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Pre-processing
Pre-processing algorithms consist of for procedures
- Dark run scan,
- Pedestals averaging,
- Data scan, and
- Data averaging,
described in this section.
Dark run scan
Defines for the dark run
- the number of events
- time records and average time interval
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Pedestals averaging
Defines for the dark run
- pedestals
- RMS
- hot pixel mask
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The ImgAlgos.ImgMaskEvaluation produces the saturated pixel mask; the image size txt file *-satpix-mask-level-65000ADU.
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Data processing
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txt, consistiong 0(zero) or 1(one) for each bin.
Data processing
Data processing stage consists of three procedures:
- Spliting,
- Processing, and
- Merging,
described in this section.
Spliting
Submit command
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psana -c /reg/neh/home1/dubrovin/LCLS/PSANA-V01/work/t1-cora-xcsi0112-r0015-split.cfg /reg/d/ana12/xcs/xcsi0112/xtc/e167-r0015-*.xtc |
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- ImgAlgos.ImgCalib.cpp
- ImgAlgos.ImgCalib.h
This module is responsible for basic image intensity transformation. For correlation analysis it applys a couple of corrections: - subtract pedestals and
- apply LLD threshold.
PSANA module ImgAlgos.ImgIntMonCorr
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Presentation of results
Presentation of results is implemented in the GUIViewResults.py, which basically is a panel of buttons for different plots.
Summary
In this note we presented a functional description of implemented procedures for time correlation analysis. All modules have convenient reference to the latest version of the code.
References
- Module
ImgAlgos.GlobalMethods - ImgAlgos.GlobalMethods.cpp
- ImgAlgos.GlobalMethods.h
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Overview
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