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peller |
1.1 |
#!/usr/bin/env python
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import sys
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import os
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import ROOT
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from ROOT import TFile
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print 'hello\n'
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from array import array
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from math import sqrt
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from copy import copy
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#suppres the EvalInstace conversion warning bug
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import warnings
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warnings.filterwarnings( action='ignore', category=RuntimeWarning, message='creating converter.*' )
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warnings.filterwarnings( action='ignore', category=RuntimeWarning, message='Error in <TTree::Fill>:*' )
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from ConfigParser import SafeConfigParser
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from samplesclass import sample
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from mvainfos import mvainfo
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import pickle
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from progbar import progbar
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from printcolor import printc
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class DevNull:
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def write(self, msg):
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pass
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sys.stderr = DevNull()
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#CONFIGURE
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#load config
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config = SafeConfigParser()
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config.read('./config')
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#get locations:
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Wdir=config.get('Directories','Wdir')
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#systematics
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systematics=config.get('systematics','systematics')
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systematics=systematics.split(' ')
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#TreeVar Array
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MVA_Vars={}
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for systematic in systematics:
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MVA_Vars[systematic]=config.get('treeVars',systematic)
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MVA_Vars[systematic]=MVA_Vars[systematic].split(' ')
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weightF=config.get('Weights','weightF')
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def getTree(job,cut):
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Tree = ROOT.TChain(job.tree)
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Tree.Add(job.getpath())
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#Tree.SetDirectory(0)
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CuttedTree=Tree.CopyTree(cut)
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#CuttedTree.SetDirectory(0)
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print '\t--> read in %s'%job.name
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return CuttedTree
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'''
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def getTree(job):
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Tree = ROOT.TChain(job.tree)
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Tree.Add(job.getpath())
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Tree.SetDirectory(0)
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#CuttedTree.SetDirectory(0)
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return Tree
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''
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def getTree(job):
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Tree = ROOT.TChain(job.tree)
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Tree.Add(job.getpath())
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Tree.SetDirectory(0)
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#CuttedTree.SetDirectory(0)
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return Tree
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'''
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def getScale(job):
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input = TFile.Open(job.getpath())
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CountWithPU = input.Get("CountWithPU")
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CountWithPU2011B = input.Get("CountWithPU2011B")
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#print lumi*xsecs[i]/hist.GetBinContent(1)
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peller |
1.2 |
return float(job.lumi)*float(job.xsec)*float(job.sf)/(0.46502*CountWithPU.GetBinContent(1)+0.53498*CountWithPU2011B.GetBinContent(1))*2/float(job.split)
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peller |
1.1 |
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def getHistoFromTree(job,options):
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treeVar=options[0]
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name=job.name
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#title=job.plotname()
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nBins=int(options[3])
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xMin=float(options[4])
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xMax=float(options[5])
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if job.type != 'DATA':
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cutcut=config.get('Cuts',options[7])
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treeCut='%s & EventForTraining == 0'%cutcut
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elif job.type == 'DATA':
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treeCut=config.get('Cuts',options[8])
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input = TFile.Open(job.getpath(),'read')
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Tree = input.Get(job.tree)
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#Tree=tmpTree.CloneTree()
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#Tree.SetDirectory(0)
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#Tree=tmpTree.Clone()
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weightF=config.get('Weights','weightF')
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#hTree = ROOT.TH1F('%s'%name,'%s'%title,nBins,xMin,xMax)
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#hTree.SetDirectory(0)
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#hTree.Sumw2()
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#print 'drawing...'
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if job.type != 'DATA':
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#print treeCut
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Tree.Draw('%s>>%s(%s,%s,%s)' %(treeVar,name,nBins,xMin,xMax),'(%s)*(%s)' %(treeCut,weightF), "goff,e")
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elif job.type == 'DATA':
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Tree.Draw('%s>>%s(%s,%s,%s)' %(treeVar,name,nBins,xMin,xMax),treeCut, "goff,e")
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hTree = ROOT.gDirectory.Get(name)
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#print job.name + ' Sumw2', hTree.GetEntries()
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if job.type != 'DATA':
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ScaleFactor = getScale(job)
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if ScaleFactor != 0:
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hTree.Scale(ScaleFactor)
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print '\t-->import %s\t Integral: %s'%(job.name,hTree.Integral())
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return hTree, job.group
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'''
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def getHistoFromTree(job,options):
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treeVar=options[0]
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name=job.name
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#title=job.plotname()
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nBins=int(options[3])
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xMin=float(options[4])
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xMax=float(options[5])
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if job.type != 'DATA':
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cutcut=config.get('Cuts',options[7])
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treeCut='%s&&EventForTraining==0'%cutcut
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elif job.type == 'DATA':
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treeCut=config.get('Cuts',options[8])
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Tree = getTree(job,treeCut)
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weightF=config.get('Weights','weightF')
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hTree = ROOT.TH1F('%s'%name,'%s'%title,nBins,xMin,xMax)
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hTree.Sumw2()
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#print 'drawing...'
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if job.type != 'DATA':
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Tree.Draw('%s>>%s(%s,%s,%s)' %(treeVar,name,nBins,xMin,xMax),'%s*(%s)' %(weightF,'1'), "goff,e")
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else:
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Tree.Draw('%s>>%s(%s,%s,%s)' %(treeVar,name,nBins,xMin,xMax),'1', "goff,e")
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hTree = ROOT.gDirectory.Get(name)
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hTree.SetDirectory(0)
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#print job.name + ' Sumw2', hTree.GetEntries()
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if job.type != 'DATA':
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ScaleFactor = getScale(job)
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if ScaleFactor != 0:
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hTree.Scale(ScaleFactor)
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print '\t-->import %s\t Integral: %s'%(job.name,hTree.Integral())
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return hTree, job.group
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'''
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######################
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path=sys.argv[1]
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var=sys.argv[2]
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plot=config.get('Limit',var)
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infofile = open(path+'/samples.info','r')
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info = pickle.load(infofile)
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infofile.close()
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options = plot.split(',')
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name=options[1]
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title = options[2]
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nBins=int(options[3])
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xMin=float(options[4])
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xMax=float(options[5])
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mass=options[9]
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data=options[10]
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setup=config.get('Limit','setup')
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setup=setup.split(',')
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ROOToutname = options[6]
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outpath=config.get('Directories','limits')
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outfile = ROOT.TFile(outpath+'vhbb_TH_'+ROOToutname+'.root', 'RECREATE')
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peller |
1.2 |
discr_names = ['ZjLF','ZjCF','ZjHF', 'TT','VV', 's_Top', 'VH', 'WjLF', 'WjHF', 'QCD']
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peller |
1.1 |
data_name = ['data_obs']
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WS = ROOT.RooWorkspace('%s'%options[10],'%s'%options[10]) #Zee
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print 'WS initialized'
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disc= ROOT.RooRealVar('BDT','BDT',-1,1)
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obs = ROOT.RooArgList(disc)
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ROOT.gROOT.SetStyle("Plain")
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#c = ROOT.TCanvas(name,title, 800, 600)
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datas = []
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datatyps =[]
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histos = []
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typs = []
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statUps=[]
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statDowns=[]
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for job in info:
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#print job.name
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if job.type == 'BKG':
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#print 'MC'
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hTemp, typ = getHistoFromTree(job,options)
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histos.append(hTemp)
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typs.append(typ)
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elif job.type == 'SIG' and job.name == mass:
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hTemp, typ = getHistoFromTree(job,options)
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histos.append(hTemp)
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typs.append(typ)
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elif job.name in data:
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#print 'DATA'
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hTemp, typ = getHistoFromTree(job,options)
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datas.append(hTemp)
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datatyps.append(typ)
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MC_integral=0
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MC_entries=0
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for histo in histos:
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MC_integral+=histo.Integral()
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#MC_entries+=histo.GetEntries()
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print "\033[1;32m\n\tMC integral = %s\033[1;m"%MC_integral
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#flow = MC_entries-MC_integral
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#if flow > 0:
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# print "\033[1;31m\tU/O flow: %s\033[1;m"%flow
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#ORDER AND ADD TOGETHER
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ordnung=[]
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ordnungtyp=[]
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num=[0]*len(setup)
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for i in range(0,len(setup)):
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for j in range(0,len(histos)):
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if typs[j] == setup[i]:
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num[i]+=1
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ordnung.append(histos[j])
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ordnungtyp.append(typs[j])
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del histos
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del typs
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histos=ordnung
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typs=ordnungtyp
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for k in range(0,len(num)):
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for m in range(0,num[k]):
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if m > 0:
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#add
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#for IND in range(histos[k].GetNbinsX()):
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# content=histos[k].GetBinContent(IND)+histos[k+1].GetBinContent(IND)
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# histos[k].SetBinContent(IND,content)
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#histos[k].Sumw2()
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#histos[k+1].Sumw2()
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histos[k].Add(histos[k+1],1)
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printc('red','','\t--> added %s to %s'%(typs[k],typs[k+1]))
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del histos[k+1]
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del typs[k+1]
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for i in range(0,len(histos)):
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histos[i].SetName(discr_names[i])
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histos[i].SetDirectory(outfile)
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histos[i].Write()
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#histos[i].Draw("goff")
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#histos[i].Write()
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#printc('blue','',discr_names[i])
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#print i
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statUps.append(histos[i].Clone())
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statDowns.append(histos[i].Clone())
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statUps[i].SetName('%sCMS_vhbb_stats_%s_%sUp'%(discr_names[i],discr_names[i],options[10]))
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statDowns[i].SetName('%sCMS_vhbb_stats_%s_%sDown'%(discr_names[i],discr_names[i],options[10]))
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statUps[i].Sumw2()
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statDowns[i].Sumw2()
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#shift up and down with statistical error
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for j in range(histos[i].GetNbinsX()):
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#print '\t\t Up : %s'%(statUps[i].GetBinContent(j)+statUps[i].GetBinError(j))
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#print '\t\t Nominal: %s'%histos[i].GetBinContent(j)
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statUps[i].SetBinContent(j,statUps[i].GetBinContent(j)+statUps[i].GetBinError(j))
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#print '\t\t Down: %s'%(statDowns[i].GetBinContent(j)-statDowns[i].GetBinError(j))
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statDowns[i].SetBinContent(j,statDowns[i].GetBinContent(j)-statDowns[i].GetBinError(j))
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statUps[i].SetDirectory(outfile)
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statDowns[i].SetDirectory(outfile)
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#statUps[i].Draw("goff")
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statUps[i].Write()
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#statUp.Write()
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statDowns[i].Write()
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#statDowns[i].Draw("goff")
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#statDown.Write()
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histPdf = ROOT.RooDataHist(discr_names[i],discr_names[i],obs,histos[i])
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| 345 |
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|
#UP stats of MCs
|
| 346 |
|
|
RooStatsUp = ROOT.RooDataHist('%sCMS_vhbb_stats_%s_%sUp'%(discr_names[i],discr_names[i],options[10]),'%sCMS_vhbb_stats_%s_%sUp'%(discr_names[i],discr_names[i],options[10]),obs, statUps[i])
|
| 347 |
|
|
#DOWN stats of MCs
|
| 348 |
|
|
RooStatsDown = ROOT.RooDataHist('%sCMS_vhbb_stats_%s_%sDown'%(discr_names[i],discr_names[i],options[10]),'%sCMS_vhbb_stats_%s_%sDown'%(discr_names[i],discr_names[i],options[10]),obs, statDowns[i])
|
| 349 |
|
|
|
| 350 |
|
|
|
| 351 |
|
|
|
| 352 |
|
|
|
| 353 |
|
|
getattr(WS,'import')(histPdf)
|
| 354 |
|
|
getattr(WS,'import')(RooStatsUp)
|
| 355 |
|
|
getattr(WS,'import')(RooStatsDown)
|
| 356 |
|
|
|
| 357 |
|
|
|
| 358 |
|
|
|
| 359 |
|
|
#frame=disc.frame()
|
| 360 |
|
|
|
| 361 |
|
|
|
| 362 |
|
|
#ROOT.RooAbsData.plotOn(histPdf,frame)
|
| 363 |
|
|
#frame.Draw()
|
| 364 |
|
|
|
| 365 |
|
|
#c.Print('~/Hbb/WStest/%s.png'%discr_names[i])
|
| 366 |
|
|
|
| 367 |
|
|
#del statUp
|
| 368 |
|
|
#del statDown
|
| 369 |
|
|
|
| 370 |
|
|
|
| 371 |
|
|
|
| 372 |
|
|
#print discr_names[i]
|
| 373 |
|
|
#print histos[i].Integral(0,nBins)
|
| 374 |
|
|
|
| 375 |
|
|
|
| 376 |
|
|
|
| 377 |
|
|
#dunnmies
|
| 378 |
|
|
#Wlight,Wbb,QCD
|
| 379 |
|
|
for i in range(6,9):
|
| 380 |
|
|
dummy = ROOT.TH1F(discr_names[i], "discriminator", nBins, xMin, xMax)
|
| 381 |
|
|
dummy.SetDirectory(outfile)
|
| 382 |
|
|
dummy.Write()
|
| 383 |
|
|
#dummy.Draw("goff")
|
| 384 |
|
|
|
| 385 |
|
|
#nominal
|
| 386 |
|
|
histPdf = ROOT.RooDataHist(discr_names[i],discr_names[i],obs,dummy)
|
| 387 |
|
|
#UP stats of MCs
|
| 388 |
|
|
RooStatsUp = ROOT.RooDataHist('%sCMS_vhbb_stats_%s_%sUp'%(discr_names[i],discr_names[i],options[10]),'%sCMS_vhbb_stats_%s_%sUp'%(discr_names[i],discr_names[i],options[10]),obs, dummy)
|
| 389 |
|
|
#DOWN stats of MCs
|
| 390 |
|
|
RooStatsDown = ROOT.RooDataHist('%sCMS_vhbb_stats_%s_%sDown'%(discr_names[i],discr_names[i],options[10]),'%sCMS_vhbb_stats_%s_%sDown'%(discr_names[i],discr_names[i],options[10]),obs, dummy)
|
| 391 |
|
|
|
| 392 |
|
|
getattr(WS,'import')(histPdf)
|
| 393 |
|
|
getattr(WS,'import')(RooStatsUp)
|
| 394 |
|
|
getattr(WS,'import')(RooStatsDown)
|
| 395 |
|
|
|
| 396 |
|
|
|
| 397 |
|
|
|
| 398 |
|
|
|
| 399 |
|
|
|
| 400 |
|
|
#HISTOGRAMM of DATA
|
| 401 |
|
|
d1 = ROOT.TH1F('d1','d1',nBins,xMin,xMax)
|
| 402 |
|
|
for i in range(0,len(datas)):
|
| 403 |
|
|
d1.Add(datas[i],1)
|
| 404 |
|
|
print "\033[1;32m\n\tDATA integral = %s\033[1;m"%d1.Integral()
|
| 405 |
|
|
flow = d1.GetEntries()-d1.Integral()
|
| 406 |
|
|
if flow > 0:
|
| 407 |
|
|
print "\033[1;31m\tU/O flow: %s\033[1;m"%flow
|
| 408 |
|
|
|
| 409 |
|
|
#datas[0]: data_obs
|
| 410 |
|
|
d1.SetName(data_name[0])
|
| 411 |
|
|
d1.SetDirectory(outfile)
|
| 412 |
|
|
d1.Write()
|
| 413 |
|
|
#d1.Draw("goff")
|
| 414 |
|
|
|
| 415 |
|
|
#ROOT.RooDataHist('data_obsHist','',RooArgList,??)
|
| 416 |
|
|
histPdf = ROOT.RooDataHist('data_obs','data_obs',obs,d1)
|
| 417 |
|
|
#ROOT.RooAbsData.plotOn(histPdf,frame)
|
| 418 |
|
|
#frame.Draw()
|
| 419 |
|
|
|
| 420 |
|
|
#c.Print('~/Hbb/WStest/d1.png')
|
| 421 |
|
|
#IMPORT
|
| 422 |
|
|
getattr(WS,'import')(histPdf)
|
| 423 |
|
|
|
| 424 |
|
|
#Number of Obs?
|
| 425 |
|
|
#nObs = int(d1.Integral())
|
| 426 |
|
|
|
| 427 |
|
|
|
| 428 |
|
|
|
| 429 |
|
|
|
| 430 |
|
|
#SYSTEMATICS:
|
| 431 |
|
|
|
| 432 |
|
|
#systematics=config.get('systematics','systematics')
|
| 433 |
|
|
#for sys in systematics[1:]
|
| 434 |
|
|
|
| 435 |
|
|
ud = ['up','down']
|
| 436 |
|
|
UD = ['Up','Down']
|
| 437 |
|
|
|
| 438 |
|
|
systhistosarray=[]
|
| 439 |
|
|
Coco=0
|
| 440 |
|
|
|
| 441 |
|
|
for sys in ['JER','JES','beff','bmis']:
|
| 442 |
|
|
|
| 443 |
|
|
for Q in range(0,2):
|
| 444 |
|
|
|
| 445 |
|
|
ff=options[0].split('.')
|
| 446 |
|
|
ff[1]='%s_%s'%(sys,ud[Q])
|
| 447 |
|
|
options[0]='.'.join(ff)
|
| 448 |
|
|
|
| 449 |
|
|
|
| 450 |
|
|
printc('blue','','\t\t--> doing systematic %s %s'%(sys,ud[Q]))
|
| 451 |
|
|
|
| 452 |
|
|
systhistosarray.append([])
|
| 453 |
|
|
#histosX = []
|
| 454 |
|
|
typsX = []
|
| 455 |
|
|
|
| 456 |
|
|
for job in info:
|
| 457 |
|
|
#print job.name
|
| 458 |
|
|
if job.type == 'BKG':
|
| 459 |
|
|
#print 'MC'
|
| 460 |
|
|
hTemp, typ = getHistoFromTree(job,options)
|
| 461 |
|
|
systhistosarray[Coco].append(hTemp)
|
| 462 |
|
|
typsX.append(typ)
|
| 463 |
|
|
|
| 464 |
|
|
elif job.type == 'SIG' and job.name == mass:
|
| 465 |
|
|
#print 'MC'
|
| 466 |
|
|
hTemp, typ = getHistoFromTree(job,options)
|
| 467 |
|
|
systhistosarray[Coco].append(hTemp)
|
| 468 |
|
|
typsX.append(typ)
|
| 469 |
|
|
|
| 470 |
|
|
|
| 471 |
|
|
MC_integral=0
|
| 472 |
|
|
MC_entries=0
|
| 473 |
|
|
|
| 474 |
|
|
for histoX in systhistosarray[Coco]:
|
| 475 |
|
|
MC_integral+=histoX.Integral()
|
| 476 |
|
|
#MC_entries+=histo.GetEntries()
|
| 477 |
|
|
print "\033[1;32m\n\tMC integral = %s\033[1;m"%MC_integral
|
| 478 |
|
|
#flow = MC_entries-MC_integral
|
| 479 |
|
|
#if flow > 0:
|
| 480 |
|
|
# print "\033[1;31m\tU/O flow: %s\033[1;m"%flow
|
| 481 |
|
|
|
| 482 |
|
|
#ORDER AND ADD TOGETHER
|
| 483 |
|
|
ordnungX=[]
|
| 484 |
|
|
ordnungtypX=[]
|
| 485 |
|
|
num=[0]*len(setup)
|
| 486 |
|
|
#printc('red','','num=%s'%num)
|
| 487 |
|
|
for i in range(0,len(setup)):
|
| 488 |
|
|
#printc('blue','','i am in %s'%setup[i])
|
| 489 |
|
|
for j in range(0,len(systhistosarray[Coco])):
|
| 490 |
|
|
#printc('blue','','i compare %s'%typsX[j])
|
| 491 |
|
|
if typsX[j] == setup[i]:
|
| 492 |
|
|
#print 'yes'
|
| 493 |
|
|
num[i]+=1
|
| 494 |
|
|
ordnungX.append(systhistosarray[Coco][j])
|
| 495 |
|
|
|
| 496 |
|
|
ordnungtypX.append(typsX[j])
|
| 497 |
|
|
#printc('red','','num=%s'%num)
|
| 498 |
|
|
|
| 499 |
|
|
#del systhistosarray[Coco]
|
| 500 |
|
|
del typsX
|
| 501 |
|
|
systhistosarray[Coco]=ordnungX
|
| 502 |
|
|
typsX=ordnungtypX
|
| 503 |
|
|
for k in range(0,len(num)):
|
| 504 |
|
|
for m in range(0,num[k]):
|
| 505 |
|
|
if m > 0:
|
| 506 |
|
|
systhistosarray[Coco][k].Add(systhistosarray[Coco][k+1],1)
|
| 507 |
|
|
#printc('red','','added %s to %s'%(typsX[k],typsX[k+1]))
|
| 508 |
|
|
del systhistosarray[Coco][k+1]
|
| 509 |
|
|
del typsX[k+1]
|
| 510 |
|
|
for i in range(0,len(systhistosarray[Coco])):
|
| 511 |
|
|
systhistosarray[Coco][i].SetName('%sCMS_%s%s'%(discr_names[i],sys,UD[Q]))
|
| 512 |
|
|
systhistosarray[Coco][i].SetDirectory(outfile)
|
| 513 |
|
|
systhistosarray[Coco][i].Write()
|
| 514 |
|
|
#systhistosarray[Coco][i].Draw("goff")
|
| 515 |
|
|
#histosX[i].Write()
|
| 516 |
|
|
|
| 517 |
|
|
histPdf = ROOT.RooDataHist('%sCMS_%s%s'%(discr_names[i],sys,UD[Q]),'%sCMS_%s%s'%(discr_names[i],sys,UD[Q]),obs,systhistosarray[Coco][i])
|
| 518 |
|
|
getattr(WS,'import')(histPdf)
|
| 519 |
|
|
|
| 520 |
|
|
|
| 521 |
|
|
Coco+=1
|
| 522 |
|
|
#print Coco
|
| 523 |
|
|
|
| 524 |
|
|
WS.writeToFile(outpath+'vhbb_WS_'+ROOToutname+'.root')
|
| 525 |
|
|
#WS.writeToFile("testWS.root")
|
| 526 |
|
|
|
| 527 |
|
|
|
| 528 |
|
|
|
| 529 |
|
|
|
| 530 |
|
|
#write DATAcard:
|
| 531 |
|
|
|
| 532 |
|
|
pier = open (Wdir+'/pier.txt','r')
|
| 533 |
|
|
scalefactors=pier.readlines()
|
| 534 |
|
|
pier.close()
|
| 535 |
|
|
|
| 536 |
|
|
f = open(outpath+'vhbb_DC_'+ROOToutname+'.txt','w')
|
| 537 |
|
|
f.write('imax\t1\tnumber of channels\n')
|
| 538 |
peller |
1.2 |
f.write('jmax\t9\tnumber of backgrounds (\'*\' = automatic)\n')
|
| 539 |
peller |
1.1 |
f.write('kmax\t*\tnumber of nuisance parameters (sources of systematical uncertainties)\n\n')
|
| 540 |
|
|
|
| 541 |
peller |
1.2 |
f.write('shapes * * vhbb_WS_%s.root $CHANNEL:$PROCESS $CHANNEL:$PROCESS$SYSTEMATIC\n\n'%ROOToutname)
|
| 542 |
peller |
1.1 |
f.write('bin\t%s\n\n'%options[10])
|
| 543 |
|
|
f.write('observation\t%s\n\n'%d1.Integral())
|
| 544 |
peller |
1.2 |
f.write('bin\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\n'%(options[10],options[10],options[10],options[10],options[10],options[10],options[10],options[10],options[10],options[10]))
|
| 545 |
|
|
f.write('process\tVH\tWjLF\tWjHF\tZjLF\tZjCF\tZjHF\tTT\ts_Top\tVV\tQCD\n')
|
| 546 |
|
|
f.write('process\t0\t1\t2\t3\t4\t5\t6\t7\t8\t9\n')
|
| 547 |
|
|
f.write('rate\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\n'%(histos[6].Integral(),0,0,histos[0].Integral(),histos[1].Integral(),histos[2].Integral(),histos[3].Integral(),histos[5].Integral(),histos[4].Integral(),0)) #\t1.918\t0.000 0.000\t135.831 117.86 18.718 1.508\t7.015\t0.000
|
| 548 |
|
|
|
| 549 |
|
|
|
| 550 |
|
|
f.write('lumi\tlnN\t1.045\t-\t-\t-\t-\t-\t-\t1.045\t1.045\t1.045\n\n')
|
| 551 |
|
|
f.write('pdf_qqbar\tlnN\t1.01\t-\t-\t-\t-\t-\t-\t-\t1.01\t-\n')
|
| 552 |
|
|
f.write('pdf_gg\tlnN\t-\t-\t-\t-\t-\t-\t-\t1.01\t-\t1.01\n')
|
| 553 |
|
|
f.write('QCDscale_VH\tlnN\t1.04\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 554 |
|
|
f.write('QCDscale_ttbar\tlnN\t-\t-\t-\t-\t-\t-\t-\t1.06\t-\t-\n')
|
| 555 |
|
|
f.write('QCDscale_VV\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t1.04\t-\n')
|
| 556 |
|
|
f.write('QCDscale_QCD\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\t1.30\n')
|
| 557 |
|
|
f.write('CMS_vhbb_boost_EWK\tlnN\t1.05\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 558 |
|
|
f.write('CMS_vhbb_boost_QCD\tlnN\t1.10\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 559 |
|
|
f.write('CMS_vhbb_ST\tlnN\t-\t-\t-\t-\t-\t-\t-\t1.29\t-\t-\n')
|
| 560 |
|
|
f.write('CMS_vhbb__VV\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t1.30\t-\n')
|
| 561 |
peller |
1.1 |
|
| 562 |
|
|
for line in scalefactors:
|
| 563 |
|
|
f.write(line)
|
| 564 |
|
|
|
| 565 |
|
|
'''
|
| 566 |
|
|
f.write('CMS_vhbb_WjLF_SF\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 567 |
|
|
f.write('CMS_vhbb_WjHF_SF\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 568 |
|
|
f.write('CMS_vhbb_ZjLF_SF\tlnN\t-\t-\t-\t1.06\t-\t-\t-\t-\t-\n')
|
| 569 |
|
|
f.write('CMS_vhbb_ZjHF_SF\tlnN\t-\t-\t-\t-\t1.17\t-\t-\t-\t-\n')
|
| 570 |
|
|
f.write('CMS_vhbb_TT_SF\tlnN\t-\t-\t-\t-\t-\t1.14\t-\t-\t-\n')
|
| 571 |
|
|
f.write('CMS_vhbb_QCD_SF\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 572 |
|
|
'''
|
| 573 |
|
|
|
| 574 |
peller |
1.2 |
f.write('CMS_trigger_m\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 575 |
|
|
f.write('CMS_trigger_e\tlnN\t1.02\t-\t-\t-\t-\t-\t-\t1.02\t1.02\t-\n')
|
| 576 |
|
|
f.write('CMS_vhbb_trigger_MET\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 577 |
peller |
1.1 |
'''
|
| 578 |
|
|
f.write('CMS_eff_m\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 579 |
|
|
f.write('CMS_eff_e\tlnN\t1.04\t-\t-\t-\t-\t-\t1.04\t1.04\t1.04\n')
|
| 580 |
|
|
f.write('CMS_toteff_b\tlnN\t1.10\t1.10\t1.00\t1.10\t1.00\t1.10\t1.10\t1.10\t1.10\n')
|
| 581 |
|
|
f.write('CMS_totscale_j\tlnN\t1.02\t-\t-\t-\t-\t-\t1.02\t1.02\t-\n')
|
| 582 |
|
|
f.write('CMS_totres_j\tlnN\t1.05\t1.03\t1.03\t1.03\t1.03\t1.03\t1.03\t1.05\t-\n')
|
| 583 |
|
|
f.write('CMS_vhbb_MET_nojets\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 584 |
|
|
f.write('CMS_vhbb_stats_VH_Wmn\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 585 |
|
|
f.write('CMS_vhbb_stats_WjLF_Wmn\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 586 |
|
|
f.write('CMS_vhbb_stats_WjHF_Wmn\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 587 |
|
|
f.write('CMS_vhb_stats_ZjLF_Wmn\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 588 |
|
|
f.write('CMS_vhbb_stats_ZjHF_Wmn\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 589 |
|
|
f.write('CMS_vhbb_stats_TT_Wmn\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 590 |
|
|
f.write('CMS_vhbb_stats_sT_Wmn\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 591 |
|
|
f.write('CMS_vhbb_stats_VV_Wmn\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 592 |
|
|
f.write('CMS_vhbb_stats_QCD_Wmn\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 593 |
|
|
f.write('CMS_vhbb_stats_Wen\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 594 |
|
|
f.write('CMS_vhbb_stats_WjLF_Wen\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 595 |
|
|
f.write('CMS_vhbb_stats_WjHF_Wen\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 596 |
|
|
f.write('CMS_vhb_stats_ZjLF_Wen\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 597 |
|
|
f.write('CMS_vhbb_stats_ZjHF_Wen\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 598 |
|
|
f.write('CMS_vhbb_stats_TT_Wen\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 599 |
|
|
f.write('CMS_vhbb_stats_sT_Wen\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 600 |
|
|
f.write('CMS_vhbb_stats_VV_Wen\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 601 |
|
|
f.write('CMS_vhbb_stats_QCD_Wen\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 602 |
|
|
f.write('CMS_vhbb_stats_VH_Zmm\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 603 |
|
|
f.write('CMS_vhbb_stats_WjLF_Zmm\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 604 |
|
|
f.write('CMS_vhbb_stats_WjHF_Zmm\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 605 |
|
|
f.write('CMS_vhb_stats_ZjLF_Zmm\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 606 |
|
|
f.write('CMS_vhbb_stats_ZjHF_Zmm\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 607 |
|
|
f.write('CMS_vhbb_stats_TT_Zmm\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 608 |
|
|
f.write('CMS_vhbb_stats_sT_Zmm\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 609 |
|
|
f.write('CMS_vhbb_stats_VV_Zmm\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 610 |
|
|
f.write('CMS_vhbb_stats_QCD_Zmm\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 611 |
|
|
f.write('CMS_vhbb_stats_VH_Zee\tlnN\t1.03\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 612 |
|
|
f.write('CMS_vhbb_stats_WjLF_Zee\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 613 |
|
|
f.write('CMS_vhbb_stats_WjHF_Zee\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 614 |
|
|
f.write('CMS_vhb_stats_ZjLF_Zee\tlnN\t-\t-\t-\t1.05\t-\t-\t-\t-\t-\n')
|
| 615 |
|
|
f.write('CMS_vhbb_stats_ZjHF_Zee\tlnN\t-\t-\t-\t-\t1.07\t-\t-\t-\t-\n')
|
| 616 |
|
|
f.write('CMS_vhbb_stats_TT_Zee\tlnN\t-\t-\t-\t-\t-\t1.06\t-\t-\t-\n')
|
| 617 |
|
|
f.write('CMS_vhbb_stats_sT_Zee\tlnN\t-\t-\t-\t-\t-\t-\t1.30\t-\t-\n')
|
| 618 |
|
|
f.write('CMS_vhbb_stats_Diboson_Zee\tlnN\t-\t-\t-\t-\t-\t-\t-\t1.06\t-\n')
|
| 619 |
|
|
f.write('CMS_vhbb_stats_QCD_Zee\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 620 |
|
|
f.write('CMS_vhbb_stats_VH_Znn\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 621 |
|
|
f.write('CMS_vhbb_stats_WjLF_Znn\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 622 |
|
|
f.write('CMS_vhbb_stats_WjHF_Znn\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 623 |
|
|
f.write('CMS_vhb_stats_ZjLF_Znn\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 624 |
|
|
f.write('CMS_vhbb_stats_ZjHF_Znn\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 625 |
|
|
f.write('CMS_vhbb_stats_TT_Znn\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 626 |
|
|
f.write('CMS_vhbb_stats_sT_Znn\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 627 |
|
|
f.write('CMS_vhbb_stats_VV_Znn\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 628 |
|
|
f.write('CMS_vhbb_stats_QCD_Znn\tlnN\t-\t-\t-\t-\t-\t-\t-\t-\t-\n')
|
| 629 |
|
|
'''
|
| 630 |
|
|
#STATS
|
| 631 |
|
|
#f.write('Stats\tshape\t1.0\t-\t-\t1.0\t1.0\t1.0\t1.0\t1.0\t-\n')
|
| 632 |
|
|
|
| 633 |
|
|
|
| 634 |
|
|
# discr_names = ['Zudscg', 'Zbb', 'TTbar','VV', 'ST', 'Sig115', 'Wudscg', 'Wbb', 'QCD']
|
| 635 |
|
|
|
| 636 |
|
|
'''
|
| 637 |
|
|
f.write('Sig%sStats\tshape\t1.0\t-\t-\t-\t-\t-\t-\t-\t-\n'%mass[2:5])
|
| 638 |
|
|
#f.write('Stats\tshape\t-\t1.0\t-\t-\t-\t-\t-\t-\t-\n')
|
| 639 |
|
|
#f.write('Stats\tshape\t-\t-\t1.0\t-\t-\t-\t-\t-\t-\n')
|
| 640 |
|
|
f.write('ZudscgStats\tshape\t-\t-\t-\t1.0\t-\t-\t-\t-\t-\n')
|
| 641 |
|
|
f.write('ZbbStats\tshape\t-\t-\t-\t-\t1.0\t-\t-\t-\t-\n')
|
| 642 |
|
|
f.write('TTbarStats\tshape\t-\t-\t-\t-\t-\t1.0\t-\t-\t-\n')
|
| 643 |
|
|
f.write('STStats\tshape\t-\t-\t-\t-\t-\t-\t1.0\t-\t-\n')
|
| 644 |
|
|
f.write('VVStats\tshape\t-\t-\t-\t-\t-\t-\t-\t1.0\t-\n')
|
| 645 |
|
|
#f.write('Stats\tshape\t-\t-\t-\t-\t-\t-\t-\t-\t1.0\n')
|
| 646 |
|
|
'''
|
| 647 |
|
|
|
| 648 |
peller |
1.2 |
f.write('CMS_vhbb_stats_VH_%s\tshape\t1.0\t-\t-\t-\t-\t-\t-\t-\t-\t-\n'%options[10])
|
| 649 |
peller |
1.1 |
#f.write('Stats\tshape\t-\t1.0\t-\t-\t-\t-\t-\t-\t-\n')
|
| 650 |
|
|
#f.write('Stats\tshape\t-\t-\t1.0\t-\t-\t-\t-\t-\t-\n')
|
| 651 |
peller |
1.2 |
f.write('CMS_vhbb_stats_ZjLF_%s\tshape\t-\t-\t-\t1.0\t-\t-\t-\t-\t-\t-\n'%options[10])
|
| 652 |
|
|
f.write('CMS_vhbb_stats_ZjCF_%s\tshape\t-\t-\t-\t-\t1.0\t-\t-\t-\t-\t-\n'%options[10])
|
| 653 |
|
|
f.write('CMS_vhbb_stats_ZjHF_%s\tshape\t-\t-\t-\t-\t-\t1.0\t-\t-\t-\t-\n'%options[10])
|
| 654 |
|
|
f.write('CMS_vhbb_stats_TT_%s\tshape\t-\t-\t-\t-\t-\t-\t1.0\t-\t-\t-\n'%options[10])
|
| 655 |
|
|
f.write('CMS_vhbb_stats_s_Top_%s\tshape\t-\t-\t-\t-\t-\t-\t-\t1.0\t-\t-\n'%options[10])
|
| 656 |
|
|
f.write('CMS_vhbb_stats_VV_%s\tshape\t-\t-\t-\t-\t-\t-\t-\t-\t1.0\t-\n'%options[10])
|
| 657 |
peller |
1.1 |
#f.write('Stats\tshape\t-\t-\t-\t-\t-\t-\t-\t-\t1.0\n')
|
| 658 |
|
|
|
| 659 |
|
|
#Sig115 Wudscg Wbb Zudscg Zbb TTbar ST VV QCD
|
| 660 |
|
|
|
| 661 |
|
|
#SYST
|
| 662 |
peller |
1.2 |
f.write('CMS_JER\tshape\t1.0\t-\t-\t1.0\t1.0\t1.0\t1.0\t1.0\t1.0\t-\n')
|
| 663 |
|
|
f.write('CMS_JES\tshape\t1.0\t-\t-\t1.0\t1.0\t1.0\t1.0\t1.0\t1.0\t-\n')
|
| 664 |
|
|
f.write('CMS_beff\tshape\t1.0\t-\t-\t1.0\t1.0\t1.0\t1.0\t1.0\t1.0\t-\n')
|
| 665 |
|
|
f.write('CMS_bmis\tshape\t1.0\t-\t-\t1.0\t1.0\t1.0\t1.0\t1.0\t1.0\t-\n')
|
| 666 |
peller |
1.1 |
|
| 667 |
|
|
|
| 668 |
|
|
f.close()
|
| 669 |
|
|
|
| 670 |
|
|
|
| 671 |
|
|
outfile.Write()
|
| 672 |
|
|
outfile.Close()
|
| 673 |
|
|
|
| 674 |
|
|
|
| 675 |
|
|
|
| 676 |
|
|
|
| 677 |
|
|
|
