def DrawSignalEff(cut_lst,
inputdir="b77",
inputroot="sum",
outputname="",
normalization=1.0,
plotrange=(0, 3100),
logy=0):
### the first argument is the input directory
### the second argument is the output prefix name
### the third argument is relative to what normalization: 0 for total number of events
### 1 for signal mass region
histname = "_Signal_Significance"
canv = ROOT.TCanvas(
outputname + "_" + str(plotrange[0]) + "_" + str(plotrange[1]),
"Efficiency", 800, 800)
xleg, yleg = 0.65, 0.7
legend = ROOT.TLegend(xleg, yleg, xleg + 0.2, yleg + 0.2)
# two pad
pad0 = ROOT.TPad("pad0", "pad0", 0.0, 0.31, 1., 1.)
pad0.SetRightMargin(0.05)
pad0.SetBottomMargin(0.0001)
pad0.SetFrameFillColor(0)
pad0.SetFrameBorderMode(0)
pad0.SetFrameFillColor(0)
pad0.SetBorderMode(0)
pad0.SetBorderSize(0)
pad1 = ROOT.TPad("pad1", "pad1", 0.0, 0.0, 1., 0.30)
pad1.SetRightMargin(0.05)
pad1.SetBottomMargin(0.38)
pad1.SetTopMargin(0.0001)
pad1.SetFrameFillColor(0)
pad1.SetFillStyle(0) # transparent
pad1.SetFrameBorderMode(0)
pad1.SetFrameFillColor(0)
pad1.SetBorderMode(0)
pad1.SetBorderSize(0)
#top pad
canv.cd()
pad0.SetLogy(logy)
pad0.Draw()
pad0.cd()
# setup basic plot parameters
lowmass = -50
highmass = 3150
# load input MC file
input_mc = ROOT.TFile.Open(CONF.inputpath + inputdir + "/" + inputroot +
"_" + inputdir + ".root")
maxbincontent = normalization
minbincontent = 0.0001
temp_all = input_mc.Get(cut_lst[0] + histname).Clone()
temp_all.SetName("Combined")
input_mc_ref = ROOT.TFile.Open(CONF.inputpath + "ref/" + "sum_ref" +
".root")
temp_ref = input_mc_ref.Get(cut_lst[0] + histname).Clone()
temp_ref.SetName("Run2-ref")
temp_ratio = input_mc.Get(cut_lst[0] + histname).Clone()
temp_ratio.SetName("Ratio")
for j in range(1, temp_all.GetNbinsX() + 1):
temp_all.SetBinContent(j, 0)
temp_all.SetBinError(j, 0)
temp_ref.SetBinContent(j, 0)
temp_ref.SetBinError(j, 0)
temp_all.SetMinimum(minbincontent)
temp_ref.SetMinimum(minbincontent)
graph_lst = []
for i, cut in enumerate(cut_lst):
#print cut
sig_mc = input_mc.Get(cut + histname) #get the input histogram
sig_mc_ref = input_mc_ref.Get(cut + histname) #get the input histogram
for j in range(1, temp_all.GetNbinsX() + 1):
#temp_all.SetBinContent(j, ROOT.TMath.Sqrt(temp_all.GetBinContent(j) * temp_all.GetBinContent(j) + sig_mc.GetBinContent(j) * sig_mc.GetBinContent(j)))
temp_ref.SetBinContent(
j,
ROOT.TMath.Sqrt(
temp_ref.GetBinContent(j) * temp_ref.GetBinContent(j) +
sig_mc_ref.GetBinContent(j) * sig_mc_ref.GetBinContent(j)))
temp_all.SetBinContent(
j,
ROOT.TMath.Sqrt(
temp_all.GetBinContent(j) * temp_all.GetBinContent(j) +
sig_mc.GetBinContent(j) * sig_mc.GetBinContent(j)))
temp_ref.SetBinError(
j,
ROOT.TMath.Sqrt(
temp_ref.GetBinError(j) * temp_ref.GetBinError(j) +
sig_mc_ref.GetBinError(j) * sig_mc_ref.GetBinError(j)))
temp_all.SetBinError(
j,
ROOT.TMath.Sqrt(
temp_all.GetBinError(j) * temp_all.GetBinError(j) +
sig_mc.GetBinError(j) * sig_mc.GetBinError(j)))
del (sig_mc_ref)
graph_lst.append(helpers.TH1toTAsym(sig_mc, pltrange=plotrange))
graph_lst[i].SetMaximum(maxbincontent * 1.5)
graph_lst[i].SetMinimum(minbincontent)
graph_lst[i].SetLineColor(CONF.clr_lst[i])
graph_lst[i].SetMarkerStyle(20 + i)
graph_lst[i].SetMarkerColor(CONF.clr_lst[i])
graph_lst[i].SetMarkerSize(1)
legend.AddEntry(graph_lst[i], cut.replace("_", " "), "APL")
if cut == cut_lst[0]:
graph_lst[i].Draw("APC")
else:
graph_lst[i].Draw("PC")
del (sig_mc)
graph_all = helpers.TH1toTAsym(temp_all)
graph_all.SetLineColor(2)
graph_all.SetLineStyle(2)
graph_all.SetMarkerStyle(5)
graph_all.SetMarkerColor(2)
graph_all.SetMarkerSize(1)
graph_all.GetXaxis().SetRangeUser(plotrange[0], plotrange[1])
legend.AddEntry(graph_all, graph_all.GetName().replace("_", " "), "APL")
graph_all.Draw("PC")
graph_ref = helpers.TH1toTAsym(temp_ref)
graph_ref.SetLineColor(1)
graph_ref.SetLineStyle(3)
graph_ref.SetMarkerStyle(4)
graph_ref.SetMarkerColor(1)
graph_ref.SetMarkerSize(1)
graph_ref.GetXaxis().SetRangeUser(plotrange[0], plotrange[1])
legend.AddEntry(graph_ref, graph_ref.GetName().replace("_", " "), "APL")
graph_ref.Draw("PC")
legend.SetBorderSize(0)
legend.SetMargin(0.3)
legend.SetTextSize(0.02)
legend.Draw()
# draw reference lines
xline05 = ROOT.TLine(lowmass, 0.05, highmass, 0.05)
xline05.SetLineStyle(3)
xline05.Draw()
xline10 = ROOT.TLine(lowmass, 0.1, highmass, 0.1)
xline10.SetLineStyle(4)
xline10.Draw()
yline05 = ROOT.TLine(1000, 0.0, 1000, maxbincontent)
yline05.SetLineStyle(9)
yline05.Draw()
yline10 = ROOT.TLine(2000, 0.0, 2000, maxbincontent)
yline10.SetLineStyle(9)
yline10.Draw()
# draw watermarks
xatlas, yatlas = 0.35, 0.87
atlas = ROOT.TLatex(xatlas, yatlas, "ATLAS Internal")
hh4b = ROOT.TLatex(xatlas, yatlas - 0.06, "RSG c=1.0")
lumi = ROOT.TLatex(xatlas, yatlas - 0.12, "MC #sqrt{s} = 13 TeV")
watermarks = [atlas, hh4b, lumi]
for wm in watermarks:
wm.SetTextAlign(22)
wm.SetTextSize(0.04)
wm.SetTextFont(42)
wm.SetNDC()
wm.Draw()
#bottom pad
canv.cd()
pad1.Draw()
pad1.cd()
for j in range(1, temp_ratio.GetNbinsX() + 1):
try:
temp_ratio.SetBinContent(
j,
temp_all.GetBinContent(j) / temp_ref.GetBinContent(j))
temp_ratio.SetBinError(j, helpers.ratioerror(\
temp_all.GetBinContent(j), temp_ref.GetBinContent(j), \
temp_all.GetBinError(j), temp_ref.GetBinError(j)))
except ZeroDivisionError:
pass
#print "Divide by zero! Check bin content in", canv.GetName()
temp_ratio.SetMarkerStyle(20)
temp_ratio.SetMarkerColor(1)
temp_ratio.SetMarkerSize(1)
temp_ratio.GetYaxis().SetTitleFont(43)
temp_ratio.GetYaxis().SetTitleSize(28)
temp_ratio.GetYaxis().SetLabelFont(43)
temp_ratio.GetYaxis().SetLabelSize(28)
temp_ratio.GetYaxis().SetTitle(" %s/ ref" % inputdir)
temp_ratio.GetYaxis().SetRangeUser(0.7, 1.2) #set range for ratio plot
temp_ratio.GetYaxis().SetNdivisions(405)
temp_ratio.GetXaxis().SetTitleFont(43)
temp_ratio.GetXaxis().SetTitleOffset(3.5)
temp_ratio.GetXaxis().SetTitleSize(28)
temp_ratio.GetXaxis().SetLabelFont(43)
temp_ratio.GetXaxis().SetLabelSize(28)
temp_ratio.GetXaxis().SetRangeUser(plotrange[0], plotrange[1])
temp_ratio.GetXaxis().SetTitle("mass, GeV")
temp_ratio.Draw("ep")
# draw the ratio 1 line
line = ROOT.TLine(plotrange[0], 1.0, plotrange[1], 1.0)
line.SetLineStyle(1)
line.Draw()
# finish up
if logy != 0:
canv.SetName(canv.GetName() + "_1")
canv.SaveAs(outputpath + canv.GetName() + ".pdf")
pad0.Close()
pad1.Close()
canv.Close()
input_mc.Close()
input_mc_ref.Close()
#clean up all the pointers...
del (temp_all)
del (temp_ref)
del (temp_ratio)
del (graph_all)
del (graph_ref)
del (graph_lst)
def DrawSignalTruth(outputroot,
dcut_lst,
scut_lst,
inputdir="",
outputname="",
normalization=0):
### the first argument is the input directory
### the second argument is the output prefix name
### the third argument is relative to what normalization: 0 for total number of events
### 1 for signal mass region
# setup basic plot parameters
lowmass = -50
highmass = 3150
# load input MC file
maxbincontent = .4 # approx
minbincontent = -0.01
for i, (dcut, scut) in enumerate(zip(dcut_lst, scut_lst)):
canv = ROOT.TCanvas(inputdir + "_" + outputname + str(normalization),
"Efficiency", 800, 800)
xleg, yleg = 0.55, 0.7
legend = ROOT.TLegend(xleg, yleg, xleg + 0.3, yleg + 0.2)
sfiles = [
"/signal_G_hh_c10_M%i/hist-MiniNTuple.root" % mass
for mass in mass_lst
]
sinfos = ["RSG " + str(m) + " GeV" for m in mass_lst]
dfiles = ["/data_test/hist-MiniNTuple.root"]
dinfos = ["0Tag data"]
allmc = []
for j, (f, info) in enumerate(zip(dfiles + sfiles, dinfos + sinfos)):
cut = dcut if "data" in f else scut
#here could be changed to have more options
input_mc = ROOT.TFile.Open(CONF.inputpath + inputdir + f)
if not input_mc:
print CONF.inputpath + inputdir + f
try:
temp_mc = input_mc.Get(cut).Clone()
#temp_mc = temp_mc.ProjectionY()
except:
print CONF.inputpath + inputdir + f
print cut
raise
# rebin the hist for pt
# set other options
temp_mc.GetYaxis().SetTitle("Normalized")
temp_mc.GetXaxis().SetNdivisions(510)
temp_mc.GetXaxis().SetLabelSize(0.03)
temp_mc.GetYaxis().SetNdivisions(505)
if cut.split("_")[-1] == "pt":
temp_mc.Rebin(10)
temp_mc.GetXaxis().SetTitle(temp_mc.GetXaxis().GetTitle() +
" [GeV]")
elif "deta" in cut.lower():
temp_mc.Rebin(30)
maxbincontent = .6 / 1.5
# draw line at the cut value
cutval = 1.7
line = ROOT.TLine(1.7, 0, 1.7, 0.4)
line.SetLineWidth(3)
line.SetLineStyle(9)
line.Draw()
else:
temp_mc.GetXaxis().SetTitle("#DeltaR between H, child b")
dR_type = cut.split("/")[1][0:4]
if dR_type != "h0h1":
temp_mc.GetXaxis().SetRangeUser(0, 3)
maxbincontent = 1.0 / 1.5
else:
maxbincontent = .5
if dR_type == "h1b2" or dR_type == "h0b0":
dR1_line = ROOT.TLine(1, 0, 1, maxbincontent)
dR04_line = ROOT.TLine(.4, 0, .4, maxbincontent)
dR1_line.Draw("")
dR04_line.Draw("")
elif dR_type == "b0b1" or dR_type == "b2b3":
dR1_line = ROOT.TLine(2, 0, 2, maxbincontent)
dR04_line = ROOT.TLine(.8, 0, .8, maxbincontent)
dR1_line.Draw("")
dR04_line.Draw("")
if temp_mc.GetNbinsX() == 76:
temp_mc.Rebin(4)
elif temp_mc.GetNbinsX() > 20:
temp_mc.Rebin(temp_mc.GetNbinsX() / 20)
if "data" in f:
temp_mc.Sumw2(True)
outputroot.cd()
temp_mc.Scale(1 / temp_mc.Integral())
temp_mc.SetName("RSG_" + info + "_" + cut.replace("/", "_"))
temp_mc.Write()
temp2_mc = outputroot.Get(temp_mc.GetName())
if temp_mc.Integral() < 1e-4:
continue
truth_mc = helpers.TH1toTAsym(temp2_mc, efficiency=False)
truth_mc.SetLineColor(CONF.clr_lst[j])
truth_mc.SetMarkerStyle(20 + j)
truth_mc.SetMarkerColor(CONF.clr_lst[j])
truth_mc.SetMarkerSize(1)
truth_mc.SetMaximum(maxbincontent * 1.5)
truth_mc.SetMinimum(minbincontent)
truth_mc.GetXaxis().SetTitle(cut.split("/")[1].replace("_", " "))
canv.cd()
#reset data style
if "data" in f:
truth_mc.SetLineColor(1)
truth_mc.SetMarkerColor(1)
if j == 0:
truth_mc.Draw("APC")
else:
truth_mc.Draw("PC")
allmc.append(truth_mc)
legend.AddEntry(truth_mc, info, "apl")
input_mc.Close()
legend.SetBorderSize(0)
legend.SetMargin(0.3)
legend.SetTextSize(0.04)
legend.Draw()
# draw watermarks
xatlas, yatlas = 0.35, 0.87
atlas = ROOT.TLatex(xatlas, yatlas, "ATLAS Internal")
hh4b = ROOT.TLatex(xatlas, yatlas - 0.06, "RSG c=1.0")
lumi = ROOT.TLatex(xatlas, yatlas - 0.12, "MC #sqrt{s} = 13 TeV")
watermarks = [atlas, hh4b, lumi]
for wm in watermarks:
wm.SetTextAlign(22)
wm.SetTextSize(0.04)
wm.SetTextFont(42)
wm.SetNDC()
wm.Draw()
# finish up
outputroot.cd()
helpers.checkpath(CONF.inputpath + inputdir + "/Plot/Truth/")
#print CONF.inputpath + inputdir + "/Plot/Truth/"
canv.SaveAs(CONF.inputpath + inputdir + "/Plot/Truth/" +
canv.GetName() + "_" + cut.replace("/", "_") + ".pdf")
canv.Close()
def DrawPtEff(inputdir, outputname=""):
### the first argument is the input directory
### the second argument is the output prefix name
### the third argument is relative to what normalization: 0 for total number of events
### 1 for signal mass region
canv = ROOT.TCanvas(inputdir + "_pT_" + "Efficiency", "Efficiency", 800,
800)
xleg, yleg = 0.55, 0.7
legend = ROOT.TLegend(xleg, yleg, xleg + 0.3, yleg + 0.2)
# setup basic plot parameters
# load input MC file
eff_lst = []
graph_lst = []
maxbincontent = 1
minbincontent = -0.01
year = (outputname.split("_")[1] if "_" in outputname else "")
file_lst = [
"data_test", "signal_G_hh_c10_M1000", "signal_G_hh_c10_M1100",
"signal_G_hh_c10_M1200"
]
leg_lst = ["Data" + year, "RSG 1TeV", "RSG 1.1TeV", "RSG 1.2TeV"]
for i, file in enumerate(file_lst):
input_mc = ROOT.TFile.Open(inputpath + file +
(year if "data" in file else "") +
"/hist-MiniNTuple" + ".root")
hist_tag = input_mc.Get(
"h_leadHCand_pT_pre_trig").Clone() #hist before trigger
hist_prob = input_mc.Get(
"h_leadHCand_pT_aft_trig").Clone() #hist after trigger
xMin = hist_tag.GetXaxis().GetXmin()
xMax = hist_tag.GetXaxis().GetXmax()
#print xMin, xMax
eff_lst.append(
ROOT.TH1F(file + "_pT_eff", ";p_{T} [GeV]; Efficiency",
hist_tag.GetXaxis().GetNbins(), xMin, xMax))
for j in range(hist_tag.GetXaxis().GetNbins() + 1):
#print j, hist_prob.GetBinContent(j), hist_prob.GetBinCenter(j)
if hist_prob.GetBinContent(j) > 0:
eff_lst[i].SetBinContent(
j,
hist_prob.GetBinContent(j) / hist_tag.GetBinContent(j))
eff_lst[i].SetBinError(
j,
helpers.ratioerror(hist_prob.GetBinContent(j),
hist_tag.GetBinContent(j),
hist_prob.GetBinError(j),
hist_tag.GetBinError(j)))
graph_lst.append(helpers.TH1toTAsym(eff_lst[i]))
graph_lst[i].SetLineColor(CONF.clr_lst[i])
graph_lst[i].SetMarkerStyle(20 + i)
graph_lst[i].SetMarkerColor(CONF.clr_lst[i])
graph_lst[i].SetMarkerSize(1)
graph_lst[i].SetMaximum(maxbincontent * 1.5)
graph_lst[i].SetMinimum(minbincontent)
legend.AddEntry(graph_lst[i], leg_lst[i].replace("_", " "), "apl")
canv.cd()
if i == 0:
graph_lst[i].Draw("APC")
else:
graph_lst[i].Draw("PC")
input_mc.Close()
legend.SetBorderSize(0)
legend.SetMargin(0.3)
legend.SetTextSize(0.04)
legend.Draw()
# draw reference lines
xline90 = ROOT.TLine(xMin, 0.9, xMax, 0.9)
xline90.SetLineStyle(3)
xline90.Draw()
xline95 = ROOT.TLine(xMin, 0.95, xMax, 0.95)
xline95.SetLineStyle(4)
xline95.Draw()
xline98 = ROOT.TLine(xMin, 0.98, xMax, 0.98)
xline98.SetLineStyle(5)
xline98.Draw()
yline45 = ROOT.TLine(450, 0.00, 450, 1.00)
yline45.SetLineStyle(5)
yline45.Draw()
# draw watermarks
xatlas, yatlas = 0.35, 0.87
atlas = ROOT.TLatex(xatlas, yatlas, "ATLAS Internal")
hh4b = ROOT.TLatex(xatlas, yatlas - 0.06, "RSG c=1.0")
lumi = ROOT.TLatex(xatlas, yatlas - 0.12, "MC #sqrt{s} = 13 TeV")
watermarks = [atlas, hh4b, lumi]
for wm in watermarks:
wm.SetTextAlign(22)
wm.SetTextSize(0.04)
wm.SetTextFont(42)
wm.SetNDC()
wm.Draw()
# finish up
canv.SaveAs(outputpath + outputname + "_" + canv.GetName() + ".pdf")
canv.Close()
def Compare_Optimise(targetdir="AllTag_Signal",
targetplot="hCandDeta",
masslist=[1000, 1200, 1500, 1800, 2000, 2500, 3000]):
print targetdir, targetplot
canv = ROOT.TCanvas(targetdir + "_" + targetplot, "Optimizer", 800, 800)
xleg, yleg = 0.52, 0.7
legend = ROOT.TLegend(xleg, yleg, xleg + 0.3, yleg + 0.2)
# setup basic plot parameters
# load input MC file
eff_lst = []
graph_lst = []
maxbincontent = 0.0001
minbincontent = 0.00001
for i, mass in enumerate(masslist):
print mass,
eff_lst.append(
Optimise(
"data_test/hist-MiniNTuple.root",
("signal_G_hh_c10_M" if not ops.Xhh else "signal_X_hh_M") +
str(mass) + "/hist-MiniNTuple.root", "NoTag_Signal", targetdir,
targetplot))
maxbincontent = max(eff_lst[i].GetMaximum(), maxbincontent)
canv.cd()
#convert it to a TGraph
graph_lst.append(helpers.TH1toTAsym(eff_lst[i]))
graph_lst[i].SetLineColor(CONF.clr_lst[i])
graph_lst[i].SetMarkerStyle(20 + i)
graph_lst[i].SetMarkerColor(CONF.clr_lst[i])
graph_lst[i].SetMarkerSize(1)
graph_lst[i].SetMaximum(maxbincontent * 1.5)
graph_lst[i].SetMinimum(minbincontent)
legend.AddEntry(graph_lst[i], str(mass).replace("_", " "), "apl")
if i == 0:
graph_lst[i].Draw("APC")
#gr.Draw("same L hist")
else:
graph_lst[i].Draw("PC")
#gr.Draw("same L hist")
legend.SetBorderSize(0)
legend.SetMargin(0.3)
legend.SetTextSize(0.04)
legend.Draw()
# draw reference lines
yline05 = ROOT.TLine(1000, 0.0, 1000, maxbincontent)
yline05.SetLineStyle(9)
yline05.Draw()
yline10 = ROOT.TLine(2000, 0.0, 2000, maxbincontent)
yline10.SetLineStyle(9)
yline10.Draw()
# draw watermarks
xatlas, yatlas = 0.35, 0.87
atlas = ROOT.TLatex(xatlas, yatlas, "ATLAS Internal")
hh4b = ROOT.TLatex(xatlas, yatlas - 0.06,
"RSG c=1.0" if not ops.Xhh else "2HDM")
lumi = ROOT.TLatex(xatlas, yatlas - 0.12, "MC #sqrt{s} = 13 TeV")
watermarks = [atlas, hh4b, lumi]
for wm in watermarks:
wm.SetTextAlign(22)
wm.SetTextSize(0.04)
wm.SetTextFont(42)
wm.SetNDC()
wm.Draw()
# finish up
# canv.SetLogy(1)
canv.SaveAs(outputpath + ("G10_" if not ops.Xhh else "2HDM_") +
canv.GetName() + ".pdf")
canv.Close()
def DrawSignalEff(cut_lst,
inputdir="b77",
outputname="",
normalization="All",
doint=False,
donormint=False,
dorel=False):
### the first argument is the input directory
### the second argument is the output prefix name
### the third argument is relative to what normalization: 0 for total number of events
### 1 for signal mass region
afterscript = "_rel" if dorel else ""
canv = ROOT.TCanvas(
inputdir + "_" + "Efficiency" + "_" + normalization + afterscript,
"Efficiency", 800, 800)
xleg, yleg = 0.55, 0.73
legend = ROOT.TLegend(xleg, yleg, xleg + 0.3, yleg + 0.18)
# setup basic plot parameters
# load input MC file
eff_lst = []
graph_lst = []
maxbincontent = 0.001
minbincontent = -0.001
for i, cut in enumerate(cut_lst):
eff_lst.append(
ROOT.TH1F(inputdir + "_" + cut,
"%s; Mass [GeV]; Acceptance x Efficiency" % cut,
int((highmass - lowmass) / 100), lowmass, highmass))
for mass in mass_lst:
#here could be changed to have more options
input_mc = ROOT.TFile.Open(
inputpath + "signal_G_hh_c10_M%i/hist-MiniNTuple.root" % mass)
cutflow_mc = input_mc.Get("CutFlowNoWeight").Clone(
) #notice here we use no weight for now!
cutflow_mc_w = input_mc.Get("CutFlowWeight").Clone()
if dorel:
maxbincontent = 1.0
if i > 0:
normalization = cut_lst[i - 1]
totevt_mc = cutflow_mc.GetBinContent(
cutflow_mc.GetXaxis().FindBin(normalization))
cutevt_mc = cutflow_mc.GetBinContent(
cutflow_mc.GetXaxis().FindBin(cut))
#this is a really dirty temp fix
scale_weight = (cutflow_mc.GetBinContent(cutflow_mc.GetXaxis().FindBin("All")) * 1.0)\
/ (cutflow_mc_w.GetBinContent(cutflow_mc.GetXaxis().FindBin("All")) * 1.0)
#for cuts that are defined in folders but not in the cutflow table...
if doint:
cuthist_temp = input_mc.Get(cut + "/mHH_l")
cutevt_mc = cuthist_temp.Integral(
0,
cuthist_temp.GetXaxis().GetNbins() + 1) * scale_weight
if donormint:
cuthist_temp = input_mc.Get(normalization + "/mHH_l")
totevt_mc = cuthist_temp.Integral(
0,
cuthist_temp.GetXaxis().GetNbins() + 1) * scale_weight
eff_content = cutevt_mc / totevt_mc
eff_lst[i].SetBinContent(eff_lst[i].GetXaxis().FindBin(mass),
cutevt_mc / totevt_mc)
eff_lst[i].SetBinError(eff_lst[i].GetXaxis().FindBin(mass),
helpers.ratioerror(cutevt_mc, totevt_mc))
maxbincontent = max(maxbincontent, eff_content)
# print ratioerror(cutevt_mc, totevt_mc)
input_mc.Close()
canv.cd()
#maxbincontent = 0.15
#convert it to a TGraph
graph_lst.append(helpers.TH1toTAsym(eff_lst[i]))
graph_lst[i].SetLineColor(CONF.clr_lst[i])
graph_lst[i].SetMarkerStyle(CONF.mrk_lst[i])
graph_lst[i].SetMarkerColor(CONF.clr_lst[i])
graph_lst[i].SetMarkerSize(1)
graph_lst[i].SetMaximum(maxbincontent * 1.6)
graph_lst[i].SetMinimum(minbincontent)
#print cut_dic[cut]
legend.AddEntry(graph_lst[i], cut_dic[cut], "apl")
if cut == cut_lst[0]:
graph_lst[i].Draw("APC")
#gr.Draw("same L hist")
else:
graph_lst[i].Draw("PC")
#gr.Draw("same L hist")
legend.SetBorderSize(0)
legend.SetMargin(0.3)
legend.SetTextFont(42)
legend.SetTextSize(0.03)
legend.Draw()
# draw reference lines
yline05 = ROOT.TLine(1000, 0.0, 1000, maxbincontent)
yline05.SetLineStyle(9)
#yline05.Draw()
yline10 = ROOT.TLine(2000, 0.0, 2000, maxbincontent)
yline10.SetLineStyle(9)
#yline10.Draw()
# draw watermarks
xatlas, yatlas = 0.2, 0.87
#atlas = ROOT.TLatex(xatlas, yatlas, "ATLAS Preliminary")
#ATLASLabel(xatlas, yatlas, "Preliminary")
atlas = ROOT.TLatex(xatlas, yatlas, "ATLAS")
#atlas.SetTextAlign(22)
atlas.SetTextSize(0.04)
atlas.SetTextFont(72)
atlas.SetNDC()
atlas.Draw()
status = ROOT.TLatex(xatlas + 0.14, yatlas, CONF.StatusLabel)
#status.SetTextAlign(22)
status.SetTextSize(0.04)
status.SetTextFont(42)
status.SetNDC()
status.Draw()
myText(xatlas, yatlas - 0.05, 1, "G c=1.0, #sqrt{s} = 13 TeV",
CONF.paperlegsize - 2)
myText(xatlas, yatlas - 0.1, 1, "Boosted", CONF.paperlegsize - 2)
# finish up
canv.SaveAs(outputpath + outputname + "_" + canv.GetName() + ".pdf")
canv.SaveAs(outputpath + outputname + "_" + canv.GetName() + ".eps")
canv.SaveAs(outputpath + outputname + "_" + canv.GetName() + ".png")
canv.SaveAs(outputpath + outputname + "_" + canv.GetName() + ".C")
canv.Close()
def DrawSignalEff(cut_lst,
inputdir="b77",
outputname="",
normalization="All",
doint=False,
donormint=False,
dorel=False,
dorelfcomp=False):
### the first argument is the input directory
### the second argument is the output prefix name
### the third argument is relative to what normalization: 0 for total number of events
### 1 for signal mass region
afterscript = ("_rel" if dorel else "") + ("_ref" if dorelfcomp else "")
canv = ROOT.TCanvas(
inputdir + "_" + "Efficiency" + "_" + normalization + afterscript,
"Efficiency", 800, 800)
xleg, yleg = 0.52, 0.7
legend = ROOT.TLegend(xleg, yleg, xleg + 0.3, yleg + 0.2)
# setup basic plot parameters
# load input MC file
eff_lst = []
graph_lst = []
maxbincontent = 0.001
minbincontent = -0.001
for i, cut in enumerate(cut_lst):
eff_lst.append(
ROOT.TH1F(inputdir + "_" + cut, "%s; Mass, GeV; Efficiency" % cut,
int((highmass - lowmass) / 100), lowmass, highmass))
for mass in mass_lst:
#here could be changed to have more options
input_mc_type = "signal_G_hh_c10_M" if not ops.Xhh else "signal_X_hh_M"
input_mc = ROOT.TFile.Open(inputpath + input_mc_type +
"%i/hist-MiniNTuple.root" % mass)
cutflow_mc = input_mc.Get("CutFlowNoWeight").Clone(
"CutFlowNoWeight") #notice here we use no weight for now!
cutflow_mc_w = input_mc.Get("CutFlowWeight").Clone("CutFlowWeight")
if dorel:
maxbincontent = 1.0
if i > 0:
normalization = cut_lst[i - 1]
totevt_mc = cutflow_mc.GetBinContent(
cutflow_mc.GetXaxis().FindBin(normalization))
cutevt_mc = cutflow_mc.GetBinContent(
cutflow_mc.GetXaxis().FindBin(cut))
#this is a really dirty temp fix
scale_weight = (cutflow_mc.GetBinContent(cutflow_mc.GetXaxis().FindBin("All")) * 1.0)\
/ (cutflow_mc_w.GetBinContent(cutflow_mc_w.GetXaxis().FindBin("All")) * 1.0)
#this is really only for doing reference comparison only!
input_mc_ref = ROOT.TFile.Open(CONF.inputpath + "ref" + "/" +
"signal_G_hh_c10_M" +
"%i/hist-MiniNTuple.root" % mass)
cutflow_mc_ref = input_mc_ref.Get("CutFlowNoWeight").Clone(
"CutFlowNoWeight_ref") #notice here we use no weight for now!
cutflow_mc_w_ref = input_mc_ref.Get("CutFlowWeight").Clone(
"CutFlowWeight_ref")
totevt_mc_ref = cutflow_mc_ref.GetBinContent(
cutflow_mc_ref.GetXaxis().FindBin(normalization))
cutevt_mc_ref = cutflow_mc_ref.GetBinContent(
cutflow_mc_ref.GetXaxis().FindBin(cut))
scale_weight_ref = (cutflow_mc_ref.GetBinContent(cutflow_mc_ref.GetXaxis().FindBin("All")) * 1.0)\
/ (cutflow_mc_w_ref.GetBinContent(cutflow_mc_w_ref.GetXaxis().FindBin("All")) * 1.0)
#print cut, mass, cutevt_mc, totevt_mc, cutevt_mc_ref, totevt_mc_ref
#for cuts that are defined in folders but not in the cutflow table...
if doint:
cuthist_temp = input_mc.Get(cut + "/mHH_l")
cutevt_mc = cuthist_temp.Integral(
0,
cuthist_temp.GetXaxis().GetNbins() + 1) * scale_weight
cuthist_temp_ref = input_mc_ref.Get(cut + "/mHH_l")
cutevt_mc_ref = cuthist_temp_ref.Integral(
0,
cuthist_temp_ref.GetXaxis().GetNbins() +
1) * scale_weight_ref
if donormint:
cuthist_temp = input_mc.Get(normalization + "/mHH_l")
totevt_mc = cuthist_temp.Integral(
0,
cuthist_temp.GetXaxis().GetNbins() + 1) * scale_weight
cuthist_temp_ref = input_mc_ref.Get(normalization + "/mHH_l")
totevt_mc_ref = cuthist_temp_ref.Integral(
0,
cuthist_temp_ref.GetXaxis().GetNbins() +
1) * scale_weight_ref
#for ref comparison
if dorel and dorelfcomp:
totevt_mc = totevt_mc * (cutevt_mc_ref / totevt_mc_ref) * 1.0
elif dorelfcomp:
totevt_mc = cutevt_mc_ref * 1.0
minbincontent = 0.5
# if mass == 2500:
# print "m:{:>5} c:{:>24} evt:{:>8};".format(mass, cut, cutevt_mc)
#continue as usual
eff_content = cutevt_mc / totevt_mc
eff_lst[i].SetBinContent(eff_lst[i].GetXaxis().FindBin(mass),
cutevt_mc / totevt_mc)
eff_lst[i].SetBinError(eff_lst[i].GetXaxis().FindBin(mass),
helpers.ratioerror(cutevt_mc, totevt_mc))
maxbincontent = max(maxbincontent, eff_content)
# print ratioerror(cutevt_mc, totevt_mc)
input_mc.Close()
input_mc_ref.Close()
canv.cd()
#convert it to a TGraph
graph_lst.append(helpers.TH1toTAsym(eff_lst[i]))
graph_lst[i].SetLineColor(CONF.clr_lst[i])
graph_lst[i].SetMarkerStyle(20 + i)
graph_lst[i].SetMarkerColor(CONF.clr_lst[i])
graph_lst[i].SetMarkerSize(1)
graph_lst[i].SetMaximum(maxbincontent * 1.5)
graph_lst[i].SetMinimum(minbincontent)
legend.AddEntry(graph_lst[i], cut.replace("_", " "), "apl")
if cut == cut_lst[0]:
graph_lst[i].Draw("APC")
#gr.Draw("same L hist")
else:
graph_lst[i].Draw("PC")
#gr.Draw("same L hist")
legend.SetBorderSize(0)
legend.SetMargin(0.3)
legend.SetTextSize(0.03)
legend.Draw()
# draw reference lines
yline05 = ROOT.TLine(1000, 0.0, 1000, maxbincontent)
yline05.SetLineStyle(9)
yline05.Draw()
yline10 = ROOT.TLine(2000, 0.0, 2000, maxbincontent)
yline10.SetLineStyle(9)
yline10.Draw()
# draw watermarks
xatlas, yatlas = 0.35, 0.87
atlas = ROOT.TLatex(xatlas, yatlas, "ATLAS Internal")
hh4b = ROOT.TLatex(xatlas, yatlas - 0.06,
"RSG c=1.0" if not ops.Xhh else "2HDM")
lumi = ROOT.TLatex(xatlas, yatlas - 0.12, "MC #sqrt{s} = 13 TeV")
watermarks = [atlas, hh4b, lumi] if not CONF.thesis else [hh4b, lumi]
for wm in watermarks:
wm.SetTextAlign(22)
wm.SetTextSize(0.04)
wm.SetTextFont(42)
wm.SetNDC()
wm.Draw()
# finish up
canv.SaveAs(outputpath + outputname + ("_" if not ops.Xhh else "_2HDM_") +
canv.GetName() + ".pdf")
canv.Close()
def plot_RSG_syst_detail(masterdic, cut):
canv = ROOT.TCanvas(cut + "_" + "RSG" + "_" + "syst_detail", "Sytematics", 800, 800)
xleg, yleg = 0.52, 0.7
legend = ROOT.TLegend(xleg, yleg, xleg+0.3, yleg+0.2)
# setup basic plot parameters
# load input MC file
mass_lst = [1000, 1100, 1200, 1300, 1400, 1500, 1600, 1800, 2000, 2250, 2500, 2750, 3000]
eff_lst = []
graph_lst = []
maxbincontent = 100.0
minbincontent = -0.001
lowmass = 950
highmass = 3150
#create bsyst list
bsyst_lst = []
for i in bsyst:
if "up" in i:
bsyst_lst.append(i.replace("up", ""))
#now loop
draw_counter = 0
for i, syst in enumerate(bsyst_lst):
eff_lst.append( ROOT.TH1F(syst, "%s; Mass, GeV; Systematic Percentage Diff" %syst, int((highmass-lowmass)/100), lowmass, highmass) )
maxsyst = 0.0
for mass in mass_lst:
temp_col_dic = find_syst(masterdic, cut, syst, "RSG1_" + str(mass))
syst_eff = add_syst(temp_col_dic) #this is a tuple!
# if (syst_eff[0] * 100 < 3): #if the systematic contribution is less than 3 percent
# continue
eff_lst[i].SetBinContent(eff_lst[i].GetXaxis().FindBin(mass), syst_eff[0] * 100)
eff_lst[i].SetBinError(eff_lst[i].GetXaxis().FindBin(mass), 0)
#print syst, syst_eff[0]
maxbincontent = max(maxbincontent, syst_eff[0] * 100)
maxsyst = max(maxsyst, syst_eff[0] * 100)
#print maxsyst, i
#start the canvas
canv.cd()
#convert it to a graph
if maxsyst < 3: #don't draw everything
print syst
continue
graph_lst.append(helpers.TH1toTAsym(eff_lst[i]))
graph_lst[-1].SetLineColor(CONF.clr_lst[draw_counter])
graph_lst[-1].SetMarkerStyle(20 + draw_counter)
graph_lst[-1].SetMarkerColor(CONF.clr_lst[draw_counter])
graph_lst[-1].SetMarkerSize(1)
graph_lst[-1].SetMaximum(maxbincontent * 1.5)
graph_lst[-1].SetMinimum(minbincontent)
legend.AddEntry(graph_lst[-1], syst.replace("_", " "), "apl")
if draw_counter==0:
graph_lst[-1].Draw("APC")
draw_counter += 1
else:
graph_lst[-1].Draw("PC")
draw_counter += 1
legend.SetBorderSize(0)
legend.SetMargin(0.3)
legend.SetTextSize(0.04)
legend.Draw()
# draw reference lines
# draw watermarks
xatlas, yatlas = 0.35, 0.87
atlas = ROOT.TLatex(xatlas, yatlas, "ATLAS Internal")
hh4b = ROOT.TLatex(xatlas, yatlas-0.06, "RSG c=1.0")
lumi = ROOT.TLatex(xatlas, yatlas-0.12, "MC #sqrt{s} = 13 TeV")
watermarks = [atlas, hh4b, lumi]
for wm in watermarks:
wm.SetTextAlign(22)
wm.SetTextSize(0.04)
wm.SetTextFont(42)
wm.SetNDC()
wm.Draw()
# finish up
helpers.checkpath(CONF.inputpath + ops.inputdir + "/" + "Plot/Syst/")
canv.SaveAs(CONF.inputpath + ops.inputdir + "/" + "Plot/Syst/" + canv.GetName() + ".pdf")
canv.Close()
def plot_RSG_syst(masterdic, cut):
### the first argument is the input dictionary
### the second argument is the 2b/3b/4b regions
canv = ROOT.TCanvas(cut + "_" + "RSG" + "_" + "syst", "Sytematics", 800, 800)
xleg, yleg = 0.52, 0.7
legend = ROOT.TLegend(xleg, yleg, xleg+0.3, yleg+0.2)
# setup basic plot parameters
# load input MC file
mass_lst = [1000, 1100, 1200, 1300, 1400, 1500, 1600, 1800, 2000, 2250, 2500, 2750, 3000]
systag_lst = ["JER", "JMR", "Rtrk", "EFF", "Stat"]
systag_dic = {"JER":"JER", "JMR":"JMR", "Rtrk":"JES/JMS", "EFF":"b-tag SF", "Stat":"Stats"}
eff_lst = []
graph_lst = []
maxbincontent = 40.0
minbincontent = -0.001
lowmass = 950
highmass = 3150
for i, syst in enumerate(systag_lst):
eff_lst.append( ROOT.TH1F(syst, "%s; Mass, GeV; Systematic Percentage Diff" %syst, int((highmass-lowmass)/100), lowmass, highmass) )
for mass in mass_lst:
if syst is "Stat":
for key2 in masterdic[cut]:
if "RSG1_" + str(mass) in key2:
eff_lst[i].SetBinContent(eff_lst[i].GetXaxis().FindBin(mass), masterdic[cut][key2]["int_err"]/masterdic[cut][key2]["int"] * 100)
eff_lst[i].SetBinError(eff_lst[i].GetXaxis().FindBin(mass), 0)
else:
temp_col_dic = find_syst(masterdic, cut, syst, "RSG1_" + str(mass))
syst_eff = add_syst(temp_col_dic) #this is a tuple!
eff_lst[i].SetBinContent(eff_lst[i].GetXaxis().FindBin(mass), syst_eff[0] * 100)
eff_lst[i].SetBinError(eff_lst[i].GetXaxis().FindBin(mass), 0)
#print syst_eff[0]
maxbincontent = max(maxbincontent, syst_eff[0])
#start the canvas
canv.cd()
#convert it to a TGraph
graph_lst.append(helpers.TH1toTAsym(eff_lst[i]))
graph_lst[i].SetLineColor(CONF.clr_lst[i])
graph_lst[i].SetMarkerStyle(20 + i)
graph_lst[i].SetMarkerColor(CONF.clr_lst[i])
graph_lst[i].SetMarkerSize(1)
graph_lst[i].SetMaximum(maxbincontent * 1.5)
graph_lst[i].SetMinimum(minbincontent)
legend.AddEntry(graph_lst[i], systag_dic[syst].replace("_", " "), "apl")
if syst==systag_lst[0]:
graph_lst[i].Draw("APC")
#gr.Draw("same L hist")
else:
graph_lst[i].Draw("PC")
#gr.Draw("same L hist")
legend.SetBorderSize(0)
legend.SetMargin(0.3)
legend.SetTextSize(0.04)
legend.Draw()
# draw reference lines
# draw watermarks
xatlas, yatlas = 0.35, 0.87
atlas = ROOT.TLatex(xatlas, yatlas, "ATLAS Internal")
hh4b = ROOT.TLatex(xatlas, yatlas-0.06, "RSG c=1.0")
lumi = ROOT.TLatex(xatlas, yatlas-0.12, "MC #sqrt{s} = 13 TeV")
watermarks = [atlas, hh4b, lumi]
for wm in watermarks:
wm.SetTextAlign(22)
wm.SetTextSize(0.04)
wm.SetTextFont(42)
wm.SetNDC()
wm.Draw()
# finish up
helpers.checkpath(CONF.inputpath + ops.inputdir + "/" + "Plot/Syst/")
canv.SaveAs(CONF.inputpath + ops.inputdir + "/" + "Plot/Syst/" + canv.GetName() + ".pdf")
canv.Close()
