def get_block_lines(s, t):
lines = []
s_tokens = [(index, i) for index, i in enumerate(s) if not is_punctuation(i)]
t_tokens = [(index, i) for index, i in enumerate(t) if not is_punctuation(i)]
if len(s_tokens) < 5 and len(t_tokens) < 5:
return lines
# Try matching.
s_lemmas = lemma_sequence(i[1] for i in s_tokens)
t_lemmas = lemma_sequence(i[1] for i in t_tokens)
matcher.set_seqs(s_lemmas, t_lemmas)
s_tokens_start = s_tokens_stop = t_tokens_start = t_tokens_stop = 0
for block_type, s_start, s_stop, t_start, t_stop in iter_blocks(s_lemmas, t_lemmas, matcher.get_matching_blocks()):
s_slice = s_tokens[s_start:s_stop]
t_slice = t_tokens[t_start:t_stop]
s_text = " ".join(i[1] for i in s_slice)
t_text = " ".join(i[1] for i in t_slice)
if block_type == NON_MATCH:
s_text = green(s_text)
t_text = red(t_text)
text = "{}\t{}".format(s_text, t_text)
else:
text = s_text
# Calculate real offsets, including punctuation.
if s_slice:
s_tokens_start = s_slice[0][0]
s_tokens_stop = s_slice[-1][0] + 1
if t_slice:
t_tokens_start = t_slice[0][0]
t_tokens_stop = t_slice[-1][0] + 1
lines.append(
"{}\t{}\t{}\t{}\t{}\t{}".format(
block_type, s_tokens_start, s_tokens_stop, t_tokens_start, t_tokens_stop, text
)
)
s_tokens_start = s_tokens_stop
t_tokens_start = t_tokens_stop
return lines
def first_norm(s):
return [tok.lower() for tok in s if not is_punctuation(tok)]
