def rooFit601(): print ">>> setup pdf and likelihood..." x = RooRealVar("x", "x", -20, 20) mean = RooRealVar("mean", "mean of g1 and g2", 0) sigma1 = RooRealVar("sigma1", "width of g1", 3) sigma2 = RooRealVar("sigma2", "width of g2", 4, 3.0, 6.0) # intentional strong correlations gauss1 = RooGaussian("gauss1", "gauss1", x, mean, sigma1) gauss2 = RooGaussian("gauss2", "gauss2", x, mean, sigma2) frac = RooRealVar("frac", "frac", 0.5, 0.0, 1.0) model = RooAddPdf("model", "model", RooArgList(gauss1, gauss2), RooArgList(frac)) print ">>> generate to data..." data = model.generate(RooArgSet(x), 1000) # RooDataSet print ">>> construct unbinned likelihood of model wrt data..." nll = model.createNLL(data) # RooAbsReal print ">>> interactive minimization and error analysis with MINUIT interface object..." minuit = RooMinuit(nll) print ">>> set avtive verbosity for logging of MINUIT parameter space stepping..." minuit.setVerbose(kTRUE) print ">>> call MIGRAD to minimize the likelihood..." minuit.migrad() print "\n>>> parameter values and error estimates that are back propagated from MINUIT:" model.getParameters(RooArgSet(x)).Print("s") print "\n>>> disable verbose logging..." minuit.setVerbose(kFALSE) print ">>> run HESSE to calculate errors from d2L/dp2..." minuit.hesse() print ">>> value of and error on sigma2 (back propagated from MINUIT):" sigma2.Print() print "\n>>> run MINOS on sigma2 parameter only..." minuit.minos(RooArgSet(sigma2)) print "\n>>> value of and error on sigma2 (back propagated from MINUIT after running MINOS):" sigma2.Print() print "\n>>> saving results, contour plots..." # Save a snapshot of the fit result. This object contains the initial # fit parameters, the final fit parameters, the complete correlation # matrix, the EDM, the minimized FCN , the last MINUIT status code and # the number of times the RooFit function object has indicated evaluation # problems (e.g. zero probabilities during likelihood evaluation) result = minuit.save() # RooFitResult # Make contour plot of mx vs sx at 1,2,3 sigma frame1 = minuit.contour(frac, sigma2, 1, 2, 3) # RooPlot frame1.SetTitle("RooMinuit contour plot") # Print the fit result snapshot result.Print("v") print "\n>>> change value of \"mean\" parameter..." mean.setVal(0.3) # Rerun MIGRAD,HESSE print ">>> rerun MIGRAD, HESSE..." minuit.migrad() minuit.hesse() print ">>> value on and error of frac:" frac.Print() print "\n>>> fix value of \"sigma\" parameter (setConstant)..." sigma2.setConstant(kTRUE) print ">>> rerun MIGRAD, HESSE..." minuit.migrad() minuit.hesse() frac.Print()