def test_mask(self):
numpy_array = np.zeros((10, 10, 30, 30))
numpy_array[:, :, 0, 0] = 1000
numpy_array[:, :, -1, -1] = 1
dask_array = da.from_array(numpy_array, chunks=(5, 5, 5, 5))
centre_x, centre_y = np.ones((2, 100)) * 15
data = pst._radial_average_dask_array(
dask_array,
return_sig_size=22,
centre_x=centre_x,
centre_y=centre_y,
normalize=False,
show_progressbar=False,
)
assert data.shape == (10, 10, 22)
assert (data != 0.0).any()
mask = pst._make_circular_mask(15, 15, 30, 30, 15)
data = pst._radial_average_dask_array(
dask_array,
return_sig_size=22,
centre_x=centre_x,
centre_y=centre_y,
normalize=False,
mask_array=mask,
show_progressbar=False,
)
assert data.shape == (10, 10, 22)
assert (data == 0.0).all()
def test_different_size(self):
dask_array = da.zeros((5, 10, 12, 15), chunks=(5, 5, 5, 5))
centre_x, centre_y = np.ones((2, 100)) * 7.5
data = pst._radial_average_dask_array(
dask_array,
return_sig_size=11,
centre_x=centre_x,
centre_y=centre_y,
normalize=False,
show_progressbar=False,
)
assert data.shape == (5, 10, 11)
assert (data == 0.0).all()
