#set seed cuts

seed_filter = gTowers.SeedFilter(ETthresh = seed_ETthresh, numSeeds = 1)

leading_trigger_jets = []

#column names to pull from the file, must be in this order to sync with the predefined classes in atlas_jets package

offline_column_names = ['jet_AntiKt10LCTopo_%s' % col for col in ['E', 'pt', 'm', 'eta', 'phi']]

gTower_column_names = ['gTower%s' % col for col in ['E', 'NCells', 'EtaMin', 'EtaMax', 'PhiMin', 'PhiMax']]

#bins for all histograms

num_offlineEvents = 0

# main loop that goes over the file

for event_num in range(total_num_events):

if event_num % 100 == 0:

print "doing event_num=%d for (%d, %d, %d)" % (event_num, offline_jetpT_threshold, gTower_jetET_threshold, seed_ETthresh)

# pull in data row by row

data = rnp.root2rec(filename, treename='%s/%s' % (directory,tree), branches=offline_column_names + gTower_column_names, start=(event_num), stop=(event_num+1))

oEvent = OfflineJets.Event(event=[data[col][0] for col in offline_column_names])

# if there are no offline jets, we skip it

if len(oEvent.jets) == 0 or oEvent.jets[0].pT < offline_jetpT_threshold:

continue

num_offlineEvents += 1

'''can use seed_filter on an event by event basis'''

# max number of seeds based on number of offline jets

#seed_filter = gTowers.SeedFilter(numSeeds = len(oEvent.jets))

tEvent = gTowers.TowerEvent(event=[data[col][0] for col in gTower_column_names], seed_filter = seed_filter)

tEvent.get_event()

leading_trigger_jets = leading_trigger_jets + tEvent.event.jets

'''at this point, we've processed all the data and we just need to make plots'''

bins_leading_trigger_jets = np.arange(0.,4000.,5.)

hist_leading_trigger_jets = np.histogram([jet.E/np.cosh(jet.eta) for jet in leading_trigger_jets], bins=bins_leading_trigger_jets)[0]

# first get the widths of the bins when we make the plots

width_leading_trigger_jets = np.array([x - bins_leading_trigger_jets[i-1] for i,x in enumerate(bins_leading_trigger_jets)][1:])

filename_ending = 'offline%d_gTower%d_seed%d_unweighted' % (offline_jetpT_threshold, gTower_jetET_threshold, seed_filter.ETthresh)

#make figures

'''Leading Trigger Jets Histogram'''

pl.figure()

pl.xlabel('$E_T^{\mathrm{jet}}$ [GeV]')

pl.ylabel('Number of leading trigger jets')

pl.title('$p_T^{\mathrm{offline jet}}$ > %d GeV, %d events, $E_T^{\mathrm{tower jet}}$ > %d GeV, $E_T^{\mathrm{seed}}$ > %d GeV' % (offline_jetpT_threshold, num_offlineEvents, gTower_jetET_threshold, seed_filter.ETthresh))

pl.bar(bins_leading_trigger_jets[:-1], hist_leading_trigger_jets, width=width_leading_trigger_jets)

pl_lJet = {'bins': bins_leading_trigger_jets,\

'values': hist_leading_trigger_jets,\

'width': width_leading_trigger_jets}

pickle.dump(pl_lJet, file('events_histogram_leading_trigger_jets_%s.pkl' % filename_ending, 'w+') )

pl.savefig('events_histogram_leading_trigger_jets_%s.png' % filename_ending)

def __init__(self, offline_jetpT_threshold, gTower_jetET_threshold):

self.offline_jetpT_threshold = offline_jetpT_threshold

self.gTower_jetET_threshold = gTower_jetET_threshold

def __call__(self, seed_ETthresh):