smalldata_tools will pass on an unmasked data array throughout the different functions, along with two masks that are also saved in the userDataCfg datasets in the hdf5 file.
mask will be the status mask from the pedestal production , including masked edgepixels
cmask will add a potential user mask as saved in pixel_mask
detFuncObjects will use the mask along with the data to derived the 'reduced/transformed' dataset (e.g. projections of an ROI, droplet or photon finding etc).
smalldata_tools provides an interface to create a user mask as described here. Among other options, you can tighten the cut used to mask bad pixels based on their pedestal or noise from the dark run. As we use the status mask as a base, you cannot loosen cuts this way but would need to rerun the pedestal creating step.
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