def test_map_values_std_isset(self, weighted):
self._post_setup_method(weighted)
m = self.m
L = Gaussian(centre=15.)
L.centre.free = L.sigma.free = False
m.append(L)
m.multifit(iterpath="serpentine")
nonlinear = L.A.map.copy()
L.A.map['is_set'] = False
cm = pytest.warns(UserWarning) if weighted and not self.s._lazy else \
dummy_context_manager()
with cm:
m.multifit(optimizer='lstsq', calculate_errors=True)
linear = L.A.map.copy()
np.testing.assert_allclose(nonlinear['values'], linear['values'])
np.testing.assert_allclose(nonlinear['std'], linear['std'])
np.testing.assert_allclose(nonlinear['is_set'], linear['is_set'])
cm = pytest.warns(UserWarning) if weighted and not self.s._lazy else \
dummy_context_manager()
with cm:
m.multifit(optimizer='lstsq', calculate_errors=False)
np.testing.assert_equal(L.A.map['std'], np.nan)
def test_offset(self, weighted):
self._post_setup_method(weighted)
m = self.m
L = Offset(offset=1.)
m.append(L)
m.fit(optimizer='lstsq')
single = m.as_signal()
m.assign_current_values_to_all()
cm = pytest.warns(UserWarning) if weighted and not self.s._lazy else \
dummy_context_manager()
with cm:
m.multifit(optimizer='lstsq', iterpath='serpentine')
multi = m.as_signal()
# compare fits from first pixel
np.testing.assert_allclose(single(), multi())
def test_gaussian(self, weighted):
self._post_setup_method(weighted)
m = self.m
L = Gaussian(centre=15.)
L.centre.free = L.sigma.free = False
m.append(L)
m.fit(optimizer='lstsq')
single = m.as_signal()
m.assign_current_values_to_all()
cm = pytest.warns(UserWarning) if weighted and not self.s._lazy else \
dummy_context_manager()
with cm:
m.multifit(optimizer='lstsq', iterpath='serpentine')
multi = m.as_signal()
np.testing.assert_allclose(single(), multi())
def test_main_header_from_signal(unit, expected_scale_factor, version, fheb,
sig, fake_signals, metadata, fake_metadatas):
signal = fake_signals[sig]
if metadata is not None:
signal._metadata = fake_metadatas[metadata]
signal.axes_manager[-1].units = unit
signal.axes_manager[-2].units = unit
original_scale_x = signal.axes_manager[-2].scale
if unit == "foo":
cm = pytest.warns(UserWarning)
else:
cm = dummy_context_manager()
with cm:
header = _get_main_header_from_signal(signal, version, fheb)
assert header["size"] == np.dtype(TVIPS_RECORDER_GENERAL_HEADER).itemsize
assert header["version"] == version
assert header["dimx"] == signal.axes_manager[-2].size
assert header["dimy"] == signal.axes_manager[-1].size
assert header["offsetx"] == 0
assert header["offsety"] == 0
assert header["pixelsize"] == original_scale_x * expected_scale_factor
assert header["frameheaderbytes"] == np.dtype(
TVIPS_RECORDER_FRAME_HEADER).itemsize + fheb
if metadata == "diffraction" and unit == "1/pm":
assert header[
"magtotal"] == signal.metadata.Acquisition_instrument.TEM.camera_length
elif metadata == "imaging" and unit == "um":
assert header[
"magtotal"] == signal.metadata.Acquisition_instrument.TEM.magnification
else:
assert header["magtotal"] == 0
if metadata is None:
assert header["ht"] == 0
else:
assert header[
"ht"] == signal.metadata.Acquisition_instrument.TEM.beam_energy
