Note
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Coordinates in Pyxem#
Pyxem is flexible in how it handles coordinates for a diffraction pattern.
There are three main ways to handle coordinates in Pyxem:
Pixel coordinates
Calibrated Coordinates with evenly spaced axes
Calibrated Coordinates with unevenly spaced axes (e.g. corrected for the Ewald sphere)
import pyxem as pxm
from skimage.morphology import disk
s = pxm.signals.Diffraction2D(disk((10)))
s.calibrate.center = None
print(s.calibrate.center)
[10.0, 10.0]
s.plot(axes_ticks=True)
# From the plot above you can see that hyperspy automatically sets the axes ticks to be centered
# on each pixel. This means that for a 21x21 pixel image, the center is at (-10, -10) in pixel coordinates.
# if we change the scale using the calibrate function it will automatically adjust the center. Here it is
# now (-1, -1)
s.calibrate.scale = 0.1
s.calibrate.units = "nm$^{-1}$"
s.plot(axes_ticks=True)
print(s.calibrate.center)
[10.0, 10.0]
# Azimuthal Integration
# ---------------------
#
# Now if we do integrate this dataset it will choose the appropriate center based on the center pixel.
az = s.get_azimuthal_integral2d(npt=30)
az.plot()
[ ] | 0% Completed | 142.43 us
[########################################] | 100% Completed | 100.50 ms
# Non-Linear Axes
# ---------------
#
# Now consider the case where we have non-linear axes. In this case the center is still (10,10)
# but things are streatched based on the effects of the Ewald Sphere.
s.calibrate.beam_energy = 200
s.calibrate.detector(pixel_size=0.1, detector_distance=3)
print(s.calibrate.center)
s.plot()
az = s.get_azimuthal_integral2d(npt=30)
az.plot()
[10, 10]
[ ] | 0% Completed | 157.43 us
[########################################] | 100% Completed | 100.46 ms
Total running time of the script: (0 minutes 7.877 seconds)