Noise, bad pedestal
To assess noise:
python -i CalcNoiseAndMean.py -r 383 --special noCommonMode,slice --label calib
python -i CalcNoiseAndMean.py -r 383 --special regionCommonMode,slice --label common
To make a fake pedestal, just call python CalcNoiseAndMean.py -r 383
Standard pedestal
(No evskip 6000 and events 100k unless we're taking 6k + 2 events)
epix10ka_pedestals_calibration -k exp=ascdaq18,run=407 -d epixhr --evskip 6000 --events 100000
epix10ka_deploy_constants -k exp=ascdaq18,run=407 -d epixhr -D
Check for deployed pedestal:
SinglePhotons
To estimate the occupancy, do e.g.
python simplePhotonCounter.py -r 329 --special slice
This assumes a sensible pedestal.
To make the h5 files, assuming the normal pedestal works, do
python SimpleClustersParallelSlice.py --special regionCommonMode,FH -r 389
Else do --fakePedestals ... after doing Calc
where you'll want FM for FM and AML-M. Eventually we'll want to have specialized cluster cuts for all modes, but for now check that the seedCut in SimpleClustersParallelSlice.py is about 0.5 photons.
When all the runs are done, you can go to the rix directory and run e.g.
python runAnalyzeH5.py /sdf/data/lcls/ds/asc/ascdaq18/results/lowFlux 384 SimpleClusters 384,385,386,387,388,389
This makes plots and .npy labelled run 384 using the SimpleClusters analysis for the listed runs.
Let me know if this makes sense and works for you. At the end you can do e.g.
(ps-4.6.1) display ../test/*384*285*62*png
(ps-4.6.1) display ../test/*384*gain*png