itertools.product(metrics, scalings, message_lengths)))
def eval_one_parameter_set(metric, scaling, message_length):
- for i in range(trials):
+ for _ in range(trials):
sample_start = random.randint(0, corpus_length - message_length)
sample = corpus[sample_start:(sample_start + message_length)]
key = random.randint(1, 25)
sample_ciphertext = caesar_encipher(sample, key)
- (found_key, score) = caesar_break(sample_ciphertext,
+ found_key, _ = caesar_break(sample_ciphertext,
metric=metric['func'],
target_counts=scaling['corpus_frequency'],
message_frequency_scaling=scaling['scaling'])