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python EventScanParallelSlice.py -r 777 --fakePedestal CalcNoiseAndMean_mean_r666_step0.npy --special commonModeregionCommonMode

and

python EventScanParallelSlice.py -r 777 -f ../scan/EventScanParallel_c0_r777_n1.h5 -L cm

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One can run the clustering by doing

python SimpleClustersParallelSimpleClustersParallelSlice.py -r 777 --fakePedestal CalcNoiseAndMean_mean_r666_step0.npy --special commonModeregionCommonMode,FH

and

python SimpleClustersParallelSimpleClustersParallelSlice.py -r 777 -f ../lowFlux/SimpleClustersParallel_c0_r777_n1.h5 -L cm

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This makes per-pixel gain histograms with fits and plots all the slice pixel gains (peaks).  It also makes a histogram of all slice pixels energy across the run before clustering.