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create_workspace_varbin_76x.py
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import os
import math
from array import array
import optparse
import ROOT
from ROOT import *
import scipy, copy
import Alphabet_Header
from Alphabet_Header import *
import Plotting_Header
from Plotting_Header import *
#gSystem.Load("PU_C.so")
'''
gInterpreter.ProcessLine( 'TFile *f = TFile::Open("trigger_objects.root")')
gInterpreter.ProcessLine( 'TH1F *histo_efficiency = (TH1F*)f->Get("histo_efficiency")')
gInterpreter.ProcessLine( 'TH1F *histo_efficiency_lower = (TH1F*)f->Get("histo_efficiency_lower")')
gInterpreter.ProcessLine( 'TH1F *histo_efficiency_upper = (TH1F*)f->Get("histo_efficiency_upper")')
gInterpreter.ProcessLine(".x trigger_function.cxx")
'''
#background1 = TFile("Hbb_outputup.root")
#qcd_trigger_up=copy.copy(background1.Get("QCD"))
#background2 = TFile("Hbb_outputlow.root")
#qcd_trigger_low=copy.copy(background2.Get("QCD"))
#qcd_trigger_up.SetName("QCD_up")
#qcd_trigger_low.SetName("QCD_low")
#background1.Close()
#background2.Close()
mass=[1000,1200,1400,1600,1800,2000,2500,3000]
VAR = "dijetmass_corr"
#variable bin from dijet analysis 788 838
binBoundaries = [800, 838, 890, 944, 1000, 1058, 1118, 1181, 1246, 1313, 1383, 1455, 1530, 1607, 1687,
1770, 1856, 1945, 2037, 2132, 2231, 2332, 2438, 2546, 2659, 2775, 2895, 3019 ]#, 3147, 3279, 3416, 3558, 3704, 3854, 4010, 4171, 4337, 4509,
vartitle = "m_{X} (GeV)"
sigregcutNoTrig = "(dijetmass_corr>800&jet1tau21<0.6&jet2tau21<0.6&jet2pmass<135&jet2pmass>105&&(jet1pmass<135&jet1pmass>105)&jet2bbtag>0.6 &jet1bbtag>0.6&&jet1ID>0.&&jet2ID>0.)"
sigregcut = "(triggerpassbb>0.&dijetmass_corr>800&jet1tau21<0.6&jet2tau21<0.6&jet2pmass<135&jet2pmass>105&&(jet1pmass<135&jet1pmass>105)&jet2bbtag>0.6 &jet1bbtag>0.6&&jet1ID>0.&&jet2ID>0.)"
#(dijetmass_corr>800&jet1tau21<0.6&jet2tau21<0.6&(jet2pmass<130&jet2pmass>90)&(jet1pmass<130&jet1pmass>100)&(jet1bbtag>0.6&jet2bbtag>0.6))"
lumi =2691.
background = TFile("Hbb_Unblind.root")
UD = ['Up','Down']
SF_tau21=0.979
#SF_bbtag=0.95
for m in mass:
output_file = TFile("datacard/hh_mX_%s_13TeV.root"%(m),"RECREATE")
hh=output_file.mkdir("hh")
hh.cd()
Signal_mX = TH1F("Signal_mX_%s"%(m), "", len(binBoundaries)-1, array('d',binBoundaries))
Signal_mX_trig_up = TH1F("Signal_mX_%s_CMS_eff_trigUp"%(m), "", len(binBoundaries)-1, array('d',binBoundaries))
Signal_mX_trig_down = TH1F("Signal_mX_%s_CMS_eff_trigDown"%(m), "", len(binBoundaries)-1, array('d',binBoundaries))
Signal_mX_btag_up = TH1F("Signal_mX_%s_CMS_eff_btagUp"%(m), "", len(binBoundaries)-1, array('d',binBoundaries))
Signal_mX_btag_down = TH1F("Signal_mX_%s_CMS_eff_btagDown"%(m), "", len(binBoundaries)-1, array('d',binBoundaries))
Signal_mX_pu_up = TH1F("Signal_mX_%s_CMS_eff_puUp"%(m), "", len(binBoundaries)-1, array('d',binBoundaries))
Signal_mX_pu_down = TH1F("Signal_mX_%s_CMS_eff_puDown"%(m), "", len(binBoundaries)-1, array('d',binBoundaries))
Signal_mX_FJEC_Up = TH1F("Signal_mX_%s_CMS_eff_JECUp"%(m), "", len(binBoundaries)-1, array('d',binBoundaries))
Signal_mX_FJEC_Down = TH1F("Signal_mX_%s_CMS_eff_JECDown"%(m), "", len(binBoundaries)-1, array('d',binBoundaries))
Signal_mX_FJER_Up = TH1F("Signal_mX_%s_CMS_eff_JERUp"%(m), "", len(binBoundaries)-1, array('d',binBoundaries))
Signal_mX_FJER_Down = TH1F("Signal_mX_%s_CMS_eff_JERDown"%(m), "", len(binBoundaries)-1, array('d',binBoundaries))
Signal_mX_MJEC_Up = TH1F("Signal_mX_%s_CMS_eff_massJECUp"%(m), "", len(binBoundaries)-1, array('d',binBoundaries))
Signal_mX_MJEC_Down = TH1F("Signal_mX_%s_CMS_eff_massJECDown"%(m), "", len(binBoundaries)-1, array('d',binBoundaries))
print(m)
signal_file= TFile("/uscms_data/d3/cvernier/test-alice/HbbAnalysis/BG_%s_76X_boost_None.root"%(m))
#signal_file= TFile("/uscms_data/d3/asady1/HHcode/CMSSW_7_4_2/src/Analysis/HbbAnalysis/BG_%s_76X_boost_0.root"%(m))
bbj = signal_file.Get("bbj")
generatedEvents =bbj.GetEntries()
print(generatedEvents)
tree = signal_file.Get("myTree")
writeplot(tree, Signal_mX_pu_up, VAR, sigregcut, "puWeightsUp*SF")
writeplot(tree, Signal_mX_pu_down, VAR, sigregcut, "puWeightsDown*SF")
writeplot(tree, Signal_mX, VAR, sigregcut, "puWeights*SF")#(trigger_function(int(round(htJet40eta3)))*weight2(nTrueInt))")
writeplot(tree, Signal_mX_btag_up, VAR, sigregcut, "puWeights*SFup")
writeplot(tree, Signal_mX_btag_down, VAR, sigregcut, "puWeights*SFdown")
writeplot(tree, Signal_mX_trig_up, VAR, sigregcutNoTrig, "trigWeightUp*puWeights*SF")
writeplot(tree, Signal_mX_trig_down, VAR, sigregcutNoTrig, "trigWeightDown*puWeights*SF")
print(Signal_mX.Integral())
btaglnN= 1.+ abs(Signal_mX_btag_up.GetSumOfWeights()-Signal_mX_btag_down.GetSumOfWeights())/(2.*Signal_mX_btag_up.GetSumOfWeights())
pulnN= 1.+ abs(Signal_mX_pu_up.GetSumOfWeights()-Signal_mX_pu_down.GetSumOfWeights())/(2.*Signal_mX.GetSumOfWeights())
#triglnN= 1.+ abs(Signal_mX_trig_up.GetSumOfWeights()-Signal_mX_trig_down.GetSumOfWeights())/(2.*Signal_mX.GetSumOfWeights())
Signal_mX.Scale(lumi*SF_tau21*SF_tau21*0.01/generatedEvents)
Signal_mX_btag_up.Scale(lumi*SF_tau21*SF_tau21*0.01/generatedEvents)
Signal_mX_btag_down.Scale(lumi*SF_tau21*SF_tau21*0.01/generatedEvents)
Signal_mX_pu_up.Scale(lumi*SF_tau21*SF_tau21*0.01/generatedEvents)
Signal_mX_pu_down.Scale(lumi*SF_tau21*SF_tau21*0.01/generatedEvents)
Signal_mX_trig_up.Scale(0.01*lumi*SF_tau21*SF_tau21/generatedEvents)
Signal_mX_trig_down.Scale(0.01*lumi*SF_tau21*SF_tau21/generatedEvents)
if not (m==1200 or m==3000 or m==1800):
signal_file_FJEC_Up= TFile("/uscms_data/d3/cvernier/test-alice/HbbAnalysis/BG_%s_76X_boost_FJEC_Up.root"%(m))
tree_FJEC_Up = signal_file_FJEC_Up.Get("myTree")
writeplot(tree_FJEC_Up, Signal_mX_FJEC_Up, VAR, sigregcut, "puWeights*SF")
Signal_mX_FJEC_Up.Scale(lumi*SF_tau21*SF_tau21*0.01/generatedEvents)
signal_file_FJEC_Down= TFile("/uscms_data/d3/cvernier/test-alice/HbbAnalysis/BG_%s_76X_boost_FJEC_Down.root"%(m))
tree_FJEC_Down = signal_file_FJEC_Down.Get("myTree")
writeplot(tree_FJEC_Down, Signal_mX_FJEC_Down, VAR, sigregcut, "puWeights*SF")
Signal_mX_FJEC_Down.Scale(lumi*SF_tau21*SF_tau21*0.01/generatedEvents)
signal_file_FJER_Up= TFile("/uscms_data/d3/cvernier/test-alice/HbbAnalysis/BG_%s_76X_boost_FJER_Up.root"%(m))
tree_FJER_Up = signal_file_FJEC_Up.Get("myTree")
writeplot(tree_FJER_Up, Signal_mX_FJER_Up, VAR, sigregcut, "puWeights*SF")
Signal_mX_FJER_Up.Scale(lumi*SF_tau21*SF_tau21*0.01/generatedEvents)
signal_file_FJER_Down= TFile("/uscms_data/d3/cvernier/test-alice/HbbAnalysis/BG_%s_76X_boost_FJER_Down.root"%(m))
tree_FJER_Down = signal_file_FJER_Down.Get("myTree")
writeplot(tree_FJER_Down, Signal_mX_FJER_Down, VAR, sigregcut, "puWeights*SF")
Signal_mX_FJER_Down.Scale(lumi*SF_tau21*SF_tau21*0.01/generatedEvents)
signal_file_MJEC_Up= TFile("/uscms_data/d3/cvernier/test-alice/HbbAnalysis/BG_%s_76X_boost_MJEC_Up.root"%(m))
tree_MJEC_Up = signal_file_MJEC_Up.Get("myTree")
writeplot(tree_MJEC_Up, Signal_mX_MJEC_Up, VAR, sigregcut, "puWeights*SF")
Signal_mX_MJEC_Up.Scale(lumi*SF_tau21*SF_tau21*0.01/generatedEvents)
signal_file_MJEC_Down= TFile("/uscms_data/d3/cvernier/test-alice/HbbAnalysis/BG_%s_76X_boost_MJEC_Down.root"%(m))
tree_MJEC_Down = signal_file_MJEC_Down.Get("myTree")
writeplot(tree_MJEC_Down, Signal_mX_MJEC_Down, VAR, sigregcut, "puWeights*SF")
Signal_mX_MJEC_Down.Scale(lumi*SF_tau21*SF_tau21*0.01/generatedEvents)
MJEClnN= 1.+ abs(Signal_mX_MJEC_Up.GetSumOfWeights()-Signal_mX_MJEC_Down.GetSumOfWeights())/(2.*Signal_mX.GetSumOfWeights())
FJEClnN= 1.+ abs(Signal_mX_FJEC_Up.GetSumOfWeights()-Signal_mX_FJEC_Down.GetSumOfWeights())/(2.*Signal_mX.GetSumOfWeights())
FJERlnN= 1.+ abs(Signal_mX_FJER_Up.GetSumOfWeights()-Signal_mX_FJER_Down.GetSumOfWeights())/(2.*Signal_mX.GetSumOfWeights())
else :
MJEClnN= 1.02
FJEClnN= 1.02
FJERlnN= 1.02
print("%s %s %s")%(MJEClnN,FJEClnN,FJERlnN)
signal_integral = Signal_mX.Integral()
print(signal_integral)
background.cd()
qcd_integral = EST.Integral()
qcd =EST
qcd_antitag = EST_Antitag
qcd_up = EST_CMS_scale_13TeVUp
qcd_down = EST_CMS_scale_13TeVDown
data = data_obs
data_integral = data_obs.Integral()
output_file.cd()
hh.cd()
qcd_stat_up =TH1F("qcd_stat_up","",len(binBoundaries)-1, array('d',binBoundaries))
qcd_stat_down =TH1F("qcd_stat_down","",len(binBoundaries)-1, array('d',binBoundaries))
for bin in range(0,len(binBoundaries)-1):
for Q in UD:
qcd_syst =TH1F("%s_bin%s%s"%("EST_CMS_stat_13TeV",bin,Q),"",len(binBoundaries)-1, array('d',binBoundaries))
bin_stat = qcd.GetBinContent(bin+1)
for bin1 in range(0,len(binBoundaries)-1):
bin_stat1 = qcd.GetBinContent(bin1+1)
qcd_syst.SetBinContent(bin1+1,bin_stat1)
#if bin_stat==0 :
# bin_stat = 1.5
bin_at = qcd_antitag.GetBinContent(bin+1)
if bin_at < 1 and bin_at >0:
bin_at=1.
if Q == 'Up':
if bin_at >0 :
qcd_stat_up.SetBinContent(bin+1,bin_stat+qcd_antitag.GetBinError(bin+1)/bin_at*bin_stat)
qcd_syst.SetBinContent(bin+1,bin_stat+qcd_antitag.GetBinError(bin+1)/bin_at*bin_stat)
else :
qcd_syst.SetBinContent(bin+1,bin_stat)
qcd_stat_up.SetBinContent(bin+1,bin_stat)
if Q == 'Down':
if bin_at >0 :
if ( bin_stat-qcd_antitag.GetBinError(bin+1)/bin_at*bin_stat >0 ):
qcd_syst.SetBinContent(bin+1,bin_stat-qcd_antitag.GetBinError(bin+1)/bin_at*bin_stat)
qcd_stat_down.SetBinContent(bin+1,bin_stat-qcd_antitag.GetBinError(bin+1)/bin_at*bin_stat)
else :
qcd_syst.SetBinContent(bin+1, 0.1)
qcd_stat_down.SetBinContent(bin+1, 0.1)
else :
qcd_syst.SetBinContent(bin+1,bin_stat)
qcd_stat_down.SetBinContent(bin+1,bin_stat)
qcd_syst.Write()
#qcd_trigger_up.Write()
#qcd_trigger_low.Write()
qcd.Write()
qcd_up.Write()
qcd_down.Write()
qcd_stat_up.Write()
qcd_stat_down.Write()
Signal_mX.Write()
Signal_mX_btag_up.Write()
Signal_mX_btag_down.Write()
Signal_mX_pu_up.Write()
Signal_mX_pu_down.Write()
Signal_mX_trig_up.Write()
Signal_mX_trig_down.Write()
data.Write()
hh.Write()
output_file.Write()
#output_file.Close()
text_file = open("datacard/hh_mX_%s_13TeV.txt"%(m), "w")
text_file.write("max 1 number of categories\n")
text_file.write("jmax 1 number of samples minus one\n")
text_file.write("kmax * number of nuisance parameters\n")
text_file.write("-------------------------------------------------------------------------------\n")
text_file.write("shapes * * hh_mX_%s_13TeV.root hh/$PROCESS hh/$PROCESS_$SYSTEMATIC\n"%(m))
text_file.write("-------------------------------------------------------------------------------\n")
text_file.write("bin hh4b\n")
text_file.write("observation %f\n"%(data_integral))
text_file.write("-------------------------------------------------------------------------------\n")
text_file.write("bin hh4b hh4b\n")
text_file.write("process 0 1\n")
text_file.write("process Signal_mX_%s EST\n"%(m))
text_file.write("rate %f %f\n"%(signal_integral,qcd_integral))
text_file.write("-------------------------------------------------------------------------------\n")
text_file.write("lumi_13TeV lnN 1.027 -\n")
text_file.write("CMS_eff_tau21_sf lnN 1.057 -\n") #(0.028/0.979)*(2)
text_file.write("CMS_pileup lnN %f -\n"%(pulnN))
text_file.write("CMS_eff_Htag_sf lnN 1.1 -\n")
text_file.write("CMS_JEC lnN %f -\n"%(FJEClnN))
text_file.write("CMS_massJEC lnN %f -\n"%(MJEClnN))
text_file.write("CMS_eff_bbtag_sf lnN %f -\n"%(btaglnN))
text_file.write("CMS_JER lnN %f -\n"%(FJERlnN))
#text_file.write("CMS_eff_trig lnN %f -\n"%(triglnN))
text_file.write("CMS_eff_trig shapeN2 1.0 -\n")
text_file.write("CMS_scale_13TeV shapeN2 - 1.000\n")
text_file.write("CMS_PDF_Scales lnN 1.02 - \n")
for bin in range(0,len(binBoundaries)-1):
text_file.write("CMS_stat_13TeV_bin%s shapeN2 - 1.000\n"%(bin))
text_file.close()
qcd_up.SetLineColor(kBlack)
qcd_down.SetLineColor(kBlack)
qcd_up.SetLineStyle(2)
qcd_down.SetLineStyle(2)
qcd_stat_up.SetLineColor(kAzure+1)
qcd_stat_down.SetLineColor(kAzure+1)
qcd_stat_up.SetLineStyle(2)
qcd_stat_down.SetLineStyle(2)
qcd.SetLineColor(kBlack)
qcd.SetFillColor(kPink+3)
data.SetStats(0)
data.Sumw2()
data.SetLineColor(1)
data.SetFillColor(0)
data.SetMarkerColor(1)
data.SetMarkerStyle(20)
#qcd.GetYaxis().SetTitle("events / "+str((bins[2]-bins[1])/bins[0])+" GeV")
qcd.GetXaxis().SetTitle(vartitle)
leg2 = TLegend(0.6,0.6,0.89,0.89)
leg2.SetLineColor(0)
leg2.SetFillColor(0)
leg2.AddEntry(data, "QCD in SR", "PL")
leg2.AddEntry(qcd, "QCD prediction", "F")
leg2.AddEntry(qcd_up, "transfer function uncertainty", "F")
leg2.AddEntry(qcd_stat_up, "statistical uncertainty", "F")
FindAndSetMax([qcd,qcd_up,qcd_stat_up,data])
C3 = TCanvas("C3", "", 800, 600)
C3.cd()
qcd.Draw("Hist")
data.Draw("same E0")
qcd_up.Draw("same")
qcd_down.Draw("same")
qcd_stat_up.Draw("same")
qcd_stat_down.Draw("same")
leg2.Draw()
if m< 1400 :
C3.Print("split_unc.pdf")
#output_file.Close()