def getPlotters(samples, isData=False, corr="1"):
sampleTypes = samples.split(',')
plotters = []
for filename in os.listdir('samples'):
for sampleType in sampleTypes:
if filename.find(sampleType) != -1:
fnameParts = filename.split('.')
fname = fnameParts[0]
ext = fnameParts[1]
if ext.find("root") == -1:
continue
print 'Adding file', fname
plotters.append(
TreePlotter('samples/' + fname + '.root', 'tree'))
if not isData:
plotters[-1].setupFromFile('samples/' + fname + '.pck')
plotters[-1].addCorrectionFactor('xsec', 'tree')
plotters[-1].addCorrectionFactor('genWeight', 'tree')
plotters[-1].addCorrectionFactor('puWeight', 'tree')
plotters[-1].addCorrectionFactor('lnujj_sf', 'tree')
plotters[-1].addCorrectionFactor('truth_genTop_weight',
'tree')
plotters[-1].addCorrectionFactor(corr, 'flat')
return plotters
def __init__(self, directory, filenames, isData):
self.dataPlotters = []
sampleTypes = filenames.split(',')
for filename in os.listdir(directory):
for sampleType in sampleTypes:
if filename.find(sampleType) != -1:
fnameParts = filename.split('.')
fname = fnameParts[0]
ext = fnameParts[1]
if ext.find("root") == -1:
continue
self.dataPlotters.append(
TreePlotter(directory + '/' + fname + '.root', 'tree'))
if not isData:
self.dataPlotters[-1].setupFromFile(directory + '/' +
fname + '.pck')
self.dataPlotters[-1].addCorrectionFactor(
'xsec', 'tree')
self.dataPlotters[-1].addCorrectionFactor(
'genWeight', 'tree')
self.dataPlotters[-1].addCorrectionFactor(
'puWeight', 'tree')
self.plotter = MergedPlotter(self.dataPlotters)
samples[mass] = fname
print 'found', filename, 'mass', str(mass)
scaleFactors = options.scaleFactors.split(',')
#Now we have the samples: Sort the masses and run the fits
N = 0
Fhists = ROOT.TFile("massHISTOS_" + options.output, "RECREATE")
for mass in sorted(samples.keys()):
print 'fitting', str(mass)
plotter = TreePlotter(args[0] + '/' + samples[mass] + '.root', 'tree')
plotter.addCorrectionFactor('genWeight', 'tree')
plotter.addCorrectionFactor('puWeight', 'tree')
if options.scaleFactors != '':
for s in scaleFactors:
plotter.addCorrectionFactor(s, 'tree')
fitter = Fitter(['MVV'])
fitter.signalResonanceCBGaus('model', 'MVV', mass)
if options.fixPars != "1":
fixedPars = options.fixPars.split(',')
print fixedPars
for par in fixedPars:
parVal = par.split(':')
if len(parVal) > 1:
fitter.w.var(parVal[0]).setVal(float(parVal[1]))
samples[mass] = fname
print 'found',filename,'mass',str(mass)
#Now we have the samples: Sort the masses and run the fits
N=0
for mass in sorted(samples.keys()):
if mass<999:
continue
print 'fitting',str(mass)
plotter=TreePlotter(args[0]+'/'+samples[mass]+'.root','tree')
plotter.setupFromFile(args[0]+'/'+samples[mass]+'.pck')
plotter.addCorrectionFactor('genWeight','tree')
plotter.addCorrectionFactor('xsec','tree')
plotter.addCorrectionFactor('puWeight','tree')
fitter=Fitter(['m','M'])
fitter.signal2D('model',options.boson)
fitter.w.var("MH").setVal(mass)
histo = plotter.drawTH2(options.mjj+":"+options.mvv,options.cutShape,"1",500,0,13000,120,60,140)
histoYield = plotter.drawTH2(options.mjj+":"+options.mvv,options.cutYield,"1",130,0,13000,100,25,165)
fitter.importBinnedData(histo,['M','m'],'data')
fitter.fit('model','data',[ROOT.RooFit.SumW2Error(1)])
import ROOT
from CMGTools.VVResonances.plotting.TreePlotter import TreePlotter
from CMGTools.VVResonances.plotting.MergedPlotter import MergedPlotter
from CMGTools.VVResonances.plotting.StackPlotter import StackPlotter
#create the W+jets plotters
wjPlotters = []
for sample in [
"WJetsToLNu_HT1200to2500", "WJetsToLNu_HT2500toInf",
"WJetsToLNu_HT400to600", "WJetsToLNu_HT600to800",
"WJetsToLNu_HT800to1200", 'WJetsToLNu_HT100to200',
'WJetsToLNu_HT200to400'
]:
wjPlotters.append(TreePlotter('samples/' + sample + '.root', 'tree'))
wjPlotters[-1].setupFromFile('samples/' + sample + '.pck')
wjPlotters[-1].addCorrectionFactor('xsec', 'tree')
wjPlotters[-1].addCorrectionFactor('genWeight', 'tree')
wjPlotters[-1].addCorrectionFactor('puWeight', 'tree')
WJets = MergedPlotter(wjPlotters)
tt = TreePlotter('samples/TTJets.root', 'tree')
tt.setupFromFile('samples/TTJets.pck')
tt.addCorrectionFactor('xsec', 'tree')
tt.addCorrectionFactor('genWeight', 'tree')
tt.addCorrectionFactor('puWeight', 'tree')
#create the Z+jets plotters
ext = fnameParts[1]
if ext.find("root") == -1:
continue
mass = float(fname.split('_')[-1])
samples[mass] = fname
print 'found', filename, 'mass', str(mass)
#Now we have the samples: Sort the masses and run the fits
N = 0
for mass in sorted(samples.keys()):
print 'fitting', str(mass)
plotter = TreePlotter(args[0] + '/' + samples[mass] + '.root', 'tree')
plotter.setupFromFile(args[0] + '/' + samples[mass] + '.pck')
plotter.addCorrectionFactor('genWeight', 'tree')
plotter.addCorrectionFactor('xsec', 'tree')
plotter.addCorrectionFactor('puWeight', 'tree')
fitter = Fitter(['m', 'M'])
fitter.signal2D('model', options.boson)
fitter.w.var("MH").setVal(mass)
histo = plotter.drawTH2(options.mjj + ":" + options.mvv, options.cutShape,
"1", 500, 0, 13000, 120, 25, 165)
histoYield = plotter.drawTH2(options.mjj + ":" + options.mvv,
options.cutYield, "1", 130, 0, 13000, 100, 25,
165)
fitter.importBinnedData(histo, ['M', 'm'], 'data')
def getPlotters(samples, sampleDir, isData=False, corr="1"):
sampleTypes = samples.split(',')
plotters = []
pcuts = []
filelist = []
if sampleDir == 'ntuples':
filelist = [
g for flist in [[(path + '/' + f)
for f in os.listdir(sampleDir + '/' + path)]
for path in os.listdir(sampleDir)] for g in flist
]
else:
filelist = os.listdir(sampleDir)
for filename in filelist:
for sampleType in sampleTypes:
if filename.find(sampleType) != -1:
fnameParts = filename.split('.')
fname = fnameParts[0]
ext = fnameParts[1]
if ext.find("root") == -1:
continue
fpath = sampleDir + '/' + fname
print 'Adding file', fpath
plotters.append(TreePlotter(fpath + '.root', 'tree'))
## Fix for cuts and weights for which the branches differ between years:
if "ntuples2016" in fpath:
pcuts.append(
'(HLT_MU||HLT_ELE||HLT_ISOMU||HLT_ISOELE||HLT_MET||HLT_PHOTON)*L1PrefireWeight'
)
elif "ntuples2017" in fpath:
pcuts.append(
'(HLT_MU||HLT_ELE||HLT_ISOMU||HLT_ISOELE||HLT_MET||HLT_PHOTON)*L1PrefireWeight'
)
elif "ntuples2018" in fpath:
pcuts.append(
'(HLT_MU||HLT_ELE||HLT_ISOMU||HLT_ISOELE||HLT_MET)')
else:
sys.exit("Year not found, aborting.")
if not isData:
plotters[-1].setupFromFile(fpath + '.pck')
plotters[-1].addCorrectionFactor('xsec', 'tree')
plotters[-1].addCorrectionFactor('genWeight', 'tree')
plotters[-1].addCorrectionFactor('puWeight', 'tree')
plotters[-1].addCorrectionFactor('truth_genTop_weight',
'branch')
##plotters[-1].addCorrectionFactor('lnujj_sfWV','branch')
##plotters[-1].addCorrectionFactor('lnujj_btagWeight','branch')
plotters[-1].addCorrectionFactor(corr, 'flat')
#''' ## remove the Madgraph background NLO k-factors
if REMOVEBKGDKFAC:
if fname.find("WJetsToLNu_HT") != -1:
wjetsAntiKFactor = 1. / 1.21
plotters[-1].addCorrectionFactor(
wjetsAntiKFactor, 'flat')
print ' reweighting ' + fpath + ' ' + str(
wjetsAntiKFactor)
elif fname.find("DYJetsToLL_M50_HT") != -1:
dyAntiKFactor = 1. / 1.23
plotters[-1].addCorrectionFactor(
dyAntiKFactor, 'flat')
print ' reweighting ' + fpath + ' ' + str(
dyAntiKFactor)
#'''
#''' ## rescale the W+jets yields (the current factors were computed from 30 < mjet < 50 GeV, on top of the NLO k-factors)
if RESCALEWJETS:
if fname.find("WJetsToLNu_HT") != -1:
wjetsFactor = 1.
if "ntuples2016" in fpath: wjetsFactor = 1.022
elif "ntuples2017" in fpath: wjetsFactor = 0.926
elif "ntuples2018" in fpath: wjetsFactor = 0.860
plotters[-1].addCorrectionFactor(
wjetsFactor, 'flat')
print ' reweighting ' + fpath + ' ' + str(
wjetsFactor)
#'''
return MergedPlotter(plotters, pcuts)
ext = fnameParts[1]
if ext.find("root") == -1:
continue
mass = float(fname.split('_')[-1])
samples[mass] = fname
print 'found', filename, 'mass', str(mass)
#Now we have the samples: Sort the masses and run the fits
N = 0
for mass in sorted(samples.keys()):
print 'fitting', str(mass)
plotter = TreePlotter(args[0] + '/' + samples[mass] + '.root', 'tree')
# plotter.setupFromFile(args[0]+'/'+samples[mass]+'.pck')
plotter.addCorrectionFactor('genWeight', 'tree')
# plotter.addCorrectionFactor('xsec','tree')
plotter.addCorrectionFactor('puWeight', 'tree')
fitter = Fitter(['x'])
fitter.jetResonance('model', 'x')
# fitter.w.var("MH").setVal(mass)
histo = plotter.drawTH1(options.mvv, options.cut, "1", 40, 40, 160)
fitter.importBinnedData(histo, ['x'], 'data')
fitter.fit('model', 'data', [ROOT.RooFit.SumW2Error(0)])
fitter.fit('model', 'data',
[ROOT.RooFit.SumW2Error(0),
ROOT.RooFit.Minos(1)])
ext = fnameParts[1]
if ext.find("root") == -1:
continue
mass = float(fname.split('_')[-1])
samples[mass] = fname
print 'found', filename, 'mass', str(mass)
#Now we have the samples: Sort the masses and run the fits
N = 0
for mass in sorted(samples.keys()):
print 'fitting', str(mass)
plotter = TreePlotter(args[0] + '/' + samples[mass] + '.root', 'tree')
# plotter.setupFromFile(args[0]+'/'+samples[mass]+'.pck')
plotter.addCorrectionFactor('genWeight', 'tree')
# plotter.addCorrectionFactor('xsec','tree')
plotter.addCorrectionFactor('puWeight', 'tree')
fitter = Fitter(['MVV', 'MJJ'])
fitter.signal2D('model', ['MVV', 'MJJ'])
fitter.w.var("MH").setVal(mass)
histo = plotter.drawTH2(options.mjj + ':' + options.mvv, options.cut, "1",
500, 0, 6000, 100, options.minMJJ, options.maxMJJ)
fitter.importBinnedData(histo, ['MVV', 'MJJ'], 'data')
fitter.fit('model', 'data', [ROOT.RooFit.SumW2Error(0)])
fitter.fit('model', 'data', [ROOT.RooFit.SumW2Error(0)])
name = fname.split('_')[0]
samples[name] = fname
print 'found', filename
sigmas = []
params = {}
NRes = [0, 0]
NnonRes = [0, 0]
legs = ["l1", "l2"]
plotters = []
for name in samples.keys():
plotters.append(
TreePlotter(args[0] + '/' + samples[name] + '.root', 'tree'))
plotters[-1].setupFromFile(args[0] + '/' + samples[name] + '.pck')
plotters[-1].addCorrectionFactor('xsec', 'tree')
plotters[-1].addCorrectionFactor('genWeight', 'tree')
plotters[-1].addCorrectionFactor('puWeight', 'tree')
corrFactor = options.corrFactorW
if samples[name].find('Z') != -1: corrFactor = options.corrFactorZ
plotters[-1].addCorrectionFactor(corrFactor, 'flat')
plotter = MergedPlotter(plotters)
print 'Fitting Mjet:'
for leg in legs:
mass = float(fname.split('_')[-1])
if mass < options.minMass:
continue
samples[mass] = fname
print 'found', filename, 'mass', str(mass)
#Now we have the samples: Sort the masses and run the fits
N = 0
for mass in sorted(samples.keys()):
print 'fitting', str(mass)
plotter = TreePlotter(args[0] + '/' + samples[mass] + '.root', 'tree')
plotter.setupFromFile(args[0] + '/' + samples[mass] + '.pck')
plotter.addCorrectionFactor('genWeight', 'tree')
plotter.addCorrectionFactor('xsec', 'tree')
plotter.addCorrectionFactor('puWeight', 'tree')
histo = plotter.drawTH1(
options.mvv, options.cut + '*(jj_LV_mass>%f&&jj_LV_mass<%f)' %
(mass * 0.8, mass * 1.2), "1", 500, options.min, options.max)
err = ROOT.Double(0)
integral = histo.IntegralAndError(1, histo.GetNbinsX(), err)
yieldgraph.SetPoint(N, mass, integral * options.BR)
yieldgraph.SetPointError(N, 0.0, err * options.BR)
N = N + 1
func = ROOT.TF1("func", options.function, 0, 13000)
from CMGTools.VVResonances.plotting.StackPlotter import StackPlotter
#create the W+jets plotters
wjPlotters=[]
for sample in ['WJetsToLNu_HT100to200','WJetsToLNu_HT200to400','WJetsToLNu_HT400to600','WJetsToLNu_HT600toInf']:
wjPlotters.append(TreePlotter('samples/'+sample+'.root','tree'))
wjPlotters[-1].setupFromFile('samples/'+sample+'.pck')
wjPlotters[-1].addCorrectionFactor('xsec','xsec',0.0,'lnN')
wjPlotters[-1].addCorrectionFactor('genWeight','genWeight',0.0,'lnN')
WJets = MergedPlotter(wjPlotters)
WJets.setFillProperties(1001,ROOT.kAzure-9)
RSGWWLNuQQ = TreePlotter('samples/RSGravToWWToLNQQ_kMpl01_2500.root','tree')
RSGWWLNuQQ.setupFromFile('samples/RSGravToWWToLNQQ_kMpl01_2500.pck')
RSGWWLNuQQ.setFillProperties(0,ROOT.kWhite)
RSGWWLNuQQ.setLineProperties(1,ROOT.kOrange+10,3)
RSGWWLNuQQ.addCorrectionFactor('xsec',0.001,0.0,'lnN')
#Stack
vvStack = StackPlotter()
vvStack.addPlotter(WJets,"W+jets","W+Jets","background")
vvStack.addPlotter(RSGWWLNuQQ,"RSG2000","RSGWW #rightarrow l#nu QQ","signal")
samples[mass] = fname
print 'found',filename,'mass',str(mass)
scaleFactors=options.scaleFactors.split(',')
#Now we have the samples: Sort the masses and run the fits
N=0
for mass in sorted(samples.keys()):
if mass>6000: continue
print 'fitting',str(mass)
plotter=TreePlotter(args[0]+'/'+samples[mass]+'.root','tree')
plotter.addCorrectionFactor('genWeight','tree')
plotter.addCorrectionFactor('puWeight','tree')
if options.scaleFactors!='':
for s in scaleFactors:
plotter.addCorrectionFactor(s,'tree')
fitter=Fitter(['MVV'])
fitter.signalResonanceCBGaus('model','MVV',mass)
fitter.w.var("MH").setVal(mass)
histo = plotter.drawTH1(options.mvv,options.cut+"*(jj_LV_mass>%f&&jj_LV_mass<%f)"%(0.8*mass,1.2*mass),"1",140,700,8000)
fitter.importBinnedData(histo,['MVV'],'data')
fitter.fit('model','data',[ROOT.RooFit.SumW2Error(0)])#,ROOT.RooFit.Range(1000,8000)])
if mass < options.minMX or mass > options.maxMX: continue
samples[mass] = fname
print 'found',filename,'mass',str(mass)
leg = options.mvv.split('_')[1]
#Now we have the samples: Sort the masses and run the fits
N=0
for mass in sorted(samples.keys()):
print 'fitting',str(mass)
plotter=TreePlotter(args[0]+'/'+samples[mass]+'.root','tree')
# plotter.setupFromFile(args[0]+'/'+samples[mass]+'.pck')
plotter.addCorrectionFactor('genWeight','tree')
# plotter.addCorrectionFactor('xsec','tree')
plotter.addCorrectionFactor('puWeight','tree')
fitter=Fitter(['x'])
if options.doExp==1:
fitter.jetResonance('model','x')
else:
fitter.jetResonanceNOEXP('model','x')
if options.fixPars!="1":
fixedPars =options.fixPars.split(',')
lumi_13TeV = "12.9 fb^{-1}"
lumi_sqrtS = "13 TeV" # used with iPeriod = 0, e.g. for simulation-only plots (default is an empty string)
iPeriod = 4
iPos = 11
#create the W+jets plotters
wjPlotters = []
for sample in [
"WJetsToLNu_HT1200to2500", "WJetsToLNu_HT2500toInf",
"WJetsToLNu_HT400to600", "WJetsToLNu_HT600to800",
"WJetsToLNu_HT800to1200", 'WJetsToLNu_HT100to200',
'WJetsToLNu_HT200to400'
]:
#for sample in ["WJetsToLNu_HT1200to2500","WJetsToLNu_HT2500toInf","WJetsToLNu_HT400to600","WJetsToLNu_HT600to800","WJetsToLNu_HT800to1200",'WJetsToLNu_HT100to200','WJetsToLNu_HT200to400']:
wjPlotters.append(TreePlotter('samples/' + sample + '.root', 'tree'))
wjPlotters[-1].setupFromFile('samples/' + sample + '.pck')
wjPlotters[-1].addCorrectionFactor('xsec', 'tree')
wjPlotters[-1].addCorrectionFactor('genWeight', 'tree')
wjPlotters[-1].addCorrectionFactor('puWeight', 'tree')
# wjPlotters[-1].addCorrectionFactor('0.82','flat')
WJets = MergedPlotter(wjPlotters)
ttO = TreePlotter('samples/TTJets.root', 'tree')
ttO.setupFromFile('samples/TTJets.pck')
ttO.addCorrectionFactor('xsec', 'tree')
ttO.addCorrectionFactor('genWeight', 'tree')
ttO.addCorrectionFactor('puWeight', 'tree')
ttO.addCorrectionFactor(
'(!(lnujj_l2_mergedVTruth==1&&lnujj_l2_nearestBDRTruth>0.8))', 'tree')
def loadSignalNtuples(samples, sampleDir, minMX, maxMX, corr=1.):
sampleTypes = samples.split(',')
plotters = {}
pcuts = {}
filelist = []
if sampleDir == 'ntuples':
filelist = [
g for flist in [[(path + '/' + f)
for f in os.listdir(sampleDir + '/' + path)]
for path in os.listdir(sampleDir)] for g in flist
]
else:
filelist = os.listdir(sampleDir)
for filename in filelist:
for sampleType in sampleTypes:
if filename.find(sampleType) != -1:
fnameParts = filename.split('.')
fname = fnameParts[0]
ext = fnameParts[1]
if ext.find("root") == -1:
continue
fpath = sampleDir + '/' + fname
mass = float(fname.split('_')[-1])
if mass < minMX or mass > maxMX:
continue
if not mass in plotters.keys():
plotters[mass] = []
pcuts[mass] = []
plotters[mass].append(TreePlotter(fpath + '.root', 'tree'))
## Fix for cuts and weights for which the branches differ between years:
if "ntuples2016" in fpath:
pcuts[mass].append(
'(HLT_MU||HLT_ELE||HLT_ISOMU||HLT_ISOELE||HLT_MET||HLT_PHOTON)*L1PrefireWeight'
)
elif "ntuples2017" in fpath:
pcuts[mass].append(
'(HLT_MU||HLT_ELE||HLT_ISOMU||HLT_ISOELE||HLT_MET||HLT_PHOTON)*L1PrefireWeight'
)
elif "ntuples2018" in fpath:
pcuts[mass].append(
'(HLT_MU||HLT_ELE||HLT_ISOMU||HLT_ISOELE||HLT_MET)')
else:
sys.exit("Year not found, aborting.")
plotters[mass][-1].setupFromFile(fpath + '.pck')
plotters[mass][-1].addCorrectionFactor('xsec', 'tree')
plotters[mass][-1].addCorrectionFactor('genWeight', 'tree')
plotters[mass][-1].addCorrectionFactor('puWeight', 'tree')
#plotters[mass][-1].addCorrectionFactor('lnujj_sfWV','branch')
#plotters[mass][-1].addCorrectionFactor('lnujj_btagWeight','branch')
plotters[mass][-1].addCorrectionFactor(corr, 'flat')
plotters[mass][-1].filename = fname
print 'found', fpath, 'mass', str(mass)
mergedplotters = {}
for mass in sorted(plotters.keys()):
if len(plotters[mass]) != (
1, (3, 2)['Wprime_VBF_Wh_Wlephinc_narrow' in samples]
)[sampleDir == 'ntuples']: ##FIXME: rechange when 2017 VBFWH is ready
continue
mergedplotters[mass] = MergedPlotter(plotters[mass], pcuts[mass])
return mergedplotters
import ROOT
from CMGTools.VVResonances.plotting.TreePlotter import TreePlotter
from CMGTools.VVResonances.plotting.MergedPlotter import MergedPlotter
from CMGTools.VVResonances.plotting.StackPlotter import StackPlotter
#create the W+jets plotters
wjPlotters = []
for sample in [
'WJetsToLNu_HT100to200', 'WJetsToLNu_HT200to400',
'WJetsToLNu_HT400to600', 'WJetsToLNu_HT600toInf'
]:
wjPlotters.append(TreePlotter('samples/' + sample + '.root', 'tree'))
wjPlotters[-1].setupFromFile('samples/' + sample + '.pck')
wjPlotters[-1].addCorrectionFactor('xsec', 'xsec', 0.0, 'lnN')
WJets = MergedPlotter(wjPlotters)
WJets.setFillProperties(1001, ROOT.kAzure - 9)
RSGWWLNuQQ = TreePlotter('samples/RSGravToWWToLNQQ_2000.root', 'tree')
RSGWWLNuQQ.setupFromFile('samples/RSGravToWWToLNQQ_2000.pck')
RSGWWLNuQQ.setFillProperties(0, ROOT.kWhite)
RSGWWLNuQQ.setLineProperties(1, ROOT.kOrange + 10, 3)
#RSGWWLNuQQ..addCorrectionFactor('xsec',0.001,0.0,'lnN')
#Stack
vvStack = StackPlotter()
vvStack.addPlotter(WJets, "W+jets", "W+Jets", "background")
vvStack.addPlotter(RSGWWLNuQQ, "RSG2000", "RSGWW #rightarrow l#nu QQ",
import ROOT
from CMGTools.VVResonances.plotting.TreePlotter import TreePlotter
from CMGTools.VVResonances.plotting.MergedPlotter import MergedPlotter
from CMGTools.VVResonances.plotting.StackPlotter import StackPlotter
#create the W+jets plotters
wjPlotters=[]
for sample in ["WJetsToLNu_HT1200to2500","WJetsToLNu_HT2500toInf","WJetsToLNu_HT400to600","WJetsToLNu_HT600to800","WJetsToLNu_HT800to1200",'WJetsToLNu_HT100to200','WJetsToLNu_HT200to400']:
wjPlotters.append(TreePlotter('samples/'+sample+'.root','tree'))
wjPlotters[-1].setupFromFile('samples/'+sample+'.pck')
wjPlotters[-1].addCorrectionFactor('xsec','tree')
wjPlotters[-1].addCorrectionFactor('genWeight','tree')
wjPlotters[-1].addCorrectionFactor('puWeight','tree')
WJets = MergedPlotter(wjPlotters)
tt=TreePlotter('samples/TTJets.root','tree')
tt.setupFromFile('samples/TTJets.pck')
tt.addCorrectionFactor('xsec','tree')
tt.addCorrectionFactor('genWeight','tree')
tt.addCorrectionFactor('puWeight','tree')
#create the Z+jets plotters
import ROOT
from CMGTools.VVResonances.plotting.TreePlotter import TreePlotter
from CMGTools.VVResonances.plotting.StackPlotter import StackPlotter
ROOT.gROOT.ProcessLine('.x tdrstyle.C')
w = TreePlotter('samples/W.root','tree')
w.addCorrectionFactor('xsec','xsec',0.0,'lnN')
w.addCorrectionFactor('mc','l_mcPt>0',0.0,'lnN')
w.setFillProperties(0,ROOT.kWhite)
w.setLineProperties(1,ROOT.kOrange+10,3)
qcd = TreePlotter('samples/W.root','tree')
qcd.addCorrectionFactor('xsec','xsec',0.0,'lnN')
qcd.addCorrectionFactor('mc','l_mcPt==0',0.0,'lnN')
qcd.setFillProperties(3003,ROOT.kBlue)
qcd.setLineProperties(1,ROOT.kBlue,3)
#Stack
lStack = StackPlotter()
lStack.addPlotter(qcd,"QCD","Non prompt","background")
lStack.addPlotter(w,"Prompt_leptons","Prompt","signal")
import ROOT
from CMGTools.VVResonances.plotting.TreePlotter import TreePlotter
from CMGTools.VVResonances.plotting.MergedPlotter import MergedPlotter
from CMGTools.VVResonances.plotting.StackPlotter import StackPlotter
#create the W+jets plotters
wjPlotters=[]
WJets = TreePlotter('samples/WJetsToLNu_50ns.root','tree')
WJets.setupFromFile('samples/WJetsToLNu_50ns.pck')
WJets.addCorrectionFactor('xsec','xsec',0.0,'lnN')
WJets.addCorrectionFactor('genWeight','genWeight',0.0,'lnN')
WJets.setFillProperties(1001,ROOT.kAzure-9)
TTJets = TreePlotter('samples/TTJets_50ns.root','tree')
TTJets.setupFromFile('samples/TTJets_50ns.pck')
TTJets.addCorrectionFactor('xsec','xsec',0.0,'lnN')
TTJets.addCorrectionFactor('genWeight','genWeight',0.0,'lnN')
TTJets.setFillProperties(1001,ROOT.kGreen-5)
qcdPlotters=[]
for sample in [
"QCD_Pt1000to1400_50ns","QCD_Pt120to170_50ns","QCD_Pt1400to1800_50ns","QCD_Pt170to300_50ns","QCD_Pt1800to2400_50ns","QCD_Pt2400to3200_50ns","QCD_Pt300to470_50ns","QCD_Pt3200_50ns","QCD_Pt470to600_50ns","QCD_Pt600to800_50ns","QCD_Pt800to1000_50ns","QCD_Pt80to120_50ns"
import ROOT
from CMGTools.VVResonances.plotting.TreePlotter import TreePlotter
from CMGTools.VVResonances.plotting.MergedPlotter import MergedPlotter
from CMGTools.VVResonances.plotting.StackPlotter import StackPlotter
#create the W+jets plotters
wjPlotters = []
WJets = TreePlotter('samples/WJetsToLNu_50ns.root', 'tree')
WJets.setupFromFile('samples/WJetsToLNu_50ns.pck')
WJets.addCorrectionFactor('xsec', 'xsec', 0.0, 'lnN')
WJets.addCorrectionFactor('genWeight', 'genWeight', 0.0, 'lnN')
WJets.setFillProperties(1001, ROOT.kAzure - 9)
TTJets = TreePlotter('samples/TTJets_50ns.root', 'tree')
TTJets.setupFromFile('samples/TTJets_50ns.pck')
TTJets.addCorrectionFactor('xsec', 'xsec', 0.0, 'lnN')
TTJets.addCorrectionFactor('genWeight', 'genWeight', 0.0, 'lnN')
TTJets.setFillProperties(1001, ROOT.kGreen - 5)
qcdPlotters = []
for sample in [
"QCD_Pt1000to1400_50ns", "QCD_Pt120to170_50ns",
"QCD_Pt1400to1800_50ns", "QCD_Pt170to300_50ns",
"QCD_Pt1800to2400_50ns", "QCD_Pt2400to3200_50ns",
"QCD_Pt300to470_50ns", "QCD_Pt3200_50ns", "QCD_Pt470to600_50ns",
"QCD_Pt600to800_50ns", "QCD_Pt800to1000_50ns", "QCD_Pt80to120_50ns"
]:
qcdPlotters.append(TreePlotter('samples/' + sample + '.root', 'tree'))
sampleTypes=options.samples.split(',')
dataPlotters=[]
for filename in os.listdir(args[0]):
for sampleType in sampleTypes:
if filename.find(sampleType)!=-1:
fnameParts=filename.split('.')
fname=fnameParts[0]
ext=fnameParts[1]
if ext.find("root") ==-1:
continue
dataPlotters.append(TreePlotter(args[0]+'/'+fname+'.root','tree'))
dataPlotters[-1].setupFromFile(args[0]+'/'+fname+'.pck')
dataPlotters[-1].addCorrectionFactor('xsec','tree')
dataPlotters[-1].addCorrectionFactor('genWeight','tree')
dataPlotters[-1].addCorrectionFactor('puWeight','tree')
sigmas=[]
for d in dataPlotters:
sigmas.append(d.tree.GetMaximum("xsec")/d.weightinv)
sigmaW=max(sigmas)
for p in dataPlotters:
p.addCorrectionFactor(1.0/sigmaW,'flat')
data=MergedPlotter(dataPlotters)
while mass<5000:
fitter=Fitter(['MVV'])
fitter.signalResonance('model','MVV')
fitter.w.factory("MH[0,20000]")
for var in ['MEAN','SIGMA'
#Now we have the samples: Sort the masses and run the fits
N=0
for mass in sorted(samples.keys()):
print 'fitting',str(mass)
plotter=TreePlotter(args[0]+'/'+samples[mass]+'.root','tree')
plotter.setupFromFile(args[0]+'/'+samples[mass]+'.pck')
plotter.addCorrectionFactor('genWeight','tree')
plotter.addCorrectionFactor('xsec','tree')
plotter.addCorrectionFactor('puWeight','tree')
fitter.w.var("MH").setVal(mass)
histo = plotter.drawTH1(options.mvv,options.cut,"1",500,0,13000)
fitter.importBinnedData(histo,['MVV'],'data')
fitter.fit('model','data',[ROOT.RooFit.SumW2Error(0)])
events=histo.Integral()*options.BR
graphs['yield'].SetPoint(N,mass,events)
fitter.projection("model","data","MVV","debugVV_"+str(mass)+".root")
samples = {}
sampleTypes = options.samples.split(',')
dataPlotters = []
for filename in os.listdir(args[0]):
for sampleType in sampleTypes:
if filename.find(sampleType) != -1:
fnameParts = filename.split('.')
fname = fnameParts[0]
ext = fnameParts[1]
if ext.find("root") == -1:
continue
dataPlotters.append(
TreePlotter(args[0] + '/' + fname + '.root', 'tree'))
dataPlotters[-1].setupFromFile(args[0] + '/' + fname + '.pck')
dataPlotters[-1].addCorrectionFactor('xsec', 'tree')
dataPlotters[-1].addCorrectionFactor('genWeight', 'tree')
dataPlotters[-1].addCorrectionFactor('puWeight', 'tree')
data = MergedPlotter(dataPlotters)
graphs = runFits(data, options)
f = ROOT.TFile(options.output + ".root", "RECREATE")
f.cd()
for i, g in enumerate(graphs):
g.Write("p" + str(i))
f.Close()
import ROOT
from CMGTools.VVResonances.plotting.TreePlotter import TreePlotter
from CMGTools.VVResonances.plotting.MergedPlotter import MergedPlotter
from CMGTools.VVResonances.plotting.StackPlotter import StackPlotter
#create the W+jets plotters
wjPlotters = []
for sample in [
'WJetsToLNu_HT100to200', 'WJetsToLNu_HT200to400',
'WJetsToLNu_HT400to600', 'WJetsToLNu_HT600toInf'
]:
wjPlotters.append(TreePlotter('samples/' + sample + '.root', 'tree'))
wjPlotters[-1].setupFromFile('samples/' + sample + '.pck')
wjPlotters[-1].addCorrectionFactor('xsec', 'xsec', 0.0, 'lnN')
wjPlotters[-1].addCorrectionFactor('genWeight', 'genWeight', 0.0, 'lnN')
WJets = MergedPlotter(wjPlotters)
WJets.setFillProperties(1001, ROOT.kAzure - 9)
RSGWWLNuQQ = TreePlotter('samples/RSGravToWWToLNQQ_kMpl01_2500.root', 'tree')
RSGWWLNuQQ.setupFromFile('samples/RSGravToWWToLNQQ_kMpl01_2500.pck')
RSGWWLNuQQ.setFillProperties(0, ROOT.kWhite)
RSGWWLNuQQ.setLineProperties(1, ROOT.kOrange + 10, 3)
RSGWWLNuQQ.addCorrectionFactor('xsec', 0.001, 0.0, 'lnN')
#Stack
vvStack = StackPlotter()
vvStack.addPlotter(WJets, "W+jets", "W+Jets", "background")