def test_sine_extraction_scale(self):
frame_size = 1024
hop_size = 512
bin_freq = 44100. / float(frame_size)
num_frames = 10
batch_size = 10
spectral = SpectralSummarized()
features = np.ndarray((
10,
22,
))
for i in range(batch_size):
sine = utils.make_test_cosine(22050, bin_freq * (i + 1), 44100)
audio = AudioBuffer(sine, 44100)
features[i] = spectral(audio)
assert features.shape == (10, 22)
scaled = spectral.fit_scaler(features)
assert scaled.mean() == pytest.approx(0.)
assert scaled.std() == pytest.approx(1.)
np.testing.assert_array_almost_equal(scaled.mean(0), np.zeros(22))
np.testing.assert_array_almost_equal(scaled.std(0), np.ones(22))
def test_batch_scale_magnitude(self):
bin_freq = 44100. / 1024.
feature_batch = np.zeros((10, 513))
fft = FFT(output='magnitude', scale_axis=None)
for i in range(10):
bin = (i + 1) * 2
sine = utils.make_test_cosine(1024, bin_freq * bin, 44100)
audio = AudioBuffer(sine, 44100)
feature_batch[i] = fft(audio)
scaled = fft.fit_scaler(feature_batch)
expected_mean = (512.0 * 10) / (513.0 * 10)
assert fft.scaler.mean == pytest.approx(expected_mean)
def test_sine_wave_stft_power(self):
bin_freq = 44100. / 1024.
sine = utils.make_test_cosine(1024 + 1, bin_freq * 10, 44100)
audio = AudioBuffer(sine, 44100)
stft = STFT(output='power', fft_size=1024)
features = stft(audio)
expected = np.zeros((513, 3))
# amplitude is spread out over neighbouring bins
expected[9, :] = 128. * 128.
expected[10, :] = 256. * 256.
expected[11, :] = 128. * 128.
assert features.shape == (513, 3)
assert isinstance(features[0][0], np.float32)
np.testing.assert_array_almost_equal(features, expected)
def test_sine_wave_fft_power_phase(self):
bin_freq = 44100. / 1024.
# Using a cosine here to get zero initial phase
sine = utils.make_test_cosine(1024, bin_freq * 10, 44100)
audio = AudioBuffer(sine, 44100)
fft = FFT(output='power_phase')
features = fft(audio)
expected = np.zeros((513, 2))
expected[10][0] = 512. * 512.
assert features.shape == (513, 2)
assert isinstance(features[0][0], np.float32)
assert isinstance(features[0][1], np.float32)
# Assert correct magnitude
np.testing.assert_array_almost_equal(features[:, 0], expected[:, 0])
# Uncertain about phase, except for 10th bin
assert features[10][1] == pytest.approx(0.)
def test_sine_wave_stft_magnitude_scaled(self):
bin_freq = 44100. / 1024.
length = (1024. * 10) + 1
stft = STFT(output='magnitude',
fft_size=1024,
hop_size=512,
time_major=True,
scale_axis=None)
batch_size = 10
features = np.zeros((10, 21, 513))
for i in range(batch_size):
sine = utils.make_test_cosine(int(length), bin_freq * (i + 10),
44100)
audio = AudioBuffer(sine, 44100)
features[i] = stft(audio)
scaled = stft.fit_scaler(features)
assert scaled.shape == (10, 21, 513)
assert scaled.mean() == pytest.approx(0.)
assert scaled.std() == pytest.approx(1.)
def test_sine_extraction(self):
frame_size = 1024
hop_size = 512
bin_freq = 44100. / float(frame_size)
sine = utils.make_test_cosine(1024 + 1, bin_freq * 10, 44100)
audio = AudioBuffer(sine, 44100)
spectral = SpectralSummarized(frame_size=1024, hop_size=512)
features = spectral(audio)
assert features.shape == (22, )
assert features[0] == pytest.approx(bin_freq * 10)
assert features[1] == pytest.approx(0.)
assert features[2] == pytest.approx(30.452547928239625)
assert features[3] == pytest.approx(0.)
assert features[4] == pytest.approx(0.)
assert features[5] == pytest.approx(0.)
assert features[6] == pytest.approx(bin_freq * 11)
assert features[7] == pytest.approx(0.)
# Spectral flatness subbands
assert features[8] == pytest.approx(44.0823996531185)
assert features[9] == pytest.approx(0.)
assert features[10] == pytest.approx(44.0823996531185)
assert features[11] == pytest.approx(0.)
assert features[12] == pytest.approx(124.0823996531185)
assert features[13] == pytest.approx(0.)
assert features[14] == pytest.approx(44.0823996531185)
assert features[15] == pytest.approx(0.)
assert features[16] == pytest.approx(44.0823996531185)
assert features[17] == pytest.approx(0.)
assert features[18] == pytest.approx(44.0823996531185)
assert features[19] == pytest.approx(0.)
assert features[20] == pytest.approx(44.0823996531185)
assert features[21] == pytest.approx(0.)
