def runclient(args):
hd=hitdata()
hf=tofhitfind()
ds = DataSource(args.exprun+':smd')
det1 = Detector('pnccdFront',ds.env())
det2 = Detector('ACQ4',ds.env())
epics = ds.env().epicsStore()
thresh = 0.40
# print "rank, size = ", rank, size
for nevent,evt in enumerate(ds.events()):
if nevent%(size-1)==rank-1: # different ranks look at different events
# print rank," processing event", nevent
eid = evt.get(EventId)
sec = eid.time()[0]
nsec = eid.time()[1]
fid = eid.fiducials()
et = EventTime(int((sec<<32)|nsec),fid)
tof, tofAxis = det2.raw(evt)
if (hf.hitfind(tof[0],tofAxis[0],thresh)):
epdict=dict()
for name in epics.names():
epdict[name]=epics.value(name)
img = det1.image(evt)
obj = dofitting(img) #call fitting routine
comp = {'et':et , 'tof':tof[0], 'tofAxis':tofAxis[0], 'epics':epdict, 'drop':obj['drop'],'tofsum':hf.sum}
hd.send(comp, obj['orig'], obj['fit'])
if nevent == args.noe : break
hd.endrun()
def runmaster(args,nClients, mask):
hd = hitdata()
inith5(args)
initHist('DropSize',100,0,1000)
while nClients > 0:
# Remove client if the run ended
if hd.recv():
# print "end run called"
nClients -= 1
else:
# print "Calling plot?"
plot(hd)
writeh5(hd)
closeh5(mask)
def runmaster(args,nClients, mask):
hd = hitdata()
inith5(args)
initHist('DropSize',50,500,2000)
initHist('TOFhits',1000,-500,1000)
initHist('IMGhits',1000,0,5000)
bkgTOF = np.empty(10000)
nTOF = 0
startTime = time.time()
while nClients > 0:
# Remove client if the run ended
if hd.recv():
# print "end run called"
nClients -= 1
bkgTOF += hd.myobj['tof']
nTOF = nTOF+hd.myobj['ntof']
else:
# print "Calling plot?"
if hd.myobj['diodeDrop']:
print 'master detected drop'
plotDDrop = Image(0,"Diode Drop Image",hd.myobj['img'])
publish.send('DDROP',plotDDrop)
continue
comp = hd.myobj['comp']
size=(comp['drop']['a']+comp['drop']['b'])/2.0
plot(hd, args)
pushToHist('DropSize',size)
pushToHist('TOFhits',comp['tofsum'])
pushToHist('IMGhits',comp['imgsum'])
writeh5(hd)
endTime = time.time()
hitRate = nHits / (endTime - startTime)
print('Hitrate = ', hitRate)
closeh5(mask, bkgTOF/nTOF, hitRate)
def runmaster(args,nClients):
hd = hitdata()
inith5(args)
initHist('DropSize',100,0,2000)
initHist('TOFhits',1000,-2,2)
while nClients > 0:
# Remove client if the run ended
if hd.recv():
# print "end run called"
nClients -= 1
else:
# print "Calling plot?"
plot(hd)
comp = hd.myobj['comp']
size=(comp['drop']['a']+comp['drop']['b'])/2.0
pushToHist('DropSize',size)
pushToHist('TOFhits',comp['tofsum'])
writeh5(hd)
closeh5()
def runclient(args, mask, thresholds):
hd=hitdata()
hf=tofhitfind()
ihf=imghitfind()
ds = DataSource('exp=amoj5415:run=' + args.exprun+':smd')
# ds = DataSource('exp=amoj5415:' + args.exprun+':smd'+':dir=/reg/d/ffb/amo/amoj5415/xtc:live')
# ds = DataSource(args.exprun+':smd'+':dir=/reg/d/ffb/amo/amoj5415/xtc:live')
det1 = Detector('pnccdFront',ds.env())
det2 = Detector('ACQ4',ds.env())
epics = ds.env().epicsStore()
diodeThresh = thresholds['diode'] #0.15 #diode drop threshold. 0.15=diode drop active, -100=disble drop detection
thresh = thresholds['tof'] #2 #tof threshold. 0=none, 1=loose, 2=typical, 20=AQUIRIS scale = 1
upperThresh = thresholds['tofUpper'] #2000E10 #tof threshold to dump IR only shots
ithr = thresholds['image'] #850 #image threshold. -1e6 = none, (80) 500=typical
bkgTOF = np.zeros(10000)
bkgN = 0
# print "rank, size = ", rank, size
try:
for nevent,evt in enumerate(ds.events()):
howFarBehind = time.time() - evt.get(EventId).time()[0]
if howFarBehind < 30.0:
time.sleep(30.0-howFarBehind)
if nevent == args.noe : break #kill if we reach event noe
# if (rank == 1) : print("nevent", nevent)
if nevent%(size-1)==rank-1: # different ranks look at different events
try:
# print rank," processing event", nevent
eid = evt.get(EventId)
sec = eid.time()[0]
nsec = eid.time()[1]
fid = eid.fiducials()
et = EventTime(int((sec<<32)|nsec),fid)
tof = det2.raw(evt)
if tof is not None:
tof, tofAxis = det2.raw(evt)
else:
print nevent, " tof read failure"
continue
diode = np.max(tof[2])
#print ("event " + str(nevent) + " diode is " + str(diode))
if (diode < diodeThresh):
#if (np.random.random() > 0.99):
print('diode below thresh @ ' + str(diode))
img = det1.image(evt)
hd.sendDiode(img)
continue
if (hf.hitfind(tof[0],tofAxis[0],thresh, upperThresh)):
#if (np.random.random() > 0):
epdict=dict()
for name in epics.names():
epdict[name]=epics.value(name)
# if(np.random.random() > 0): #
img = det1.image(evt)
if (ihf.pixelCountThreshold(img[200:475,150:940],ithr)):
print ("hit at ", time.ctime(), eid)
obj = dummyFit(img, mask) #call fitting routine
comp = { 'et':et , 'tof':tof[0], 'tofAxis':tofAxis[0], 'epics':epdict, 'drop':obj['drop'], 'tofsum':hf.sum , 'imgsum':ihf.sum, 'diode':diode }
hd.send(comp, obj['orig'], obj['fit'])
else:
# if (bkgN < 60):
# img = det1.calib(evt)
# ihf.formBackground(img[:,:])
bkgTOF += tof[0]
bkgN += 1
except Exception as e:
print "Exception on rank: ", rank, " event ", nevent
print e
continue
except Exception as e:
print "Exception wiht for loop on rank: ", rank
print e
hd.endrun(bkgTOF, bkgN)
