def test_apodization(lazy, window_type, inplace):
SIZE_NAV0 = 2
SIZE_NAV1 = 3
SIZE_NAV2 = 4
SIZE_SIG0 = 50
SIZE_SIG1 = 60
SIZE_SIG2 = 70
ax_dict0 = {'size': SIZE_NAV0, 'navigate': True}
ax_dict1 = {'size': SIZE_SIG0, 'navigate': False}
ax_dict2 = {'size': SIZE_SIG1, 'navigate': False}
ax_dict3 = {'size': SIZE_SIG2, 'navigate': False}
# 1. Test apodization for signal 1D, 2D, 3D:
data = np.random.rand(SIZE_NAV0 * SIZE_NAV1 * SIZE_SIG0 *
SIZE_NAV2).reshape(
(SIZE_NAV0, SIZE_NAV1, SIZE_NAV2, SIZE_SIG0))
data2 = np.random.rand(SIZE_NAV0 * SIZE_NAV1 * SIZE_SIG0 *
SIZE_SIG1).reshape(
(SIZE_NAV0, SIZE_NAV1, SIZE_SIG0, SIZE_SIG1))
data3 = np.random.rand(SIZE_NAV0 * SIZE_SIG2 * SIZE_SIG0 *
SIZE_SIG1).reshape(
(SIZE_NAV0, SIZE_SIG0, SIZE_SIG1, SIZE_SIG2))
signal1d = Signal1D(data)
signal2d = Signal2D(data2)
signal3d = BaseSignal(data3, axes=[ax_dict0, ax_dict1, ax_dict2, ax_dict3])
if lazy:
signal1d = signal1d.as_lazy()
signal2d = signal2d.as_lazy()
signal3d = signal3d.as_lazy()
if window_type == 'hann':
window = np.hanning(SIZE_SIG0)
window1 = np.hanning(SIZE_SIG1)
window2 = np.hanning(SIZE_SIG2)
window2d = np.outer(window, window1)
window3d = outer_nd(window, window1, window2)
if inplace:
signal1d_a = signal1d.deepcopy()
signal1d_a.apply_apodization(window=window_type, inplace=inplace)
else:
signal1d_a = signal1d.apply_apodization(window=window_type)
data_a = data * window[np.newaxis, np.newaxis, np.newaxis, :]
if inplace:
signal2d_a = signal2d.deepcopy()
signal2d_a.apply_apodization(window=window_type, inplace=inplace)
else:
signal2d_a = signal2d.apply_apodization(window=window_type,
inplace=inplace)
data2_a = data2 * window2d[np.newaxis, np.newaxis, :, :]
if inplace:
signal3d_a = signal3d.deepcopy()
signal3d_a.apply_apodization(window=window_type, inplace=inplace)
else:
signal3d_a = signal3d.apply_apodization(window=window_type,
inplace=inplace)
data3_a = data3 * window3d[np.newaxis, :, :, :]
assert np.allclose(signal1d_a.data, data_a)
assert np.allclose(signal2d_a.data, data2_a)
assert np.allclose(signal3d_a.data, data3_a)
for hann_order in 9 * (np.random.rand(5)) + 1:
window = hann_window_nth_order(SIZE_SIG0, order=int(hann_order))
signal1d_a = signal1d.apply_apodization(window=window_type,
hann_order=int(hann_order))
data_a = data * window[np.newaxis, np.newaxis, np.newaxis, :]
assert np.allclose(signal1d_a.data, data_a)
elif window_type == 'hamming':
window = np.hamming(SIZE_SIG0)
signal1d_a = signal1d.apply_apodization(window=window_type)
data_a = data * window[np.newaxis, np.newaxis, np.newaxis, :]
assert np.allclose(signal1d_a.data, data_a)
elif window_type == 'tukey':
for tukey_alpha in np.random.rand(5):
window = tukey(SIZE_SIG0, alpha=tukey_alpha)
signal1d_a = signal1d.apply_apodization(window=window_type,
tukey_alpha=tukey_alpha)
data_a = data * window[np.newaxis, np.newaxis, np.newaxis, :]
assert np.allclose(signal1d_a.data, data_a)
# 2. Test raises:
with pytest.raises(ValueError):
signal1d.apply_apodization(window='hamm')
