def compare_plot(var, plot_range, weight, cut, **kwargs):
histsD = dict()
for samp in samples_mc:
histsD[samp.name] = samp.drawHistogram(var, str(cut), weight=weight, plot_range=plot_range)
Styling.mc_style(histsD[samp.name].hist, samp.name)
for name, hist in histsD.items():
hist.normalize_lumi(lumi_total)
for samp in samples_data:
histsD[samp.name] = samp.drawHistogram(var, str(cut), plot_range=plot_range)
Styling.data_style(histsD[samp.name].hist)
hists_thD = dict()
for (k,v) in histsD.items():
hists_thD[k] = v.hist
merge_cmd = copy.deepcopy(merge_cmds)
merge_cmd["QCD (MC)"] = ["QCDMu"]
merged = merge_hists(hists_thD, merge_cmd)
stack = dict()
stack["mc"] = [merged[name] for name in merged.keys() if name!="single #mu"]
stack["data"] = [merged["single #mu"]]
canv = ROOT.TCanvas()
pl = plot_hists_stacked(canv, stack, **kwargs)
leg = legend(stack["data"] + stack["mc"][::-1], **kwargs)
lb = lumi_textbox(lumi_total)
canv.SaveAs(kwargs.get("filename", "plot") + ".pdf")
return stack, canv, pl, leg, lb
def compare_plot(var, plot_range, weight, cut, **kwargs):
histsD = dict()
for samp in samples_mc:
histsD[samp.name] = samp.drawHistogram(var,
str(cut),
weight=weight,
plot_range=plot_range)
Styling.mc_style(histsD[samp.name].hist, samp.name)
for name, hist in histsD.items():
hist.normalize_lumi(lumi_total)
for samp in samples_data:
histsD[samp.name] = samp.drawHistogram(var,
str(cut),
plot_range=plot_range)
Styling.data_style(histsD[samp.name].hist)
hists_thD = dict()
for (k, v) in histsD.items():
hists_thD[k] = v.hist
merge_cmd = copy.deepcopy(merge_cmds)
merge_cmd["QCD (MC)"] = ["QCDMu"]
merged = merge_hists(hists_thD, merge_cmd)
stack = dict()
stack["mc"] = [
merged[name] for name in merged.keys() if name != "single #mu"
]
stack["data"] = [merged["single #mu"]]
canv = ROOT.TCanvas()
pl = plot_hists_stacked(canv, stack, **kwargs)
leg = legend(stack["data"] + stack["mc"][::-1], **kwargs)
lb = lumi_textbox(lumi_total)
canv.SaveAs(kwargs.get("filename", "plot") + ".pdf")
return stack, canv, pl, leg, lb
from common.hist_plots import plot_hists
from common.sample_style import ColorStyleGen
from common.legend import legend
from common.tdrstyle import tdrstyle
tdrstyle()
hnames = dict()
hnames["mu"] = "nocut", "mtw", "mtw_mtop", "mtw_mtop_etalj"
hnames["ele"] = "nocut", "met", "met_mtop", "met_mtop_etalj"
for flavour in ["b", "c", "l"]:
hi = hists["3J_nocut/mu"], hists["3J_nocut/ele"], hists["3J_mtw/mu"], hists["3J_met/ele"]
hi = map(lambda x: x[flavour], hi)
ColorStyleGen.style_hists(hi)
canv = plot_hists(hi, x_label=xlab, y_label="eff_{%s}" % flavour)
leg = legend(hi, styles=(len(hi)*["f"]), pos="top-left")
canv.SaveAs(out_dir + "/3J_mu_ele_nocut_mtw_proj_%s_eff_%s_sample_%s.pdf" % (axis, flavour, sample_name))
hi = hists["3J_mtw/mu"], hists["3J_met/ele"], hists["3J_mtw_mtop/mu"], hists["3J_met_mtop/ele"]
hi = map(lambda x: x[flavour], hi)
ColorStyleGen.style_hists(hi)
canv = plot_hists(hi, x_label=xlab, y_label="eff_{%s}" % flavour)
leg = legend(hi, styles=(len(hi)*["f"]), pos="top-left")
canv.SaveAs(out_dir + "/3J_mu_ele_mtw_mtop_proj_%s_eff_%s_sample_%s.pdf" % (axis, flavour, sample_name))
for nJets in [2,3]:
for flavour in ["b", "c", "l"]:
for lep in ["mu", "ele"]:
bases = "%dJ_" % nJets
hi = map(lambda x: x[flavour],
