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Code Block
from psana import DataSource
ds#ds = DataSource(exp='tmoc00318',run=10, dir='/cds/data/psdm/prj/public01/xtc') # on pcds
ds = DataSource(exp='tmoc00318',run=10, dir='/sdf/data/lcls/ds/prj/public01/xtc')
orun = next(ds.runs())
det = orun.Detector('epix100')
for evt orun.events():
    raw = det.raw.raw()

...

Code Block
DTYPE_MASK = np.uint8
o = det.raw
mask = o._# OR: from psana.detector.UtilsMask import DTYPE_MASK, DTYPE_STATUS

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, stextra_bits:(1<<64)-1, 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, stextra_bits:(1<<64)-1, 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)

...

Code Block
kwa = {'status':True, 'status_bits':0xffff, 'gain_stextra_bits':(1<<64)-1, '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}
o =  = det.raw
a = o.calib(evt, cmpars=(7,2,100,10), **kwa)
a = o.image(evt, nda=None, **kwa)

...

Code Block
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, stextra_bits:(1<<64)-1, 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

...

Code Block
from psana.detector.mask import Mask, DTYPE_MASK

m = Mask(det,\
         status=True, status_bits=0xffff, stextra_bits:(1<<64)-1, 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.

...

Code Block
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, stextra_bits:(1<<64)-1, 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')

...

Examples of conversion image-like 2-d mask to data-like 3-d ndarray

Code Block
titleExamples of conversion image-like 2-d mask to data-like 3-d ndarrayAccess geometry parameters
collapsetrue
from psana.pscalib.geometry.GeometryAccess import GeometryAccess, img_from_pixel_arrays
geo = GeometryAccess(<geometry-file-name>)
ix, iy = geo.get_pixel_coord_indexes(**kwargs)
mask_nda =from psana.detector.UtilsMask import *
m = convert_mask2d_to_ndarray_using_pixel_coord_indexes(mask2d, ix, iy)
m = convert_mask2d_to_ndarray_using_geo(mask2d, geo, **kwargs) # kwargs passed to geo.get_pixel_coord_indexes(**kwargs)
mmask(mbits=0xffff) # returns mask associated with segment geometry
mask2d = convertimg_mask2dfrom_to_ndarray_using_geometry_file(mask2d, gfname, **kwargs) # kwargs passed to geo.get_pixel_coord_indexes(**kwargs)

See for detail UtilsMask.py

CLI

roicon -h

pixel_arrays(ix, iy, W=mask_nda)

# similar methods are available in the detector interface.
# modify mask2d - add ROI mask bad pixels/regions with mask editor or programatically.
Code Block
titleExamples of conversion image-like 2-d mask to data-like 3-d ndarray
from psana.detector.UtilsMask import *
m = convert_mask2d_to_ndarray_using_pixel_coord_indexes(mask2d, ix, iy)
m = convert_mask2d_to_ndarray_using_geo(mask2d, geo, **kwargs) # NOTE: kwargs are the same as in geo.get_pixel_coord_indexes(**kwargs)
m = convert_mask2d_to_ndarray_using_geometry_file(mask2d, gfname, **kwargs)

See for detail UtilsMask.py

CLI

roicon -h

Code Block
titleoutput after the command > roicon -h
collapsetrue
(ps-4.5.26) [dubrovin@psanagpu110:~/LCLS/con-lcls2]$ roicon 1 -g /cds/group/psdm/detector/data_test/geometry/geo-epix10ka2m-16-segment.data -i test-2d-mask.npy -t  -h
OR
(ps-4.5.26) [dubrovin@psanagpu110:~/LCLS/con-lcls2]$ roicon 1 -g /sdf/group/lcls/ds/ana/detector/data_test/geometry/geo-epix10ka2m-16-segment.data -i test-2d-mask.npy -t  -h
usage: 

1) Construct 2-d image (or mask-of-segments) from ndarray with image shaped as data using appropriate geometry file
         roicon 1 -
Code Block
titleoutput after the command > roicon -h
collapsetrue
(ps-4.5.26) [dubrovin@psanagpu110:~/LCLS/con-lcls2]$ roicon -h
usage: 

1) Construct 2-d image (or mask-of-segments) from ndarray with image shaped as data using appropriate geometry file
         roicon 1 -g <geometry-file> [-a (input)<ndarray-shaped-as-data-fname>] [-i <image-(output)file>] [-c <control-bitword>]
  ex1:   roicon 1 -g <geometry-fname>
  ex2:   roicon 1 -g <geometry-fname> -a <ndarray-shaped-as-data-fname>
  test:  roicon 1 -g /cds/group/psdm/detector/data_test/geometry/geo-epix10ka2m-16-segment.data -i test-2d-mask.npy -t

2) (TBD) Create ROI mask using mask editor "med" (DO NOT FORGET to save mask in file!)
         roicon 2 [-i <image-(input)file>] [-m <roi-mask-(output)file>]
  ex1,2: roicon 2
  ex3:   roicon 2 -i image.npy -m roi-mask.npy

3) Convert ROI mask to ndarray with mask shaped as data
         roicon 3 -g <geometry-file> [-m <roi-mask-(input)file>] [-n ndarray-with-mask-(output)-file] [-c <control-bitword>]
  ex1,2: roicon 3 -g <geometry-fname>
  test:  roicon 3 -g /cds/group/psdm/detector/data_test/geometry/geo-epix10ka2m-16-segment.data -m test-2d-mask.npy -n test-3d-mask.npy

Conversion between 2-d and 3-d masks.

positional arguments:
  args                  process number: 1-construct image, 2-run mask editor on image, 3-convert image mask to ndarray; default = 1

optional arguments:
  -h, --help            show this help message and exit
  -g GFNAME, --gfname GFNAME
                        geometry file name, default = <geometry-fname>
  -a AFNAME, --afname AFNAME
                        input ndarray file name, default = None
  -i IFNAME, --ifname IFNAME
                        image file name, default = mask-img.txt
  -m MFNAME, --mfname MFNAME
                        ROI mask file name, default = mask-roi.txt
  -n NFNAME, --nfname NFNAME
                        ndarray mask file name, default = mask-nda.txt
  -c CBITS, --cbits CBITS
                        mask control bits, =0-none, +1-edges, +2-middle, etc..., default = 65535
  -v, --verb            verbosity, default = False
  -t, --dotest          add a couple of rings to the 2-d mask for test purpose, default = False
  -SF FIGPREFIX, --savefigprefix FIGPREFIX
                        figure file name prefix under <dirrepo>/figs, None - do not save plots, default = Falsefig
  -o DIRREPO, --dirrepo DIRREPO
                        repository for logs and output files, default = ./work-roicon
  -L LOGMODE, --logmode LOGMODE
                        logging mode, one of CRITICAL FATAL ERROR WARN WARNING INFO DEBUG NOTSET TRACE, default = INFO
  -k KWARGS, --kwargs KWARGS
                        str python code evaluated to dict and passed to geo.get_pixel_coord_indexes(**kwargs), default = {}
(ps-4.5.26) [dubrovin@psanagpu110:~/LCLS/con-lcls2]$

Test commands and plots

  str python code evaluated to dict and passed to geo.get_pixel_coord_indexes(**kwargs), default = {}
(ps-4.5.26) [dubrovin@psanagpu110:~/LCLS/con-lcls2]$

Mask Editor

Test commands and plots

Code Block
titleTest commands
# on pcds:
roicon 1 -g /cds/group/psdm/detector/data_test/geometry/geo-epix10ka2m-16-segment.data -i test-2d-mask.npy -t
# or on s3df:
Code Block
titleTest commands
roicon 1 -g /cdssdf/group/lcls/ds/psdmana/detector/data_test/geometry/geo-epix10ka2m-16-segment.data -i test-2d-mask.npy -t -S
roicon 2 ... runs Mask Editor - TBD
roicon 3 -g /cdssdf/group/psdmlcls/ds/ana/detector/data_test/geometry/geo-epix10ka2m-16-segment.data -m test-2d-mask.npy -n test-3d-mask.npy -S

Content of the files for "assembled" image and "not-assembled" 3-d array

...

References