def reRunReco(r, fname):
fRT = fname.replace('.root', '_RT2.root')
os.system(
'xrdcp -f $EOSSHIP/eos/experiment/ship/data/muflux/DATA_Rebuild_8000/rootdata/'
+ r + '/' + fname + ' ' + fRT)
f = ROOT.TFile.Open(os.environ['EOSSHIP'] +
'/eos/experiment/ship/user/odurhan/muflux-recodata/' +
r + '/' + fname.replace('.root', '_RT.root'))
ftemp = ROOT.TFile(fRT, 'update')
ftemp.cd('')
upkl = Unpickler(f)
tMinAndTmax = upkl.load('tMinAndTmax')
pkl = Pickler(ftemp)
pkl.dump(tMinAndTmax, 'tMinAndTmax')
ftemp.mkdir('histos')
ftemp.histos.cd('')
for tc in ['TDCMapsX', 'hitMapsX']:
tmp = f.histos.Get(tc)
X = tmp.Clone()
X.Write()
ftemp.Write("", ROOT.TFile.kOverwrite)
ftemp.Close()
cmd = "python " + pathToMacro + "drifttubeMonitoring.py -c recoStep1 -u 1 -f " + fRT + ' &'
os.system(cmd)
print('step 1:', cmd)
def __init__(self, geoFile):
self.fgeo = ROOT.TFile.Open(geoFile)
#load geo dictionary
upkl = Unpickler(self.fgeo)
self.snd_geo = upkl.load('ShipGeo')
# -----Create geometry----------------------------------------------
run = "notNeeded"
self.modules = sndDet_conf.configure(run, self.snd_geo)
self.sGeo = self.fgeo.FAIRGeom
self.modules['Scifi'].SiPMmapping()
lsOfGlobals = ROOT.gROOT.GetListOfGlobals()
for m in self.modules:
lsOfGlobals.Add(self.modules[m])
temp = {}
for o1 in self.snd_geo:
key = o1
x = self.snd_geo[o1]
if not hasattr(x, 'items'): temp[key] = x
else:
for o2 in x:
key = o1 + '/' + o2
y = x[o2]
if not hasattr(y, 'items'): temp[key] = y
else:
for o3 in y:
key = o1 + '/' + o2 + '__' + o3
z = y[o3]
if not hasattr(z, 'items'): temp[key] = z
for key in temp:
if not key.find('MuFilter') < 0:
self.modules['MuFilter'].SetConfPar(key, temp[key])
if not key.find('Scifi') < 0:
self.modules['Scifi'].SetConfPar(key, temp[key])
dy = None
nEvents = 9999999
fiducialCut = True
measCutFK = 25
measCutPR = 22
docaCut = 2.
eosship = ROOT.gSystem.Getenv("EOSSHIP")
# geoFile = '/afs/cern.ch/user/a/amarshal/FairSHiP_run_GAN_muons/geofile_full.conical.MuonBack-TGeant4.root'
# geoFile = '/afs/cern.ch/user/a/amarshal/FairSHiP_run_GAN_muons/geofile_full.conical.Pythia8-TGeant4.root'
geoFile = '/afs/cern.ch/user/a/amarshal/FairSHiP_run_GAN_muons/geofile.root'
fgeo = ROOT.TFile(geoFile)
# new geofile, load Shipgeo dictionary written by run_simScript.py
upkl = Unpickler(fgeo)
ShipGeo = upkl.load('ShipGeo')
ecalGeoFile = ShipGeo.ecal.File
dy = ShipGeo.Yheight / u.m
# -----Create geometry----------------------------------------------
import shipDet_conf
run = ROOT.FairRunSim()
run.SetName("TGeant4") # Transport engine
run.SetOutputFile("dummy") # Output file
run.SetUserConfig("g4Config_basic.C"
) # geant4 transport not used, only needed for the mag field
rtdb = run.GetRuntimeDb()
# -----Create geometry----------------------------------------------
print('a')
modules = shipDet_conf.configure(run, ShipGeo)
#
fRman = ROOT.FairRootManager.Instance()
sTree = fRman.GetInChain()
fGeo = ROOT.gGeoManager
top = fGeo.GetTopVolume()
evmgr = ROOT.gEve
if not fRun.GetGeoFile().FindKey('ShipGeo'):
# old geofile, missing Shipgeo dictionary
# try to figure out which ecal geo to load
if fGeo.GetVolume('EcalModule3'): ecalGeoFile = "ecal_ellipse6x12m2.geo"
else: ecalGeoFile = "ecal_ellipse5x10m2.geo"
ShipGeo = ConfigRegistry.loadpy("$FAIRSHIP/geometry/geometry_config.py",
Yheight=float(dy),
EcalGeoFile=ecalGeoFile)
else:
# new geofile, load Shipgeo dictionary written by run_simScript.py
upkl = Unpickler(fRun.GetGeoFile())
ShipGeo = upkl.load('ShipGeo')
ecalGeoFile = ShipGeo.ecal.File
if hasattr(ShipGeo, 'preshowerOption'):
if ShipGeo.preshowerOption > 0:
mcHits['preshowerPoints'] = ROOT.FairMCPointDraw(
"preshowerPoint", ROOT.kYellow, ROOT.kFullCircle)
fMan.AddTask(mcHits['preshowerPoints'])
# switchOfAll('RockD')
rulers = Rulers()
SHiPDisplay = EventLoop()
SHiPDisplay.InitTask()
SHiPDisplay.NextEvent()
def run_track_pattern_recognition(input_file, geo_file, output_file, method):
"""
Runs all steps of track pattern recognition.
Parameters
----------
input_file : string
Path to an input .root file with events.
geo_file : string
Path to a file with SHiP geometry.
output_file : string
Path to an output .root file with quality plots.
method : string
Name of a track pattern recognition method.
"""
############################################# Load SHiP geometry ###################################################
# Check geo file
try:
fgeo = ROOT.TFile(geo_file)
except:
print "An error with opening the ship geo file."
raise
sGeo = fgeo.FAIRGeom
# Prepare ShipGeo dictionary
if not fgeo.FindKey('ShipGeo'):
if sGeo.GetVolume('EcalModule3'):
ecalGeoFile = "ecal_ellipse6x12m2.geo"
else:
ecalGeoFile = "ecal_ellipse5x10m2.geo"
if dy:
ShipGeo = ConfigRegistry.loadpy(
"$FAIRSHIP/geometry/geometry_config.py",
Yheight=dy,
EcalGeoFile=ecalGeoFile)
else:
ShipGeo = ConfigRegistry.loadpy(
"$FAIRSHIP/geometry/geometry_config.py",
EcalGeoFile=ecalGeoFile)
else:
upkl = Unpickler(fgeo)
ShipGeo = upkl.load('ShipGeo')
# Globals
builtin.ShipGeo = ShipGeo
############################################# Load SHiP modules ####################################################
run = ROOT.FairRunSim()
modules = shipDet_conf.configure(run, ShipGeo)
############################################# Load inpur data file #################################################
# Check input file
try:
fn = ROOT.TFile(input_file, 'update')
except:
print "An error with opening the input data file."
raise
sTree = fn.cbmsim
sTree.Write()
############################################# Create hists #########################################################
h = init_book_hist()
########################################## Start Track Pattern Recognition #########################################
import shipPatRec
# Init book of hists for the quality measurements
metrics = {
'n_hits': [],
'reconstructible': 0,
'passed_y12': 0,
'passed_stereo12': 0,
'passed_12': 0,
'passed_y34': 0,
'passed_stereo34': 0,
'passed_34': 0,
'passed_combined': 0,
'reco_passed': 0,
'reco_passed_no_clones': 0,
'frac_y12': [],
'frac_stereo12': [],
'frac_12': [],
'frac_y34': [],
'frac_stereo34': [],
'frac_34': [],
'reco_frac_tot': [],
'reco_mc_p': [],
'reco_mc_theta': [],
'fitted_p': [],
'fitted_pval': [],
'fitted_chi': [],
'fitted_x': [],
'fitted_y': [],
'fitted_z': [],
'fitted_mass': []
}
# Start event loop
nEvents = sTree.GetEntries()
for iEvent in range(nEvents):
if iEvent % 1000 == 0:
print 'Event ', iEvent
########################################### Select one event ###################################################
rc = sTree.GetEvent(iEvent)
########################################### Reconstructible tracks #############################################
reconstructible_tracks = getReconstructibleTracks(
iEvent, sTree, sGeo, ShipGeo)
metrics['reconstructible'] += len(reconstructible_tracks)
for i_reco in reconstructible_tracks:
h['TracksPassed'].Fill("Reconstructible tracks", 1)
h['TracksPassedU'].Fill("Reconstructible tracks", 1)
in_y12 = []
in_stereo12 = []
in_12 = []
in_y34 = []
in_stereo34 = []
in_34 = []
in_combo = []
########################################## Recognized tracks ###################################################
nTracklets = sTree.Tracklets.GetEntriesFast()
for i_track in range(nTracklets):
atracklet = sTree.Tracklets[i_track]
if atracklet.getType() != 1: # this is a not full track (tracklet)
continue
atrack = atracklet.getList()
if atrack.size() == 0:
continue
hits = {
'X': [],
'Y': [],
'Z': [],
'DetID': [],
'TrackID': [],
'Pz': [],
'Px': [],
'Py': [],
'dist2Wire': [],
'Pdg': []
}
for ihit in atrack:
ahit = sTree.strawtubesPoint[ihit]
hits['X'] += [ahit.GetX()]
hits['Y'] += [ahit.GetY()]
hits['Z'] += [ahit.GetZ()]
hits['DetID'] += [ahit.GetDetectorID()]
hits['TrackID'] += [ahit.GetTrackID()]
hits['Pz'] += [ahit.GetPz()]
hits['Px'] += [ahit.GetPx()]
hits['Py'] += [ahit.GetPy()]
hits['dist2Wire'] += [ahit.dist2Wire()]
hits['Pdg'] += [ahit.PdgCode()]
# List to numpy arrays
for key in hits.keys():
hits[key] = numpy.array(hits[key])
# Decoding
statnb, vnb, pnb, lnb, snb = decodeDetectorID(hits['DetID'])
is_stereo = ((vnb == 1) + (vnb == 2))
is_y = ((vnb == 0) + (vnb == 3))
is_before = ((statnb == 1) + (statnb == 2))
is_after = ((statnb == 3) + (statnb == 4))
# Metrics
metrics['n_hits'] += [get_n_hits(hits['TrackID'])]
# Tracks passed
frac_y12, tmax_y12 = fracMCsame(hits['TrackID'][is_before * is_y])
n_hits_y12 = get_n_hits(hits['TrackID'][is_before * is_y])
frac_stereo12, tmax_stereo12 = fracMCsame(
hits['TrackID'][is_before * is_stereo])
n_hits_stereo12 = get_n_hits(hits['TrackID'][is_before *
is_stereo])
frac_12, tmax_12 = fracMCsame(hits['TrackID'][is_before])
n_hits_12 = get_n_hits(hits['TrackID'][is_before])
frac_y34, tmax_y34 = fracMCsame(hits['TrackID'][is_after * is_y])
n_hits_y34 = get_n_hits(hits['TrackID'][is_after * is_y])
frac_stereo34, tmax_stereo34 = fracMCsame(
hits['TrackID'][is_after * is_stereo])
n_hits_stereo34 = get_n_hits(hits['TrackID'][is_after * is_stereo])
frac_34, tmax_34 = fracMCsame(hits['TrackID'][is_after])
n_hits_34 = get_n_hits(hits['TrackID'][is_after])
frac_tot, tmax_tot = fracMCsame(hits['TrackID'])
n_hits_tot = get_n_hits(hits['TrackID'])
is_reconstructed = 0
is_reconstructed_no_clones = 0
if tmax_y12 in reconstructible_tracks:
metrics['passed_y12'] += 1
metrics['frac_y12'] += [frac_y12]
h['TracksPassed'].Fill("Y view station 1&2", 1)
if tmax_y12 not in in_y12:
h['TracksPassedU'].Fill("Y view station 1&2", 1)
in_y12.append(tmax_y12)
if tmax_stereo12 == tmax_y12:
metrics['passed_stereo12'] += 1
metrics['frac_stereo12'] += [frac_stereo12]
h['TracksPassed'].Fill("Stereo station 1&2", 1)
if tmax_stereo12 not in in_stereo12:
h['TracksPassedU'].Fill("Stereo station 1&2", 1)
in_stereo12.append(tmax_stereo12)
if tmax_12 == tmax_y12:
metrics['passed_12'] += 1
metrics['frac_12'] += [frac_12]
h['TracksPassed'].Fill("station 1&2", 1)
if tmax_12 not in in_12:
h['TracksPassedU'].Fill("station 1&2", 1)
in_12.append(tmax_12)
if tmax_y34 in reconstructible_tracks:
metrics['passed_y34'] += 1
metrics['frac_y34'] += [frac_y34]
h['TracksPassed'].Fill("Y view station 3&4", 1)
if tmax_y34 not in in_y34:
h['TracksPassedU'].Fill(
"Y view station 3&4", 1)
in_y34.append(tmax_y34)
if tmax_stereo34 == tmax_y34:
metrics['passed_stereo34'] += 1
metrics['frac_stereo34'] += [frac_stereo34]
h['TracksPassed'].Fill("Stereo station 3&4", 1)
if tmax_stereo34 not in in_stereo34:
h['TracksPassedU'].Fill(
"Stereo station 3&4", 1)
in_stereo34.append(tmax_stereo34)
if tmax_34 == tmax_y34:
metrics['passed_34'] += 1
metrics['frac_34'] += [frac_34]
h['TracksPassed'].Fill("station 3&4", 1)
if tmax_34 not in in_34:
h['TracksPassedU'].Fill(
"station 3&4", 1)
in_34.append(tmax_34)
if tmax_12 == tmax_34:
metrics['passed_combined'] += 1
h['TracksPassed'].Fill(
"Combined stations 1&2/3&4", 1)
metrics['reco_passed'] += 1
is_reconstructed = 1
if tmax_34 not in in_combo:
h['TracksPassedU'].Fill(
"Combined stations 1&2/3&4", 1)
metrics['reco_passed_no_clones'] += 1
in_combo.append(tmax_34)
is_reconstructed_no_clones = 1
# For reconstructed tracks
if is_reconstructed == 0:
continue
metrics['reco_frac_tot'] += [frac_tot]
# Momentum
Pz = hits['Pz']
Px = hits['Px']
Py = hits['Py']
P = numpy.sqrt(Pz**2 + Px**2 + Py**2)
P = P[hits['TrackID'] == tmax_tot]
p = numpy.mean(P)
metrics['reco_mc_p'] += [p]
h['TracksPassed_p'].Fill(p, 1)
# Direction
Z = hits['Z'][(hits['TrackID'] == tmax_tot) * is_before]
X = hits['X'][(hits['TrackID'] == tmax_tot) * is_before]
Y = hits['Y'][(hits['TrackID'] == tmax_tot) * is_before]
Z = Z - Z[0]
X = X - X[0]
Y = Y - Y[0]
R = numpy.sqrt(X**2 + Y**2 + Z**2)
Theta = numpy.arccos(Z[1:] / R[1:])
theta = numpy.mean(Theta)
metrics['reco_mc_theta'] += [theta]
h['n_hits_reco_y12'].Fill(n_hits_y12)
h['n_hits_reco_stereo12'].Fill(n_hits_stereo12)
h['n_hits_reco_12'].Fill(n_hits_12)
h['n_hits_reco_y34'].Fill(n_hits_y34)
h['n_hits_reco_stereo34'].Fill(n_hits_stereo34)
h['n_hits_reco_34'].Fill(n_hits_34)
h['n_hits_reco'].Fill(n_hits_tot)
h['n_hits_y12'].Fill(p, n_hits_y12)
h['n_hits_stereo12'].Fill(p, n_hits_stereo12)
h['n_hits_12'].Fill(p, n_hits_12)
h['n_hits_y34'].Fill(p, n_hits_y34)
h['n_hits_stereo34'].Fill(p, n_hits_stereo34)
h['n_hits_34'].Fill(p, n_hits_34)
h['n_hits_total'].Fill(p, n_hits_tot)
h['frac_y12'].Fill(p, frac_y12)
h['frac_stereo12'].Fill(p, frac_stereo12)
h['frac_12'].Fill(p, frac_12)
h['frac_y34'].Fill(p, frac_y34)
h['frac_stereo34'].Fill(p, frac_stereo34)
h['frac_34'].Fill(p, frac_34)
h['frac_total'].Fill(p, frac_tot)
# Fitted track
thetrack = sTree.FitTracks[i_track]
fitStatus = thetrack.getFitStatus()
thetrack.prune(
"CFL"
) # http://sourceforge.net/p/genfit/code/HEAD/tree/trunk/core/include/Track.h#l280
nmeas = fitStatus.getNdf()
pval = fitStatus.getPVal()
chi2 = fitStatus.getChi2() / nmeas
metrics['fitted_pval'] += [pval]
metrics['fitted_chi'] += [chi2]
h['chi2fittedtracks'].Fill(chi2)
h['pvalfittedtracks'].Fill(pval)
fittedState = thetrack.getFittedState()
fittedMom = fittedState.getMomMag()
fittedMom = fittedMom #*int(charge)
metrics['fitted_p'] += [fittedMom]
perr = (p - fittedMom) / p
h['ptrue-p/ptrue'].Fill(perr)
h['perr'].Fill(p, perr)
h['perr_direction'].Fill(numpy.rad2deg(theta), perr)
if math.fabs(p) > 0.0:
h['pvspfitted'].Fill(p, fittedMom)
fittedtrackDir = fittedState.getDir()
fittedx = math.degrees(math.acos(fittedtrackDir[0]))
fittedy = math.degrees(math.acos(fittedtrackDir[1]))
fittedz = math.degrees(math.acos(fittedtrackDir[2]))
fittedmass = fittedState.getMass()
h['momentumfittedtracks'].Fill(fittedMom)
h['xdirectionfittedtracks'].Fill(fittedx)
h['ydirectionfittedtracks'].Fill(fittedy)
h['zdirectionfittedtracks'].Fill(fittedz)
h['massfittedtracks'].Fill(fittedmass)
metrics['fitted_x'] += [fittedx]
metrics['fitted_y'] += [fittedy]
metrics['fitted_z'] += [fittedz]
metrics['fitted_mass'] += [fittedmass]
############################################# Save hists #########################################################
save_hists(h, output_file)
return metrics
from __future__ import print_function
import ROOT,sys
from rootpyPickler import Unpickler
badBoys={}
f1,f2 = sys.argv[1], sys.argv[2]
fgeoOld=ROOT.TFile(f1)
upkl = Unpickler(fgeoOld)
ShipGeoOld = upkl.load('ShipGeo')
fgeoNew=ROOT.TFile(f2)
upkl = Unpickler(fgeoNew)
ShipGeoNew = upkl.load('ShipGeo')
for x in ShipGeoNew:
if hasattr(eval('ShipGeoNew.'+x),'z'):
zold,znew = eval('ShipGeoOld.'+x+'.z'),eval('ShipGeoNew.'+x+'.z')
print(x,'z=',znew, ' old:', zold)
if zold!=znew: badBoys[x]=[znew,zold]
if len(badBoys)>0: print("following differences detected:")
for x in badBoys:
print(x,badBoys[x])
def dmetric(input_file, geo_file, dy, reconstructiblerequired, threeprong):
############################################# Load SHiP geometry ###################################################
# Check geo file
try:
fgeo = ROOT.TFile(geo_file)
except:
print "An error with opening the ship geo file."
raise
sGeo = fgeo.FAIRGeom
# Prepare ShipGeo dictionary
if not fgeo.FindKey('ShipGeo'):
if sGeo.GetVolume('EcalModule3') :
ecalGeoFile = "ecal_ellipse6x12m2.geo"
else:
ecalGeoFile = "ecal_ellipse5x10m2.geo"
if dy:
ShipGeo = ConfigRegistry.loadpy("$FAIRSHIP/geometry/geometry_config.py", Yheight = dy, EcalGeoFile = ecalGeoFile)
else:
ShipGeo = ConfigRegistry.loadpy("$FAIRSHIP/geometry/geometry_config.py", EcalGeoFile = ecalGeoFile)
else:
upkl = Unpickler(fgeo)
ShipGeo = upkl.load('ShipGeo')
############################################# Load SHiP modules ####################################################
run = ROOT.FairRunSim()
modules = shipDet_conf.configure(run,ShipGeo)
############################################# Load input data file #################################################
# Check input file
try:
fn = ROOT.TFile(input_file,'update')
except:
print "An error with opening the input data file."
raise
sTree = fn.cbmsim
############################## Initialize SHiP Spectrometer Tracker geometry #######################################
zlayer, \
zlayerv2, \
z34layer, \
z34layerv2, \
TStation1StartZ, \
TStation4EndZ, \
VetoStationZ, \
VetoStationEndZ = initialize(ShipGeo)
########################################## Start Checking Geometry #################################################
all_hits = pandas.DataFrame(columns=['event_id', 'det_id', 'track_id', 'xtop', 'ytop', 'z', 'xbot', 'ybot'])
all_hits_i = 0
# Start event loop
nEvents = sTree.GetEntries()
for iEvent in range(nEvents):
if iEvent%100 == 0:
print 'Event ', iEvent
########################################### Select one event ###################################################
rc = sTree.GetEvent(iEvent)
############################################# Get hits #########################################################
reco_mc_tracks = getReconstructibleTracks(iEvent,
sTree,
sGeo,
reconstructiblerequired,
threeprong,
TStation1StartZ,
TStation4EndZ,
VetoStationZ,
VetoStationEndZ)
#consider only reconstructible events
if len(reco_mc_tracks) > 1:
nHits = sTree.strawtubesPoint.GetEntriesFast()
key = -1
for i in range(nHits):
ahit = sTree.strawtubesPoint[i]
key+=1
detID = ahit.GetDetectorID()
trID = ahit.GetTrackID()
top = ROOT.TVector3()
bot = ROOT.TVector3()
modules["Strawtubes"].StrawEndPoints(detID,bot,top)
all_hits.loc[all_hits_i] = [iEvent, detID, trID, top.x(), top.y(), top.z(), bot.x(), bot.y()]
all_hits_i += 1
all_hits['StatNb'] = all_hits['det_id'] // 10000000
all_hits['ViewNb'] = (all_hits['det_id'] - all_hits['StatNb'] * 10000000) // 1000000
all_hits['PlaneNb'] = (all_hits['det_id'] - all_hits['StatNb'] * 10000000 - all_hits['ViewNb'] * 1000000) // 100000
all_hits['LayerNb'] = (all_hits['det_id'] - all_hits['StatNb'] * 10000000 - all_hits['ViewNb'] * 1000000 -\
all_hits['PlaneNb'] * 100000) // 10000
all_hits['StrawNb'] = all_hits['det_id'] - all_hits['StatNb'] * 10000000 - all_hits['ViewNb'] * 1000000 -\
all_hits['PlaneNb'] * 100000 - all_hits['LayerNb'] * 10000 - 2000
#return daniel's metric
df_1_view = all_hits[(all_hits.StatNb==1)&(all_hits.ViewNb==0)]
counts = df_1_view.groupby(['event_id', 'track_id'])['StatNb'].count()
all_tracks = len(all_hits.groupby(['event_id', 'track_id'])['StatNb'].count())
return 1. * np.sum(counts>1) / all_tracks
def run_track_pattern_recognition(input_file, geo_file, output_file, method):
"""
Runs all steps of track pattern recognition.
Parameters
----------
input_file : string
Path to an input .root file with events.
geo_file : string
Path to a file with SHiP geometry.
output_file : string
Path to an output .root file with quality plots.
method : string
Name of a track pattern recognition method.
"""
############################################# Load SHiP geometry ###################################################
# Check geo file
try:
fgeo = ROOT.TFile(geo_file)
except:
print("An error with opening the ship geo file.")
raise
sGeo = fgeo.FAIRGeom
# Prepare ShipGeo dictionary
if not fgeo.FindKey('ShipGeo'):
if sGeo.GetVolume('EcalModule3'):
ecalGeoFile = "ecal_ellipse6x12m2.geo"
else:
ecalGeoFile = "ecal_ellipse5x10m2.geo"
if dy:
ShipGeo = ConfigRegistry.loadpy(
"$FAIRSHIP/geometry/geometry_config.py",
Yheight=dy,
EcalGeoFile=ecalGeoFile)
else:
ShipGeo = ConfigRegistry.loadpy(
"$FAIRSHIP/geometry/geometry_config.py",
EcalGeoFile=ecalGeoFile)
else:
upkl = Unpickler(fgeo)
ShipGeo = upkl.load('ShipGeo')
# Globals
builtin.ShipGeo = ShipGeo
############################################# Load SHiP modules ####################################################
import shipDet_conf
run = ROOT.FairRunSim()
run.SetName("TGeant4") # Transport engine
run.SetOutputFile("dummy") # Output file
run.SetUserConfig(
"g4Config_basic.C"
) # geant4 transport not used, only needed for the mag field
rtdb = run.GetRuntimeDb()
modules = shipDet_conf.configure(run, ShipGeo)
run.Init()
#run = ROOT.FairRunSim()
#modules = shipDet_conf.configure(run,ShipGeo)
######################################### Load SHiP magnetic field #################################################
import geomGeant4
if hasattr(ShipGeo.Bfield, "fieldMap"):
fieldMaker = geomGeant4.addVMCFields(ShipGeo,
'',
True,
withVirtualMC=False)
else:
print("no fieldmap given, geofile too old, not anymore support")
exit(-1)
sGeo = fgeo.FAIRGeom
geoMat = ROOT.genfit.TGeoMaterialInterface()
ROOT.genfit.MaterialEffects.getInstance().init(geoMat)
bfield = ROOT.genfit.FairShipFields()
bfield.setField(fieldMaker.getGlobalField())
fM = ROOT.genfit.FieldManager.getInstance()
fM.init(bfield)
############################################# Load inpur data file #################################################
# Check input file
try:
fn = ROOT.TFile(input_file, 'update')
except:
print("An error with opening the input data file.")
raise
sTree = fn.cbmsim
sTree.Write()
############################################# Create hists #########################################################
h = init_book_hist()
########################################## Start Track Pattern Recognition #########################################
import shipPatRec
# Init book of hists for the quality measurements
metrics = {
'n_hits': [],
'reconstructible': 0,
'passed_y12': 0,
'passed_stereo12': 0,
'passed_12': 0,
'passed_y34': 0,
'passed_stereo34': 0,
'passed_34': 0,
'passed_combined': 0,
'reco_passed': 0,
'reco_passed_no_clones': 0,
'frac_y12': [],
'frac_stereo12': [],
'frac_12': [],
'frac_y34': [],
'frac_stereo34': [],
'frac_34': [],
'reco_frac_tot': [],
'reco_mc_p': [],
'reco_mc_theta': [],
'fitted_p': [],
'fitted_pval': [],
'fitted_chi': [],
'fitted_x': [],
'fitted_y': [],
'fitted_z': [],
'fitted_mass': []
}
# Start event loop
nEvents = sTree.GetEntries()
for iEvent in range(nEvents):
if iEvent % 1000 == 0:
print('Event ', iEvent)
########################################### Select one event ###################################################
rc = sTree.GetEvent(iEvent)
########################################### Reconstructible tracks #############################################
reconstructible_tracks = getReconstructibleTracks(
iEvent, sTree, sGeo, ShipGeo)
metrics['reconstructible'] += len(reconstructible_tracks)
for i_reco in reconstructible_tracks:
h['TracksPassed'].Fill("Reconstructible tracks", 1)
h['TracksPassedU'].Fill("Reconstructible tracks", 1)
in_y12 = []
in_stereo12 = []
in_12 = []
in_y34 = []
in_stereo34 = []
in_34 = []
in_combo = []
found_track_ids = []
n_tracks = len(reconstructible_tracks)
n_recognized = 0
n_clones = 0
n_ghosts = 0
n_others = 0
min_eff = 0.
########################################## Recognized tracks ###################################################
nTracklets = sTree.Tracklets.GetEntriesFast()
for i_track in range(nTracklets):
atracklet = sTree.Tracklets[i_track]
if atracklet.getType() != 1: # this is a not full track (tracklet)
continue
atrack = atracklet.getList()
if atrack.size() == 0:
continue
hits = {
'X': [],
'Y': [],
'Z': [],
'DetID': [],
'TrackID': [],
'Pz': [],
'Px': [],
'Py': [],
'dist2Wire': [],
'Pdg': []
}
for ihit in atrack:
ahit = sTree.strawtubesPoint[ihit]
hits['X'] += [ahit.GetX()]
hits['Y'] += [ahit.GetY()]
hits['Z'] += [ahit.GetZ()]
hits['DetID'] += [ahit.GetDetectorID()]
hits['TrackID'] += [ahit.GetTrackID()]
hits['Pz'] += [ahit.GetPz()]
hits['Px'] += [ahit.GetPx()]
hits['Py'] += [ahit.GetPy()]
hits['dist2Wire'] += [ahit.dist2Wire()]
hits['Pdg'] += [ahit.PdgCode()]
# List to numpy arrays
for key in hits.keys():
hits[key] = numpy.array(hits[key])
# Decoding
statnb, vnb, pnb, lnb, snb = decodeDetectorID(hits['DetID'])
is_stereo = ((vnb == 1) + (vnb == 2))
is_y = ((vnb == 0) + (vnb == 3))
is_before = ((statnb == 1) + (statnb == 2))
is_after = ((statnb == 3) + (statnb == 4))
# Metrics
metrics['n_hits'] += [get_n_hits(hits['TrackID'])]
# Tracks passed
frac_y12, tmax_y12 = fracMCsame(hits['TrackID'][is_before * is_y])
n_hits_y12 = get_n_hits(hits['TrackID'][is_before * is_y])
frac_stereo12, tmax_stereo12 = fracMCsame(
hits['TrackID'][is_before * is_stereo])
n_hits_stereo12 = get_n_hits(hits['TrackID'][is_before *
is_stereo])
frac_12, tmax_12 = fracMCsame(hits['TrackID'][is_before])
n_hits_12 = get_n_hits(hits['TrackID'][is_before])
frac_y34, tmax_y34 = fracMCsame(hits['TrackID'][is_after * is_y])
n_hits_y34 = get_n_hits(hits['TrackID'][is_after * is_y])
frac_stereo34, tmax_stereo34 = fracMCsame(
hits['TrackID'][is_after * is_stereo])
n_hits_stereo34 = get_n_hits(hits['TrackID'][is_after * is_stereo])
frac_34, tmax_34 = fracMCsame(hits['TrackID'][is_after])
n_hits_34 = get_n_hits(hits['TrackID'][is_after])
frac_tot, tmax_tot = fracMCsame(hits['TrackID'])
n_hits_tot = get_n_hits(hits['TrackID'])
if tmax_y12 == tmax_stereo12 and tmax_y12 == tmax_y34 and tmax_y12 == tmax_stereo34:
if frac_y12 >= min_eff and frac_stereo12 >= min_eff and frac_y34 >= min_eff and frac_stereo34 >= min_eff:
if tmax_y12 in reconstructible_tracks and tmax_y12 not in found_track_ids:
n_recognized += 1
found_track_ids.append(tmax_y12)
elif tmax_y12 in reconstructible_tracks and tmax_y12 in found_track_ids:
n_clones += 1
elif tmax_y12 not in reconstructible_tracks:
n_others += 1
else:
n_ghosts += 1
else:
n_ghosts += 1
is_reconstructed = 0
is_reconstructed_no_clones = 0
if tmax_y12 in reconstructible_tracks:
metrics['passed_y12'] += 1
metrics['frac_y12'] += [frac_y12]
h['TracksPassed'].Fill("Y view station 1&2", 1)
if tmax_y12 not in in_y12:
h['TracksPassedU'].Fill("Y view station 1&2", 1)
in_y12.append(tmax_y12)
if tmax_stereo12 == tmax_y12:
metrics['passed_stereo12'] += 1
metrics['frac_stereo12'] += [frac_stereo12]
h['TracksPassed'].Fill("Stereo station 1&2", 1)
if tmax_stereo12 not in in_stereo12:
h['TracksPassedU'].Fill("Stereo station 1&2", 1)
in_stereo12.append(tmax_stereo12)
if tmax_12 == tmax_y12:
metrics['passed_12'] += 1
metrics['frac_12'] += [frac_12]
h['TracksPassed'].Fill("station 1&2", 1)
if tmax_12 not in in_12:
h['TracksPassedU'].Fill("station 1&2", 1)
in_12.append(tmax_12)
if tmax_y34 in reconstructible_tracks:
metrics['passed_y34'] += 1
metrics['frac_y34'] += [frac_y34]
h['TracksPassed'].Fill("Y view station 3&4", 1)
if tmax_y34 not in in_y34:
h['TracksPassedU'].Fill(
"Y view station 3&4", 1)
in_y34.append(tmax_y34)
if tmax_stereo34 == tmax_y34:
metrics['passed_stereo34'] += 1
metrics['frac_stereo34'] += [frac_stereo34]
h['TracksPassed'].Fill("Stereo station 3&4", 1)
if tmax_stereo34 not in in_stereo34:
h['TracksPassedU'].Fill(
"Stereo station 3&4", 1)
in_stereo34.append(tmax_stereo34)
if tmax_34 == tmax_y34:
metrics['passed_34'] += 1
metrics['frac_34'] += [frac_34]
h['TracksPassed'].Fill("station 3&4", 1)
if tmax_34 not in in_34:
h['TracksPassedU'].Fill(
"station 3&4", 1)
in_34.append(tmax_34)
if tmax_12 == tmax_34:
metrics['passed_combined'] += 1
h['TracksPassed'].Fill(
"Combined stations 1&2/3&4", 1)
metrics['reco_passed'] += 1
is_reconstructed = 1
if tmax_34 not in in_combo:
h['TracksPassedU'].Fill(
"Combined stations 1&2/3&4", 1)
metrics[
'reco_passed_no_clones'] += 1
in_combo.append(tmax_34)
is_reconstructed_no_clones = 1
# For reconstructed tracks
if is_reconstructed == 0:
continue
metrics['reco_frac_tot'] += [frac_tot]
# Momentum
Pz = hits['Pz']
Px = hits['Px']
Py = hits['Py']
p, px, py, pz = getPtruthFirst(sTree, tmax_tot)
pt = math.sqrt(px**2 + py**2)
Z_true = []
X_true = []
Y_true = []
for ahit in sTree.strawtubesPoint:
if ahit.GetTrackID() == tmax_tot:
az, ax, ay = ahit.GetZ(), ahit.GetX(), ahit.GetY()
Z_true.append(az)
X_true.append(ax)
Y_true.append(ay)
metrics['reco_mc_p'] += [p]
h['TracksPassed_p'].Fill(p, 1)
# Direction
Z = hits['Z'][(hits['TrackID'] == tmax_tot) * is_before]
X = hits['X'][(hits['TrackID'] == tmax_tot) * is_before]
Y = hits['Y'][(hits['TrackID'] == tmax_tot) * is_before]
Z = Z - Z[0]
X = X - X[0]
Y = Y - Y[0]
R = numpy.sqrt(X**2 + Y**2 + Z**2)
Theta = numpy.arccos(Z[1:] / R[1:])
theta = numpy.mean(Theta)
metrics['reco_mc_theta'] += [theta]
h['n_hits_reco_y12'].Fill(n_hits_y12)
h['n_hits_reco_stereo12'].Fill(n_hits_stereo12)
h['n_hits_reco_12'].Fill(n_hits_12)
h['n_hits_reco_y34'].Fill(n_hits_y34)
h['n_hits_reco_stereo34'].Fill(n_hits_stereo34)
h['n_hits_reco_34'].Fill(n_hits_34)
h['n_hits_reco'].Fill(n_hits_tot)
h['n_hits_y12'].Fill(p, n_hits_y12)
h['n_hits_stereo12'].Fill(p, n_hits_stereo12)
h['n_hits_12'].Fill(p, n_hits_12)
h['n_hits_y34'].Fill(p, n_hits_y34)
h['n_hits_stereo34'].Fill(p, n_hits_stereo34)
h['n_hits_34'].Fill(p, n_hits_34)
h['n_hits_total'].Fill(p, n_hits_tot)
h['frac_y12'].Fill(p, frac_y12)
h['frac_stereo12'].Fill(p, frac_stereo12)
h['frac_12'].Fill(p, frac_12)
h['frac_y34'].Fill(p, frac_y34)
h['frac_stereo34'].Fill(p, frac_stereo34)
h['frac_34'].Fill(p, frac_34)
h['frac_total'].Fill(p, frac_tot)
h['frac_y12_dist'].Fill(frac_y12)
h['frac_stereo12_dist'].Fill(frac_stereo12)
h['frac_12_dist'].Fill(frac_12)
h['frac_y34_dist'].Fill(frac_y34)
h['frac_stereo34_dist'].Fill(frac_stereo34)
h['frac_34_dist'].Fill(frac_34)
h['frac_total_dist'].Fill(frac_tot)
# Fitted track
thetrack = sTree.FitTracks[i_track]
fitStatus = thetrack.getFitStatus()
thetrack.prune(
"CFL"
) # http://sourceforge.net/p/genfit/code/HEAD/tree/trunk/core/include/Track.h#l280
nmeas = fitStatus.getNdf()
pval = fitStatus.getPVal()
chi2 = fitStatus.getChi2() / nmeas
metrics['fitted_pval'] += [pval]
metrics['fitted_chi'] += [chi2]
h['chi2fittedtracks'].Fill(chi2)
h['pvalfittedtracks'].Fill(pval)
try:
fittedState = thetrack.getFittedState()
fittedMom = fittedState.getMomMag()
fittedMom = fittedMom #*int(charge)
px_fit, py_fit, pz_fit = fittedState.getMom().x(
), fittedState.getMom().y(), fittedState.getMom().z()
p_fit = fittedMom
pt_fit = math.sqrt(px_fit**2 + py_fit**2)
metrics['fitted_p'] += [p_fit]
perr = (p - p_fit) / p
h['ptrue-p/ptrue'].Fill(perr)
h['perr'].Fill(p, perr)
h['perr_direction'].Fill(numpy.rad2deg(theta), perr)
pterr = (pt - pt_fit) / pt
h['pttrue-pt/pttrue'].Fill(pterr)
pxerr = (px - px_fit) / px
h['pxtrue-px/pxtrue'].Fill(pxerr)
pyerr = (py - py_fit) / py
h['pytrue-py/pytrue'].Fill(pyerr)
pzerr = (pz - pz_fit) / pz
h['pztrue-pz/pztrue'].Fill(pzerr)
if math.fabs(p) > 0.0:
h['pvspfitted'].Fill(p, fittedMom)
fittedtrackDir = fittedState.getDir()
fittedx = math.degrees(math.acos(fittedtrackDir[0]))
fittedy = math.degrees(math.acos(fittedtrackDir[1]))
fittedz = math.degrees(math.acos(fittedtrackDir[2]))
fittedmass = fittedState.getMass()
h['momentumfittedtracks'].Fill(fittedMom)
h['xdirectionfittedtracks'].Fill(fittedx)
h['ydirectionfittedtracks'].Fill(fittedy)
h['zdirectionfittedtracks'].Fill(fittedz)
h['massfittedtracks'].Fill(fittedmass)
metrics['fitted_x'] += [fittedx]
metrics['fitted_y'] += [fittedy]
metrics['fitted_z'] += [fittedz]
metrics['fitted_mass'] += [fittedmass]
Z_fit = []
X_fit = []
Y_fit = []
for az in Z_true:
rc, pos, mom = extrapolateToPlane(thetrack, az)
Z_fit.append(pos.Z())
X_fit.append(pos.X())
Y_fit.append(pos.Y())
for i in range(len(Z_true)):
xerr = abs(X_fit[i] - X_true[i])
yerr = abs(Y_fit[i] - Y_true[i])
h['abs(x - x-true)'].Fill(xerr)
h['abs(y - y-true)'].Fill(yerr)
rmse_x = numpy.sqrt(
numpy.mean((numpy.array(X_fit) - numpy.array(X_true))**2))
rmse_y = numpy.sqrt(
numpy.mean((numpy.array(Y_fit) - numpy.array(Y_true))**2))
h['rmse_x'].Fill(rmse_x)
h['rmse_y'].Fill(rmse_y)
except:
print("Problem with fitted state.")
h['Reco_tracks'].Fill("N total", n_tracks)
h['Reco_tracks'].Fill("N recognized tracks", n_recognized)
h['Reco_tracks'].Fill("N clones", n_clones)
h['Reco_tracks'].Fill("N ghosts", n_ghosts)
h['Reco_tracks'].Fill("N others", n_others)
############################################# Save hists #########################################################
save_hists(h, output_file)
return metrics
def run_checking(input_file, geo_file, dy, reconstructiblerequired,
threeprong):
############################################# Load SHiP geometry ###################################################
# Check geo file
try:
fgeo = ROOT.TFile(geo_file)
except:
print "An error with opening the ship geo file."
raise
sGeo = fgeo.FAIRGeom
# Prepare ShipGeo dictionary
if not fgeo.FindKey('ShipGeo'):
if sGeo.GetVolume('EcalModule3'):
ecalGeoFile = "ecal_ellipse6x12m2.geo"
else:
ecalGeoFile = "ecal_ellipse5x10m2.geo"
if dy:
ShipGeo = ConfigRegistry.loadpy(
"$FAIRSHIP/geometry/geometry_config.py",
Yheight=dy,
EcalGeoFile=ecalGeoFile)
else:
ShipGeo = ConfigRegistry.loadpy(
"$FAIRSHIP/geometry/geometry_config.py",
EcalGeoFile=ecalGeoFile)
else:
upkl = Unpickler(fgeo)
ShipGeo = upkl.load('ShipGeo')
############################################# Load SHiP modules ####################################################
run = ROOT.FairRunSim()
modules = shipDet_conf.configure(run, ShipGeo)
############################################# Load input data file #################################################
# Check input file
try:
fn = ROOT.TFile(input_file, 'update')
except:
print "An error with opening the input data file."
raise
sTree = fn.cbmsim
############################## Initialize SHiP Spectrometer Tracker geometry #######################################
#zlayer, \
#zlayerv2, \
#z34layer, \
#z34layerv2, \
#TStation1StartZ, \
#TStation4EndZ, \
#VetoStationZ, \
#VetoStationEndZ = initialize(fgeo, ShipGeo)
########################################## Start Checking Geometry #################################################
all_hits = pandas.DataFrame(
columns=['event_id', 'det_id', 'xtop', 'ytop', 'z', 'xbot', 'ybot'])
all_hits_i = 0
# Start event loop
nEvents = sTree.GetEntries()
for iEvent in range(nEvents):
if iEvent % 100 == 0:
print 'Event ', iEvent
########################################### Select one event ###################################################
rc = sTree.GetEvent(iEvent)
############################################# Get hits #########################################################
nHits = sTree.strawtubesPoint.GetEntriesFast()
key = -1
for i in range(nHits):
ahit = sTree.strawtubesPoint[i]
key += 1
detID = ahit.GetDetectorID()
top = ROOT.TVector3()
bot = ROOT.TVector3()
modules["Strawtubes"].StrawEndPoints(detID, bot, top)
all_hits.loc[all_hits_i] = [
iEvent, detID,
top.x(),
top.y(),
top.z(),
bot.x(),
bot.y()
]
all_hits_i += 1
all_hits.to_csv('hits.csv', index=False)
all_hits['StatNb'] = all_hits['det_id'] // 10000000
all_hits['ViewNb'] = (all_hits['det_id'] -
all_hits['StatNb'] * 10000000) // 1000000
all_hits['PlaneNb'] = (all_hits['det_id'] - all_hits['StatNb'] * 10000000 -
all_hits['ViewNb'] * 1000000) // 100000
all_hits['LayerNb'] = (all_hits['det_id'] - all_hits['StatNb'] * 10000000 - all_hits['ViewNb'] * 1000000 -\
all_hits['PlaneNb'] * 100000) // 10000
all_hits['StrawNb'] = all_hits['det_id'] - all_hits['StatNb'] * 10000000 - all_hits['ViewNb'] * 1000000 -\
all_hits['PlaneNb'] * 100000 - all_hits['LayerNb'] * 10000 - 2000
dots00 = all_hits[(all_hits['StatNb'].values<3) & ((all_hits['ViewNb'].values==0) + (all_hits['ViewNb'].values==3)) &\
(all_hits['PlaneNb'].values==0) & (all_hits['LayerNb'].values==0)]['ytop'].values
dots00 = all_hits[(all_hits['StatNb'].values<3) & ((all_hits['ViewNb'].values==0) + (all_hits['ViewNb'].values==3)) &\
(all_hits['PlaneNb'].values==1) & (all_hits['LayerNb'].values==0)]['ytop'].values
dots01 = all_hits[(all_hits['StatNb'].values<3) & ((all_hits['ViewNb'].values==0) + (all_hits['ViewNb'].values==3)) &\
(all_hits['PlaneNb'].values==0) & (all_hits['LayerNb'].values==1)]['ytop'].values
dots01 = all_hits[(all_hits['StatNb'].values<3) & ((all_hits['ViewNb'].values==0) + (all_hits['ViewNb'].values==3)) &\
(all_hits['PlaneNb'].values==1) & (all_hits['LayerNb'].values==1)]['ytop'].values
min_dist = np.hstack([
np.diff(np.unique(dots00)),
np.diff(np.unique(dots01)),
np.diff(np.unique(dots00)),
np.diff(np.unique(dots01))
]).min()
print('Pitch: ', np.round(min_dist, 3))
z0 = all_hits[(all_hits['StatNb']==1) & (all_hits['ViewNb']==0) & (all_hits['PlaneNb'].values==0) &\
(all_hits['LayerNb'].values==0)]['z'].mean()
z1 = all_hits[(all_hits['StatNb']==1) & (all_hits['ViewNb']==0) & (all_hits['PlaneNb'].values==0) &\
(all_hits['LayerNb'].values==1)]['z'].mean()
print('ZShiftLayer: ', np.round(z1 - z0, 3))
z2 = all_hits[(all_hits['StatNb']==1) & (all_hits['ViewNb']==0) & (all_hits['PlaneNb'].values==1) &\
(all_hits['LayerNb'].values==0)]['z'].mean()
print('ZShiftPlane: ', np.round(z2 - z0, 3))
xtop = all_hits[(all_hits['StatNb']==1) & (all_hits['ViewNb']==1) & (all_hits['PlaneNb']==0) &\
(all_hits['LayerNb']==0)]['xtop'].values[0]
ytop = all_hits[(all_hits['StatNb']==1) & (all_hits['ViewNb']==1) & (all_hits['PlaneNb']==0) &\
(all_hits['LayerNb']==0)]['ytop'].values[0]
xbot = all_hits[(all_hits['StatNb']==1) & (all_hits['ViewNb']==1) & (all_hits['PlaneNb']==0) &\
(all_hits['LayerNb']==0)]['xbot'].values[0]
ybot = all_hits[(all_hits['StatNb']==1) & (all_hits['ViewNb']==1) & (all_hits['PlaneNb']==0) &\
(all_hits['LayerNb']==0)]['ybot'].values[0]
print('Angle: ',
np.round(np.arctan((ytop - ybot) / (xtop - xbot)) * 180 / np.pi, 3))
z0 = all_hits[(all_hits['StatNb']==1) & (all_hits['ViewNb']==0) & (all_hits['PlaneNb'].values==0) &\
(all_hits['LayerNb'].values==0)]['z'].mean()
z3 = all_hits[(all_hits['StatNb']==1) & (all_hits['ViewNb']==1) & (all_hits['PlaneNb'].values==0) &\
(all_hits['LayerNb'].values==0)]['z'].mean()
print('ZShiftView: ', np.round(z3 - z0, 3))
dots0 = all_hits[(all_hits['StatNb'].values<3) & ((all_hits['ViewNb'].values==0) + (all_hits['ViewNb'].values==3)) &\
(all_hits['PlaneNb'].values==0) & (all_hits['LayerNb'].values==0)]['ytop'].values
dots1 = all_hits[(all_hits['StatNb'].values<3) & ((all_hits['ViewNb'].values==0) + (all_hits['ViewNb'].values==3)) &\
(all_hits['PlaneNb'].values==0) & (all_hits['LayerNb'].values==1)]['ytop'].values
min_dist = np.hstack([np.diff(np.unique(np.hstack([dots0, dots1])))]).min()
print('YOffsetLayer: ', np.round(min_dist, 3))
dots0 = all_hits[(all_hits['StatNb'].values<3) & ((all_hits['ViewNb'].values==0) + (all_hits['ViewNb'].values==3)) &\
(all_hits['PlaneNb'].values==0) & (all_hits['LayerNb'].values==0)]['ytop'].values
dots1 = all_hits[(all_hits['StatNb'].values<3) & ((all_hits['ViewNb'].values==0) + (all_hits['ViewNb'].values==3)) &\
(all_hits['PlaneNb'].values==1) & (all_hits['LayerNb'].values==0)]['ytop'].values
min_dist = np.hstack([np.diff(np.unique(np.hstack([dots0, dots1])))]).min()
print('YOffsetPlane: ', np.round(min_dist, 3))
return
def run_track_pattern_recognition(input_file, geo_file, dy, reconstructiblerequired, threeprong):
############################################# Load SHiP geometry ###################################################
# Check geo file
try:
fgeo = ROOT.TFile(geo_file)
except:
print "An error with opening the ship geo file."
raise
sGeo = fgeo.FAIRGeom
# Prepare ShipGeo dictionary
if not fgeo.FindKey('ShipGeo'):
if sGeo.GetVolume('EcalModule3') :
ecalGeoFile = "ecal_ellipse6x12m2.geo"
else:
ecalGeoFile = "ecal_ellipse5x10m2.geo"
if dy:
ShipGeo = ConfigRegistry.loadpy("$FAIRSHIP/geometry/geometry_config.py", Yheight = dy, EcalGeoFile = ecalGeoFile)
else:
ShipGeo = ConfigRegistry.loadpy("$FAIRSHIP/geometry/geometry_config.py", EcalGeoFile = ecalGeoFile)
else:
upkl = Unpickler(fgeo)
ShipGeo = upkl.load('ShipGeo')
############################################# Load SHiP modules ####################################################
run = ROOT.FairRunSim()
modules = shipDet_conf.configure(run,ShipGeo)
############################################# Load inpur data file #################################################
# Check input file
try:
fn = ROOT.TFile(input_file,'update')
except:
print "An error with opening the input data file."
raise
sTree = fn.cbmsim
############################## Initialize SHiP Spectrometer Tracker geometry #######################################
zlayer, \
zlayerv2, \
z34layer, \
z34layerv2, \
TStation1StartZ, \
TStation4EndZ, \
VetoStationZ, \
VetoStationEndZ = initialize(fgeo, ShipGeo)
########################################## Start Track Pattern Recognition #########################################
# Init book of hists for the quality measurements
h = init_book_hist()
# Start event loop
nEvents = sTree.GetEntries()
for iEvent in range(nEvents):
if iEvent%10 == 0:
print 'Event ', iEvent
########################################### Select one event ###################################################
rc = sTree.GetEvent(iEvent)
########################################### Smear hits #########################################################
smeared_hits = smearHits(sTree, ShipGeo, modules, no_amb=None)
if len(smeared_hits) == 0:
continue
########################################### Do track pattern recognition #######################################
reco_tracks, theTracks = execute(smeared_hits, sTree, ShipGeo)
########################################### Get MC truth #######################################################
y = get_track_ids(sTree, smeared_hits)
fittedtrackids, fittedtrackfrac = get_fitted_trackids(y, reco_tracks)
reco_mc_tracks = getReconstructibleTracks(iEvent,
sTree,
sGeo,
reconstructiblerequired,
threeprong,
TStation1StartZ,
TStation4EndZ,
VetoStationZ,
VetoStationEndZ) # TODO:!!!
########################################### Measure quality metrics ############################################
quality_metrics(smeared_hits, sTree, reco_mc_tracks, reco_tracks, h)
############################################### Save results #######################################################
save_hists(h, 'hists.root')
return
