def test_mask(args):
ds, run, det = ds_run_det(args)
#mask = det.raw._mask_from_status()
#raw = det.raw.raw()
#mask = det.raw._mask_calib()
#mask_edges = det.raw._mask_edges(mask, edge_rows=20, edge_cols=10)
#mask = det.raw._mask_edges(edge_rows=20, edge_cols=10, center_rows=4, center_cols=2)
#mask = det.raw._mask(calib=True, status=True, edges=True,\
# edge_rows=20, edge_cols=10, center_rows=4, center_cols=2)
mask = det.raw._mask_comb(mbits=0o7,\
edge_rows=20, edge_cols=10, center_rows=4, center_cols=2)
print(info_ndarr(mask, 'mask '))
if args.dograph:
from psana.detector.UtilsGraphics import gr, fleximage
evnum, evt = None, None
for evnum, evt in enumerate(run.events()):
if evt is None:
print('Event %d is None' % evnum)
continue
print('Found non-empty event %d' % evnum)
break
if evt is None: exit('ALL events are None')
#arr = det.raw.raw(evt)
arr = mask + 1
img = det.raw.image(evt,
nda=arr,
pix_scale_size_um=args.pscsize,
mapmode=args.mapmode)
flimg = fleximage(img, arr=None, h_in=8, amin=-1,
amax=2) #, cmap='jet')
gr.show()
if args.ofname is not None:
gr.save_fig(flimg.fig, fname=args.ofname, verb=True)
def plot_image(nda, tit=''):
"""Plots averaged image
"""
from psana.detector.UtilsGraphics import gr
#img = det.image(evt, nda)
img = reshape_to_2d(nda)
if img is None:
print('plot_image - image "%s" is not available.' % tit)
return
logger.info(info_ndarr(img, 'plot_image of %s' % tit))
amin = np.quantile(img, 0.01, interpolation='lower')
amax = np.quantile(img, 0.99, interpolation='higher')
gr.plotImageLarge(img, amp_range=(amin, amax), title=tit)
gr.show()
def test_image(args):
import psana.detector.UtilsEpix10ka as ue
from psana.detector.UtilsGraphics import gr, fleximage, flexhist, fleximagespec
dograph = args.dograph.lower()
flimg, flspe, flims = None, None, None
ds, run, det = ds_run_det(args)
peds = det.raw._pedestals(
) if args.grindex is None else det.raw._pedestals()[args.grindex, :]
is_epix10ka = 'epix' in det.raw._uniqueid
dcfg = ue.config_object_epix10ka(det) if is_epix10ka else None
break_event_loop = False
nframes = 0
sum_arr, sum_sta = None, None
med_vs_evt = np.zeros(args.events - args.evskip + 10, dtype=np.float64)
nrec_med = 0
for stepnum, step in enumerate(run.steps()):
print('%s\nStep %1d' % (50 * '_', stepnum))
if args.stepsel is not None and stepnum != args.stepsel:
print(' skip - step selected in option -M is %1d' %
(args.stepsel))
continue
print('%s\n begin event loop' % (50 * '_'))
for evnum, evt in enumerate(step.events()):
if evnum < args.evskip:
print('Step %1d Event %04d - skip first %04d events' % (stepnum, evnum, args.evskip),\
end=('\r' if evnum<args.evskip-1 else '\n'))
continue
if evnum > args.events:
print('break by number of events limit %d set in option -N' %
args.events)
break_event_loop = True
break
if evnum > 2 and evnum % args.evjump != 0: continue
print('%s\nStep %1d Event %04d' % (50 * '_', stepnum, evnum))
if dcfg is not None:
s = ' gain mode fractions for: FH FM FL'\
' AHL-H AML-M AHL-L AML-L\n%s' % (29*' ')
#ue.info_pixel_gain_mode_for_fractions(dcfg, data=det.raw.raw(evt), msg=s))
gmfracs = ue.pixel_gain_mode_fractions(dcfg,
data=det.raw.raw(evt))
print(ue.info_pixel_gain_mode_for_fractions(gmfracs, msg=s))
gmind = ue.gain_mode_index_from_fractions(gmfracs)
gmname = ue.gain_mode_name_for_index(gmind).upper()
print(' == major gain mode %d : %s' % (gmind, gmname))
#print(' == gain mode: %s' % ue.find_gain_mode(dcfg, data=None).upper())
if peds is None: peds = det.raw._pedestals()[gmind, :]
#user_mask = np.ones_like(det.raw.raw(evt), dtype=DTYPE_MASK) #np.uint8
#user_mask[0,100:150,200:250] = 0
user_mask = None
arr = None
if args.show == 'raw-peds-med':
arr = (det.raw.raw(evt) & 0x3fff) - peds
med = np.median(arr)
print('XXX from raw-peds subtract its median = %.3f' % med)
arr -= med
if arr is None:
arr = det.raw.calib(evt, cmpars=(7,7,100,10),\
mbits=0o7, mask=user_mask, edge_rows=10, edge_cols=10, center_rows=5, center_cols=5)\
if args.show == 'calibcm' else\
det.raw.calib(evt, cmpars=(8,7,10,10))\
if args.show == 'calibcm8' else\
det.raw.calib(evt) if args.show == 'calib' else\
peds if args.show == 'peds' else\
det.raw._gain_range_index(evt) if args.show == 'grind' else\
(det.raw.raw(evt) & 0x3fff) - peds if args.show == 'raw-peds' else\
(det.raw.raw(evt) & 0x3fff) if args.show == 'rawbm' else\
np.ones_like(det.raw.raw(evt)) if args.show == 'ones' else\
(det.raw.raw(evt) & args.bitmask)
#if args.show == 'calibcm': arr += 1 # to see panel edges
logger.info(info_ndarr(arr, 'arr '))
if arr is None: continue
med = np.median(arr)
med_vs_evt[nrec_med] = med
nrec_med += 1
if args.cumulat:
if (med > args.thrmin) and (med < args.thrmax):
nframes += 1
cond = arr > args.thrpix
if nframes != 1:
_ = np.add(sum_arr[cond], arr[cond], out=sum_arr[cond])
sum_sta[cond] += 1
else:
sum_arr = np.array(arr, dtype=np.float64)
sum_sta = np.zeros_like(arr, dtype=np.uint64)
#if nframes > 1: arr = sum_arr/float(nframes)
if nframes > 1: arr = divide_protected(sum_arr, sum_sta)
print('Step %1d event:%04d nframes:%04d arr median:%.3f' %
(stepnum, evnum, nframes, med))
else:
continue
t0_sec = time()
img = det.raw.image(evt,
nda=arr,
pix_scale_size_um=args.pscsize,
mapmode=args.mapmode)
print('image composition time = %.6f sec ' % (time() - t0_sec))
logger.info(info_ndarr(img, 'img '))
logger.info(info_ndarr(arr, 'arr '))
if img is None: continue
title = '%s %s run:%s ev:%d' % (args.detname, args.expname,
args.runs, evnum)
if 'i' in dograph:
if flimg is None:
flimg = fleximage(img, arr=arr, fraclo=0.05, frachi=0.95)
flimg.move(10, 20)
else:
flimg.update(img, arr=arr)
flimg.fig.canvas.set_window_title(title)
flimg.axtitle(title)
if 'h' in dograph:
if flspe is None:
flspe = flexhist(arr,
bins=50,
color='green',
fraclo=0.001,
frachi=0.999)
flspe.move(800, 20)
else:
flspe.update(arr,
bins=50,
color='green',
fraclo=0.001,
frachi=0.999)
flspe.fig.canvas.set_window_title(title)
flspe.axtitle(title)
if 'c' in dograph:
if flims is None:
flims = fleximagespec(img, arr=arr, bins=100, color='lightgreen',\
amin=args.gramin, amax=args.gramax,\
nneg=args.grnneg, npos=args.grnpos,\
fraclo=args.grfrlo, frachi=args.grfrhi,\
)
flims.move(10, 20)
else:
#print(info_ndarr(arr, 'YYY before update arr: ', last=5))
flims.update(img, arr=arr)
flims.axtitle(title)
gr.show(mode=1)
if break_event_loop: break
med_vs_evt = med_vs_evt[:nrec_med]
med = np.median(med_vs_evt)
q05 = np.quantile(med_vs_evt, 0.05, interpolation='linear')
q95 = np.quantile(med_vs_evt, 0.95, interpolation='linear')
print(info_ndarr(med_vs_evt, 'per event median ', last=nrec_med - 1))
print(' median over %d event-records: %.3f' % (nrec_med, med))
print(' quantile(med_vs_evt, 0.05): %.3f' % q05)
print(' quantile(med_vs_evt, 0.95): %.3f' % q95)
if args.dograph:
print(
'\n !!! TO EXIT - close graphical window(s) - click on [x] in the window corner'
)
gr.show()
if args.ofname is not None:
if 'i' in dograph:
gr.save_fig(flimg.fig, fname=args.ofname + '-img', verb=True)
if 'h' in dograph:
gr.save_fig(flspe.fig, fname=args.ofname + '-spe', verb=True)
if 'c' in dograph:
gr.save_fig(flims.fig,
fname=args.ofname + '-imgspe',
verb=True)
print(50 * '-')
def test_single_image(args):
ds, run, det = ds_run_det(args)
#mask = det.raw._mask_from_status()
#raw = det.raw.raw()
#mask = det.raw._mask_calib()
#mask_edges = det.raw._mask_edges(mask, edge_rows=20, edge_cols=10)
#mask = det.raw._mask_edges(edge_rows=20, edge_cols=10, center_rows=4, center_cols=2)
#mask = det.raw._mask(calib=True, status=True, edges=True,\
# edge_rows=20, edge_cols=10, center_rows=4, center_cols=2)
tname = args.tname
grindex = 0 if args.grindex is None else args.grindex
arr, amin, amax, title = None, None, None, '%s for --grindex=%d ' % (
tname, grindex)
if tname == 'mask':
umask = np.ones((4, 352, 384), dtype=np.uint8)
umask[3, 100:120, 160:200] = 0
arr = 1 + 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)
amin, amax = 0, 2
title = 'mask+1'
elif tname == 'peds':
arr = det.raw._pedestals()[grindex, :]
elif tname == 'status':
arr = det.raw._status()[grindex, :]
elif tname == 'rms':
arr = det.raw._rms()[grindex, :]
elif tname == 'gain':
arr = det.raw._gain()[grindex, :]
elif tname == 'xcoords':
arr = det.raw._pixel_coords(do_tilt=True, cframe=args.cframe)[0]
elif tname == 'ycoords':
arr = det.raw._pixel_coords(do_tilt=True, cframe=args.cframe)[1]
elif tname == 'zcoords':
arr = det.raw._pixel_coords(do_tilt=True, cframe=args.cframe)[2]
else:
arr = det.raw._mask_calib()
geo = det.raw._det_geo()
pscsize = geo.get_pixel_scale_size()
print(info_ndarr(arr, 'array for %s' % tname))
if args.dograph:
from psana.detector.UtilsGraphics import gr, fleximage
evnum, evt = None, None
for evnum, evt in enumerate(run.events()):
if evt is None:
print('Event %d is None' % evnum)
continue
print('Found non-empty event %d' % evnum)
break
if evt is None: sys.exit('ALL events are None')
img = det.raw.image(evt,
nda=arr,
pix_scale_size_um=pscsize,
mapmode=args.mapmode)
print(info_ndarr(img, 'image for %s' % tname))
flimg = fleximage(img,
arr=arr,
h_in=args.fighig,
w_in=args.figwid,
amin=amin,
amax=amax) #, cmap='jet')
flimg.fig.canvas.set_window_title(title)
flimg.move(10, 20)
gr.show()
if args.ofname is not None:
gr.save_fig(flimg.fig, fname=args.ofname, verb=True)
arr = img[:352, :192]
print(info_ndarr(img, ' img'))
if flims is None:
flims = fleximagespec(img,
arr=arr,
bins=100,
w_in=11,
h_in=8,
amin=AMIN,
amax=AMAX) #fraclo=0.01, frachi=0.99
flims.move(10, 20)
else:
fname = '%s-%s.png' % (prefix, suffix)
flims.update(img, arr=arr, amin=AMIN, amax=AMAX)
flims.axtitle('Event %d %s' % (nevt, fname))
gr.show(mode=1)
if tname in ('0', '9') and args.saveimg:
flims.save(fname)
gr.show()
if args.saveimg: flims.save(fname)
sys.exit('END OF %s -t %s' % (SCRNAME, tname))
# EOF