve consistency?

Answer 1

You can use below code to achieve desirable output

import numpy as np
array = np.linspace(0, 5, 6)
f2 = lambda x: x-x
print(f2(array))

Answer 2

Slightly more explicit than previous answer :

import numpy as np
array = np.linspace(0, 5, 6)
f2 = lambda x: np.zeros_like(x)
print(f2(array))

Documentation for numpy.zeros_like : Return an array of zeros with the same shape and type as a given array.

Answer 3

To iterate over an array, evaluate the function for every element, then store it to a resulting array, a list iterator works consistently:

import numpy as np
array = np.linspace(0, 5, 6)
f1 = lambda x: x % 2
f2 = lambda x: 0

print ([f1(x) for x in array])

[0.0, 1.0, 0.0, 1.0, 0.0, 1.0]

print ([f2(x) for x in array])

[0, 0, 0, 0, 0, 0]