Versions Compared

Old Version 55

changes.mady.by.user Mikhail Dubrovin

Saved on

compared with

New Version Current

changes.mady.by.user Mikhail Dubrovin

Saved on

Key

  • This line was added.
  • This line was removed.
  • Formatting was changed.

...

Common mode correction is applied in the Detector interface method calib described in AreaDetector:<PATH>

arr = det.calib(evt, cmpars=None)

...

Each algorithm may load file with parameters from calibration directory, which by default accounts for experimnet, calibration version, data source, calibration type and run range, for example

Code Block
/reg/d/psdm<PATH>/<INS>/<experiment>/calib/<calib-version>/<data-source>/<calibration-type>/<run-range>.data

For example: 
/reg/d/psdm/<PATH>/XPP/xppi0614/calib/Epix100a::CalibV1/NoDetector.0:Epix100a.0/pedestals/0-end.data
<PATH>/reg/d/psdm/XPP/xppi0614/calib/Epix100a::CalibV1/NoDetector.0:Epix100a.0/common_mode/0-end.data

...

Selection of algorithm of particular type is controlled by the list of cmpars or similar list of parameters in file for common_mode calibration type.

...

  • par[0] - algorithm #
  • par[1] - maximal threshold on intensity to evaluate mean for low intensities
  • par[2] - maximal allowed common mode correction

  • par[3] - length of consecutive pixel array for common mode evaluation
    For example, for pnCCD one can evaluate common-mode for one came chip (128 channels).

    Control file:  

<PATH>/reg/d/psdm/amo/<exp-name>/calib/PNCCD::CalibV1/Camp.0:pnCCD.0/calib/PNCCD::CalibV1/Camp.0:pnCCD.0/common_mode/0-end.data

Code Block
2 1000 1000 128


  • The algorithm loops over the data and evaluates consecutive arrays of specified length (which might represent for example a row of pixels in a readout chip) and finds the mean value for values below a threshold, ignoring masked pixels.  It corrects all the data if the calculated common mode is less than the maximal allowed correction.  The median algorithm is more stable in many cases and is recommended.

...

#7 - MEDIAN algorithm for jungfrau and epix10ka

This algorithm evaluates common mode offset for specified by par[1] groups of pixels using method numpy.median.

  • par[0] - algorithm # 7
  • par[1] - mode 0/ +1/ +2/ +4 - turned off /  in rows /  in columns / in banks. Each correction consumes extra time.
  • par[2] - maximal allowed common mode correction in det.raw ADU to protect from over-correction at high illumination - needs to be adjusted by users per experiment
  • par[3] - minimal number of good pixels in mask and gain mode to evaluate median offset (optional, default =10)
Note

rows and columns are one dimensional set of pixels limited by the shape of bank.

  • jungfrau panel shape=(512,1024) consists of 2x4=8 ASICs (512256,512256), each ASIC contains 4 banks, bank shape=(256,64) 
  • epix10ka panel shape=(352,384) consists of 2x2=4 ASICs (176,192), each ASIC contains 4 banks, bank shape=(176,48) 

...