Content

Data

  • exp=sxrx22915:run=104
  • Camp.0:pnCCD.1
  • /reg/d/psdm/sxr/sxrx22915/calib/PNCCD::CalibV1/Camp.0:pnCCD.1/
  • all plots for event 10

Raw image

Mask

mask = det.mask(evt, calib=True, status=True)

returns a combination of masks

  • /reg/d/psdm/sxr/sxrx22915/calib/PNCCD::CalibV1/Camp.0:pnCCD.1/pixel_status/103-end.data
  • /reg/d/psdm/sxr/sxrx22915/calib/PNCCD::CalibV1/Camp.0:pnCCD.1/pixel_mask/0-end.data

Pedestals

Gain

Corrected data

raw - pedestal

Raw-pedestals daq array: DAQ shape is (4,512,512). Raw data is re-shaped as (4*512, 512), 2048 rows and 512 columns

The same array combined in image using geometry

/reg/d/psdm/sxr/sxrx22915/calib/PNCCD::CalibV1/Camp.0:pnCCD.1/geometry/0-end.data

image is shaped as (1027, 1273) rows,cols:

 

Rows and columns in ASICS have the same direction as in image, although some ASICS in image may be combined upside-down.

raw - pedestal - cm in rows (512 pixels in median)

raw - pedestal - cm in rows (512) and columns (512)

Gain map is not applied

Standard Detector correction (128 in rows)

raw - pedestal cm in rows(128) and columns (512) using mask for square regions

Last version of common mode correction for pnccd

  • Bill requested to correct all pixels.
  • For each group of pixels common mode is evaluated using pixels defined by mask (1), then applied to all pixels in the group.

Best pnccd image correction algorithm for sxrx22915

  • raw data - pedestal
  • apply gain factor
  • apply common mode correction in rows (128 pixel), mode=1
  • apply common mode correction in columns (512 pixel), mode=4
  • apply mask from status (bad pixels only)

Summary

  • Image for raw data has horizontal and vertical stripes
  • pedestals and gain, averaged for many images (common mode is averaged to zero), have vertical strips ONLY!
  • So, common mode effect gives strong contribution in rows (horizantal strips)
  • Median algorithms gives bands in image depending on regions of image brightness
  • Algorithm properly accounting masked pixel regions with large signal removes image artifacts.

References

 

 

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