def get_radial_profile(self,
mask_array=None,
inplace=False,
*args,
**kwargs):
"""Return the radial profile of the diffraction pattern.
Parameters
----------
mask_array : numpy.array
Optional array with the same dimensions as the signal axes.
Consists of 0s for excluded pixels and 1s for non-excluded
pixels. The 0-pixels are excluded from the radial average.
inplace : bool
If True (default), this signal is overwritten. Otherwise, returns a
new signal.
*args:
Arguments to be passed to map().
**kwargs:
Keyword arguments to be passed to map().
Returns
-------
radial_profile: :obj:`pyxem.signals.ElectronDiffraction1D`
The radial average profile of each diffraction pattern in the
ElectronDiffraction2D signal as an ElectronDiffraction1D.
See also
--------
:func:`pyxem.utils.expt_utils.radial_average`
"""
radial_profiles = self.map(radial_average,
mask=mask_array,
inplace=inplace,
*args,
**kwargs)
radial_profiles.axes_manager.signal_axes[0].offset = 0
signal_axis = radial_profiles.axes_manager.signal_axes[0]
rp = ElectronDiffraction1D(radial_profiles.as_signal1D(signal_axis))
ax_old = self.axes_manager.navigation_axes
rp.axes_manager.navigation_axes[0].scale = ax_old[0].scale
rp.axes_manager.navigation_axes[0].units = ax_old[0].units
rp.axes_manager.navigation_axes[0].name = ax_old[0].name
if len(ax_old) > 1:
rp.axes_manager.navigation_axes[1].scale = ax_old[1].scale
rp.axes_manager.navigation_axes[1].units = ax_old[1].units
rp.axes_manager.navigation_axes[1].name = ax_old[1].name
rp_axis = rp.axes_manager.signal_axes[0]
rp_axis.name = 'k'
rp_axis.scale = self.axes_manager.signal_axes[0].scale
rp_axis.units = '$A^{-1}$'
return rp
def electron_diffraction1d():
"""A simple, multiuse diffraction profile, with dimensions:
ElectronDiffraction1D <2,2|12>
"""
data = np.array([
[[1.0, 0.25, 0.0, 0.0, 0.0], [1.0, 0.25, 0.0, 0.0, 0.0]],
[[1.0, 0.25, 0.0, 0.0, 0.16666667], [1.5, 0.5, 0.0, 0.0, 0.0]],
])
return ElectronDiffraction1D(data)
def test_2d_data_as_lazy(self):
data = np.random.random((100, 150))
s = ElectronDiffraction1D(data)
scale0, scale1, metadata_string = 0.5, 1.5, "test"
s.axes_manager[0].scale = scale0
s.axes_manager[1].scale = scale1
s.metadata.Test = metadata_string
s_lazy = s.as_lazy()
assert isinstance(s_lazy, LazyElectronDiffraction1D)
assert hasattr(s_lazy.data, "compute")
assert s_lazy.axes_manager[0].scale == scale0
assert s_lazy.axes_manager[1].scale == scale1
assert s_lazy.metadata.Test == metadata_string
assert data.shape == s_lazy.data.shape
def test_2d_data_as_lazy(self):
data = np.random.random((100, 150))
s = ElectronDiffraction1D(data)
scale0, scale1, metadata_string = 0.5, 1.5, 'test'
s.axes_manager[0].scale = scale0
s.axes_manager[1].scale = scale1
s.metadata.Test = metadata_string
s_lazy = s.as_lazy()
assert s_lazy.__class__ == LazyElectronDiffraction1D
assert hasattr(s_lazy.data, 'compute')
assert s_lazy.axes_manager[0].scale == scale0
assert s_lazy.axes_manager[1].scale == scale1
assert s_lazy.metadata.Test == metadata_string
assert data.shape == s_lazy.data.shape
def red_int_generator():
data = np.arange(10, 0, -1).reshape(1, 10) * np.arange(1, 5).reshape(4, 1)
data = data.reshape(2, 2, 10)
rp = ElectronDiffraction1D(data)
rigen = ReducedIntensityGenerator1D(rp)
return rigen
def test_3d_data_as_lazy(self):
data = np.random.random((4, 10, 15))
s = ElectronDiffraction1D(data)
s_lazy = s.as_lazy()
assert isinstance(s_lazy, LazyElectronDiffraction1D)
assert data.shape == s_lazy.data.shape
def test_3d_data_as_lazy(self):
data = np.random.random((4, 10, 15))
s = ElectronDiffraction1D(data)
s_lazy = s.as_lazy()
assert s_lazy.__class__ == LazyElectronDiffraction1D
assert data.shape == s_lazy.data.shape
