This script lives in /reg/g/psdmin /sdf/group/lcls/ds/ana/tutorials/examplePythonpsana1_examples/areaDetAccess.py and py and demonstrates how to access calibrated "unassembled data" (3D array, no geometry applied) and "assembled images" (2D array, geometry applied).  Assembled/unassembled are only different for multi-panel detectors.  For monolithic 2D area detectors they are the same.

NOTE: there are many other python methods of the Detector object for Area Detectors (e.g. x,y pixel coordinates, pedestal values, masks).  One can see all the methods of a class using ipython tab completion, or looking at more complete documentation here, or examining examples in /reg/g/psdm/sw/releases/ana-current/Detector/examples/ex_all_dets.py.

from psana import *
ds = DataSource('exp=xpptut15:run=54:smd')
det = Detector('cspad')
for nevent,evt in enumerate(ds.events()):
    # includes pedestal subtraction, common-mode correction, bad-pixel
    # suppresion, and returns an "unassembled" 3D array of cspad panels
    calib_array = det.calib(evt)
    # this is the same as the above, but also uses geometry to
    # create an "assembled" 2D image (including "fake pixels" in gaps)
    img = det.image(evt)
    break
import matplotlib.pyplot as plt
plt.imshow(img,vmin=-2,vmax=2)
plt.show()

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The "image" method can also be used to convert any array with the "unassembled" shape into "assembled" format (that is, applying the geometry) with a line like this:

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NOTE: A table showing which corrections are applied to which detectors is shown on this page: Method det.calib algorithms

NOTE: There are two conventions for mapping pixels to an image, called "Cartesian" (row/column array indices are x/y) and "matrix" (row/column array indices are y/x) which are transposes of each other, as discussed here:  https://eli.thegreenplace.net/2014/meshgrids-and-disambiguating-rows-and-columns-from-cartesian-coordinates/.  psana uses the Cartesian convention.  This is shown by the following example.  If we used the matrix convention then the size of the x/y shapes would be flipped.

(ana-4.0.43) psanagpu101:~$ cat junk.py
from psana import *
runnum = 610
ds = DataSource('exp=xpptut15:run='+str(runnum))
det = Detector('jungfrau4M')
im_x = det.image_xaxis(runnum)
im_y = det.image_yaxis(runnum)
for evt in ds.events():
    img = det.image(evt)
    break
print(f'Image shape: {img.shape}, X shape: {im_x.shape}, Y shape:{im_y.shape}')
(ana-4.0.43) psanagpu101:~$ python junk.py
('Image shape: (2203, 2299), X shape: (2203,), Y shape: (2299,))
(ana-4.0.43) psanagpu101:~$ 

References

• AreaDetector - documentation of methods of the "Area"  Detector interface.
  
  • calib()
  • image()
  • Method det.calib algorithms

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