QC documentation system: QC procedure vimos_imgscrflt.py for VIMOS

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vimos_bias.py vimos_dark.py vimos_detlin.py vimos_mask2ccd.py
vimos_imgskyflt.py vimos_imgscrflt.py vimos_astimg.py vimos_stdimg.py vimos_nightzp.py
vimos_moscal.py vimos_stdmos.py
vimos_ifucal.py vimos_stdifu.py
vimos_sciimg.py vimos_scimos.py vimos_sciifu.py
 
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NAME vimos_imgscrflt.py
VERSION 1.0 -- change from MIDAS to Python (February 2010)
1.0.1 -- updating qcDocu description (2011-03-07)
1.0.2 -- skip call of scoreQC (2011-05-31)
1.0.3 -- create cover sheet (2011-08-30)
1.0.4 -- changes needed for muc (2013-02-07)
1.0.5 -- changes for qc_mstplt v1.4 (2014-01-15)
1.0.6 -- changes for qc_mstdisp v1.3 (2014-01-20)
1.0.7 -- remove usage of has_key dictionary attribute (2014-03-24)
SYNTAX PYTHON
CALL processQC
from $DFS_PRODUCT/SFLAT_IMG/$DATE
/home/vimos/python/vimos_imgscrflt.py -i -a $AB
INSTRUMENT VIMOS
RAWTYPE SFLAT_IMG
PURPOSE QC check on raw and product imaging lamp flats
PROCINPUT products: IMG_MASTER_SCREEN_FLAT
raw frames: first raw frame
reference IMG_MASTER_SCREEN_FLAT
QC1TABLE trending | table(s) in QC1 database:
vimos_scrflat
TRENDPLOT trending | HealthCheck plot(s) associated to this procedure:
trend_report_FLT_UB_HC.html | trend_report_FLT_VR_HC.html | trend_report_FLT_Iz_HC.html | trend_report_GAIN_HC.html | trend_report_NOISE_HC.html
QC1PAGE trending | associated documentation:
scrflat_qc1.html
QC1PLOTS
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scrflat1.png
left: first input raw frame
middle: current IMG_MASTER_SCREEN_FLAT
right: comparison to reference master flat
scrflat2.png
left: first input raw frame (central area)
middle: current IMG_MASTER_SCREEN_FLAT (central area)
right: comparison to reference master flat (central area)
scrflat3.png
cuts through current master and reference, histograms, comparison to reference
QC1PARAM QC1 parameters written in QC1 database:
QC1 DB names: median_master | sigma_master | efficiency | fixp_noise | photon_noise | structure | conad_avg | sig_conad_avg
All parameters are calculated by the pipeline recipe.
ALGORITHM Description of algorithms:
median_master: median of the 1600x1800 central pixels of IMG_COMBINED_SCREEN_FLAT
sigma_master: standard deviation of the 1600x1800 central pixels of IMG_COMBINED_SCREEN_FLAT
efficiency: median of the 1600x1800 central pixels of the first input raw frame divided by exposure time
fixp_noise: standard deviation of the 1600x1800 central pixels of the difference of the first and second raw input flat, with the second shifted by 10x10 pixels; photon_noise is quadratically subtracted
photon_noise: standard deviation of the 1600x1800 central pixels of the difference of the first two raw frames, divided by sqrt(2)
structure: standard deviation of the 1600x1800 central pixels of the first input raw flat with fixp_noise and photon_noise quadratically subtracted
conad_avg: conversion factor from ADU to electrons (e/ADU). The difference frame of the first two input raw frames is computed and the variance (square of standard deviation) of the difference frame is calculated; the 1600x1800 central region is divided into 16x18 boxes with 100x100 pixels; for each box, the median is calculated and divided by (2 x variance); the median value of the results from all boxes is the gain factor, which is 1/CONAD
sig_conad_avg: standard deviation of the 16x18 CONAD values, divided by sqrt(16x18)
CERTIF Imaging lamp flats are not used for data reduction; they are used for trending CONAD, noise parameters, and filter performance.
In case of lamp failures, affected QC1 DB entries would have to be cleaned.
COMMENTS none
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