def test_compute_cleanup_after_one_utterance(self):
test_file_path = resources.sample_wav_file('wav_1.wav')
y, sr = librosa.load(test_file_path, sr=None)
frames = librosa.util.frame(y, frame_length=2048, hop_length=1024).T
# EXPECTED
S = np.abs(librosa.stft(y, center=False, n_fft=2048,
hop_length=1024))**2
S = librosa.feature.melspectrogram(S=S, n_mels=128, sr=sr)
S = librosa.power_to_db(S)
onsets = librosa.onset.onset_strength(S=S, center=False)
exp_tgram = librosa.feature.tempogram(onset_envelope=onsets,
sr=sr,
win_length=11,
center=True).T
# ACTUAL
tgram_step = pipeline.Tempogram(win_length=11)
# FIRST RUN
tgrams = tgram_step.process_frames(frames, sr, last=True)
assert np.allclose(tgrams, exp_tgram)
# SECOND RUN
tgrams = tgram_step.process_frames(frames, sr, last=True)
assert np.allclose(tgrams, exp_tgram)
def test_compute_online(self):
# Data: 41523 samples, 16 kHz
# yields 40 frames with frame-size 2048 and hop-size 1024
test_file_path = resources.sample_wav_file('wav_1.wav')
y, sr = librosa.load(test_file_path, sr=None)
# EXPECTED
y_pad = np.pad(y, (0, 1024), mode='constant', constant_values=0)
S = np.abs(
librosa.stft(y_pad, center=False, n_fft=2048, hop_length=1024))**2
S = librosa.feature.melspectrogram(S=S, n_mels=128, sr=sr)
S = librosa.power_to_db(S)
onsets = librosa.onset.onset_strength(S=S, center=False)
exp_tgram = librosa.feature.tempogram(onset_envelope=onsets,
sr=sr,
win_length=4,
center=True).T
# ACTUAL
tgram_step = pipeline.Tempogram(win_length=4)
tgram_gen = tgram_step.process_file_online(test_file_path,
2048,
1024,
chunk_size=5)
chunks = list(tgram_gen)
tgrams = np.vstack(chunks)
assert np.allclose(tgrams, exp_tgram)