def test_matches_fftfreq(self):
samplerate = SR44100()
n_bands = 2048
fft_freqs = np.fft.rfftfreq(n_bands, 1 / int(samplerate))
bands = LinearScale.from_sample_rate(samplerate, n_bands // 2)
linear_freqs = np.array([b.start_hz for b in bands])
np.testing.assert_allclose(linear_freqs, fft_freqs[:-1])
def fft(x, axis=-1, padding_samples=0):
"""
Apply an FFT along the given dimension, and with the specified amount of
zero-padding
Args:
x (ArrayWithUnits): an :class:`~zounds.core.ArrayWithUnits` instance
which has one or more :class:`~zounds.timeseries.TimeDimension`
axes
axis (int): The axis along which the fft should be applied
padding_samples (int): The number of padding zeros to apply along
axis before performing the FFT
"""
if padding_samples > 0:
padded = np.concatenate(
[x, np.zeros((len(x), padding_samples), dtype=x.dtype)], axis=axis)
else:
padded = x
transformed = np.fft.rfft(padded, axis=axis, norm='ortho')
sr = audio_sample_rate(int(Seconds(1) / x.dimensions[axis].frequency))
scale = LinearScale.from_sample_rate(sr, transformed.shape[-1])
new_dimensions = list(x.dimensions)
new_dimensions[axis] = FrequencyDimension(scale)
return ArrayWithUnits(transformed, new_dimensions)
def _process(self, data):
transformed = self._process_raw(data)
sr = audio_sample_rate(data.dimensions[1].samples_per_second)
scale = LinearScale.from_sample_rate(sr, transformed.shape[1])
yield ArrayWithUnits(
transformed,
[data.dimensions[0], FrequencyDimension(scale)])
def _process(self, data):
raw = self._process_raw(data)
sr = audio_sample_rate(
int(data.shape[1] / data.dimensions[0].duration_in_seconds))
scale = LinearScale.from_sample_rate(
sr, data.shape[1], always_even=self.scale_always_even)
yield ArrayWithUnits(
raw,
[data.dimensions[0], FrequencyDimension(scale)])
def _process(self, data):
transformed = dct(data, norm='ortho', axis=self._axis)
sr = audio_sample_rate(
int(data.shape[1] / data.dimensions[0].duration_in_seconds))
scale = LinearScale.from_sample_rate(
sr, transformed.shape[-1], always_even=self.scale_always_even)
yield ArrayWithUnits(
transformed,
[data.dimensions[0], FrequencyDimension(scale)])
def test_can_get_all_even_sized_bands(self):
samplerate = SR44100()
scale = LinearScale.from_sample_rate(samplerate,
44100,
always_even=True)
log_scale = GeometricScale(20, 20000, 0.01, 64)
slices = [scale.get_slice(band) for band in log_scale]
sizes = [s.stop - s.start for s in slices]
self.assertTrue(
not any([s % 2 for s in sizes]),
'All slice sizes should be even but were {sizes}'.format(
**locals()))