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())
def setup_method(self, method):
s = EDSTEMSpectrum(np.ones([2, 2, 1024]))
energy_axis = s.axes_manager.signal_axes[0]
energy_axis.scale = 1e-2
energy_axis.units = 'keV'
energy_axis.name = "Energy"
s.set_microscope_parameters(beam_energy=200,
live_time=2.5,
tilt_stage=0.0,
azimuth_angle=0,
elevation_angle=35,
energy_resolution_MnKa=130,
beam_current=0.05)
elements = ['Al', 'Zn']
xray_lines = ['Al_Ka', 'Zn_Ka']
intensities = [300, 500]
for i, xray_line in enumerate(xray_lines):
gauss = Gaussian()
line_energy, FWHM = s._get_line_energy(xray_line, FWHM_MnKa='auto')
gauss.centre.value = line_energy
gauss.A.value = intensities[i]
gauss.sigma.value = FWHM
s.data[:] += gauss.function(energy_axis.axis)
s.set_elements(elements)
s.add_lines(xray_lines)
s.axes_manager[0].scale = 0.5
s.axes_manager[1].scale = 0.5
s.axes_manager[0].units = 'nm'
s.axes_manager[1].units = 'nm'
self.signal = s
def test_decomposition(normalise_poissonian_noise):
s = EDSTEMSpectrum(np.ones(shape=(32, 32, 1024)))
s.add_poissonian_noise()
# default uses `vacuum_mask`
s.decomposition(normalise_poissonian_noise)
# test with numpy array mask
mask = s.vacuum_mask().data
s.decomposition(normalise_poissonian_noise, navigation_mask=mask)
def setup_method(self, method):
s = EDSTEMSpectrum(np.ones([2, 2, 1024]))
energy_axis = s.axes_manager.signal_axes[0]
energy_axis.scale = 1e-2
energy_axis.units = 'keV'
energy_axis.name = "Energy"
s.set_microscope_parameters(beam_energy=200,
live_time=2.5, tilt_stage=0.0,
azimuth_angle=0, elevation_angle=35,
energy_resolution_MnKa=130,
beam_current=0.05)
elements = ['Al', 'Zn']
xray_lines = ['Al_Ka', 'Zn_Ka']
intensities = [300, 500]
for i, xray_line in enumerate(xray_lines):
gauss = Gaussian()
line_energy, FWHM = s._get_line_energy(xray_line, FWHM_MnKa='auto')
gauss.centre.value = line_energy
gauss.A.value = intensities[i]
gauss.sigma.value = FWHM
s.data[:] += gauss.function(energy_axis.axis)
s.set_elements(elements)
s.add_lines(xray_lines)
s.axes_manager[0].scale = 0.5
s.axes_manager[1].scale = 0.5
self.signal = s
def setUp(self):
s = EDSTEMSpectrum(np.ones([2, 2, 1024]))
energy_axis = s.axes_manager.signal_axes[0]
energy_axis.scale = 1e-2
energy_axis.units = "keV"
energy_axis.name = "Energy"
s.set_microscope_parameters(
beam_energy=200,
live_time=3.1,
tilt_stage=0.0,
azimuth_angle=None,
elevation_angle=35,
energy_resolution_MnKa=130,
)
s.metadata.Acquisition_instrument.TEM.Detector.EDS.real_time = 2.5
s.metadata.Acquisition_instrument.TEM.beam_current = 0.05
elements = ["Al", "Zn"]
xray_lines = ["Al_Ka", "Zn_Ka"]
intensities = [300, 500]
for i, xray_line in enumerate(xray_lines):
gauss = Gaussian()
line_energy, FWHM = s._get_line_energy(xray_line, FWHM_MnKa="auto")
gauss.centre.value = line_energy
gauss.A.value = intensities[i]
gauss.sigma.value = FWHM
s.data[:] += gauss.function(energy_axis.axis)
s.set_elements(elements)
s.add_lines(xray_lines)
s.axes_manager[0].scale = 0.5
s.axes_manager[1].scale = 0.5
self.signal = s
def _create_signal(
shape,
dim,
dtype,
):
data = np.arange(np.product(shape)).reshape(shape).astype(dtype)
if dim == 1:
if len(shape) > 2:
s = EELSSpectrum(data)
s.set_microscope_parameters(beam_energy=100.,
convergence_angle=1.,
collection_angle=10.)
else:
s = EDSTEMSpectrum(data)
s.set_microscope_parameters(beam_energy=100.,
live_time=1.,
tilt_stage=2.,
azimuth_angle=3.,
elevation_angle=4.,
energy_resolution_MnKa=5.)
else:
s = BaseSignal(data)
s.axes_manager.set_signal_dimension(dim)
for i, axis in enumerate(s.axes_manager._axes):
i += 1
axis.offset = i * 0.5
axis.scale = i * 100
axis.name = "%i" % i
if axis.navigate:
axis.units = "m"
else:
axis.units = "eV"
return s
def test_get_calibration_from(self):
s = self.signal
scalib = EDSTEMSpectrum(np.ones(1024))
energy_axis = scalib.axes_manager.signal_axes[0]
energy_axis.scale = 0.01
energy_axis.offset = -0.10
s.get_calibration_from(scalib)
assert (s.axes_manager.signal_axes[0].scale == energy_axis.scale)
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_eds():
s = EDSTEMSpectrum(([0, 1]))
s2 = EDSSEMSpectrum(([0, 1]))
s.axes_manager[0].convert_to_non_uniform_axis()
s2.axes_manager[0].convert_to_non_uniform_axis()
s.set_microscope_parameters(20)
with pytest.raises(NotImplementedError):
s.get_calibration_from(s)
with pytest.raises(NotImplementedError):
s2.get_calibration_from(s2)
m = s.create_model()
with pytest.raises(NotImplementedError):
m.add_family_lines('Al_Ka')
with pytest.raises(NotImplementedError):
m._set_energy_scale('Al_Ka', [1.0])
with pytest.raises(NotImplementedError):
m._set_energy_offset('Al_Ka', [1.0])
# numpy dataset
np.random.seed(1001)
imageds = np.random.randint(1, 5, size=(3, 32, 32))
imageds_da = da.from_array(imageds)
hsimage = Signal2D(imageds)
hsimage_da = Signal2D(imageds_da).as_lazy()
hsimage.metadata.General.original_filename = "non/existant/path.emd"
hsimage.metadata.General.title = "dummy"
hsimage_da.metadata.General.original_filename = "non/existant/path.emd"
hsimage_da.metadata.General.title = "dummy"
# spectrum maps
specmap = np.random.randint(1, 5, size=(3, 32, 32, 3))
specmap_da = da.from_array(specmap)
hsspecmap = EDSTEMSpectrum(specmap)
hsspecmap_da = EDSTEMSpectrum(specmap_da).as_lazy()
@pytest.mark.parametrize("data", [imageds, imageds_da, hsimage, hsimage_da])
def test_match_series_create(data):
mso = ms.MatchSeries(data)
assert not mso.completed
assert type(mso.data) == type(data)
@pytest.mark.xfail(raises=ValueError)
def test_match_series_fail():
ms.MatchSeries()
def setup_method(self, method):
s = EDSTEMSpectrum(np.array([np.linspace(0.001, 0.5, 20)] * 100).T)
s.add_poissonian_noise()
self.signal = s
def test_sum_minimum_missing(self):
s = EDSTEMSpectrum(np.ones((4, 2, 1024)))
s.sum()
def setup_method(self, method):
# Create an empty spectrum
s = EDSTEMSpectrum(np.ones((4, 2, 1024)))
s.metadata.Acquisition_instrument.TEM.Detector.EDS.live_time = 3.1
s.metadata.Acquisition_instrument.TEM.beam_energy = 15.0
self.signal = s
def setUp(self):
# Create an empty spectrum
s = EDSTEMSpectrum(np.ones((4, 2, 1024)))
s.mapped_parameters.TEM.EDS.live_time = 3.1
s.mapped_parameters.TEM.beam_energy = 15.0
self.signal = s
def test_sum_minimum_missing(self):
s = EDSTEMSpectrum(np.ones((4, 2, 1024)))
s.sum()
def setup_method(self, method):
s = EDSTEMSpectrum(np.array([np.linspace(0.001, 0.5, 20)] * 100).T)
s.add_poissonian_noise()
self.signal = s
def setUp(self):
s = Simulation(np.array([np.linspace(0.001, 0.5, 20)] * 100).T)
s.add_poissonian_noise()
s = EDSTEMSpectrum(s.data)
self.signal = s
