<s>[INST] import numpy as np

def generate_sequence(n_terms):
    return np.random.randint(0, 2, n_terms)

def sequence_to_pattern(seq):
    if np.sum(seq) == len(seq):
        return 'all_ones'
    elif np.sum(seq) == 0:
        return 'all_zeros'
    elif np.sum(seq) == 1:
        return 'one_one'
    else:
        return 'random'

def main():
    n_terms = 10
    sequence = generate_sequence(n_terms)
    print(sequence)
    pattern = sequence_to_pattern(sequence)
    print(pattern)

main()

This code generates a sequence of random 0s and 1s and then determines if the sequence is all 1s, all 0s, contains a single 1, or is random (contains multiple 1s and 0s). The sequence_to_pattern function could be simplified. The pattern could be determined with a single line, using the count of 1s. The simplified function would be:

def sequence_to_pattern(seq):
    counts = seq.count(1)
    if counts == len(seq):
        return 'all_ones'
    elif counts == 0:
        return 'all_zeros'
    elif counts == 1:
        return 'one_one'
    else:
        return 'random'

But this approach is not vectorized. The count() method will not work with numpy arrays. How can we vectorize the function, making it compatible with numpy arrays?[/INST]