def init_proc(self):
self.my_proc = fmwk.ana_processor()
# Set input root file
for x in xrange(len(sys.argv) - 1):
self.my_proc.add_input_file(sys.argv[x + 1])
# Specify IO mode
self.my_proc.set_io_mode(fmwk.storage_manager.kREAD)
self.my_proc.add_process(fmwk.DrawRaw())
def init_proc(self):
self.my_proc = fmwk.ana_processor()
# Set input root file
for x in xrange(len(sys.argv)-1):
self.my_proc.add_input_file(sys.argv[x+1])
# Specify IO mode
self.my_proc.set_io_mode(fmwk.storage_manager.kREAD)
self.my_proc.add_process(fmwk.DrawRaw())
import sys
if len(sys.argv) < 2:
msg = '\n'
msg += "Usage 1: %s $INPUT_ROOT_FILE\n" % sys.argv[0]
msg += '\n'
sys.stderr.write(msg)
sys.exit(1)
from seltool import ertool
from larlite import larlite as fmwk
import empartDef
# Create ana_processor instance
my_proc = fmwk.ana_processor()
# Set input root file
for x in xrange(len(sys.argv) - 1):
my_proc.add_input_file(sys.argv[x + 1])
# Specify IO mode
my_proc.set_io_mode(fmwk.storage_manager.kREAD)
# Specify output root file name
my_proc.set_ana_output_file("EMPartSelection.root")
my_algo = empartDef.EMPartAlgo()
my_ana = empartDef.EMPartAna()
my_anaunit = empartDef.AnaUnit()
my_anaunit._mgr.AddAlgo(my_algo)
my_anaunit._mgr.AddAna(my_ana)
msg = '\n'
msg += "Usage 1: %s track_producer vtx_producer calo_producer mcc71_ext2_bnb3 $OUTPUT_DIR $INPUT_ROOT_FILE(s)\n" % sys.argv[0]
msg += '\n'
sys.stderr.write(msg)
sys.exit(1)
from larlite import larlite as fmwk
track_producer = sys.argv[1]
vtx_producer = sys.argv[2]
calo_producer = sys.argv[3]
mcc71_ext2_bnb3 = int(sys.argv[4])
outdir = sys.argv[5]
# Create ana_processor instance
my_proc = fmwk.ana_processor()
# Set input root file
for x in xrange(len(sys.argv) - 6):
my_proc.add_input_file(sys.argv[x + 6])
# Specify IO mode
my_proc.set_io_mode(fmwk.storage_manager.kREAD)
my_proc.enable_filter(True)
# Specify output root file name
anaoutname = 'ana_out_trk%s_vtx%s_mcc71ext2bnb3_%d_THESIS.root'%(track_producer,vtx_producer,mcc71_ext2_bnb3)
#anaoutname = 'f**k.root'
my_proc.set_ana_output_file(outdir+'/'+anaoutname)
myxiao = fmwk.XiaoEventAna()
import sys,os
from larlite import larlite as fmwk
from recotool.matchDef import *
mgr = fmwk.ana_processor()
#args should be input file name
for x in xrange(len(sys.argv)-1):
mgr.add_input_file(sys.argv[x+1])
mgr.set_io_mode(fmwk.storage_manager.kREAD)
mgr.set_ana_output_file("dedx_ana.root")
dedx_module = fmwk.TunedEdX()
mgr.add_process(dedx_module)
mgr.run()
import sys
if len(sys.argv) < 2:
msg = '\n'
msg += "Usage 1: %s $INPUT_ROOT_FILE(s)\n" % sys.argv[0]
msg += '\n'
sys.stderr.write(msg)
sys.exit(1)
from larlite import larlite
from ROOT import larutil, argoutils
# Create ana_processor instance
my_proc = larlite.ana_processor()
larutil.LArUtilManager.Reconfigure(larlite.geo.kArgoNeuT)
# Set input root file
for x in xrange(len(sys.argv) - 1):
my_proc.add_input_file(sys.argv[x + 1])
# Specify IO mode
my_proc.set_io_mode(larlite.storage_manager.kREAD)
# Specify output root file name
my_proc.set_ana_output_file("trainingParameters.root")
# Attach an analysis unit ... here we use a base class which does nothing.
# Replace with your analysis unit if you wish.
# Configure the process:
proc = argoutils.GenFANNTrainingData()
#main_algo = cmtool.CFAlgoZOverlap()
#main_algo = cmtool.CFAlgoChargeDistrib()
#main_algo = cmtool.CFAlgoShowerCompat()
#main_algo = cmtool.CFAlgoStartTimeCompat()
#main_algo = cmtool.CFAlgoVolumeOverlap()
#main_algo.RequireThreePlanes(False)
algo_array.AddAlgo(main_algo)
#algo_array.AddAlgo(cmtool.CFAlgoTimeProf())
#algo_array.AddAlgo(cmtool.CFAlgo3DAngle())
#algo_array.AddAlgo(cmtool.CFAlgoStartPointMatch())
return palgo_array, algo_array
mgr = fmwk.ana_processor()
#args should be input file name
for x in xrange(len(sys.argv) - 3):
mgr.add_input_file(sys.argv[x + 1])
# second to last argument is output pfpart producer
match_producer = sys.argv[-2]
#last arg should be output file name
out_file = sys.argv[-1]
if os.path.isfile(out_file):
print
print 'ERROR: output file already exist...'
import sys, os
import ROOT
from larlite import larlite as ll
from ROOT import cluster, cmtool
mgr = ll.ana_processor()
#args should be input file name
for x in xrange(len(sys.argv) - 2):
mgr.add_input_file(sys.argv[x + 1])
#last arg should be output file name
out_file = sys.argv[-1]
if os.path.isfile(out_file):
print
print 'ERROR: output file already exist...'
print
sys.exit(0)
mgr.set_output_file(out_file)
mgr.set_io_mode(ll.storage_manager.kBOTH)
mgr.set_ana_output_file("")
merger_instance = ll.ClusterMerger()
merger_instance.SaveOutputCluster(True)
polar = cmtool.CBAlgoPolar()
polar.SetBufferAngle(0.0)
def main():
if len(sys.argv) < 2:
msg = '\n'
msg += "Usage: %s $INPUT_ROOT_FILE\n" % sys.argv[0]
msg += "$INPUT_ROOT_FILE containing 'gamma' ('electron') is used for training AlgoEMPart gamma (electron) mode.\n"
msg += '\n'
sys.stderr.write(msg)
sys.exit(1)
# Create ana_processor instance
my_proc = fmwk.ana_processor()
# Create algorithm
my_algo = ertool.AlgoEMPart()
# ******* Set Fit ranges **********
# Fit ranges for Reconstructed Info
#my_algo.SetFitRange_dEdx(1.2,2,False); # False = e- / True = gamma
#my_algo.SetFitRange_dEdx(3.0,4.5,True);
#my_algo.SetFitRange_RadLen(5.,25.,True);
#my_algo.SetFitRange_RadLen(0.,10.,False);
# Fit ranges for MC Info:
my_algo.SetFitRange_dEdx(0.5,6,False); # False = e- / True = gamma
my_algo.SetFitRange_dEdx(0.5,6,True);
my_algo.SetFitRange_RadLen(5.,25.,True);
my_algo.SetFitRange_RadLen(0.,5.,False);
# ******* End Set Fit Ranges *******
my_algo.setVerbose(True)
# Create analysis unit
my_ana = fmwk.ExampleERSelection()
my_ana.SetMinEDep(10)
# Set Producers
# First Argument: True = MC, False = Reco
my_ana.SetShowerProducer(True,"mcreco");
#my_ana.SetTrackProducer(True,"mcreco");
my_ana.SetVtxProducer(True,"generator");
#my_ana.SetShowerProducer(False,"pandoraNuShower");
#my_ana.SetShowerProducer(False,"showerreco");
my_ana.SetTrackProducer(False,"");
#my_ana.SetVtxProducer(False,"");
my_ana._mgr.SetAlgo(my_algo)
my_ana._mgr._training_mode =True
# Check if gamma/electron files are provided:
gamma_files = []
electron_files = []
for x in xrange(len(sys.argv)-1):
fname = sys.argv[x+1]
if fname.find('gamma')>=0:
gamma_files.append(fname)
else:
electron_files.append(fname)
print
print ' Running AlgoEMPart training script...'
print
print ' Identified %2d input files for gamma' % len(gamma_files)
print ' Identified %2d input files for electron' % len(electron_files)
if not ask_binary(' Proceed? [y/n]:'): return False
print
if ask_binary(' Load previously extracted fit parameters? [y/n]:'):
my_algo.LoadParams()
#
# Training for gamma mode
#
gamma_trained = False
if len(gamma_files) and ask_binary(' Run training for gamma? [y/n]:'):
my_proc.set_io_mode(fmwk.storage_manager.kREAD)
my_proc.add_process(my_ana)
for f in gamma_files:
my_proc.add_input_file(f)
my_algo.SetMode(True)
my_ana._mgr.Reset()
my_proc.set_ana_output_file("gamma_training.root")
print ' Start running gamma training...'
my_proc.run()
print
print ' Finished running gamma training...'
print
# Re-set
my_proc.reset()
gamma_trained = True
#
# Training for electron mode
#
electron_trained = False
if len(electron_files) and ask_binary(' Run training for electron? [y/n]:'):
my_proc.set_io_mode(fmwk.storage_manager.kREAD)
my_proc.add_process(my_ana)
for f in electron_files:
my_proc.add_input_file(f)
my_algo.SetMode(False)
my_ana._mgr.Reset()
my_proc.set_ana_output_file("electron_training.root")
print ' Start running electron training...'
my_proc.run()
print
print ' Finished running electron training...'
print
# Re-set
my_proc.reset()
electron_trained = True
#
# Store trained parameters
#
if (gamma_trained or electron_trained) and ask_binary(' Store train result parameters? [y/n]:'):
my_algo.StoreParams()
print ' Parameter stored...'
print
return True
def main():
if len(sys.argv) < 2:
msg = '\n'
msg += "Usage: %s $INPUT_ROOT_FILE\n" % sys.argv[0]
msg += "$INPUT_ROOT_FILE containing 'gamma' ('electron') is used for training AlgoEMPart gamma (electron) mode.\n"
msg += '\n'
sys.stderr.write(msg)
sys.exit(1)
# Create ana_processor instance
my_proc = fmwk.ana_processor()
# Create algorithm
my_algo = ertool.AlgoEMPart()
# ******* Set Fit ranges **********
# Fit ranges for Reconstructed Info
my_algo.SetFitRange_dEdx(0.5, 8, False)
# False = e- / True = gamma
my_algo.SetFitRange_dEdx(0.5, 9, True)
my_algo.SetFitRange_RadLen(1., 4., False)
my_algo.SetFitRange_RadLen(5., 35., True)
# Fit ranges for MC Info:
#my_algo.SetFitRange_dEdx(0.5,8,False); # False = e- / True = gamma
#my_algo.SetFitRange_dEdx(0.5,9,True);
#my_algo.SetFitRange_RadLen(5.,25.,True);
#my_algo.SetFitRange_RadLen(0.,5.,False);
# ******* End Set Fit Ranges *******
#my_algo.setVerbose(False)
my_algo.setPlot(True)
# Create analysis unit
my_ana = fmwk.ExampleERSelection()
my_ana.SetMinEDep(10)
my_ana.SetCheater(True)
# Set Producers
# First Argument: True = MC, False = Reco
#my_ana.SetShowerProducer(True,"mcreco");
#my_ana.SetTrackProducer(True,"mcreco");
#my_ana.SetShowerProducer(False,"pandoraNuShower");
my_ana.SetShowerProducer(False, "showerreco")
my_ana.SetTrackProducer(False, "")
#my_ana._mgr.SetAlgo(my_algo)
my_ana._mgr.AddAlgo(my_algo)
my_ana._mgr._training_mode = True
# Check if gamma/electron files are provided:
gamma_files = []
electron_files = []
for x in xrange(len(sys.argv) - 1):
fname = sys.argv[x + 1]
if fname.find('gamma') >= 0:
gamma_files.append(fname)
else:
electron_files.append(fname)
print
print ' Running AlgoEMPart training script...'
print
print ' Identified %2d input files for gamma' % len(gamma_files)
print ' Identified %2d input files for electron' % len(electron_files)
if not ask_binary(' Proceed? [y/n]:'): return False
print
if ask_binary(' Load previously extracted fit parameters? [y/n]:'):
my_algo.setLoadParams(True)
else:
my_algo.setLoadParams(False)
#
# Training for gamma mode
#
gamma_trained = False
if len(gamma_files) and ask_binary(' Run training for gamma? [y/n]:'):
my_proc.set_io_mode(fmwk.storage_manager.kREAD)
my_proc.add_process(my_ana)
for f in gamma_files:
my_proc.add_input_file(f)
my_algo.SetMode(True)
my_ana._mgr.Reset()
my_proc.set_ana_output_file("gamma_training.root")
print ' Start running gamma training...'
my_proc.run()
print
print ' Finished running gamma training...'
print
# Re-set
my_proc.reset()
gamma_trained = True
#
# Training for electron mode
#
electron_trained = False
if len(electron_files) and ask_binary(
' Run training for electron? [y/n]:'):
my_proc.set_io_mode(fmwk.storage_manager.kREAD)
my_proc.add_process(my_ana)
for f in electron_files:
my_proc.add_input_file(f)
my_algo.SetMode(False)
my_ana._mgr.Reset()
my_proc.set_ana_output_file("electron_training.root")
print ' Start running electron training...'
my_proc.run()
print
print ' Finished running electron training...'
print
# Re-set
my_proc.reset()
electron_trained = True
#
# Store trained parameters
#
if (gamma_trained or electron_trained
) and ask_binary(' Store train result parameters? [y/n]:'):
my_ana._mgr.StorePSet("new_empart.txt")
#my_algo.StoreParams()
print ' Parameter stored...'
print
return True
import sys,os
import ROOT
from larlite import larlite as ll
from ROOT import cluster, cmtool
mgr = ll.ana_processor()
#args should be input file name
for x in xrange(len(sys.argv)-2):
mgr.add_input_file(sys.argv[x+1])
#last arg should be output file name
out_file = sys.argv[-1]
if os.path.isfile(out_file):
print
print 'ERROR: output file already exist...'
print
sys.exit(0)
mgr.set_output_file(out_file)
mgr.set_io_mode(ll.storage_manager.kBOTH)
mgr.set_ana_output_file("")
merger_instance = ll.ClusterMerger()
merger_instance.SaveOutputCluster(True)
polar = cmtool.CBAlgoPolar()
polar.SetBufferAngle(0.0)
def main():
if len(sys.argv) < 2:
msg = '\n'
msg += "Usage: %s $INPUT_ROOT_FILE\n" % sys.argv[0]
msg += '\n'
sys.stderr.write(msg)
sys.exit(1)
ertool.Manager()
#viewer
plt.ion()
display_reco = ERViewer()
display_mc = ERViewer()
display_reco.show()
display_mc.show()
# Create ana_processor instance
my_proc = fmwk.ana_processor()
# Create algorithm
my_algo = ertool.AlgoPi0()
my_algo.setVerbose(True)
my_algo.setMinShrEnergy(10)
my_algo.setMaxShrEnergy(1000)
my_algo.setIPMax(10)
my_algo.setMinFitMass(50)
my_algo.setMaxFitMass(200)
my_algo.setAngleMax(3.14)
# Create analysis unit
my_ana = fmwk.ExampleERSelection()
# ************Set Producers**************
# First Argument: True = MC, False = Reco
my_ana.SetShowerProducer(True, "mcreco")
my_ana.SetTrackProducer(True, "mcreco")
my_ana.SetVtxProducer(False, "")
my_ana.SetShowerProducer(False, "showerreco")
my_ana.SetTrackProducer(False, "")
my_ana.SetVtxProducer(False, "")
#my_ana.SetShowerProducer(True,"mcreco");
#my_ana.SetTrackProducer(True,"mcreco");
#my_ana.SetVtxProducer(False,"");
# ************Set Producers**************
#help(my_ana._mgr)
my_ana._mgr.SetAlgo(my_algo)
my_ana._mgr._training_mode = True
# Obtain input root files
files = []
for x in xrange(len(sys.argv) - 1):
fname = sys.argv[x + 1]
if fname.endswith('.root'):
files.append(fname)
print
print ' Running AlgoPi0 training script...'
print
print ' Identified %2d input files' % len(files)
if not ask_binary(' Proceed? [y/n]:'): return False
print
if ask_binary(' Load previously extracted fit parameters? [y/n]:'):
my_algo.LoadParams()
my_proc.set_io_mode(fmwk.storage_manager.kREAD)
my_proc.add_process(my_ana)
for f in files:
my_proc.add_input_file(f)
my_ana._mgr.Reset()
my_proc.set_ana_output_file("pi0_viewing.root")
print ' Start running pi0 training...'
# Start event-by-event loop
counter = 0
while (counter < 1000):
try:
counter = input(
'Hit Enter to continue to next evt, or type in an event number to jump to that event:'
)
except SyntaxError:
counter = counter + 1
my_proc.process_event(counter)
# get objets and display
display_reco.clear()
display_mc.clear()
data_reco = my_ana.GetData()
part_reco = my_ana.GetParticles()
data_mc = my_ana.GetData(True)
part_mc = my_ana.GetParticles(True)
#display_reco.add(part_reco, data_reco, False)
display_mc.add(part_mc, data_mc, False)
display_reco.add(part_reco, data_reco, False)
for x in xrange(part_mc.size()):
print part_mc[x].Diagram()
#for x in xrange(part_reco.size()):
# print part_reco[x].Diagram()
#Last argument decides if un-taggeg showers/tracks should have random color (True) or grey (False)
display_reco.show()
display_mc.show()
#my_proc.run()
print
print ' Finished running pi0 training...'
print
#
# Store trained parameters
#
if ask_binary(' Store train result parameters? [y/n]:'):
my_algo.StoreParams()
print ' Parameter stored...'
print
return True
import larlite
import ROOT
from ROOT import larlite
if len(sys.argv) < 2:
msg = '\n'
msg += "Usage 1: %s $INPUT_ROOT_FILE(s)\n" % sys.argv[0]
msg += '\n'
sys.stderr.write(msg)
sys.exit(1)
# from larlite import larlite as fmwk
from ROOT import *
# Create ana_processor instance
my_proc = larlite.ana_processor()
# Set input root file
for x in xrange(len(sys.argv)-1):
my_proc.add_input_file(sys.argv[x+1])
# Specify IO mode
my_proc.set_io_mode(larlite.storage_manager.kREAD)
# Specify output root file name
my_proc.set_ana_output_file("from_test_ana_you_can_remove_me.root");
# Attach an analysis unit ... here we use a base class which does nothing.
# Replace with your analysis unit if you wish.
ana_unit = cluster.ClusterParamsAna()
my_proc.add_process(ana_unit)
def main():
if len(sys.argv) < 2:
msg = '\n'
msg += "Usage: %s $INPUT_ROOT_FILE\n" % sys.argv[0]
msg += '\n'
sys.stderr.write(msg)
sys.exit(1)
ertool.Manager()
#viewer
plt.ion()
display_reco = ERViewer()
display_mc = ERViewer()
display_reco.show()
display_mc.show()
# Create ana_processor instance
my_proc = fmwk.ana_processor()
# Create algorithm
my_algo = ertool.AlgoPi0()
my_algo.setVerbose(True)
my_algo.setMinShrEnergy(10)
my_algo.setMaxShrEnergy(1000)
my_algo.setIPMax(10)
my_algo.setMinFitMass(50)
my_algo.setMaxFitMass(200)
my_algo.setAngleMax(3.14)
# Create analysis unit
my_ana = fmwk.ExampleERSelection()
# ************Set Producers**************
# First Argument: True = MC, False = Reco
my_ana.SetShowerProducer(True,"mcreco");
my_ana.SetTrackProducer(True,"mcreco");
my_ana.SetVtxProducer(False,"");
my_ana.SetShowerProducer(False,"showerreco")
my_ana.SetTrackProducer(False,"");
my_ana.SetVtxProducer(False,"");
#my_ana.SetShowerProducer(True,"mcreco");
#my_ana.SetTrackProducer(True,"mcreco");
#my_ana.SetVtxProducer(False,"");
# ************Set Producers**************
#help(my_ana._mgr)
my_ana._mgr.SetAlgo(my_algo)
my_ana._mgr._training_mode =True
# Obtain input root files
files = []
for x in xrange(len(sys.argv)-1):
fname = sys.argv[x+1]
if fname.endswith('.root'):
files.append(fname)
print
print ' Running AlgoPi0 training script...'
print
print ' Identified %2d input files' % len(files)
if not ask_binary(' Proceed? [y/n]:'): return False
print
if ask_binary(' Load previously extracted fit parameters? [y/n]:'):
my_algo.LoadParams()
my_proc.set_io_mode(fmwk.storage_manager.kREAD)
my_proc.add_process(my_ana)
for f in files:
my_proc.add_input_file(f)
my_ana._mgr.Reset()
my_proc.set_ana_output_file("pi0_viewing.root")
print ' Start running pi0 training...'
# Start event-by-event loop
counter = 0
while (counter < 1000):
try:
counter = input('Hit Enter to continue to next evt, or type in an event number to jump to that event:')
except SyntaxError:
counter = counter + 1
my_proc.process_event(counter)
# get objets and display
display_reco.clear()
display_mc.clear()
data_reco = my_ana.GetData()
part_reco = my_ana.GetParticles()
data_mc = my_ana.GetData(True)
part_mc = my_ana.GetParticles(True)
#display_reco.add(part_reco, data_reco, False)
display_mc.add(part_mc, data_mc, False)
display_reco.add(part_reco, data_reco, False)
for x in xrange(part_mc.size()):
print part_mc[x].Diagram()
#for x in xrange(part_reco.size()):
# print part_reco[x].Diagram()
#Last argument decides if un-taggeg showers/tracks should have random color (True) or grey (False)
display_reco.show()
display_mc.show()
#my_proc.run()
print
print ' Finished running pi0 training...'
print
#
# Store trained parameters
#
if ask_binary(' Store train result parameters? [y/n]:'):
my_algo.StoreParams()
print ' Parameter stored...'
print
return True