A numpy vectorized function doesn't return the expected result

First I define a relu function and vectorize it.

Then I feed an arbitrary list into this relu function, but it returns the wrong result, because the value of relu(1.5) should be 1.5.

The code is as follows:

import numpy as np

def relu(x):
    return x if x > 0 else 0

relu = np.vectorize(relu)

print(relu([-3,-1.5,0,1.5,3]))
# result: array([0, 0, 0, 1, 3])

Could you please explain to me why this happens?

>Solution :

Because vectorize assumes the type from the first element unless output type is specified. Use

relu = np.vectorize(relu,otypes=[float])