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DTYPE_MASK = np.uint8
o = det.raw
mask = o._mask_default(dtype=DTYPE_MASK)
mask = o._mask_calib()
mask = o._mask_calib_or_default(dtype=DTYPE_MASK)
mask = o._mask_from_status(status_bits=0xffff, gain_range_inds=(0,1,2,3,4), dtype=DTYPE_MASK, **kwa) # gain_range_inds for appropriate detectors
mask = o._mask_neighbors(mask, rad=9, ptrn='r')
mask = o._mask_edges(width=0, edge_rows=1, edge_cols=1, dtype=DTYPE_MASK, **kwa)
mask = o._mask_center(wcenter=0, center_rows=1, center_cols=1, dtype=DTYPE_MASK, **kwa)
mask = o._mask(status=True, status_bits=0xffff, gain_range_inds=(0,1,2,3,4),\
               neighbors=False, rad=3, ptrn='r',\
               edges=True, width=0, edge_rows=10, edge_cols=5,\
               center=True, wcenter=0, center_rows=5, center_cols=3,\
               calib=False,\
               umask=None,\
               force_update=False, dtype=DTYPE_MASK)

umask = np.ones((4, 352, 384), dtype=np.uint8)
umask[3,100:120,160:200] = 0

mask = det.raw._mask(status=True, status_bits=0xffff, gain_range_inds=(0,1,2,3,4),\
                     neighbors=True, rad=5, ptrn='r',\
                     edges=True, edge_rows=10, edge_cols=5,\
                     center=True, center_rows=5, center_cols=3,\
                     calib=False,\
                     umask=umask,\
                     force_update=False, dtype=DTYPE_MASK)
mask += 1 # for visibility of the mask 0 and 1 relative to image background

from psana.detector.mask import Mask, DTYPE_MASK

m = Mask(det,\
         status=True, status_bits=0xffff, gain_range_inds=(0,1,2,3,4),\
         neighbors=True, rad=5, ptrn='r',\
         edges=True, width=0, edge_rows=10, edge_cols=5,\
         center=True, wcenter=0, center_rows=5, center_cols=3,\
         calib=True,\
         umask=test_umask(det),\
         force_update=False, dtype=DTYPE_MASK)

m = Mask(det) # minimal version of the Mask object instantiation.

# All other methods are shotcuts to det._mask* methods w/o "_"
m = Mask(det)
m.set_mask(**kwa) # forced update of cached mask, **kwa - the same list of keyword arguments as in class Mask w/o det.
mask = m.mask(**kwa) # returns cached mask, **kwa - the same list of keyword arguments as in class Mask w/o det.
mask = m.mask_default()
mask = m.mask_calib_or_default() # if available returns mask from "pixel_mask" calibration type, otherwise array of ones. 
mask = m.mask_from_status(status_bits=0xffff, gain_range_inds=(0,1,2,3,4), dtype=DTYPE_MASK)
mask = m.mask_edges(width=0, edge_rows=1, edge_cols=1, dtype=DTYPE_MASK)
mask = m.mask_center(wcenter=0, center_rows=1, center_cols=1, dtype=DTYPE_MASK)
mask = m.mask_neighbors(mask, rad=9, ptrn='r')