Example #1
0
                # Do a likelihood scan over mH and mu_gg
                for binmu_gg in xrange(20):
                    mu_gg_point  = xmin + binmu_gg * stepsize
                    mu2.setVal(mu_gg_point)        

                    #, RooArgList(mu1, mu2)
                    roohistpg = RooHistPoissonGamma("pghistpdf","pghistpdf",RooArgSet(m4l, D), rdata, samples, scales, 0)

                    zval = nullzval - roohistpg.getVal() 
                    if zval > 0:
                        likelihoods[len(likelihoods)-1].SetPoint( likelihoods[len(likelihoods)-1].GetN(), float(mass), mu_gg_point, zval);
                    else:
                        likelihoods[len(likelihoods)-1].SetPoint( likelihoods[len(likelihoods)-1].GetN(), float(mass), mu_gg_point, zval);

    #dt = plot_util.multiply_likelihood(likelihoods)
    dt = plot_util.add_loglikelihood(likelihoods, int(i+1))

    print int(dt.GetZmax() - dt.GetZmin())
    dt.GetHistogram().SetContour(int(dt.GetZmax() - dt.GetZmin()))

    dt.Draw("colz")   
    dt.Draw("cont2 same")

    c1.Update()         

    
    
c = TCanvas()
c.Divide(2,2)
c.cd(1)
likelihoods[0].Draw("colz")
    gr = TGraph(len(masses), array("d", massint) , array("d",scanmu1d) )
    gr.SetName("nll_mu_mH_{}".format(channel))
    c1.cd(1)
    likelihoods[len(likelihoods)-1].Draw("colz")
    c1.cd(2)
    gr.Draw("AC*")
    c1.Update()
    sleep(4)
    fout.cd()
    gr.Write()
    likelihoods1d.append(gr)

            

#dt = plot_util.multiply_likelihood(likelihoods)
dt = plot_util.add_loglikelihood(likelihoods, 1)

#reset to zero 
dt = plot_util.setzero_likelihood(dt)

dt1d = plot_util.add_tgraph(likelihoods1d)
dt1d.SetName("nll_mH_1d")
dt1d.Write()

dt1d.Draw()
sleep(4)
    
c = TCanvas()
c.Divide(2,2)
c.cd(1)
likelihoods[0].Draw("colz")
                zval = 2*roohistpg.getVal() # 2*(nullzval - roohistpg.getVal())
                scanmu1d[i] += zval

        for i, mass in enumerate(masses):
            scanmu1d[i] = scanmu1d[i]/points
        print len(masses)
        print len(massint)
        print massint
        print scanmu1d    
        gr = TGraph(len(masses), array("d", massint) , array("d",scanmu1d) )
        gr.SetName("nll_mu_mH_{0}".format(channel))
        fout.cd()
        gr.Write()
        likelihoods1d.append(gr)
    
    tot_lh = plot_util.add_loglikelihood(likelihoods, 1)
    tot_lh.SetName("nll_mu_gg_vs_mH_{0}".format(iter))
    fout.cd()
    tot_lh.Write()
    likelihoods_iter.append(plot_util.add_loglikelihood(likelihoods, 1))

#dt = plot_util.multiply_likelihood(likelihoods)
dt = plot_util.ave_ln_loglikelihood(likelihoods_iter)
#reset to zero 
dt = plot_util.setzero_likelihood(dt)

c1 = TCanvas()
c1.Divide(2)

c1.cd(1)
likelihoods_iter[0].Draw("colz")