-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathtri_ZHLep_analysis.py
488 lines (406 loc) · 21.9 KB
/
tri_ZHLep_analysis.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
#!/usr/bin/env python
# Author: Jonathon Langford
# Imperial College London
# CMS, Hgg IC group
# Description: To perform trilinear analysis on ZHLeptonic tagged events
# Use reco information to tag events with diphoton, dilepton consistent with ZH kinematics
# > The lepton selection is lacking: 2nd bullet point in PAS for ttHLeptonic Category, discuss with Nick how to implement this
# This incluse: Loose requirements on electron and tight on Muon
# Output pT(H) and m_ZH distribution: reco and gen-level
# > Compatible with extract C1 values using event re-weighting
# m_gg distribution in each bin of kinematic distribution
# To be run on generated MC samples: signal + background (expect background to be very small)
# UPDATE: Now use gen-level Higgs (instead of diphoton pair as Delphes card does not extract genPhotons)
###############################################################################
# PRELIMINARIES
#Import Libraries
import sys
import ROOT
import math
from array import array
#Check for correct input
if len(sys.argv) != 3:
print " Usage: Example1.py input_file input_file_rwgt output_file"
sys.exit(1)
#Load delphes ROOT libraries
ROOT.gSystem.Load("libDelphes")
#Including packages to read TTree
try:
ROOT.gInterpreter.Declare('#include "classes/DelphesClasses.h"')
ROOT.gInterpreter.Declare('#include "external/ExRootAnalysis/ExRootTreeReader.h"')
except:
pass
#Take input file from command line
inputFile = sys.argv[1]
inputFile_rwgt = sys.argv[2]
# Create chain of root trees
chain = ROOT.TChain("Delphes")
chain_rwgt = ROOT.TChain("Delphes")
chain.Add(inputFile)
chain_rwgt.Add(inputFile_rwgt)
# Create objects of class ExRootTreeReader
treeReader = ROOT.ExRootTreeReader(chain)
treeReader_rwgt = ROOT.ExRootTreeReader(chain_rwgt)
numberOfEntries = treeReader.GetEntries()
#numberOfEntries = 10000
# Get pointers to branches used in this analysis
branchEvent = treeReader.UseBranch("Event")
branchEvent_rwgt = treeReader_rwgt.UseBranch("Event")
branchGenParticle = treeReader.UseBranch("Particle")
branchPhoton = treeReader.UseBranch("Photon")
branchElectron = treeReader.UseBranch("Electron")
branchMuon = treeReader.UseBranch("Muon")
##############################################################################
# CONFIGURE OUTPUT
#Open .root file to write histograms to
f = ROOT.TFile.Open( "output_ZHLep_1e5.root" ,"RECREATE")
# Book histograms
#pT_H
#Gen-level
hist_pTH_gen_LO = ROOT.TH1F("h_pTH_gen_LO", "LO Diphoton p_{T} (gen level)", 30, 0, 300 )
hist_pTH_gen_O3 = ROOT.TH1F("h_pTH_gen_O3", "O3 Diphoton p_{T} (gen level) (rwgt)", 30, 0, 300 )
hist_pTH_gen_LO_lb = ROOT.TH1F("h_pTH_gen_LO_lb", "LO Diphoton p_{T} (gen-level)", 6, 0, 300 )
hist_pTH_gen_O3_lb = ROOT.TH1F("h_pTH_gen_O3_lb", "O3 Diphoton p_{T} (gen-level) (rwgt)", 6, 0, 300 )
#Reco-level
hist_pTH_reco_LO = ROOT.TH1F("h_pTH_reco_LO", "LO Diphoton p_{T} (reco level)", 30, 0, 300 )
hist_pTH_reco_O3 = ROOT.TH1F("h_pTH_reco_O3", "O3 Diphoton p_{T} (reco level) (rwgt)", 30, 0, 300 )
hist_pTH_reco_LO_lb = ROOT.TH1F("h_pTH_reco_LO_lb", "LO Diphoton p_{T} (reco-level)", 6, 0, 300 )
hist_pTH_reco_O3_lb = ROOT.TH1F("h_pTH_reco_O3_lb", "O3 Diphoton p_{T} (reco-level) (rwgt)", 6, 0, 300 )
#m_llgg
#Gen-level
hist_mZH_gen_LO = ROOT.TH1F("h_mZH_gen_LO", "LO m_{ZH} (gen level)", 30, 200, 500 )
hist_mZH_gen_O3 = ROOT.TH1F("h_mZH_gen_O3", "O3 m_{ZH} (gen level) (rwgt)", 30, 200, 500 )
hist_mZH_gen_LO_lb = ROOT.TH1F("h_mZH_gen_LO_lb", "LO m_{ZH} (gen-level)", 6, 200, 500 )
hist_mZH_gen_O3_lb = ROOT.TH1F("h_mZH_gen_O3_lb", "O3 m_{ZH} (gen-level) (rwgt)", 6, 200, 500 )
#Reco-level
hist_mZH_reco_LO = ROOT.TH1F("h_mZH_reco_LO", "LO m_{ZH} (reco level)", 30, 200, 500 )
hist_mZH_reco_O3 = ROOT.TH1F("h_mZH_reco_O3", "O3 m_{ZH} (reco level) (rwgt)", 30, 200, 500 )
hist_mZH_reco_LO_lb = ROOT.TH1F("h_mZH_reco_LO_lb", "LO m_{ZH} (reco-level)", 6, 200, 500 )
hist_mZH_reco_O3_lb = ROOT.TH1F("h_mZH_reco_O3_lb", "O3 m_{ZH} (reco-level) (rwgt)", 6, 200, 500 )
#m_gg
hist_mgg_reco = ROOT.TH1F("h_mgg_reco", "Diphoton invariant mass spectrum (reco level)", 30, 110, 140 )
hist_mgg_gen = ROOT.TH1F("h_mgg_gen", "Diphoton invariant mass spectrum (gen level)", 30, 110, 140 )
#m_ll
hist_mll_reco = ROOT.TH1F("h_mll_reco", "Dilepton invariant mass spectrum (reco level)", 50, 65, 115 )
hist_mll_gen = ROOT.TH1F("h_mll_gen", "Dilepton invariant mass spectrum (gen level)", 50, 65, 115 )
#m_gg: In bins of pTH
hist_mgg_reco_1 = ROOT.TH1F("h_mgg_reco_1", "m_{#gamma#gamma}^{reco} for p_{T}^{reco}(#gamma#gamma) #in [0,50] GeV", 30, 110, 140 )
hist_mgg_reco_2 = ROOT.TH1F("h_mgg_reco_2", "m_{#gamma#gamma}^{reco} for p_{T}^{reco}(#gamma#gamma) #in [50,100] GeV", 30, 110, 140 )
hist_mgg_reco_3 = ROOT.TH1F("h_mgg_reco_3", "m_{#gamma#gamma}^{reco} for p_{T}^{reco}(#gamma#gamma) #in [100,150] GeV", 30, 110, 140 )
hist_mgg_reco_4 = ROOT.TH1F("h_mgg_reco_4", "m_{#gamma#gamma}^{reco} for p_{T}^{reco}(#gamma#gamma) #in [150,200] GeV", 30, 110, 140 )
hist_mgg_reco_5 = ROOT.TH1F("h_mgg_reco_5", "m_{#gamma#gamma}^{reco} for p_{T}^{reco}(#gamma#gamma) #in [200,250] GeV", 30, 110, 140 )
hist_mgg_reco_6 = ROOT.TH1F("h_mgg_reco_6", "m_{#gamma#gamma}^{reco} for p_{T}^{reco}(#gamma#gamma) #in [250,350] GeV", 30, 110, 140 )
#Response matrix plots
hist_pTH_responseMatrix = ROOT.TH2F("h_pTH_responseMatrix","; p_{T}^{reco}(#gamma#gamma) GeV; p_{T}^{gen}(#gamma#gamma) GeV", 6, 0, 300, 6, 0, 300 )
hist_mZH_responseMatrix = ROOT.TH2F("h_mZH_responseMatrix","; m_{ZH}^{reco} GeV; m_{ZH}^{gen} GeV", 6, 200, 500, 6, 200, 500 )
###############################################################################
# FUNCTIONS FOR KINEMATICS
def deltaR( eta1, phi1, eta2, phi2 ):
return math.sqrt( (eta1-eta2)*(eta1-eta2) + (phi1-phi2)*(phi1-phi2) )
def pT_vector_calc( part1, part2 ):
Px1 = part1.PT*math.cos( part1.Phi )
Px2 = part2.PT*math.cos( part2.Phi )
Py1 = part1.PT*math.sin( part1.Phi )
Py2 = part2.PT*math.sin( part2.Phi )
return math.sqrt( (Px1+Px2)*(Px1+Px2) + (Py1+Py2)*(Py1+Py2) )
###############################################################################
# FUNCTIONS FOR EVENT SELECTION
def SelectPhoton( _photon, photonPtThreshold, photonEtaThresholds, phoIsoChRelThreshold ):
photon_pass = True
if( _photon.PT < photonPtThreshold ): photon_pass = False
#Eta: inc outside transition region between barrel and endcap
if( ( abs( _photon.Eta ) > photonEtaThresholds[2] ) | ( ( abs( _photon.Eta ) > photonEtaThresholds[0] ) & ( abs( _photon.Eta ) < photonEtaThresholds[1] ) ) ): photon_pass = False
#Isolation: currently only using Ich, need Ipho and Itrk
if( (_photon.SumPtCharged/_photon.PT) > phoIsoChRelThreshold ): photon_pass = False
#SHOWER SHAPE VARIABLES: R9, sigma_etaeta, need to access from Delphes in some way
return photon_pass
def SelectDiPhoton( _leadPhoton, _subleadPhoton, leadPhoPTOverMassThreshold, subleadPhoPTOverMassThreshold ):
diphoton_pass = True
q_gg = _leadPhoton.P4()+_subleadPhoton.P4()
m_gg = math.sqrt( q_gg*q_gg )
if( _leadPhoton.PT/m_gg < leadPhoPTOverMassThreshold ) | ( _subleadPhoton.PT/m_gg < subleadPhoPTOverMassThreshold ): diphoton_pass = False
#DIPHOTON MVA EQUIVALENT
return diphoton_pass
def SelectMuon( _muon, _dipho, muonPtThreshold, muonEtaThreshold, muPFIsoSumRelThreshold, deltaRMuonPhoThreshold ):
muon_pass = True
if( _muon.PT < muonPtThreshold ): muon_pass = False
if( abs( _muon.Eta ) > muonEtaThreshold ): muon_pass = False
#Vertex: missing, require vertex info in CMS card, copy isTightMuon() (see implementation on git)
#Isolation: using sumPt variable: assuming same as hard sum in flashgg::LeptonSelection.cc
if( (_muon.SumPt/_muon.PT) > muPFIsoSumRelThreshold ): muon_pass = False
#if muon passed then calc dR between leadPho and subleadPho
if muon_pass:
dR_Muon_LeadPho = deltaR( _dipho[0][0].Eta, _dipho[0][0].Phi, _muon.Eta, _muon.Phi )
dR_Muon_SubleadPho = deltaR( _dipho[0][1].Eta, _dipho[0][1].Phi, _muon.Eta, _muon.Phi )
if( dR_Muon_LeadPho < deltaRMuonPhoThreshold ) | ( dR_Muon_SubleadPho < deltaRMuonPhoThreshold ): muon_pass = False
return muon_pass
def SelectElectron( _electron, _dipho, electronPtThreshold , electronEtaThresholds, electronPhoMassThreshold , deltaRElectronPhoThreshold ):
electron_pass = True
if( _electron.PT < electronPtThreshold ): electron_pass = False
#Eta: inc outside transition region between barrel and endcap
if( ( abs( _electron.Eta ) > electronEtaThresholds[2] ) | ( ( abs( _electron.Eta ) > electronEtaThresholds[0] ) & ( abs( _electron.Eta ) < electronEtaThresholds[1] ) ) ): electron_pass = False
#Vertex: missing, require vertex info
#ID: flashgg::passLooseID()
#mass of electron+photon not close to Z mass: fasely recon electrons
if electron_pass:
m_eLeadPho = math.sqrt( abs((_dipho[0][0].P4()+_electron.P4())*(_dipho[0][0].P4()+_electron.P4())) )
m_eSubleadPho = math.sqrt( abs((_dipho[0][1].P4()+_electron.P4())*(_dipho[0][1].P4()+_electron.P4())) )
if( abs( m_eLeadPho-91.2 ) < 5. ) | ( abs( m_eSubleadPho-91.2 ) < 5. ): electron_pass = False
#if electron passed then calc dR between leadPho and subleadPho
if electron_pass:
dR_Electron_LeadPho = deltaR( _dipho[0][0].Eta, _dipho[0][0].Phi, _electron.Eta, _electron.Phi )
dR_Electron_SubleadPho = deltaR( _dipho[0][1].Eta, _dipho[0][1].Phi, _electron.Eta, _electron.Phi )
if( dR_Electron_LeadPho < deltaRElectronPhoThreshold ) | ( dR_Electron_SubleadPho < deltaRElectronPhoThreshold ): electron_pass = False
return electron_pass
###############################################################################
# COUNTERS FOR DEBUGGING
N_dipho = 0
N_diMuon = 0
N_diElectron = 0
N_selection = 0
N_Zll = 0
###############################################################################
# EVENTS LOOP
# Loop over all events
for entry in range(0, numberOfEntries ):
if entry % 10000 == 0: print "Processing event: (", entry, "/", numberOfEntries, ")"
#############################################################################
#Define boolean for event passing selection
event_pass = False
# Load selected branches with data from specified event
treeReader.ReadEntry(entry)
treeReader_rwgt.ReadEntry(entry)
#############################################################################
#Event branch: get event weight
_event = branchEvent.At(0)
LO_weight = _event.Weight
_event_rwgt = branchEvent_rwgt.At(0)
O3_weight = _event_rwgt.Weight
#############################################################################
#ZHLeptonicTag:
# > For now: Using gen-level photons. This needs to be changed to reco-level, how can I mimic diphotonMVA?
# > 2 same-flavour leptons at reco-level. Passing same selection requirements as in flashgg::ZHLeptonicTagDumper
# > Use selectMuons and selectElectrons function defined above
#list to hold photon and lepton candidates
photons = []
diphotons = []
photon_pair = []
muons = []
electrons = []
#booleans describing event passing different stages of selection
photon_selection = False
isDiMuon = False
isDiElectron = False
isZ = False
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#Photon Selection
if branchPhoton.GetEntries() > 0:
#Loop over photons in event and apply photon selection
for i in range( branchPhoton.GetEntries() ):
photon = branchPhoton.At(i)
#Apply selection on single photonsL Pt threshold currently relaxed to 20GeV
if( SelectPhoton( photon, photonPtThreshold=20., photonEtaThresholds=[1.4442,1.566,2.5], phoIsoChRelThreshold=0.3 ) ): photons.append( photon )
#if atleast 2 photons in event
if len( photons ) >= 2:
#sort photons according to pT (descending)
photons.sort( key=lambda g: g.PT, reverse=True )
#Loop over photon pairs in event and apply diphoton selection
for leadPho_idx in range( len( photons ) ):
for subleadPho_idx in range( len( photons ) ):
#Only once for each pair
if subleadPho_idx > leadPho_idx:
if( SelectDiPhoton( photons[leadPho_idx], photons[subleadPho_idx], leadPhoPTOverMassThreshold=0.375, subleadPhoPTOverMassThreshold=0.25) ): diphotons.append( [photons[leadPho_idx],photons[subleadPho_idx]] )
#If atleast one diphoton pair passing selection then set photon_selection to true
#if >1 diphoton passing selection: choose pair with highest sum pT
if( len( diphotons ) > 1 ):
pT_max = -999.
dipho_idx_opt = -999
for dipho_idx in range( len(diphotons) ):
pT_H = pT_vector_calc( diphotons[dipho_idx][0], diphotons[dipho_idx][1] )
if pT_H > pT_max:
pT_max = pT_H
dipho_idx_opt = dipho_idx
photon_pair.append( diphotons[ dipho_idx ] )
photon_selection = True
#else if = 1 then append photon_pair list
elif( len( diphotons ) == 1 ):
photon_pair.append( diphotons[0] )
photon_selection = True
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#Lepton Selection: to be performed if diphoton pair found
if( photon_selection ):
if branchMuon.GetEntries() > 0:
#loop over Muons in event and extract those which satisfy criteria
for i in range( branchMuon.GetEntries() ):
muon = branchMuon.At(i)
#Muon Selection
if( SelectMuon( muon, photon_pair, muonPtThreshold=20., muonEtaThreshold=2.4, muPFIsoSumRelThreshold=0.25, deltaRMuonPhoThreshold=0.5 ) ):
muons.append( muon )
if branchElectron.GetEntries() > 0:
#loop over Electrons in event and extract those which satisfy criteria
for i in range( branchElectron.GetEntries() ):
electron = branchElectron.At(i)
#Electron selection
if( SelectElectron( electron, photon_pair, electronPtThreshold=20., electronEtaThresholds=[1.4442,1.566,2.5], electronPhoMassThreshold=5., deltaRElectronPhoThreshold=1. ) ):
electrons.append( electron )
#check for size of vectors
if len(muons) >= 2: isDiMuon = True
if len(electrons) >= 2: isDiElectron = True
#Z mass window: invariant mass of lepton pair
if( isDiMuon ):
q_ll = muons[0].P4()+muons[1].P4()
m_ll = math.sqrt( q_ll*q_ll )
if( m_ll > 70 ) & ( m_ll < 110 ): isZ = True
if( isDiElectron ):
q_ll = electrons[0].P4()+electrons[1].P4()
m_ll = math.sqrt( q_ll*q_ll )
if( m_ll > 70 ) & ( m_ll < 110 ): isZ = True
##############################################################################
#Couters for debugging
if( photon_selection ):
N_dipho += 1
if( isDiMuon ): N_diMuon += 1
if( isDiElectron ): N_diElectron += 1
if( isDiMuon | isDiElectron ):
N_selection += 1
if( isZ ): N_Zll += 1
##############################################################################
# EVENTS PASSING SELECTION
if( photon_selection & ( isDiMuon | isDiElectron ) & isZ ):
#Define final photons and leptons
leadPhoton = photon_pair[0][0]
subleadPhoton = photon_pair[0][1]
if( isDiMuon ):
lep1 = muons[0]
lep2 = muons[1]
else:
lep1 = electrons[0]
lep2 = electrons[1]
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# GEN PARTICLE EXTRACTION
dR_genPartleadPho_min = 9999.
dR_genPartsubleadPho_min = 9999.
dR_genPartLep1_min = 9999.
dR_genPartLep2_min = 9999.
#initialise
genleadPho_idx = -999
gensubleadPho_idx = -999
genLep1_idx = -999
genLep2_idx = -999
if branchGenParticle.GetEntries() > 0:
#loop over GenParticles in event
for i in range( branchGenParticle.GetEntries() ):
genPart = branchGenParticle.At(i)
#Photon pair extraction: use PID and Status
if( genPart.PID == 22 ):
dR = deltaR( genPart.Eta, genPart.Phi, leadPhoton.Eta, leadPhoton.Phi ) # LeadPhoton
if( dR < dR_genPartleadPho_min ):
dR_genPartleadPho_min = dR
genleadPho_idx = i
dR = deltaR( genPart.Eta, genPart.Phi, subleadPhoton.Eta, subleadPhoton.Phi ) # SubleadPhoton
if( dR < dR_genPartsubleadPho_min ):
dR_genPartsubleadPho_min = dR
gensubleadPho_idx = i
#Lepton pair extraction
if( isDiMuon ): #Muons
if( abs( genPart.PID ) == 13 ):
dR = deltaR( genPart.Eta, genPart.Phi, lep1.Eta, lep1.Phi ) # lepton 1
if( dR < dR_genPartLep1_min ):
dR_genPartLep1_min = dR
genLep1_idx = i
dR = deltaR( genPart.Eta, genPart.Phi, lep2.Eta, lep2.Phi ) # lepton 2
if( dR < dR_genPartLep2_min ):
dR_genPartLep2_min = dR
genLep2_idx = i
else: #Electrons
if( abs( genPart.PID ) == 11 ):
dR = deltaR( genPart.Eta, genPart.Phi, lep1.Eta, lep1.Phi ) # lepton 1
if( dR < dR_genPartLep1_min ):
dR_genPartLep1_min = dR
genLep1_idx = i
dR = deltaR( genPart.Eta, genPart.Phi, lep2.Eta, lep2.Phi ) # lepton 2
if( dR < dR_genPartLep2_min ):
dR_genPartLep2_min = dR
genLep2_idx = i
leadPhoton_gen = branchGenParticle.At( genleadPho_idx )
subleadPhoton_gen = branchGenParticle.At( gensubleadPho_idx )
lep1_gen = branchGenParticle.At( genLep1_idx )
lep2_gen = branchGenParticle.At( genLep2_idx )
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#Calculate kinematics
pT_H_reco = pT_vector_calc( leadPhoton, subleadPhoton )
pT_H_gen = pT_vector_calc( leadPhoton_gen, subleadPhoton_gen )
q_ggll_reco = leadPhoton.P4()+subleadPhoton.P4()+lep1.P4()+lep2.P4()
q_ggll_gen = leadPhoton_gen.P4()+subleadPhoton_gen.P4()+lep1_gen.P4()+lep2_gen.P4()
m_ZH_reco = math.sqrt( q_ggll_reco*q_ggll_reco )
m_ZH_gen = math.sqrt( q_ggll_gen*q_ggll_gen )
m_gg_reco = math.sqrt( (leadPhoton.P4()+subleadPhoton.P4())*(leadPhoton.P4()+subleadPhoton.P4()) )
m_gg_gen = math.sqrt( (leadPhoton_gen.P4()+subleadPhoton_gen.P4())*(leadPhoton_gen.P4()+subleadPhoton_gen.P4()) )
m_ll_reco = math.sqrt( (lep1.P4()+lep2.P4())*(lep1.P4()+lep2.P4()) )
m_ll_gen = math.sqrt( (lep1_gen.P4()+lep2_gen.P4())*(lep1_gen.P4()+lep2_gen.P4()) )
#Fill histograms
hist_pTH_reco_LO.Fill( pT_H_reco, LO_weight )
hist_pTH_reco_O3.Fill( pT_H_reco, O3_weight )
hist_pTH_reco_LO_lb.Fill( pT_H_reco, LO_weight )
hist_pTH_reco_O3_lb.Fill( pT_H_reco, O3_weight )
hist_pTH_gen_LO.Fill( pT_H_gen, LO_weight )
hist_pTH_gen_O3.Fill( pT_H_gen, O3_weight )
hist_pTH_gen_LO_lb.Fill( pT_H_gen, LO_weight )
hist_pTH_gen_O3_lb.Fill( pT_H_gen, O3_weight )
hist_mZH_reco_LO.Fill( m_ZH_reco, LO_weight )
hist_mZH_reco_O3.Fill( m_ZH_reco, O3_weight )
hist_mZH_reco_LO_lb.Fill( m_ZH_reco, LO_weight )
hist_mZH_reco_O3_lb.Fill( m_ZH_reco, O3_weight )
hist_mZH_gen_LO.Fill( m_ZH_gen, LO_weight )
hist_mZH_gen_O3.Fill( m_ZH_gen, O3_weight )
hist_mZH_gen_LO_lb.Fill( m_ZH_gen, LO_weight )
hist_mZH_gen_O3_lb.Fill( m_ZH_gen, O3_weight )
hist_mgg_reco.Fill( m_gg_reco, LO_weight )
hist_mgg_gen.Fill( m_gg_gen, LO_weight )
hist_mll_reco.Fill( m_ll_reco, LO_weight )
hist_mll_gen.Fill( m_ll_gen, LO_weight )
if( pT_H_reco >= 0. ) & ( pT_H_reco < 50. ): hist_mgg_reco_1.Fill( m_gg_reco, LO_weight )
elif( pT_H_reco >= 50. ) & ( pT_H_reco < 100. ): hist_mgg_reco_2.Fill( m_gg_reco, LO_weight )
elif( pT_H_reco >= 100. ) & ( pT_H_reco < 150. ): hist_mgg_reco_3.Fill( m_gg_reco, LO_weight )
elif( pT_H_reco >= 150. ) & ( pT_H_reco < 200. ): hist_mgg_reco_4.Fill( m_gg_reco, LO_weight )
elif( pT_H_reco >= 200. ) & ( pT_H_reco < 250. ): hist_mgg_reco_5.Fill( m_gg_reco, LO_weight )
elif( pT_H_reco >= 250. ) & ( pT_H_reco < 300. ): hist_mgg_reco_6.Fill( m_gg_reco, LO_weight )
#Fill response matrix
hist_pTH_responseMatrix.Fill( pT_H_reco, pT_H_gen, LO_weight )
hist_mZH_responseMatrix.Fill( m_ZH_reco, m_ZH_gen, LO_weight )
#
###############################################################################
# FINAL OUTPUT CONFIG
#normalise matrix by column: i.e. see what percentage gen level falls in each reco bin
#loop over columns
for i in range(1,hist_pTH_responseMatrix.GetNbinsX()+1):
column_sum = 0
#loop over rows and sum up
for j in range(1,hist_pTH_responseMatrix.GetNbinsY()+1):
column_sum += hist_pTH_responseMatrix.GetBinContent( i, j )
#loop over rows again and scale value
for j in range(1, hist_pTH_responseMatrix.GetNbinsY()+1):
hist_pTH_responseMatrix.SetBinContent( i, j, (hist_pTH_responseMatrix.GetBinContent(i,j)*100)/column_sum )
#loop over columns
for i in range(1,hist_mZH_responseMatrix.GetNbinsX()+1):
column_sum = 0
#loop over rows and sum up
for j in range(1,hist_mZH_responseMatrix.GetNbinsY()+1):
column_sum += hist_mZH_responseMatrix.GetBinContent( i, j )
#loop over rows again and scale value
for j in range(1, hist_mZH_responseMatrix.GetNbinsY()+1):
hist_mZH_responseMatrix.SetBinContent( i, j, (hist_mZH_responseMatrix.GetBinContent(i,j)*100)/column_sum )
# WRITE HISTOGRAMS TO FILE AND CLOSE
f.Write()
f.Close()
#Print out info
print "########################################################## "
print " CUT COUNTERS "
print "Total events:", numberOfEntries
print " -> Diphoton events:", N_dipho
print " -> DiMuon events:", N_diMuon
print " -> DiElec events:", N_diElectron
print " -> DiSele events:", N_selection
print " -> DiSele in Z mass window events:", N_Zll
print "########################################################## "
raw_input("Press Enter to continue...")