nuDict = {}
if args.old_pid:
nuDict = {'nue':66,'numu':68,'nutau':133,'nue_bar':67,'numu_bar':69,'nutau_bar':134}
else:
nuDict = {'nue':12,'numu':14,'nutau':16,'nue_bar':-12,'numu_bar':-14,'nutau_bar':-16}
# Now do CC events, and write to file:
cc_cut_list = cut_list + [('I3MCWeightDict','InteractionType',1)]
nc_cut_list = cut_list + [('I3MCWeightDict','InteractionType',2)]
for flavor in data_files.keys():
data = tables.openFile(data_files[flavor]['filename'],'r')
#############
# First do nu:
cuts_cc = get_arb_cuts(data,cc_cut_list,nuIDList=[nuDict[flavor]],mcnu=args.mcnu)
arrays_cc = get_reco_arrays(data,cuts_cc,data_files[flavor]['nfiles'],
reco_string=args.mn_reco,mcnu=args.mcnu)
logging.warn("flavor %s number of CC events: %d"%(flavor,np.sum(cuts_cc)))
cuts_nc = get_arb_cuts(data,nc_cut_list,nuIDList=[nuDict[flavor]],mcnu=args.mcnu)
arrays_nc = get_reco_arrays(data,cuts_nc,data_files[flavor]['nfiles'],
reco_string=args.mn_reco,mcnu=args.mcnu)
logging.warn("flavor %s number of NC events: %d"%(flavor,np.sum(cuts_nc)))
logging.info("Saving %s..."%flavor)
write_to_hdf5(outfilename,flavor,arrays_cc,arrays_nc)
################
# Next do nu_bar:
flav_bar = flavor+'_bar'
if args.all_cz:
# Then use all sky, don't remove simulated downgoing events:
cut_sim_down = False
solid_angle = 4.0*np.pi
# Loop over all neutrino flavours, and get cc Aeff:
for flav,val in nuDict.items():
logging.info("Loading data for %s..."%flav)
data = LoadData(args.data_dir,args.geom_str,flav)
cc_cuts = list(s1_s2_cuts)
cc_cuts.append(("I3MCWeightDict","InteractionType",1))
cc_cuts.append((args.mcnu,"type",val))
cut_list = get_arb_cuts(data,cc_cuts,mcnu=args.mcnu,cut_sim_down=cut_sim_down)
logging.info(" NEvents: %d"%np.sum(cut_list))
if 'nue' in flav: nfiles = args.nfiles_nue
elif 'numu' in flav: nfiles = args.nfiles_numu
elif 'nutau' in flav: nfiles = args.nfiles_nutau
else: raise ValueError("Unrecognized flav: %s"%flav)
aeff_cc,aeff_cc_err,xedges = get_aeff1D(data,cut_list,ebins,nfiles,
mcnu=args.mcnu,solid_angle=solid_angle)
aeff_list.append(aeff_cc)
aeff_err_list.append(aeff_cc_err)
flavor_list.append(flav)
elif args.nocuts:
logging.warn("Using no selection cuts!")
cut_list = []
elif args.custom:
logging.warn("Using CUSTOM cuts: %s..."%args.custom_str)
cut_list = eval(args.custom_str)
else:
logging.warn("No cuts selected!")
# Should never happen!
# First do all NC events combined-must keep filehandle open
dummy_fh = [tables.openFile(f,mode='r') for f in data_files.values()]
data_nc = HDFChain(data_files.values())
nc_cut_list = cut_list + [('I3MCWeightDict','InteractionType',2)]
cuts_nc = get_arb_cuts(data_nc,nc_cut_list,mcnu=args.mcnu)
arrays_nc = get_reco_arrays(data_nc,cuts_nc,reco_string=args.mn_reco,
mcnu=args.mcnu)
logging.warn("NC number of events: %d"%np.sum(cuts_nc))
# Now do CC events, and write to file:
cc_cut_list = cut_list + [('I3MCWeightDict','InteractionType',1)]
for flavor in data_files.keys():
data = tables.openFile(data_files[flavor],'r')
cuts_cc = get_arb_cuts(data,cc_cut_list,mcnu=args.mcnu)
arrays_cc = get_reco_arrays(data,cuts_cc,reco_string=args.mn_reco,
mcnu=args.mcnu)
logging.warn("flavor %s number of events: %d"%(flavor,np.sum(cuts_cc)))
logging.info("Saving %s..."%flavor)
if args.all_cz:
# Then use all sky, don't remove simulated downgoing events:
cut_sim_down = False
solid_angle = 4.0*np.pi
# Loop over all neutrino flavours, and get cc Aeff:
for flav,val in nuDict.items():
logging.info("Loading data for %s..."%flav)
data = LoadData(args.data_dir,args.geom_str,flav)
cc_cuts = list(s1_s2_cuts)
cc_cuts.append(("I3MCWeightDict","InteractionType",1))
cc_cuts.append((args.mcnu,"type",val))
cut_list = get_arb_cuts(data,cc_cuts,mcnu=args.mcnu,cut_sim_down=cut_sim_down)
logging.info(" NEvents: %d"%np.sum(cut_list))
if 'nue' in flav: nfiles = args.ne
elif 'numu' in flav: nfiles = args.nmu
elif 'nutau' in flav: nfiles = args.ntau
else: raise ValueError("Unrecognized flav: %s"%flav)
aeff_cc,aeff_cc_err,xedges = get_aeff1D(data,cut_list,ebins,nfiles,
mcnu=args.mcnu,solid_angle=solid_angle)
aeff_list.append(aeff_cc)
aeff_err_list.append(aeff_cc_err)
flavor_list.append(flav)
elif args.cutsV4:
logging.warn("Using cuts V4...")
cut_list.append(('Cuts_V4_Step1','value',True))
cut_list.append(('Cuts_V4_Step2','value',True))
elif args.cutsV5:
logging.warn("Using cuts V5...")
cut_list.append(('Cuts_V5_Step1','value',True))
cut_list.append(('Cuts_V5_Step2','value',True))
# First do all NC events combined-must keep filehandle open
dummy_fh = [tables.openFile(f,mode='r') for f in data_files.values()]
data_nc = HDFChain(data_files.values())
nc_cut_list = cut_list + [('I3MCWeightDict','InteractionType',2)]
cuts_nc = get_arb_cuts(data_nc,nc_cut_list)
arrays_nc = get_reco_arrays(data_nc,cuts_nc,reco_string=args.mn_reco)
logging.warn("NC number of events: %d"%np.sum(cuts_nc))
# Now do CC events, and write to file:
cc_cut_list = cut_list + [('I3MCWeightDict','InteractionType',1)]
for flavor in data_files.keys():
data = tables.openFile(data_files[flavor],'r')
cuts_cc = get_arb_cuts(data,cc_cut_list)
arrays_cc = get_reco_arrays(data,cuts_cc,reco_string=args.mn_reco)
logging.warn("flavor %s number of events: %d"%(flavor,np.sum(cuts_cc)))
logging.info("Saving %s..."%flavor)
write_to_hdf5(outfilename,flavor,arrays_cc,arrays_nc)
elif args.nocuts:
logging.warn("Using no selection cuts!")
cut_list = []
elif args.custom:
logging.warn("Using CUSTOM cuts: %s..." % args.custom_str)
cut_list = eval(args.custom_str)
else:
logging.warn("No cuts selected!")
# Should never happen!
# First do all NC events combined-must keep filehandle open
dummy_fh = [tables.openFile(f, mode='r') for f in data_files.values()]
data_nc = HDFChain(data_files.values())
nc_cut_list = cut_list + [('I3MCWeightDict', 'InteractionType', 2)]
cuts_nc = get_arb_cuts(data_nc, nc_cut_list, mcnu=args.mcnu)
arrays_nc = get_reco_arrays(data_nc,
cuts_nc,
reco_string=args.mn_reco,
mcnu=args.mcnu)
logging.warn("NC number of events: %d" % np.sum(cuts_nc))
# Now do CC events, and write to file:
cc_cut_list = cut_list + [('I3MCWeightDict', 'InteractionType', 1)]
for flavor in data_files.keys():
data = tables.openFile(data_files[flavor], 'r')
cuts_cc = get_arb_cuts(data, cc_cut_list, mcnu=args.mcnu)
arrays_cc = get_reco_arrays(data,
cuts_cc,
reco_string=args.mn_reco,
