Alternatives for numpy.random generation with choice values and specific frequency of values

I am working in generating an (1109, 8) array with random values generated from a fixed set of numbers [18, 24, 36, 0], I need to ensure each row contains 5 zeros at all times, but it wasn't happening even after adjusting the weightings for probabilities.

My workaround code is below but wanted to know if there is an easier way with another function? or perhaps by adjusting some of the parameters of the generator? https://numpy.org/doc/stable/reference/random/generator.html

#Random output using new method
from numpy.random import default_rng
rng = default_rng(1)

#generate an array with random values of test duration,
test_duration = rng.choice([18, 24, 36, 0], size = arr.shape, p=[0.075, 0.1, 0.2, 0.625])
# ensure number of tests equals n_tests
n_tests = 3
non_tested = arr.shape[1] - n_tests


for row in range(len(test_duration)):
    while np.count_nonzero(test_duration[row, :]) != n_tests:
        new_test = rng.choice([18, 24, 36, 0], size = arr.shape[1], p=[0.075, 0.1, 0.2, 0.625])
        test_duration[row, :] = np.array(new_test)
    else:
        pass
print('There are no days exceeding n_tests')
#print(test_durations)
print(test_duration[:10, :])