def timestamps_roughly_match(f1, f2):
parser = GenericSubtitleParser()
extractor = SubtitleSpeechTransformer(sample_rate=ffsubsync.DEFAULT_FRAME_RATE)
pipe = make_pipeline(parser, extractor)
f1_bitstring = pipe.fit_transform(f1).astype(bool)
f2_bitstring = pipe.fit_transform(f2).astype(bool)
return np.alltrue(f1_bitstring == f2_bitstring)
def test_speech_extraction(sample_rate, start_seconds):
parser = GenericSubtitleParser(start_seconds=start_seconds)
extractor = SubtitleSpeechTransformer(sample_rate=sample_rate, start_seconds=start_seconds)
pipe = make_pipeline(parser, extractor)
bitstring = pipe.fit_transform(BytesIO(fake_srt)).astype(bool)
bitstring_shifted_left = np.append(bitstring[1:], [False])
bitstring_shifted_right = np.append([False], bitstring[:-1])
bitstring_cumsum = np.cumsum(bitstring)
consec_ones_end_pos = np.nonzero(bitstring_cumsum *
(bitstring ^ bitstring_shifted_left) *
(bitstring_cumsum != np.cumsum(bitstring_shifted_right)))[0]
prev = 0
for pos, sub in zip(consec_ones_end_pos, parser.subs_):
start = int(round(sub.start.total_seconds() * sample_rate))
duration = sub.end.total_seconds() - sub.start.total_seconds()
stop = start + int(round(duration * sample_rate))
assert bitstring_cumsum[pos] - prev == stop - start
prev = bitstring_cumsum[pos]
def test_max_time_found():
parser = GenericSubtitleParser()
extractor = SubtitleSpeechTransformer(sample_rate=100)
pipe = make_pipeline(parser, extractor)
pipe.fit(BytesIO(fake_srt))
assert extractor.max_time_ == 6.062