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:

  1. Pixel coordinates

  2. Calibrated Coordinates with evenly spaced axes

  3. 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.calibration.center = None
print(s.calibration.center)
[10.0, 10.0]
s.plot(axes_ticks=True)
Signal

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 calibration function it will automatically adjust the center. Here it is now (-1, -1)

s.calibration.scale = 0.1
s.calibration.units = "nm$^{-1}$"
s.plot(axes_ticks=True)
print(s.calibration.center)
Signal
[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()
Signal
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 50%|█████     | 1/2 [00:03<00:03,  3.41s/it]
100%|██████████| 2/2 [00:03<00:00,  1.71s/it]

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.calibration.beam_energy = 200
s.calibration.detector(pixel_size=0.1, detector_distance=3)
print(s.calibration.center)
s.plot()

az = s.get_azimuthal_integral2d(npt=30)
az.plot()
  • Signal
  • Signal
[np.int64(10), np.int64(10)]

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100%|██████████| 2/2 [00:00<00:00, 2990.59it/s]

sphinx_gallery_thumbnail_number = 4

Total running time of the script: (0 minutes 10.962 seconds)

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