def jobtrackgen():
""" Job to generate ntracks and store them into a ntuple
"""
# confifure aplication
alex = Alex('alex')
alex.nevts = 100
root = ROOTSvc('root',fname='atrackgen.root')
alex.addsvc(root)
# configure flow
gen = TrackGen('trackgen')
gen.imports.append('root')
alex.addalg(gen)
histos = TrackHistos('histos')
histos.imports.append('root')
histos.path = 'trackgen'
alex.addalg(histos)
root.h2d('hxz',100,0.,40.,100,-30.,30.)
root.h2d('hyz',100,0.,40.,100,-30.,30.)
root.h2d('huxz',100,0.,40.,100,-1.2,1.2)
root.h2d('huyz',100,0.,40.,100,-1.2,1.2)
root.h2d('hez',100,0.,40.,100,0.,2.6)
# run!
alex.run()
return
def jobtrackgen():
""" Job to generate ntracks and store them into a ntuple
"""
# confifure aplication
alex = Alex('alex')
alex.nevts = 100
root = ROOTSvc('root', fname='atrackgen.root')
alex.addsvc(root)
# configure flow
gen = TrackGen('trackgen')
gen.imports.append('root')
alex.addalg(gen)
histos = TrackHistos('histos')
histos.imports.append('root')
histos.path = 'trackgen'
alex.addalg(histos)
root.h2d('hxz', 100, 0., 40., 100, -30., 30.)
root.h2d('hyz', 100, 0., 40., 100, -30., 30.)
root.h2d('huxz', 100, 0., 40., 100, -1.2, 1.2)
root.h2d('huyz', 100, 0., 40., 100, -1.2, 1.2)
root.h2d('hez', 100, 0., 40., 100, 0., 2.6)
# run!
alex.run()
return
def jobtrackrecover():
""" Job to recover ntracks and fill some histograms
"""
# confifure aplication
alex = Alex('alex')
alex.nevts = 400
root = ROOTSvc(name='root', fname='atrackrecover.root')
alex.addsvc(root)
# configure flow
RR = lambda fname: TreeReader(fname, tname='trackgen')
reader = Reader(name='reader', freader=RR)
#read.fnames = ['trackgen1.root','trackgen2.root','trackgen3.root']
reader.fnames = ['atrackgen.root']
alex.addalg(reader)
recover = TrackRecover('recover')
alex.addalg(recover)
histos = TrackHistos('histos')
histos.imports.append('root')
histos.path = 'recover'
alex.addalg(histos)
root.h2d('hxz', 100, 0., 40., 100, -30., 30.)
root.h2d('hyz', 100, 0., 40., 100, -30., 30.)
root.h2d('huxz', 100, 0., 40., 100, -1.1, 1.1)
root.h2d('huyz', 100, 0., 40., 100, -1.1, 1.1)
root.h2d('hez', 100, 0., 40., 100, 0., 3.)
# run!
alex.run()
return
def jobtrackrecover():
""" Job to recover ntracks and fill some histograms
"""
# confifure aplication
alex = Alex('alex')
alex.nevts = 400
root = ROOTSvc(name='root',fname='atrackrecover.root')
alex.addsvc(root)
# configure flow
RR = lambda fname : TreeReader(fname,tname='trackgen')
reader = Reader(name='reader',freader=RR)
#read.fnames = ['trackgen1.root','trackgen2.root','trackgen3.root']
reader.fnames = ['atrackgen.root']
alex.addalg(reader)
recover = TrackRecover('recover')
alex.addalg(recover)
histos = TrackHistos('histos')
histos.imports.append('root')
histos.path = 'recover'
alex.addalg(histos)
root.h2d('hxz',100,0.,40.,100,-30.,30.)
root.h2d('hyz',100,0.,40.,100,-30.,30.)
root.h2d('huxz',100,0.,40.,100,-1.1,1.1)
root.h2d('huyz',100,0.,40.,100,-1.1,1.1)
root.h2d('hez',100,0.,40.,100,0.,3.)
# run!
alex.run()
return
def dotracks():
""" Alex program to generate a single electron or doble beta event with toy-MC.
and fit in forward and reverse mode. Histograms are produced.
"""
# create aplication
alex = Alex()
alex.msg.level = Message.Info
alex.nevts = 1000
root = ROOTSvc('root','akfbeta.root')
alex.addsvc(root)
# simulate states
#--------------------------
#agenstates = GenerateDoubleBeta('agenstates') # uncoment to generate doble-beta
agenstates = GenerateBeta('agenstates')
agenstates.E0 = 2.5
alex.addalg(agenstates)
# histogram simulated states
hisgenstates = HistosGenerateStates('hisgenstates')
hisgenstates.imports.append('root')
alex.addalg(hisgenstates)
# generate hits
agendigits = CreateDigits('agendigits')
agendigits.dz = 0.5
alex.addalg(agendigits)
# create nodes
agennodes = CreateNodes('agennodes')
alex.addalg(agennodes)
# uncoment to generetate doble-beta nodes in one track
#betanodes = DoubleBetaNodes('betanodes')
#alex.addalg(betanodes)
# fit
#-----------------
# fit in the forward direction
akf = FitNodes('akf')
akf.path = 'rec/nodes'
akf.opath = 'rec/kfs'
alex.addalg(akf)
# histogram the forward fit
hisakf = HistosKFFit('hisakf')
hisakf.imports.append('root')
hisakf.prefix='kf_'
hisakf.path='rec/kfs'
alex.addalg(hisakf)
# histogram the chi2-scan of the forward fit
hischiscan = HistosKFChiScan('hischiscan')
hischiscan.imports.append('root')
hischiscan.path = 'rec/kfs'
alex.addalg(hischiscan)
# reverse the nodes to do a reverse fit
arevnodes = ReverseNodes('arevnodes')
arevnodes.path = 'rec/nodes'
arevnodes.opath = 'rec/nodes/rev'
alex.addalg(arevnodes)
# do reverse fit
akfrev = FitNodes('akfrev')
akfrev.path = 'rec/nodes/rev'
akfrev.opath = 'rec/kfs/rev'
alex.addalg(akfrev)
# histogram the reverse fit
hisakfrev = HistosKFFit('hisakfrev')
hisakfrev.imports.append('root')
hisakfrev.prefix='kfrev_'
hisakfrev.path='rec/kfs/rev'
alex.addalg(hisakfrev)
# histogram the chi2-scan of the reverse fit
hischiscanrev = HistosKFChiScan('hischiscanrev')
hischiscanrev.imports.append('root')
hischiscanrev.path='rec/kfs/rev'
hischiscanrev.prefix='chiscanrev_trk'
alex.addalg(hischiscanrev)
# Compare forward/reverse fit
#-----------------------------
# do the analysis of the forward/reverse fit
anarev = HistosAnaReverse('anrev')
anarev.imports.append('root')
alex.addalg(anarev)
alex.run()
def doscan():
""" Alex program to generate doble beta events and do a scan along the track
"""
# create application
alex = Alex()
alex.nevts = 2000
root = ROOTSvc('root','akfbeta.root')
alex.addsvc(root)
# simulation
#----------------
# generate double beta
agenstates = GenerateDoubleBeta('agenstates')
#agenstates = GenerateBeta('agenstates')
alex.addalg(agenstates)
# histogram simulated states
hisgenstates = HistosGenerateStates('hisgenstates')
hisgenstates.imports.append('root')
alex.addalg(hisgenstates)
# genrate digits
agendigits = CreateDigits('agendigits')
agendigits.dz = 0.5
alex.addalg(agendigits)
# provide a track with the two electrons
betanodes = DoubleBetaNodes('betanodes')
alex.addalg(betanodes)
# fitting
#------------
# do forward fit
akf = FitNodes('kfbetanodes')
akf.path = 'rec/nodes/bb'
akf.opath = 'rec/kfs/bb'
alex.addalg(akf)
# histo forward fit
hisakf = HistosKFFit('hisakf')
hisakf.imports.append('root')
hisakf.prefix='kf_'
hisakf.path='rec/kfs/bb'
alex.addalg(hisakf)
# histo chi2-scan of the forward fit
hischiscan = HistosKFChiScan('hischiscan')
hischiscan.imports.append('root')
hischiscan.path = 'rec/kfs/bb'
alex.addalg(hischiscan)
# reverse the nodes to do the reverse fit
arevnodes = ReverseNodes('arevnodes')
arevnodes.path = 'rec/nodes/bb'
arevnodes.opath = 'rec/nodes/bb/rev'
alex.addalg(arevnodes)
# do the reverse fit
akfrev = FitNodes('akfrev')
akfrev.path = 'rec/nodes/bb/rev'
akfrev.opath = 'rec/kfs/bb/rev'
alex.addalg(akfrev)
# histotgram the reverse fit
hisakfrev = HistosKFFit('hisakfrev')
hisakfrev.imports.append('root')
hisakfrev.prefix='kfrev_'
hisakfrev.path='rec/kfs/bb/rev'
alex.addalg(hisakfrev)
# histogram the chi2-scan of the reverse fit
hischiscanrev = HistosKFChiScan('hischiscanrev')
hischiscanrev.imports.append('root')
hischiscanrev.path='rec/kfs/bb/rev'
hischiscanrev.prefix='chiscanrev_trk'
alex.addalg(hischiscanrev)
# scan along the track
#----------------------
# do the analysis of the forward/reverse fit
anarev = HistosAnaReverse('anrev')
anarev.imports.append('root')
anarev.pathnor = 'rec/kfs/bb'
anarev.pathrev = 'rec/kfs/bb/rev'
alex.addalg(anarev)
akf = FitScanNodes('ascan')
akf.path = 'rec/nodes/bb'
akf.opath = 'rec/kfs/bb/scan'
akf.iscan = 4
alex.addalg(akf)
hakf = HistosScanNodes('hscan')
hakf.imports.append('root')
alex.addalg(hakf)
# some event diplays
#---------------
#evtakf = EventDisplayScan('evtakf')
#evtakf.imports.append('root')
#alex.addalg(evtakf)
#evtdisplay = EventDisplay('evtdisplay')
#evtdisplay.imports.append('root')
#alex.addalg(evtdisplay)
alex.run()
def ck_gen():
alex = Alex()
alex.nevts = 1000
root = ROOTSvc('root','akfnext.root')
alex.addsvc(root)
#radlen = 1500 # if radlen>0 use simple generator and filter
emin = 0.5 # minimum energy to stop generation
agenstates = GenerateStates('agenstates')
agenstates.uz = 1.
agenstates.emin = emin
agenstates.deltae = 0.01
#agenstates.radlen = radlen
alex.addalg(agenstates)
hisgenstates = HistosGenerateStates('hisgenstates')
hisgenstates.imports.append('root')
alex.addalg(hisgenstates)
agendigits = GenerateDigits('agendigits')
agendigits.dz = 0.5
#agendigits.p0 = 0.25
#agendigits.nave = 10
alex.addalg(agendigits)
agennodes = GenerateNodes('agennodes')
alex.addalg(agennodes)
agensegments = GenerateSegments('agensegments')
agensegments.unique = True
agensegments.minnodes = 4
alex.addalg(agensegments)
#hisgennodes = HistosGenerateNodes('hisgennodes')
#hisgennodes.imports.append('root')
#alex.addalg(hisgennodes)
akf = KFFit2('akf')
#akf.radlen = radlen
#akf.onlyfirst = True
alex.addalg(akf)
#hisakf = HistosKFFit('hisakf')
#hisakf.imports.append('root')
#hisakf.forward = True
#hisakf.backward = True
#hisakf.emin = .5
#alex.addalg(hisakf)
hisakf2 = AnaKFFit2('hisakf2')
hisakf2.imports.append('root')
alex.addalg(hisakf2)
#anakffit = AnaKFFit('anakffit')
#anakffit.imports.append('root')
#alex.addalg(anakffit)
#evtdis = EventDisplay('evtdis')
#evtdis.imports.append('root')
#evtdis.nhits = 40
#alex.addalg(evtdis)
alex.run()
def ck_gen():
alex = Alex()
alex.nevts = 1000
root = ROOTSvc('root', 'akfnext.root')
alex.addsvc(root)
#radlen = 1500 # if radlen>0 use simple generator and filter
emin = 0.5 # minimum energy to stop generation
agenstates = GenerateStates('agenstates')
agenstates.uz = 1.
agenstates.emin = emin
agenstates.deltae = 0.01
#agenstates.radlen = radlen
alex.addalg(agenstates)
hisgenstates = HistosGenerateStates('hisgenstates')
hisgenstates.imports.append('root')
alex.addalg(hisgenstates)
agendigits = GenerateDigits('agendigits')
agendigits.dz = 0.5
#agendigits.p0 = 0.25
#agendigits.nave = 10
alex.addalg(agendigits)
agennodes = GenerateNodes('agennodes')
alex.addalg(agennodes)
agensegments = GenerateSegments('agensegments')
agensegments.unique = True
agensegments.minnodes = 4
alex.addalg(agensegments)
#hisgennodes = HistosGenerateNodes('hisgennodes')
#hisgennodes.imports.append('root')
#alex.addalg(hisgennodes)
akf = KFFit2('akf')
#akf.radlen = radlen
#akf.onlyfirst = True
alex.addalg(akf)
#hisakf = HistosKFFit('hisakf')
#hisakf.imports.append('root')
#hisakf.forward = True
#hisakf.backward = True
#hisakf.emin = .5
#alex.addalg(hisakf)
hisakf2 = AnaKFFit2('hisakf2')
hisakf2.imports.append('root')
alex.addalg(hisakf2)
#anakffit = AnaKFFit('anakffit')
#anakffit.imports.append('root')
#alex.addalg(anakffit)
#evtdis = EventDisplay('evtdis')
#evtdis.imports.append('root')
#evtdis.nhits = 40
#alex.addalg(evtdis)
alex.run()
alex.nevts = 100 # set number of events to run
root = ROOTSvc('root',fname='alexroot.root') # create root service
alex.addsvc(root) # add root service to the application
# configure flow
#------------------
eff = EffFilter('eff') # create efficiency filter algorithm
eff.eff = 0.6 # set parameter (eff) of the efficiency algorithm to a value
histo = HistoFill('histo') # create HistoFill algorithm
histo.path='eff'
# takes value from the evt store in this path
# it is the value of the efficiency EffFilter algorithm
dump = Dump('dump') # create Dump algorithms
dump.paths += ['eff']
filter = Filter('filter') # create a Filter algorithm
filter.addalg(eff) # add eff algorithm to filter
filter.addalg(histo) # add histo algorithm to filter
filter.addalg(dump) # add dump to filter
alex.addalg(filter) # add filter to alex to run it!
# run
#----------
alex.run() # run!!
from alex.alex import Alex
from alex.messenger import Message, Messenger
from alex.reader import Reader, ConsTreeReader
from alex.algorithms import Dump
# ------- Construct Alex
alex = Alex()
# create messenger service, log output in file 'alex.log', level INFO
msg = Messenger(name="msg", fname="alex_rootread.log", level=Message.Info)
alex.addsvc(msg)
alex.nevts = 10
alex.evtfreq = 2
# ----- Flow of Alex
RR = ConsTreeReader("tgauss") # filereader of a TTree named 'tgaus'
reader = Reader(name="reader", freader=RR) # reader of files
reader.fnames = ["alex_rootwrite.root"]
alex.addalg(reader)
dump = Dump("dump")
dump.paths = ["reader"]
alex.addalg(dump)
# --- Run
alex.run()