def getDetectorCalibration(verbose=False, fileName=''):
if fileName == '':
detCalib = aolUtil.struct({'path': 'detCalib', 'name': 'calib'})
# Get the latest detector callibration values from file
if not os.path.exists(detCalib.path):
os.makedirs(detCalib.path)
if not os.path.exists(detCalib.path + '/' + detCalib.name + '0.txt'):
np.savetxt(detCalib.path + '/' + detCalib.name + '0.txt', [1] * 16)
detCalib.fileNumber = np.max([
int(f[len(detCalib.name):-4]) for f in os.listdir(detCalib.path)
if len(f) > len(detCalib.name)
and f[:len(detCalib.name)] == detCalib.name
])
else:
detCalib = aolUtil.struct()
splitPath = fileName.split('/')
if len(splitPath) > 1:
detCalib.path = '/'.join(splitPath[:-1])
else:
detCalib.path = '.'
detCalib.name = splitPath[-1]
detCalib.fileNumber = np.nan
if args.calibrate == -1:
detCalib.factors = np.loadtxt(
detCalib.path + '/' + detCalib.name +
'{}.txt'.format(detCalib.fileNumber if np.
isfinite(detCalib.fileNumber) else ''))
else:
detCalib.factors = np.ones(16)
if verbose:
print 'Detector factors =', detCalib.factors
return detCalib
def getDetectorCalibration(verbose=False, fileName=''):
if fileName == '':
detCalib = aolUtil.struct({'path':'detCalib',
'name':'calib'})
# Get the latest detector callibration values from file
if not os.path.exists(detCalib.path):
os.makedirs(detCalib.path)
if not os.path.exists(detCalib.path + '/' + detCalib.name + '0.txt'):
np.savetxt(detCalib.path + '/' + detCalib.name + '0.txt', [1]*16)
detCalib.fileNumber = np.max([int(f[len(detCalib.name):-4]) for f in
os.listdir(detCalib.path) if len(f) > len(detCalib.name) and
f[:len(detCalib.name)]==detCalib.name])
else:
detCalib = aolUtil.struct()
splitPath = fileName.split('/')
if len(splitPath) > 1:
detCalib.path = '/'.join(splitPath[:-1])
else:
detCalib.path = '.'
detCalib.name = splitPath[-1]
detCalib.fileNumber = np.nan
if args.calibrate == -1:
detCalib.factors = np.loadtxt(detCalib.path + '/' + detCalib.name +
'{}.txt'.format( detCalib.fileNumber if
np.isfinite(detCalib.fileNumber) else '' ) )
else:
detCalib.factors = np.ones(16)
if verbose:
print 'Detector factors =', detCalib.factors
return detCalib
def masterLoopSetup(args, scales):
# Master loop data collector
masterLoop = aolUtil.struct()
# Define the plot interval from the command line input
masterLoop.tPlot = args.plotInterval
# set up the buffer size to be able to handle twice the amoun of
# data that is expected
masterLoop.bufSize = int(np.round(120 * masterLoop.tPlot * 1.3))
# Make template of the array that should be sent between the ranks
masterLoop.bufTemplate = np.empty((1, dSize), dtype=float)
# Make empty queues.
masterLoop.req = deque()
masterLoop.buf = deque()
# Initialize the stop time
masterLoop.tStop = time.time()
# Calibration
if args.calibrate > -1:
masterLoop.calibValues = []
return masterLoop
def eventDataContainer(args):
# Set up some data containers
event = aolUtil.struct()
event.sender = []
event.fiducials = []
event.times = []
event.full = []
event.intRoi0 = []
event.intRoi0Bg = []
event.intRoi1 = []
event.pol = []
#event.positions = []
event.ebEnergyL3 = []
event.gasDet = []
if args.photonEnergy != 'no':
event.energy = []
event.evrCodes = []
#event.deltaK = []
#event.deltaEnc = []
event.delayStage = []
event.fsTiming = []
event.ttTime = []
event.timeSignals_V = []
return event
def masterLoopSetup(args, scales):
# Master loop data collector
masterLoop = aolUtil.struct()
# Define the plot interval from the command line input
masterLoop.tPlot = args.plotInterval
# set up the buffer size to be able to handle twice the amoun of
# data that is expected
masterLoop.bufSize = int(np.round(120 * masterLoop.tPlot * 1.3))
# Make template of the array that should be sent between the ranks
masterLoop.bufTemplate = np.empty((1, dSize), dtype=float)
# Make empty queues.
masterLoop.req = deque()
masterLoop.buf = deque()
# Initialize the stop time
masterLoop.tStop = time.time()
# Calibration
if args.calibrate > -1:
masterLoop.calibValues = []
return masterLoop
def master_data_setup(args):
# Container for the master data
# This is mainly for the averaging buffers
master_data = aolUtil.struct()
#master_data.energyAmplitude = None
#master_data.energyAmplitudeRoi0 = None
#master_data.timeAmplitude = None
#master_data.timeAmplitudeFiltered = None
#master_data.timeAmplitudeRoi0 = None
#master_data.timeAmplitudeRoi1 = None
# Storage for the trace avareaging buffer
master_data.time_trace_buffer = deque([], args.traceAverage)
master_data.roi_0_buffer = deque([], args.roi0Average)
master_data.energy_trace_buffer = deque([], args.traceAverage)
# Storage for roi averaging
master_data.roi_0_buffer = deque([], args.roi0Average)
master_data.roi_1_buffer = deque([], args.roi1Average)
# Buffers for the polarization averageing
master_data.pol_degree_buffer = deque([], args.polAverage)
master_data.pol_angle_buffer = deque([], args.polAverage)
master_data.pol_amp_buffer = deque([], args.polAverage)
master_data.pol_beta_buffer = deque([], args.polAverage)
master_data.pol_roi0_buffer = deque([], args.polAverage)
return master_data
def eventDataContainer(args):
# Set up some data containers
event = aolUtil.struct()
event.sender = []
event.fiducials = []
event.times = []
event.full = []
event.intRoi0 = []
event.intRoi0Bg = []
event.intRoi1 = []
event.pol = []
#event.positions = []
event.ebEnergyL3 = []
event.gasDet = []
if args.photonEnergy != 'no':
event.energy = []
event.evrCodes = []
#event.deltaK = []
#event.deltaEnc = []
event.delayStage = []
event.fsTiming = []
event.ttTime = []
event.timeSignals_V = []
return event
def master_data_setup(args):
# Container for the master data
# This is mainly for the averaging buffers
master_data = aolUtil.struct()
#master_data.energyAmplitude = None
#master_data.energyAmplitudeRoi0 = None
#master_data.timeAmplitude = None
#master_data.timeAmplitudeFiltered = None
#master_data.timeAmplitudeRoi0 = None
#master_data.timeAmplitudeRoi1 = None
# Storage for the trace avareaging buffer
master_data.time_trace_buffer = deque([], args.traceAverage)
master_data.roi_0_buffer = deque([], args.roi0Average)
master_data.energy_trace_buffer = deque([], args.traceAverage)
# Storage for roi averaging
master_data.roi_0_buffer = deque([], args.roi0Average)
master_data.roi_1_buffer = deque([], args.roi1Average)
# Buffers for the polarization averageing
master_data.pol_degree_buffer = deque([], args.polAverage)
master_data.pol_angle_buffer = deque([], args.polAverage)
master_data.pol_amp_buffer = deque([], args.polAverage)
master_data.pol_beta_buffer = deque([], args.polAverage)
master_data.pol_roi0_buffer = deque([], args.polAverage)
return master_data
def get_scales(env, cb, verbose=False):
global dSize
global dTraces
global d_energy_trace
# A struct object to hold the scale information
scales = aolUtil.struct()
# Assume that all the tofs have the same energy scale and use only the first
# one.
scales.energy_eV = cb.get_energy_scales_eV()[0]
scales.energyRoi0_eV = cb.get_energy_scales_eV(roi=0)[0]
scales.energyRoi0_slice = slice(
scales.energy_eV.searchsorted(np.min(scales.energyRoi0_eV)),
scales.energy_eV.searchsorted(np.max(scales.energyRoi0_eV),
side='right'))
# Get all the time scales
scales.time_us = cb.get_time_scales_us()
scales.timeRoi0_us = cb.get_time_scales_us(roi=0)
scales.timeRoi0_slice = [
slice(full.searchsorted(np.min(part)),
full.searchsorted(np.max(part), side='right'))
for full, part in zip(scales.time_us, scales.timeRoi0_us)
]
scales.timeRoi2_us = cb.get_time_scales_us(roi=2)
scales.timeRoi1_us = cb.get_time_scales_us(roi=1)
scales.timeRoi1_slice = [
slice(full.searchsorted(np.min(part)),
full.searchsorted(np.max(part), side='right'))
for full, part in zip(scales.time_us, scales.timeRoi1_us)
]
for i, scale_list in enumerate(
[scales.timeRoi0_us, scales.timeRoi1_us, scales.timeRoi2_us]):
if np.any([len(s) == 0 for s in scale_list]):
print ('ERROR: Roi {} is empty for at leas one of' + \
'the detectors.').format(i)
sys.exit(0)
# Calculate the background factors
scales.tRoi0BgFactors = np.array([
np.float(len(s)) / len(bg)
for s, bg in zip(scales.timeRoi0_us, scales.timeRoi2_us)
])
# Get some angle vectors
scales.angles = cb.getAngles('rad')
scales.anglesFit = np.linspace(0, 2 * np.pi, 100)
# Update the data size descriptions in the globals
traces_size = 16 * np.max([len(t) for t in scales.time_us])
dTraces = slice(dSize, dSize + traces_size)
dSize += traces_size
energy_trace_size = len(scales.energy_eV)
d_energy_trace = slice(dSize, dSize + energy_trace_size)
dSize += energy_trace_size
return scales
def get_scales(env, cb, verbose=False):
global dSize
global dTraces
global d_energy_trace
# A struct object to hold the scale information
scales = aolUtil.struct()
# Assume that all the tofs have the same energy scale and use only the first
# one.
scales.energy_eV = cb.get_energy_scales_eV()[0]
scales.energyRoi0_eV = cb.get_energy_scales_eV(roi=0)[0]
scales.energyRoi0_slice = slice(
scales.energy_eV.searchsorted(np.min(scales.energyRoi0_eV)),
scales.energy_eV.searchsorted(np.max(scales.energyRoi0_eV), side='right'))
# Get all the time scales
scales.time_us = cb.get_time_scales_us()
scales.timeRoi0_us = cb.get_time_scales_us(roi=0)
scales.timeRoi0_slice = [slice(full.searchsorted(np.min(part)),
full.searchsorted(np.max(part),
side='right')) for full, part in
zip(scales.time_us, scales.timeRoi0_us)]
scales.timeRoi2_us = cb.get_time_scales_us(roi=2)
scales.timeRoi1_us = cb.get_time_scales_us(roi=1)
scales.timeRoi1_slice = [slice(full.searchsorted(np.min(part)),
full.searchsorted(np.max(part),
side='right')) for full, part in
zip(scales.time_us, scales.timeRoi1_us)]
for i, scale_list in enumerate([scales.timeRoi0_us,
scales.timeRoi1_us,
scales.timeRoi2_us]):
if np.any([len(s)==0 for s in scale_list]):
print ('ERROR: Roi {} is empty for at leas one of' + \
'the detectors.').format(i)
sys.exit(0)
# Calculate the background factors
scales.tRoi0BgFactors = np.array(
[np.float(len(s))/len(bg) for
s,bg in zip(scales.timeRoi0_us, scales.timeRoi2_us)])
# Get some angle vectors
scales.angles = cb.getAngles('rad')
scales.anglesFit = np.linspace(0, 2*np.pi, 100)
# Update the data size descriptions in the globals
traces_size = 16 * np.max([len(t) for t in scales.time_us])
dTraces = slice(dSize, dSize + traces_size)
dSize += traces_size
energy_trace_size = len(scales.energy_eV)
d_energy_trace = slice(dSize, dSize+energy_trace_size)
dSize += energy_trace_size
return scales
def master_loop_setup(args):
# Master loop data collector
master_loop = aolUtil.struct()
# Define the plot interval from the command line input
master_loop.tPlot = args.plotInterval
# Make template of the array that should be sent between the ranks
master_loop.buf_template = np.empty((dSize, ), dtype=float)
# Initialize the stop time
master_loop.tStop = time.time()
# Calibration
if args.calibrate > -1:
master_loop.calibValues = []
return master_loop
def master_loop_setup(args):
# Master loop data collector
master_loop = aolUtil.struct()
# Define the plot interval from the command line input
master_loop.tPlot = args.plotInterval
# Make template of the array that should be sent between the ranks
master_loop.buf_template = np.empty((dSize,), dtype=float)
# Initialize the stop time
master_loop.tStop = time.time()
# Calibration
if args.calibrate > -1:
master_loop.calibValues = []
return master_loop
def load_configuration_dict(file_name, default=None, verbose=False):
if (not os.path.isfile(file_name)):
if default is None:
raise IOError(('The file {} could not be read' +
' and no default was given.').format(file_name))
return struct(default)
with open(file_name, 'r') as fp:
config_dict = json.load(fp)
config_dict = convertToStrings(config_dict)
if verbose:
print 'Configuration file read:'
print json.dumps(config_dict, sort_keys=True, indent=4)
return config_dict
def getScales(env, config, verbose=False):
global dSize
global dTraces
scales = aolUtil.struct()
# Grab the relevant scales
scales.energy_eV = (config.energyScaleBinLimits[:-1] +
np.diff(config.energyScaleBinLimits) / 2)
scales.eRoi0S = slice(
scales.energy_eV.searchsorted(np.min(config.energyRoi0_eV_common)),
scales.energy_eV.searchsorted(np.max(config.energyRoi0_eV_common)))
scales.energyRoi0_eV = scales.energy_eV[scales.eRoi0S]
tempTime = tof.getTimeScale_us(env, config.cbSourceString, verbose=verbose)
scales.baselineSlice = slice(tempTime.searchsorted(config.baselineEnd_us))
scales.timeSlice = slice(tempTime.searchsorted(config.tMin_us),
tempTime.searchsorted(config.tMax_us))
scales.time_us = tempTime[scales.timeSlice]
scales.tRoi0S = cookieBox.sliceFromRange(scales.time_us,
[config.timeRoi0_us_common] * 16)
scales.tRoi0BgS = cookieBox.sliceFromRange(
scales.time_us, [config.timeRoi0Bg_us_common] * 16)
scales.tRoi0BgFactors = np.array([
np.float(s.stop - s.start) / (bg.stop - bg.start)
for s, bg in zip(scales.tRoi0S, scales.tRoi0BgS)
])
scales.tRoi1S = cookieBox.sliceFromRange(scales.time_us,
[config.timeRoi1_us_common] * 16)
scales.timeRoi0_us = [scales.time_us[s] for s in scales.tRoi0S]
scales.timeRoiBg0_us = [scales.time_us[s] for s in scales.tRoi0BgS]
scales.timeRoi1_us = [scales.time_us[s] for s in scales.tRoi1S]
scales.angles = cookieBox.phiRad
scales.anglesFit = np.linspace(0, 2 * np.pi, 100)
scales.scaling_VperCh, scales.offset_V = cookieBox.getSignalScaling(
env, config.cbSourceString, verbose=verbose)
dTraces = slice(dSize, dSize + 16 * len(scales.time_us))
dSize += 16 * len(scales.time_us)
return scales
def getScales(env, config, verbose=False):
global dSize
global dTraces
scales = aolUtil.struct()
# Grab the relevant scales
scales.energy_eV = (config.energyScaleBinLimits[:-1] +
np.diff(config.energyScaleBinLimits)/2)
scales.eRoi0S = slice(
scales.energy_eV.searchsorted(np.min(config.energyRoi0_eV_common)),
scales.energy_eV.searchsorted(np.max(config.energyRoi0_eV_common)))
scales.energyRoi0_eV = scales.energy_eV[scales.eRoi0S]
tempTime = tof.getTimeScale_us(env, config.cbSourceString, verbose=verbose)
scales.baselineSlice = slice( tempTime.searchsorted(config.baselineEnd_us) )
scales.timeSlice = slice(
tempTime.searchsorted(config.tMin_us),
tempTime.searchsorted(config.tMax_us) )
scales.time_us = tempTime[ scales.timeSlice ]
scales.tRoi0S = cookieBox.sliceFromRange(scales.time_us,
[config.timeRoi0_us_common]*16)
scales.tRoi0BgS = cookieBox.sliceFromRange(scales.time_us,
[config.timeRoi0Bg_us_common]*16)
scales.tRoi0BgFactors = np.array([np.float(s.stop-s.start)/(bg.stop-bg.start) for
s,bg in zip(scales.tRoi0S, scales.tRoi0BgS)])
scales.tRoi1S = cookieBox.sliceFromRange(scales.time_us,
[config.timeRoi1_us_common]*16)
scales.timeRoi0_us = [scales.time_us[s] for s in scales.tRoi0S]
scales.timeRoiBg0_us = [scales.time_us[s] for s in scales.tRoi0BgS]
scales.timeRoi1_us = [scales.time_us[s] for s in scales.tRoi1S]
scales.angles = cookieBox.phiRad
scales.anglesFit = np.linspace(0, 2*np.pi, 100)
scales.scaling_VperCh, scales.offset_V = cookieBox.getSignalScaling(env, config.cbSourceString,
verbose=verbose)
dTraces = slice(dSize, dSize + 16*len(scales.time_us))
dSize += 16*len(scales.time_us)
return scales
def event_data_container(args, event=None):
# Set up some data containers
if event is None:
event = aolUtil.struct()
event.sender = []
event.fiducials = []
event.times = []
event.intRoi0 = []
event.intRoi0Bg = []
event.intRoi1 = []
event.pol = []
event.ebEnergyL3 = []
event.gasDet = []
if args.photonEnergy != 'no':
event.energy = []
event.deltaK = []
event.deltaEnc = []
return event
def event_data_container(args, event=None):
# Set up some data containers
if event is None:
event = aolUtil.struct()
event.sender = []
event.fiducials = []
event.times = []
event.intRoi0 = []
event.intRoi0Bg = []
event.intRoi1 = []
event.pol = []
event.ebEnergyL3 = []
event.gasDet = []
if args.photonEnergy != 'no':
event.energy = []
event.deltaK = []
event.deltaEnc = []
return event
"filterWinerResponse":
1,
"filterAverageNumPoints":
4,
"detectorSource":
"DetInfo(AmoETOF.0:Acqiris.0)",
"t_min_us":
0.20, #interval to cut from raw data
"t_max_us":
0.26,
"t_slice":
True
}
lclsConfig = {'lcls_photonEnergyA': 1, 'lcls_photonEnergyB': 1}
lclsConfig = aolUtil.struct(lclsConfig)
retardationPV = 'AMO:R14:IOC:10:VHS0:CH0:VoltageMeasure'
# Acqiris channel asignment
acqiris_setup = {
0: ['ACQ4', 1],
1: ['ACQ4', 2],
2: ['ACQ4', 3],
3: ['ACQ4', 0],
4: ['ACQ1', 7],
5: ['ACQ1', 6],
6: ['ACQ1', 5],
7: ['ACQ1', 4],
8: ['ACQ1', 3],
9: ['ACQ1', 2],
def loadConfiguration(file_name, default=None, quiet=False):
return struct(load_config_dict(file_name, default, ~quiet))
+ "amoh5215/psana/tofCalibs/tof_calib_0.json"),
"filterMethod": "none", # wavelet, average, wienerDeconv
"filterWaveletLevels": 10,
"filterWinerSNR": 1,
"filterWinerResponse":1,
"filterAverageNumPoints":4,
"detectorSource": "DetInfo(AmoETOF.0:Acqiris.0)",
"t_min_us": 0.20,
"t_max_us": 0.26,
"t_slice": True
}
lclsConfig = {
'lcls_photonEnergyA':1,
'lcls_photonEnergyB':1}
lclsConfig = aolUtil.struct(lclsConfig)
retardationPV = 'AMO:R14:IOC:10:VHS0:CH0:VoltageMeasure'
# Acqiris channel asignment
acqiris_setup = {
0:['ACQ1', 4],
1:['ACQ1', 3],
2:['ACQ1', 2],
3:['ACQ1', 1],
4:['ACQ1', 0],
5:['ACQ1', 15],
6:['ACQ1', 14],
7:['ACQ1', 13],
8:['ACQ1', 12],
9:['ACQ1', 11],
def main(args, verbose=False):
verbose=args.verbose
try:
# Import the configuration file
config = importConfiguration(args, verbose=verbose)
# Read the detector transmission calibrations
detCalib = getDetectorCalibration(verbose=verbose,
fileName=args.gainCalib)
# Change the configuration fit masks according to the factors
config.nanFitMask = config.nanFitMask.astype(float)
config.nanFitMask[np.isnan(detCalib.factors)] = np.nan
config.boolFitMask[np.isnan(detCalib.factors)] = False
# Connect to the correct datasource
ds = connectToDataSource(args, config, verbose=verbose)
events = ds.events()
# Get the epics store
epics = ds.env().epicsStore()
# Get the next event. The purpouse here is only to make sure the
# datasource is initialized enough so that the env object is avaliable.
evt = events.next()
cookieBox.proj.setFitMask(config.boolFitMask)
# Get the scales that we need
scales = getScales(ds.env(), config)
#print scales
# The master have some extra things to do
if rank == 0:
# Set up the plotting in AMO
from ZmqSender import zmqSender
zmq = zmqSender()
masterLoop = masterLoopSetup(args, scales)
# Averaging factor for the augers
augerAverage = aolUtil.struct()
augerAverage.fNewRoi1 = args.roi1Average
augerAverage.fOldRoi1 = 1. - augerAverage.fNewRoi1
augerAverage.plotRoi1 = None
if args.saveData != 'no':
saveFile = openSaveFile(args.saveData, not args.offline, config)
else:
# set an empty request
req = None
# The main loop that never ends...
while 1:
# An event data container
eventData = eventDataContainer(args)
# The master should set up the recive requests
if rank == 0:
masterDataSetup(eventData, args)
setupRecives(masterLoop, verbose=verbose)
# The master should do something usefull while waiting for the time
# to pass
while (time.time() < masterLoop.tStop) if rank==0 else 1 :
# Get the next event
evt = events.next()
appendEventData(evt, eventData, config, scales, detCalib,
masterLoop if rank==0 else None, args, verbose=verbose)
appendEpicsData(epics, eventData)
# Everyone but the master goes out of the loop here
if rank > 0:
break
# Rank 0 stuff on timed loop exit
if rank == 0:
# Shift the stop time
masterLoop.tStop += masterLoop.tPlot
# Check how many arrived
masterLoop.nArrived = \
[r.Get_status() for r in masterLoop.req].count(True)
if verbose:
print 'master recived data from', masterLoop.nArrived, \
'events'
print 'with its own events it makes up', \
masterLoop.nArrived + masterLoop.nProcessed
if masterLoop.nArrived == 0 and masterLoop.nProcessed==0:
continue
# A temp buffer for the arrived data
masterLoop.arrived = [b.reshape(-1) for i,b in
enumerate(masterLoop.buf) if i < masterLoop.nArrived]
mergeMasterAndWorkerData(eventData, masterLoop, args,
verbose=False)
# Send data for plotting
zmqPlotting(eventData, augerAverage, scales, zmq)
if args.saveData != 'no':
writeDataToFile(saveFile, eventData, args.saveData)
else:
# The rest of the ranks come here after breaking out of the loop
# the goal is to send data to the master core.
req = packageAndSendData(eventData, req)
except KeyboardInterrupt:
print "Terminating program."
if rank == 0 and args.calibrate > -1:
if args.saveData != 'no':
closeSaveFile(saveFile)
saveDetectorCalibration(masterLoop, detCalib, config,
verbose=verbose, beta = args.calibBeta)
def main(args, verbose=False):
verbose = args.verbose
try:
# Import the configuration file
config = importConfiguration(args, verbose=verbose)
# Read the detector transmission calibrations
detCalib = getDetectorCalibration(verbose=verbose,
fileName=args.gainCalib)
# Change the configuration fit masks according to the factors
config.nanFitMask = config.nanFitMask.astype(float)
config.nanFitMask[np.isnan(detCalib.factors)] = np.nan
config.boolFitMask[np.isnan(detCalib.factors)] = False
# Connect to the correct datasource
ds = connectToDataSource(args, config, verbose=verbose)
events = ds.events()
# Get the epics store
epics = ds.env().epicsStore()
# Get the next event. The purpouse here is only to make sure the
# datasource is initialized enough so that the env object is avaliable.
evt = events.next()
cookieBox.proj.setFitMask(config.boolFitMask)
# Get the scales that we need
scales = getScales(ds.env(), config)
#print scales
# The master have some extra things to do
if rank == 0:
# Set up the plotting in AMO
from ZmqSender import zmqSender
zmq = zmqSender()
masterLoop = masterLoopSetup(args, scales)
# Averaging factor for the augers
augerAverage = aolUtil.struct()
augerAverage.fNewRoi1 = args.roi1Average
augerAverage.fOldRoi1 = 1. - augerAverage.fNewRoi1
augerAverage.plotRoi1 = None
if args.saveData != 'no':
saveFile = openSaveFile(args.saveData, not args.offline,
config)
else:
# set an empty request
req = None
# The main loop that never ends...
while 1:
# An event data container
eventData = eventDataContainer(args)
# The master should set up the recive requests
if rank == 0:
masterDataSetup(eventData, args)
setupRecives(masterLoop, verbose=verbose)
# The master should do something usefull while waiting for the time
# to pass
while (time.time() < masterLoop.tStop) if rank == 0 else 1:
# Get the next event
evt = events.next()
appendEventData(evt,
eventData,
config,
scales,
detCalib,
masterLoop if rank == 0 else None,
args,
verbose=verbose)
appendEpicsData(epics, eventData)
# Everyone but the master goes out of the loop here
if rank > 0:
break
# Rank 0 stuff on timed loop exit
if rank == 0:
# Shift the stop time
masterLoop.tStop += masterLoop.tPlot
# Check how many arrived
masterLoop.nArrived = \
[r.Get_status() for r in masterLoop.req].count(True)
if verbose:
print 'master recived data from', masterLoop.nArrived, \
'events'
print 'with its own events it makes up', \
masterLoop.nArrived + masterLoop.nProcessed
if masterLoop.nArrived == 0 and masterLoop.nProcessed == 0:
continue
# A temp buffer for the arrived data
masterLoop.arrived = [
b.reshape(-1) for i, b in enumerate(masterLoop.buf)
if i < masterLoop.nArrived
]
mergeMasterAndWorkerData(eventData,
masterLoop,
args,
verbose=False)
# Send data for plotting
zmqPlotting(eventData, augerAverage, scales, zmq)
if args.saveData != 'no':
writeDataToFile(saveFile, eventData, args.saveData)
else:
# The rest of the ranks come here after breaking out of the loop
# the goal is to send data to the master core.
req = packageAndSendData(eventData, req)
except KeyboardInterrupt:
print "Terminating program."
if rank == 0 and args.calibrate > -1:
if args.saveData != 'no':
closeSaveFile(saveFile)
saveDetectorCalibration(masterLoop,
detCalib,
config,
verbose=verbose,
beta=args.calibBeta)