import ROOT

rfile=ROOT.TFile("inMassKaon.root","READ")
hist=rfile.FindObjectAny("InvMassKaon_woCuts")
#hist=rfile.Get("PWG3_D2H_DStarSpectra_bhohlweg/DStarAll_bhohlweg/InvMassKaon_woCuts")

ROOT.gROOT.ProcessLine(".x rootlogon.C") 
ROOT.gROOT.ProcessLine('gROOT->SetStyle("Plain")')

x=ROOT.RooRealVar('x','x',0.48,0.52)
mu=ROOT.RooRealVar('mu_n','mu narrow',0.5,0.48,0.52)
sigma=ROOT.RooRealVar('sigma_n','sigma narrow',0.005,0,0.1)
mu_b=ROOT.RooRealVar('mu_b','mu_b',0.5,0.48,0.52)
sigma_b=ROOT.RooRealVar('sigma_b','sigma_b',0.08,0,0.1)

frac=ROOT.RooRealVar("gaus_frac","fraction",0.5,0,1)

pdf_n=ROOT.RooGaussian('gaus_n','gaus_n',x,mu,sigma)
pdf_b=ROOT.RooGaussian('gaus_b','gaus_b',x,mu_b,sigma_b)

pdf=ROOT.RooAddPdf("gaus","gaus",pdf_n,pdf_b,frac)

varset=ROOT.RooArgSet()
varset.add(x)

#dataset for unbinned tuple=ROOT.TNtuple('gauss','','x')
#dataset=ROOT.RooDataSet('dataset','dataset',tuple,varset)
dataset=ROOT.RooDataHist("dh","dh",ROOT.RooArgList(x),hist)

#here the fit happens:
pdf.fitTo(dataset)

#the plotting is done here
h1=x.frame()
dataset.plotOn(h1)
pdf.plotOn(h1,ROOT.RooFit.LineColor(ROOT.kViolet))
c1=ROOT.TCanvas()
h1.Draw()

#c2=ROOT.TCanvas()
#hist.Draw()
u=raw_input("done?")