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validate_lfv_triggers.py
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validate_lfv_triggers.py
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#!/bin/env python
# Example script to validate LFV topo triggers
#
# Example input file:
# /afs/cern.ch/user/g/gerbaudo/public/tmp/for_marco/user.olya.11640704._000003.tmptrig.root
#
# davide.gerbaudo@gmail.com
# Jul 2017
import itertools
import optparse
import re
import os
import inspect
import string
import sys
from collections import defaultdict
from pprint import pprint
from math import pi, sqrt
cmd_subfolder = os.path.realpath(os.path.abspath(os.path.join(os.path.split(inspect.getfile( inspect.currentframe() ))[0],"../L1TopoValidation/L1TopoCheck/python/")))
if cmd_subfolder not in sys.path:
sys.path.insert(0, cmd_subfolder)
import ROOT as R
R.PyConfig.IgnoreCommandLineOptions = True # don't let root steal your cmd-line options
R.gROOT.SetBatch(1) # go batch!
R.gErrorIgnoreLevel = 9999 # suppress messages about missing dict
# (can't get rid of the 'duplicate' ones?)
R.gROOT.ProcessLine('#include "L1TopoCheck/TriggerBits.h"')
R.gROOT.ProcessLine('#include "L1TopoCheck/AlgorithmBits.h"')
R.gROOT.Macro('$ROOTCOREDIR/scripts/load_packages.C')
EmTob = R.L1Topo.offline.EmTOB
JetTob = R.L1Topo.offline.JetTOB
# MuonTob = R.MuonTOB
# MuonTob = R.L1Topo.EnhancedMuonTOB
MuonTob = R.L1Topo.MuonTOB
TauTob = R.L1Topo.offline.TauTOB
import utils
def main():
difference_dphi = 0 #CHANGE
totat_dphi = 0
usage = ("Usage : %prog [options] filename"
"\n Examples :"
"\n %prog -v tmptrig.root"
)
parser = optparse.OptionParser(usage = usage)
parser.add_option('-n', '--num-events', default=None, type=int, help='number of events to process (default all)')
parser.add_option('-s', '--skip-events', default=None, type=int, help='number of events to skip (default none)')
parser.add_option('-v', '--verbose', default=False, action='store_true')
parser.add_option('-d', '--debug', default=False, action='store_true')
parser.add_option('-t', '--treename', default='trig')
(options, args) = parser.parse_args()
if len(args) != 1:
parser.error("incorrect number of arguments")
verbose = options.verbose
debug = options.debug
if verbose:
utils.print_running_conditions(parser, options)
input_filenames = utils.read_filename_arguments(args[0], options)
if verbose:
print 'Input files:'
print '\n'.join(input_filenames)
chain = R.TChain(options.treename)
for input_filename in input_filenames:
chain.Add(input_filename) #chain beomes an array with the various files .root introduced
num_available = chain.GetEntries()
num_skip = options.skip_events
num_toprocess = number_of_entries_to_process(num_available, options)
if verbose:
print "About to process %s (out of %d) entries: " % (num_toprocess, num_available)
# # test: print all branches available in the tree
# print 'chain ',chain
# print 'branches:'
# print 'list of branches ',chain.GetListOfBranches()
# print '\n'.join([k.GetName() for k in chain.GetListOfBranches()])
# print
# return
iEntry = 0
possible_outcomes = ['pass_em_pass_hw', 'pass_em_fail_hw', 'fail_em_pass_hw', 'fail_em_fail_hw']
algo_counters = defaultdict(int)
item_counters = defaultdict(int)
valid_counters = {k:0 for k in ['overflow'] + possible_outcomes}
histos = {}
histos2= {}
lvl1item_name = 'L1_LFV-MU6'
algorithm_name = '0DR15-2MU6ab'
l = lvl1item_name
num_binning = (9 , -0.5, 8.5)
dr_binning = (30 , 0 , 6)
binning_0dr15 = (15 , 0.0 , 1.5)
pt_binning = (8, 3500.0 , 11500.0)
angle_binning = (28, -3.5, 3.5)
for k in possible_outcomes: #initialize the histograms, they will still be empty after
histos[k] = {
'n_mu' : R.TH1F('n_mu'+'_'+k , l+'; N input l1mus' , *num_binning),
'n_mu6ab' : R.TH1F('n_mu6ab'+'_'+k , l+'; N mu6 muons' , *num_binning),
'n_pairs_mu6_0dr15' : R.TH1F('n_pairs_mu6_0dr15'+'_'+k , l+'; N mu6_0dr15 pairs' , *num_binning),
'n_pairs_0dr15' : R.TH1F('n_pairs_0dr15'+'_'+k , l+'; N 0dr15 pairs' , *num_binning),
'n_pairs_mu6ab' : R.TH1F('n_pairs_mu6ab'+'_'+k , l+'; N mu6 pairs' , *num_binning),
'n_cand_pairs' : R.TH1F('n_cand_pairs'+'_'+k , l+'; N candidate pairs' , *num_binning),
'dr_min' : R.TH1F('dr_min'+'_'+k , l+'; min #DeltaR best candidate pair' , *dr_binning),
'dr_0dr15' : R.TH1F('dr_0dr15'+'_'+k , l+'; #DeltaR 0dr15 pairs' , *binning_0dr15),
'dr_mu6_min' : R.TH1F('dr_mu6_min'+'_'+k , l+'; min #DeltaR best mu6 pair' , *dr_binning),
'dr_mu6' : R.TH1F('dr_mu6'+'_'+k , l+'; #DeltaR mu6 pairs' , *dr_binning),
'dr_mu6_0dr15' : R.TH1F('dr_mu6_0dr15'+'_'+k , l+'; #DeltaR mu6_0dr15' , *binning_0dr15),
'dr_any' : R.TH1F('dr_any'+'_'+k , l+'; #DeltaR any candidate pair' , *dr_binning),
'Phi_any' : R.TH1F('Phi_any'+'_'+k , l+'; Phi angle any muon' , *angle_binning),
'Phi_mu6' : R.TH1F('Phi_mu6'+'_'+k , l+'; Phi angle any mu6 muon' , *angle_binning),
'Eta_any' : R.TH1F('Eta_any'+'_'+k , l+'; Eta angle any muon' , *angle_binning),
'Eta_mu6' : R.TH1F('Eta_mu6'+'_'+k , l+'; Eta angle any mu6 muon' , *angle_binning),
'pt_0dr15' : R.TH1F('pt_0dr15'+'_'+k , l+'; #Pt 0dr15 muons' , *pt_binning),
'pt_any' : R.TH1F('pt_any'+'_'+k , l+'; #Pt any muon' , *pt_binning),
}
histos2[k] = R.TH2F('PhiEta_mu6'+'_'+k , l+'; Phi angle any mu6; Eta angle any mu6' , *2*angle_binning)
histo_names = [name for name, histo in histos[possible_outcomes[0]].items()]
for iEvent, event in enumerate(chain):
if num_skip and iEvent<num_skip: continue
if iEntry > num_toprocess: break
# see how branches are created in TopoNtuple.py
item_bits = item_tbits2bits(getattr(event,
lvl1item_name.replace('-','_')+'_iBits'))
increment_counters(item_counters, item_bits)
# # These are not filled, so don't bother for now # DG-2016-06-23
algo_bits = algo_tbits2bits(getattr(event, algorithm_name.replace('-','_')+'_0_aBits'))
increment_counters(algo_counters, algo_bits)
pass_hw = item_bits['TDT_TBP']
pass_sim = item_bits['L1SIMULATED']
overflown = algo_bits['OVERFLOWN']
if overflown:
valid_counters['overflow'] += 1
continue
# emTobs = [EmTob(w) for w in event.emTobs]
# jetTobs = [JetTob(w) for w in event.jetTobs]
# tauTobs = [TauTob(w) for w in event.tauTobs]
# if debug:
# print 'emTobs[%d]' % len(emTobs)
# for i, et in enumerate(emTobs):
# print "[%d] (%f, %f)"%(i, et.eta(), et.phi())
# print 'jetTobs[%d]' % len(jetTobs)
# for i, jt in enumerate(jetTobs):
# print "[%d] (%f, %f)"%(i, jt.eta(), jt.phi())
# print 'tauTobs[%d]' % len(tauTobs)
# for i, tt in enumerate(tauTobs):
# print "[%d] (%f, %f)"%(i, tt.eta(), tt.phi())
# these are EnhancedMuonTOB objects
# muons = [Muon(tob.pt, tob.eta, tob.phi) for tob in event.emuMuonTOB
# if tob.bcn==0] # only pick the ones from bunch crossing number 0
muons = [Muon(tob.pt, tob.eta, tob.phi) for tob in event.hdwMuonTOB
if tob.bcn==0] # only pick the ones from bunch crossing number 0
# muons = remove_equal_muons(muons)
list_mu6ab = algo_MU6ab(muons) #mu6 list
# if pass_sim!=pass_hw:
# continue
# Phi3 = algo_PHI3(muons)
# if not Phi3:
# continue
list_0dr15_pairs, list_pairs, list_0dr15= algo_0DR15(muons, muonList=True) #0dr15 couplelist
#aux = [muon for muon, Pt in list_mu6ab]
# list_mu6_0dr15_pairs, list_mu6_pairs = algo_0DR15([muon for muon in list_mu6ab], printout = pass_hw) #mu6_0dr15 couplelist
list_mu6_0dr15_pairs, list_mu6_pairs = algo_0DR15(list_mu6ab) #mu6_0dr15 couplelist
list_0dr15_mu6 = algo_MU6ab_pairs(list_0dr15_pairs)
pass_emul = len(list_mu6_0dr15_pairs) #returns true if 2mu6ab and 0dr15
#pass_emul = pass_sim
#pass_emul = len(list_0dr15_mu6) or len(list_mu6_0dr15_pairs)
#pass_emul = len(list_0dr15_mu6)
outcome = ('pass_em_pass_hw' if pass_hw and pass_emul else
'pass_em_fail_hw' if pass_emul else
'fail_em_pass_hw' if pass_hw else
'fail_em_fail_hw')
valid_counters[outcome] += 1
fill_histos(histos[outcome], histos2[outcome], muons, list_mu6ab, list_0dr15,
list_0dr15_pairs, list_pairs, list_mu6_0dr15_pairs, list_mu6_pairs) #fill histograms
# if outcome == 'pass_em_fail_hw':
# if outcome == 'fail_em_pass_hw':
# if len(list_mu6_pairs):
if False:
# mu1 = list_mu6_pairs[0].muon1.p4
# mu2 = list_mu6_pairs[0].muon2.p4
# print ("runNumber = {0:d} eventNumber = {1:d}".format(event.runNumber, event.eventNumber))
# print("muon1: Pt = {0:.2f}\t\tPhi = {1:.0f} \tEta = {2:.0f}".format(mu1.Pt()/1000, mu1.Phi()*10, mu1.Eta()*10))
# print("muon2: Pt = {0:.2f}\t\tPhi = {1:.0f} \tEta = {2:.0f}\n".format(mu2.Pt()/1000, mu2.Phi()*10, mu2.Eta()*10))
for muon in muons:
mu = muon.p4
print("Pt = {0:.0f}\t\tPhi = {1:.0f} \tEta = {2:.0f}".format(mu.Pt()/1000., mu.Phi()*10, mu.Eta()*10))
print("")
# if outcome == 'fail_em_pass_hw':
# if True:
if False:
# print ("runNumber = {0:d} eventNumber = {1:d}".format(event.runNumber, event.eventNumber))
# print("emuMuonTOB")
# for i, mu in enumerate(list(set(event.emuMuonTOB))):
# print("<{:d}>: Pt = {:.2f} Phi = {:.2f} Eta = {:.2f}".format(i, mu.pt, mu.phi, mu.eta))
for i, mu in enumerate(event.l1muon):
print("Pt = {:.0f}\t\tPhi = {:.2f} \tEta = {:.2f} \tisVetoed = {:}".format(mu.p4.Pt()/1000., mu.p4.Phi()*10, mu.p4.Eta()*10, mu.isVetoed))
# print("hdwMuonTOB")
# for i, mu in enumerate(list(set(event.hdwMuonTOB))):
# print("<{:d}>: Pt = {:.2f} Phi = {:.2f} Eta = {:.2f}".format(i, mu.pt, mu.phi, mu.eta))
print("")
if debug and pass_hw:
print "passed, %d muons" % len(muons)
iEntry += 1
print 'algo_counters:'
pprint(dict(algo_counters))
print 'item_counters:'
pprint(dict(item_counters))
print 'valid counters:'
pprint(dict(valid_counters))
if True:
#print errors
p_p=valid_counters['pass_em_pass_hw']
p_f=valid_counters['pass_em_fail_hw']
f_p=valid_counters['fail_em_pass_hw']
f_f=valid_counters['fail_em_fail_hw']
total_imputs = p_p+p_f+f_p+f_f
total_pass_em = p_p+p_f
total_pass_hw = f_p+p_p
total_discordance = 100.*(f_p+p_f)/total_imputs
pass_em_discordance = 100.*p_f/total_pass_em
pass_hw_discordance = 100.*f_p/total_pass_hw
print(' total error {:.2f}%'.format(total_discordance))
print(' em pass error {:.2f}%'.format(pass_em_discordance))
print(' hw pass error {:.2f}%'.format(pass_hw_discordance))
# print('Difference Dphi = {:.2f}%'.format(100.*difference_dphi/totat_dphi))
c = R.TCanvas('c')
order = [2,4,3,1] #is used to reorganize the histograms so that the firs line corresponds to pass emu and the first column to pass hdw
for name in histo_names:
i = 0
c.Clear()
c.Divide(2,2)
for outcome, hs in histos.items():
h = histos[outcome][name]
c.cd(order[i])
h.Draw('h text')
c.Update()
i+=1
if verbose:
print('\n')
h.Print("all")
print("- Mean = %.3f +- %.3f"%(h.GetMean(),h.GetMeanError()))
print("- Std Dev = %.3f +- %.3f"%(h.GetStdDev(), h.GetStdDevError()))
print("- Skewness = %.3f"%(h.GetSkewness()))
print("- Kurtosis = %.3f"%(h.GetKurtosis()))
if verbose:
print('\n\n')
c.SaveAs(name+'.png')
c.SaveAs(name+'.root')
i=0
c.Clear()
c.Divide(2,2)
for outcome, h in histos2.items():
c.cd(order[i])
h.Draw('Colz')
c.Update()
i+=1
if verbose:
h.Print("all")
if verbose:
print('\n')
c.SaveAs('PhiEta_mu6.png')
c.SaveAs('PhiEta_mu6.root')
def algo_MU6ab_pairs(list_0dr15_pairs):
list_0dr15_mu6 = []
for pair in list_0dr15_pairs:
if pair.muon1.p4.Pt()>5000 and pair.muon2.p4.Pt()>5000:
list_0dr15_mu6.append(pair)
return list_0dr15_mu6
#def algo_0DR15(muons, muonList=False, printout = False): #retuns ordered list with any couple of muons satisfying 0DR15
def algo_0DR15(muons, muonList=False, pass_hw = False, pass_sim = False): #retuns ordered list with any couple of muons satisfying 0DR15
couples_any = []
n_mu = len(muons)
for i in range(n_mu-1): #check all muon couples to see if Delta r is lower than 1.5
for j in range(i+1,n_mu):
pair = MuonPair(muons[i],muons[j])
couples_any.append(pair)
couples_any.sort(key = lambda couple: couple.dr) #sort list
# couples_0dr15 = [couple for couple in couples_any if (not couple.isPhi3 and couple.dr<1.505) or (couple.isPhi3 and (couple.dr<1.505 or (couple.dr>2.75 and couple.dr<3.2)))] #take only 0dr15, different algorithm for Phi>3
couples_0dr15 = [couple for couple in couples_any if couple.dr<=1.5] #take only 0dr15
# couples_0dr15 = [couple for couple in couples_any if couple.dr<=1.5 or couple.dr1<=1.5] #take only 0dr15
# couples_0dr15 = [couple for couple in couples_any if ((couple.muon1.p4.Pt()<=7 and couple.muon2.p4.Pt()<=7) and couple.dr1<=1.5) or ((couple.muon1.p4.Pt()>7 or couple.muon2.p4.Pt()>7) and couple.dr<=1.5)] #take only 0dr15 and something else
# couples_0dr15 = [couple for couple in couples_any if couple.dr2<=2.25] #take only 0dr15 and something else
# if False:
# if not len(couples_0dr15) and (printout and False):
if pass_hw == pass_sim and (pass_sim != len(couples_0dr15) and False):#not muonList):
for couple in couples_any:
#print some data to check
mu1 = couple.muon1.p4
mu2 = couple.muon2.p4
dr = couple.dr
dr2= couple.dr2
DPhi = mu1.DeltaPhi(mu2)
print("muon1: Pt = {0:.2f} Phi = {1:.2f} Eta = {2:.2f}".format(mu1.Pt(), mu1.Phi(), mu1.Eta()))
print("muon2: Pt = {0:.2f} Phi = {1:.2f} Eta = {2:.2f}".format(mu2.Pt(), mu2.Phi(), mu2.Eta()))
print("Dr = {0:.2f} Dr2 = {1:.3f} DPhi = {2:.2f}".format(dr, dr2, DPhi))
# DPhiBad = (couple[0].p4.Phi()-couple[1].p4.Phi())%(2*pi)
# print("DPhibad = {:.2f}\n\n".format(DPhiBad))
print('pass_hw = {0:d} pass_sim = {1:d} pass_em = {2:d}'.format(pass_hw,pass_sim,len(couples_0dr15)))
print("#events {:d}".format(len(couples_any)))
print("--------------")
if muonList: #return a list of the muons that belong to at least one couple of couples_0dr15
list_0dr15 = []
for couple in couples_any:
if couple.muon1 in list_0dr15:
pass
else:
list_0dr15.append(couple.muon1)
if couple.muon2 in list_0dr15:
pass
else:
list_0dr15.append(couple.muon2)
return (couples_0dr15, couples_any, list_0dr15)
return (couples_0dr15, couples_any)
def algo_PHI3(muons): #returns 1 if there is a muon satisfying PHI3 0 otherwise
for muon in muons:
if muon.p4.Phi()>3:
return 1
return 0
def algo_MU6ab(muons): #returns list with all muons satifying MU6 sorted by energy
mu6ab_list = []
for muon in muons:
pt = muon.p4.Pt()
#some error when doing >=6000 instead of >5999 I think it is due to rounding errors changed to >5000
#no difference noticed between >5999 and >5000. condition >5000 is the same as in official simulation.
if pt>5000:
muon
mu6ab_list.append(muon)
mu6ab_list.sort(key = lambda mu6ab: mu6ab.p4.Pt()) #sort list
return mu6ab_list
def fill_histos(histos, histos2, muons, list_mu6ab, list_0dr15, list_0dr15_pairs,
list_pairs, list_mu6_0dr15_pairs, list_mu6_pairs): #fills histograms
n_mu = len(muons)
n_mu6= len(list_mu6ab)
n_0dr15_pairs = len(list_0dr15_pairs)
n_mu6_pairs = len(list_mu6_pairs)
n_mu6_0dr15_pairs = len(list_mu6_0dr15_pairs)
n_pairs = len(list_pairs)
n_0dr15 = len (list_0dr15)
histos['n_mu' ].Fill(n_mu)
histos['n_mu6ab' ].Fill(n_mu6)
histos['n_pairs_mu6_0dr15'].Fill(n_mu6_0dr15_pairs) #number of mu6_0dr15 pairs
# same number obtained here than using the formula n*(n-1)/2
histos['n_pairs_0dr15' ].Fill(n_0dr15_pairs) #number of 0dr15 pairs
histos['n_pairs_mu6ab' ].Fill(n_mu6_pairs) #number of mu6 pairs
histos['n_cand_pairs' ].Fill(n_pairs) #number of candidate pairs
if n_0dr15_pairs: #fill histograms of dr
for pair in list_0dr15_pairs:
histos['dr_0dr15'].Fill(pair.dr)
if n_mu6_0dr15_pairs:
for pair in list_mu6_0dr15_pairs:
histos['dr_mu6_0dr15'].Fill(pair.dr)
if n_mu6_pairs:
histos['dr_mu6_min'].Fill(list_mu6_pairs[0].dr)
for pair in list_mu6_pairs:
histos['dr_mu6'].Fill(pair.dr)
if n_pairs:
histos['dr_min'].Fill(list_pairs[0].dr) #takes the lower dr possible
for pair in list_pairs:
histos['dr_any'].Fill(pair.dr)
for muon in muons: #fill histogram of momentums
histos['pt_any'].Fill(muon.p4.Pt())
histos['Phi_any'].Fill(muon.p4.Phi())
histos['Eta_any'].Fill(muon.p4.Eta())
for muon in list_0dr15: #fill histogram of momentums
histos['pt_0dr15'].Fill(muon.p4.Pt())
for muon in list_mu6ab: #fill histograms of angles
Phi = muon.p4.Phi()
Eta = muon.p4.Eta()
histos['Phi_mu6'].Fill(Phi)
histos['Eta_mu6'].Fill(Eta)
histos2.Fill(Phi, Eta)
class Muon(object):
def __init__(self, pt, eta, phi):
muon_mass = 105.65
#tlv = R.TLorentzVector() # four-momentum
#self.p4 = tlv.SetPtEtaPhiE(pt, eta, phi, energy)
self.p4 = R.TLorentzVector() # four-momentum
self.p4.SetPtEtaPhiM(pt, eta, phi, muon_mass)
class MuonPair(object):
def __init__(self, muon1, muon2):
# pi = 3.141592653
# tau = 2*pi
self.muon1 = muon1
self.muon2 = muon2
# Phi1 = muon1.p4.Phi()
# Phi2 = muon2.p4.Phi()
# if Phi1>3.09:
# Phi1=0
# Phi2 = muon2.p4.Phi()
# if Phi2>3.09:
# Phi2=0
# DPhi = min((Phi1-Phi2)%tau, (Phi1-Phi2+tau/2)%tau)
# DPhi = abs(Phi1-Phi2)
# if DPhi>pi:
# DPhi=2*pi-DPhi
# Eta1 = muon1.p4.Eta()
# Eta2 = muon2.p4.Eta()
# DEta = (Eta1-Eta2)
# self.dr2=DEta**2+DPhi**2
# self.dr = sqrt(self.dr2)
# self.dr1 = muon1.p4.DeltaR(muon2.p4)
self.dr = muon1.p4.DeltaR(muon2.p4)
self.isPhi3 = muon1.p4.Phi()>3 or muon2.p4.Phi()>3 #true if the Phi value of any of the muons is greater than 3.
def remove_equal_muons(muons): #remove repeated muons of a list
ZERO = 0.1
i = 0
# muons = [muon for muon in muonscopy]
while i<(len(muons)-1):
j = i+1
while j<len(muons):
if (abs(muons[i].p4.Pt()-muons[j].p4.Pt())/1000.+abs(muons[i].p4.Eta()-muons[j].p4.Eta())*10+abs(muons[i].p4.Phi()-muons[j].p4.Phi())*10)<ZERO:
muons.pop(j)
j-=1
j+=1
i+=1
return muons
def algo_bit_names_and_numbers():
"Bits stored in the TBits for each L1 algorithm"
return (('FIRED' , R.L1Topo.FIRED ),
('OVERFLOWN' , R.L1Topo.OVERFLOWN ),
('TOB_EMULATED' , R.L1Topo.TOB_EMULATED),
('ROI_EMULATED' , R.L1Topo.ROI_EMULATED),
('CTP_TIP' , R.L1Topo.CTP_TIP ),
('TOPOSIM' , R.L1Topo.TOPOSIM ))
def item_bit_names_and_numbers():
"Bits stored in the TBits for each L1 item"
return (('TDT_TBP' , R.L1Topo.TDT_TBP ),
('TDT_TAP' , R.L1Topo.TDT_TAP ),
('TDT_TAV' , R.L1Topo.TDT_TAV ),
('L1EMULATED' , R.L1Topo.L1EMULATED ),
('L1SIMULATED', R.L1Topo.L1SIMULATED),
('CTP_TBP' , R.L1Topo.CTP_TBP ))
def algo_tbits2bits(bits=None):
"convert TBits to dict"
return dict((k, bits.TestBitNumber(b)) for k, b in algo_bit_names_and_numbers())
def item_tbits2bits(bits=None):
"convert TBits to dict"
return dict((k, bits.TestBitNumber(b)) for k, b in item_bit_names_and_numbers())
def increment_counters(counters={}, bits={}):
for k, b in bits.items():
counters[k] += 1 if b else 0
def number_of_entries_to_process(available_entries, options=None):
N = available_entries
n = options.num_events
s = options.skip_events
to_process = (min([N, n, N-s]) if n and s else
min([N, n]) if n else
N-s if s else
N)
to_process = to_process if to_process > 0 else 0
return to_process
if __name__=='__main__':
main()