np.random.choice returns out of range index on masked array prob.

import numpy as np

a = np.array([0.1, 0.2, 0.4, 0.3])
masked_a = np.ma.masked_array(a, [0, 0, 1, 1])
counter = np.zeros(len(a) + 1)
while True:
    action = np.random.choice(len(a), p=masked_a)
    counter[action] += 1
    print(counter / counter.sum())
    
# [0.09931198 0.20076697 0.         0.         0.69992105]

It shouldn't returns an index > 3, but when the last element of masked array is true, it may return index = 4

Start at the np.random.choice entry point and reproduce the behavior with the masked_a example from the issue, including a mask on the final element. Trace how the masked probability array is handled and verify that repeated sampling never returns an index outside the input range.