def DetInit(self):
self.ds = DataSource(self.args.exprun + \
':smd:dir=/reg/d/psdm/amo/amolr2516/xtc:live')
XTCAVRetrieval = ShotToShotCharacterization()
XTCAVRetrieval.SetEnv(self.ds.env())
self.SHES = Detector(self.args.SHES)
self.UXS = Detector(self.args.UXS)
self.ITOF = Detector(self.args.ITOF)
self.XTCAV = Detector(self.args.XTCAV)
self.EBeam = Detector(self.args.EBeam)
self.GMD = Detector(self.args.GMD)
self.ENV = self.ds.env().configStore()
self.PRESS = Detector(self.args.PRESS)
def __init__(self):
self.s2s = ShotToShotCharacterization.ShotToShotCharacterization()
self.ds = None
self.event_ok = False
self.results = None
self.current_event = None
self.n_processed = 0
self.n_success = 0
####################################################################
############################# STARTING ANALYSIS #####################
####################################################################
if rank == 0: print "Starting analysis on ", size, " cores."
for run in runs:
###### --- Offline analysis
ds = DataSource(
"exp=AMO/amon0816:run=%s:smd:dir=/reg/d/ffb/amo/amon0816/xtc:live" %
run)
#ds = DataSource("exp=AMO/amon0816:run=%s:smd" % run)
XTCAVRetrieval = ShotToShotCharacterization()
XTCAVRetrieval.SetEnv(ds.env())
opal_det = Detector('OPAL1')
#opal4_det = Detector('OPAL4')
minitof_det = Detector('ACQ1')
minitof_channel = 0
ebeam_det = Detector('EBeam')
feegas_det = Detector('FEEGasDetEnergy')
eorbits_det = Detector('EOrbits')
for nevt, evt in enumerate(ds.events()):
if nevt % size != rank: continue
############################## READING IN DETECTORS #############################
### Opal Detector
opal_raw = opal_det.raw(evt)
def __init__(self, name='xtcav', detname='xtcav'):
self.name = name
self.detname = detname
self.nb=1
self.size=5000
self.ShotToShotCharacterization = Xtcav.ShotToShotCharacterization()
import psana
from xtcav.ShotToShotCharacterization import *
maxshots = 5 #Maximum number of valid shots to process
experiment = 'amoc8114' #Experiment label
runs = '87' #Runs
#Loading the dataset from the "dark" run, this way of working should be compatible with both xtc and hdf5 files
dataSource = psana.DataSource("exp=%s:run=%s:idx" % (experiment, runs))
#XTCAV Retrieval (setting the data source is useful to get information such as experiment name)
XTCAVRetrieval = ShotToShotCharacterization()
XTCAVRetrieval.SetDataSource(dataSource)
for r, run in enumerate(dataSource.runs()):
n_r = 0 #Counter for the total number of xtcav images processed within the run
times = run.times()
for t in times:
evt = run.event(t)
if not XTCAVRetrieval.SetCurrentEvent(evt):
continue
t, power, ok1 = XTCAVRetrieval.XRayPower()
agreement, ok2 = XTCAVRetrieval.ReconstructionAgreement()
if (ok1 and ok2):
print "%d/%d" % (n_r, maxshots
) #Debugging purposes, will be removed
print 'Agreement: %g %% Maximum power: %g GW' % (agreement * 100,
np.amax(power))
def __init__(self):
self.s2s = ShotToShotCharacterization.ShotToShotCharacterization()
self.ds = None
self.event_ok = False
self.results = None