This note describes area detector interface methods to access raw and calibrated data, reconstruct image for mutli-panel detector, retrieve calibration constants, geometry parameters, define the mask for pixel array, etc.
Set environment
Code discussed in this note works on psana nodes which have access to data in lcls2 environment described in LCLS-II psana Environment.
To run examples one has to ssh to psana node and set environment
ssh -Y pslogin.slac.stanford.edu ssh -Y psana source /cds/sw/ds/ana/conda2/manage/bin/psconda.sh
Code examples
Most updated description of this interface is on git in the head of the file detector/areadetector.py
Create DataSource, Run, and Detector objects
from psana import DataSource ds = DataSource(exp='tmoc00318',run=10, dir='/cds/data/psdm/prj/public01/xtc') orun = next(ds.runs()) det = orun.Detector('epix100')
Loop over events and access detector data
Methods guaranteed for all area detectors - raw, calib, and image:
for evt orun.events(): o = det.raw raw = o.raw(evt) clb = o.calib(evt) img = o.image(evt)
Optional parameters
kwa = <dict-of-mask-parameters> a = o.calib(evt, cmpars=(7,2,100,10), **kwa) a = o.image(evt, nda=None, **kwa)
Calibration constants
All detector calibration constants (np.array) and associated metadata (dict) are available through the dictionary det.calibconst with calibration type as a key. For example:
peds, meta = det.calibconst['pedestals']
Possible calibration types: pedestals, pixel_status, pixel_rms, pixel_gain, pixel_mask,
etc.
Mask
See for details Area detector mask examples.
from psana.detector.mask import Mask, DTYPE_MASK kwa = {'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':False, 'width':0, 'edge_rows':10, 'edge_cols':5,\ 'center':False, 'wcenter':0, 'center_rows':5, 'center_cols':3,\ 'calib':False,\ 'umask':None,\ 'force_update':False, 'dtype':DTYPE_MASK} m = Mask(det, **kwa) m = Mask(det) # minimal version.
m.set_mask(**kwa) # forced update of cached mask. mask = m.mask(**kwa) # returns cached mask. 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')
- default combined mask parameters (status=True, neighbors=False, edges=False, center=False, calib=False, umask=None) are set to define mask for pixel_status only.
- mask is used in det.raw.calib/image mask at evaluation of common mode correction, but by default it is not applied to data.
- to apply mask to data use multiplication calib *= mask.
Other useful area detector methods
# direct access to calibration constants and derived arrays peds = o._pedestals() gain = o._gain() # ADU/keV gfac = o._gain_factor() # keV/ADU rms = o._rms() status = o._status() arrx, arry, arrz = o._pixel_coords(do_tilt=True, cframe=0) indx, indy, indz = o._pixel_coord_indexes(pix_scale_size_um=None, xy0_off_pix=None, do_tilt=True, cframe=0) # array of the common mode increment incr = o._common_mode_increment(evt, cmpars=(0,7,100,10))