If/else statement vs Heaviside function

In my code I have to consider different contributions with respect to different thresholds. In particular I have a function my_index whose output must be compared to the thresholds Z_1, Z_2, Z_3 in order to determine the increment to the variable my_value. In the following MWE, for simplicity sake, the function my_index is just a uniform random generator:

import numpy as np

my_len = 100000
Z_1 = 0.2
Z_2 = 0.4
Z_3 = 0.7

first = 1

second = 2

third = -0.0003

my_value = 0

for i in range(my_len):

  my_index = np.random.uniform()

  my_value += first*np.heaviside(my_index - Z_1,0)*np.heaviside(Z_2 - my_index,0) + second*np.heaviside(my_index - Z_3,0) + third*np.heaviside(Z_3 - my_index,0)

#if Z_1 < my_index < Z_2 add first
#if my_index > Z_3 add second
#if my_index < Z_3 add third

I have replaced if/else's that could have been used for the thresholds with the Heaviside function see. Keep in mind that, in my original code, this code section has to be iterated up to 10^5 times.

My question is: does this practice make the code faster? Or is the heaviside function (np.heaviside) call better in terms of speed than the if/else control?