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To make a fake pedestal, just call python CalcNoiseAndMean.py -r 383. If 'CommonMode' is not in special it reverts to raw.
More fakePedestal info at Procedure for cluster-based gain analysis while the calib db is down or pedestals are bad
Standard pedestal
(No evskip 6000 and events 100k unless we're taking 6k + 2k events)
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which computes the Onset, the Onset of CompEnOn and the length of a transfer function for each pixel. The first figure displays the map of these 3 parameters and this map is clickable in order to see each pixel's transfer function in a separate window. Close the figures to stop the program. The picture of the maps is saved here: /sdf/data/lcls/ds/rix/rixx1003721/results/scan/ (.png format)
Example of analysis of a TimeScan:
sbatch -p milano --nodes 10 --ntasks-per-node 10 --wrap="mpirun python -u -m mpi4py.run TimeScanParallelSlice.py -r 444 -t 100"
python TimeScanParallelSlice.py -r 444 --threshold 0
python MapCompEnOn.py -f ../scan/TimeScanParallel_c0_r444_n1.h5
→ and click on the maps in order to plot the transfer function of pixel selected
SinglePhotons
To estimate the occupancy, do e.g.
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To make the h5 files, assuming the normal pedestal works, do
python SimpleClustersParallelSlice.py --special regionCommonMode,FH -r 389
or in parallel : sbatch -p milano --nodes 10 --ntasks-per-node 10 --wrap="mpirun python -u -m mpi4py.run SimpleClustersParallelSlice.py --special regionCommonMode,FH -r 389"
(FH also for AHL; FM for FM and AML.)
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self.profiles = [True, False][0] ## to get unbinned plots, turn this off
self.seabornProfiles = [True, False][1]
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