Esempio n. 1
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def comp(branchname, filename, binning, xlabel, ratio, nele, logx=False, remake=False):
	global hist_index
	lt_hists = []
	lt_sum = 0

	if not remake:
		print "opening tmp/LT_%s.root" % filename
		f = ROOT.TFile.Open("tmp/LT_%s.root" % filename, "READ")
		inclusive = f.Get("hist%d" % hist_index)
		hist_index += 1
		for i in xrange(1,11):
			lt_hists.append(f.Get("hist%d" % hist_index ))
			hist_index += 1
			print lt_hists[-1].GetTitle()
			lt_sum += lt_hists[-1].Integral()
	else:
		inclusive = plot.GetTH1(inc_chain, branchname, isMC, binning, category, label="Inclusive Madgraph", usePU = False, useEleIDSF=nele)

		for name, chain in zip(lt_names,lt_binned_chains):
			print "Getting", name
			h = plot.GetTH1(chain, branchname, isMC, binning, category, label= "L_{T} " + name + " GeV", usePU = False, useEleIDSF=nele)
			lt_hists.append(h)
			lt_sum += h.Integral()

	if remake:
		f = ROOT.TFile.Open("tmp/LT_%s.root" % filename, "RECREATE")
		for h in lt_hists + [inclusive]:
			h.Write()
		f.Close()

	plot.ColorData(inclusive)
	plot.ColorMCs(lt_hists)
	#inclusive.Scale(1./inclusive.Integral())

	rajdeep_new = [828.72, 129.496, 155.178, 217.287, 175.158, 50.51, 91.48, 3.69, 0.196, 0.0072]
	old_xs = [8.670e+02, 1.345e+02, 1.599e+02, 2.295e+02, 1.654e+02, 4.896e+01, 9.401e+01, 3.588e+00, 2.012e-01, 8.329e-03]
	fit_new = [ 9.93694e-01, 9.72633e-01, 9.90570e-01, 9.89391e-01, 9.92841e-01, 8.56845e-01, 8.91049e-01, 9.04437e-01, 6.09500e-01,1] 
	filename = "before_" + filename
	#for i, h in enumerate(lt_hists):
		#print "### XS RATIO: ", h.GetTitle(), old_xs[i], old_xs[i] * fit_new[i]
		#h.Scale(fit_new[i])
		#h.Scale(rajdeep_new[i]/old_xs[i])
	#	h.Scale(1./lt_sum)
	inclusive.Scale(1000*4.957e+03/49144274.0)
	
	lt_hists.reverse()
	plot.PlotDataMC(inclusive, lt_hists, "plots/validation/LTBinned/", "LT_comparison_" + filename, xlabel=xlabel + " [GeV]", ylabel="Fraction", ylabel_unit="GeV", stack_mc=True, ratio=ratio, logx=logx)
Esempio n. 2
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args = parser.parse_args()

sys.path.insert(0, os.getcwd() + '/python')
import plot
import ROOT

infile = ROOT.TFile.Open("LT_LT_hist.root")
stack = [key.ReadObj() for key in infile.GetListOfKeys()]

stack, _ = plot.NormalizeStack(stack)
plot.ColorMCs(stack)

incfile = ROOT.TFile.Open("LT_inc.root")
mc_inc = incfile.Get("hist0")

plot.Normalize([], mc_inc)
plot.ColorMCs(mc_inc)

mc_inc.SetLineColor(ROOT.kBlack)

ROOT.gStyle.SetOptStat(0)
ROOT.gStyle.SetOptTitle(0)
plot.PlotDataMC([], [mc_inc] + list(stack),
                "plots/validation/LTBinned/",
                "LT_stack",
                xlabel="L_{T}",
                ylabel="Events",
                ylabel_unit="GeV",
                logy=False,
                ratio=True)
Esempio n. 3
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def comp(branchname,
         filename,
         binning,
         xlabel,
         ratio,
         nele,
         logx=False,
         remake=False):
    global hist_index

    branchname = "smearerCat[0]:" + branchname
    nbins, low, hi = eval(binning)
    binning = "({nbins},{low},{hi},{ncat},0,{ncat})".format(nbins=nbins,
                                                            low=low,
                                                            hi=hi,
                                                            ncat=ncat *
                                                            (ncat + 1) / 2)
    if not remake:
        f = ROOT.TFile.Open("tmp/smear_comp_%s.root" % filename, "READ")
        histos = [
            f.Get("hist%d" % i) for i in range(hist_index, 5 + hist_index)
        ]
        data_step7_hist, data_step2_hist, mc_h, mc_step4_h, mc_step7_h = histos
        data_hists = [data_step7_hist, data_step2_hist]
        mc_hists = [mc_h, mc_step4_h, mc_step7_h]
        hist_index += 5
    else:
        data_step7_hist = plot.GetTH1(data_step7_chain,
                                      branchname,
                                      not isMC,
                                      binning,
                                      category,
                                      label="Data HggRunEtaR9Et",
                                      usePU=False,
                                      useEleIDSF=nele,
                                      scale=True)
        data_step2_hist = plot.GetTH1(data_step2_chain,
                                      branchname,
                                      not isMC,
                                      binning,
                                      category,
                                      label="Data HggRunEtaR9",
                                      usePU=False,
                                      useEleIDSF=nele,
                                      scale=True)
        data_hists = [data_step7_hist, data_step2_hist]

        mc_h = plot.GetTH1(mc_chain,
                           branchname,
                           isMC,
                           binning,
                           category,
                           label="no Correction",
                           usePU=False,
                           useEleIDSF=nele,
                           smear=False)
        mc_step4_h = plot.GetTH1(mc_step4_chain,
                                 branchname,
                                 isMC,
                                 binning,
                                 category,
                                 label="Step4 Smear",
                                 usePU=False,
                                 useEleIDSF=nele,
                                 smear=True)
        mc_step7_h = plot.GetTH1(mc_step7_chain,
                                 branchname,
                                 isMC,
                                 binning,
                                 category,
                                 label="Step7 Smear",
                                 usePU=False,
                                 useEleIDSF=nele,
                                 smear=True)
        mc_hists = [mc_h, mc_step4_h, mc_step7_h]

    if remake:
        f = ROOT.TFile.Open("tmp/smear_comp_%s.root" % filename, "RECREATE")
        for h in data_hists + mc_hists:
            h.Write()
        f.Close()

    c = ROOT.TCanvas()
    names = [
        "data_HggRunEtaR9Et", "data_HggRunEtaR9", "uncorrected", "step4",
        "step7"
    ]
    for name, h in zip(names, data_hists + mc_hists):
        h.Draw("colz")
        c.SaveAs("plots/scale_smear/%s.png" % name)

    data_step7_hs = ROOT.THStack(data_step7_hist, "x")
    data_step2_hs = ROOT.THStack(data_step2_hist, "x")
    mc_hs = ROOT.THStack(mc_h, "x")
    mc_step4_hs = ROOT.THStack(mc_step4_h, "x")
    mc_step7_hs = ROOT.THStack(mc_step7_h, "x")

    #print "CHI2 Category", " ".join(names[2:])
    for i, dicat_name in enumerate(dicat_names):
        ds = [data_step7_hs.GetHists()[i], data_step2_hs.GetHists()[i]]
        plot.ColorData(ds)
        mcs = [
            mc_hs.GetHists()[i],
            mc_step4_hs.GetHists()[i],
            mc_step7_hs.GetHists()[i]
        ]
        plot.ColorMCs(mcs)
        plot.Normalize(ds, mcs)

        ds[0].GetXaxis().SetRangeUser(80, 100)

        #print "CHI2", dicat_name,
        #for h in mcs:
        #ch2 = ds[0].Chi2Test(h, "UW CHI2/NDF")
        #print ch2,
        #for h in mcs:
        #print h.GetEntries(),
        #print
        plot.PlotDataMC(ds[0],
                        mcs,
                        "plots/smear_comp/",
                        filename + "_" + dicat_name,
                        x_range=(80, 100),
                        xlabel=xlabel + " [GeV]",
                        ylabel="Events",
                        ylabel_unit="GeV",
                        ratio=ratio,
                        logx=logx)
        mcs[1].SetFillStyle(1001)
        mcs[1].SetFillColor(ROOT.kAzure + 6)
        mcs[1].SetLineColor(ROOT.kAzure + 6)
        plot.PlotDataMC(ds,
                        mcs[1],
                        "plots/scale_comp/",
                        filename + "_" + dicat_name,
                        x_range=(80, 100),
                        xlabel=xlabel + " [GeV]",
                        ylabel="Events",
                        ylabel_unit="GeV",
                        ratio=False,
                        logx=logx)
Esempio n. 4
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    if args.data:
        print "[STATUS] Data: " + branchname
        isMC = False
        data_hs = MakeTH1s(args.data, branchname, isMC, binning, category,
                           selection)
        plot.ColorData(data_hs)
    else:
        data_hs = []

    if args.mc:
        print "[STATUS] MC: " + branchname
        isMC = True
        mc_hs = MakeTH1s(args.mc, branchname, isMC, binning, category,
                         selection)
        plot.ColorMCs(mc_hs)
    else:
        mc_hs = []

    plot.Normalize(data_hs, mc_hs)
    plot.PlotDataMC(data_hs,
                    mc_hs,
                    args.plotdir,
                    args.name,
                    xlabel=args.xlabel,
                    ylabel="Events",
                    ylabel_unit="GeV",
                    logy=False,
                    ratio=ratio)
    print "[STATUS] Done: " + branchname
Esempio n. 5
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binning = args.binning

if not args.branch:
	args.branch = [""]

for branchname in args.branch:
	if not args.name:
		args.name = branchname
	if not args.xlabel:
		args.xlabel = branchname

	if args.data:
		print "[STATUS] Data: " + branchname
		isMC = False
		data_hs = MakeTH1s(args.data, branchname, isMC, binning, category)
		plot.ColorData(data_hs)
	else:
		data_hs = []

	if args.mc:
		print "[STATUS] MC: " +  branchname
		isMC = True
		mc_hs = MakeTH1s(args.mc, branchname, isMC, binning, category)
		plot.ColorMCs(mc_hs)
	else:
		mc_hs = []

	plot.Normalize(data_hs, mc_hs)
	plot.PlotDataMC(data_hs, mc_hs, "plots/", args.name, xlabel=args.xlabel, ylabel="Events", ylabel_unit="GeV", logy = False)
	print "[STATUS] Done: " + branchname