## \file ## \ingroup tutorial_roofit ## \notebook -nodraw ## Multidimensional models: performing fits in multiple (disjoint) ranges in one or more dimensions ## ## \macro_code ## \macro_output ## ## \date February 2018 ## \authors Clemens Lange, Wouter Verkerke (C++ version) import ROOT # Create 2D pdf and data # ------------------------------------------- # Define observables x,y x = ROOT.RooRealVar("x", "x", -10, 10) y = ROOT.RooRealVar("y", "y", -10, 10) # Construct the signal pdf gauss(x)*gauss(y) mx = ROOT.RooRealVar("mx", "mx", 1, -10, 10) my = ROOT.RooRealVar("my", "my", 1, -10, 10) gx = ROOT.RooGaussian("gx", "gx", x, mx, 1.0) gy = ROOT.RooGaussian("gy", "gy", y, my, 1.0) sig = ROOT.RooProdPdf("sig", "sig", gx, gy) # Construct the background pdf (flat in x,y) px = ROOT.RooPolynomial("px", "px", x) py = ROOT.RooPolynomial("py", "py", y) bkg = ROOT.RooProdPdf("bkg", "bkg", px, py) # Construct the composite model sig+bkg f = ROOT.RooRealVar("f", "f", 0.0, 1.0) model = ROOT.RooAddPdf("model", "model", [sig, bkg], [f]) # Sample 10000 events in (x,y) from the model modelData = model.generate({x, y}, 10000) # Define signal and sideband regions # ------------------------------------------------------------------- # Construct the SideBand1,SideBand2, regions # # | # +-------------+-----------+ # | | | # | Side | Sig | # | Band1 | nal | # | | | # --+-------------+-----------+-- # | | # | Side | # | Band2 | # | | # +-------------+-----------+ # | x.setRange("SB1", -10, +10) y.setRange("SB1", -10, 0) x.setRange("SB2", -10, 0) y.setRange("SB2", 0, +10) x.setRange("SIG", 0, +10) y.setRange("SIG", 0, +10) x.setRange("FULL", -10, +10) y.setRange("FULL", -10, +10) # Perform fits in individual sideband regions # ------------------------------------------------------------------------------------- # Perform fit in SideBand1 region (ROOT.RooAddPdf coefficients will be # interpreted in full range) r_sb1 = model.fitTo(modelData, Range="SB1", Save=True, PrintLevel=-1) # Perform fit in SideBand2 region (ROOT.RooAddPdf coefficients will be # interpreted in full range) r_sb2 = model.fitTo(modelData, Range="SB2", Save=True, PrintLevel=-1) # Perform fits in joint sideband regions # ----------------------------------------------------------------------------- # Now perform fit to joint 'L-shaped' sideband region 'SB1|SB2' # (ROOT.RooAddPdf coefficients will be interpreted in full range) r_sb12 = model.fitTo(modelData, Range="SB1,SB2", Save=True, PrintLevel=-1) # Print results for comparison r_sb1.Print() r_sb2.Print() r_sb12.Print()