def test_linear_upscale_out(self):
spectrum = EDSTEMSpectrum(np.ones([4, 1, 1]))
scale = [1, 0.4, 1]
offset = [0, -0.3, 0]
res = spectrum.rebin(scale=scale)
spectrum.data[2][0] = 5
spectrum.rebin(scale=scale, out=res)
np.testing.assert_allclose(
res.data,
[
[[0.4]],
[[0.4]],
[[0.4]],
[[0.4]],
[[0.4]],
[[2.0]],
[[2.0]],
[[1.2]],
[[0.4]],
[[0.4]],
],
atol=1e-3,
)
for axis in res.axes_manager._axes:
assert scale[axis.index_in_axes_manager] == axis.scale
assert offset[axis.index_in_axes_manager] == axis.offset
def test_linear_upsize(self, dtype):
spectrum = EDSTEMSpectrum(np.ones([4, 5, 10], dtype=dtype))
scale = [0.3, 0.2, 0.5]
res = spectrum.rebin(scale=scale)
np.testing.assert_allclose(res.data, 0.03 * np.ones((20, 16, 20)))
for axis in res.axes_manager._axes:
assert scale[axis.index_in_axes_manager] == axis.scale
res = spectrum.rebin(scale=scale, crop=False)
np.testing.assert_allclose(res.data.sum(), spectrum.data.sum())
def test_linear_downsize(self, dtype):
spectrum = EDSTEMSpectrum(np.ones([3, 5, 1], dtype=dtype))
scale = (1.5, 2.5, 1)
res = spectrum.rebin(scale=scale, crop=True)
np.testing.assert_allclose(res.data, 3.75 * np.ones((1, 3, 1)))
for axis in res.axes_manager._axes:
assert scale[axis.index_in_axes_manager] == axis.scale
res = spectrum.rebin(scale=scale, crop=False)
np.testing.assert_allclose(res.data.sum(), spectrum.data.sum())
