[Python] How to vectorize a function within loop with break in Python 3 [closed]

I am trying to run the following program with numpy vector code within loop with break in Python 3 but get ValueError: The truth value of an array with more than one element is ambiguous because of the "if" (it's ok to compare a numpy array to a scalar as each element is compared to the scalar) How would this be possible to run it in a vectorized way ? The issue is managing the break within the loop.

Below a dummy program:

import numpy as np

THRESHOLD=0.5
ARRAY_LEN =10

def inner_compute():
pass

def compute(draws):
return draws /2

calculation = np.zeros(ARRAY_LEN)
for i in range(5):
draws = np.random.uniform(0, 1, ARRAY_LEN)
if draws < THRESHOLD:
# if above ^ creates a ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
calculation += compute(draws)
break
#use np.vectorize and call inner_compute?

print (f"calculation {calculation}")

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