def Dump_BKGCompare(tag="FourTag", title="SR_Varations", region="Signal"):
column_lst = ["Prediction", "QCD", "ttbar"]
column_key_lst = ["data_est", "qcd_est",
"ttbar_est"] #for looping through the objects
texoutpath = inputpath + inputdir + "/" + "Plot/Tables/"
if not os.path.exists(texoutpath):
os.makedirs(texoutpath)
outFile = open(texoutpath + tag + "_" + title + ".tex", "w")
###
tableList = []
###
#start the table
add_table_head(tableList, column_lst, title=" " + tag)
##save a temp value
nominal = {}
for i, syst in enumerate(syst_lst):
#get the corresponding region
outstr = ""
outstr += syst.replace("_", " ") if syst is not "" else "Nominal"
systpath = "_" + syst if syst is not "" else ""
inputtex = inputpath + inputdir + (systpath + "/" + "sum_" + inputdir +
systpath + ".txt")
f1 = open(inputtex, 'r')
masterdic = json.load(f1)
#save the noiminal values
if (syst is ""):
for Types in column_key_lst:
nominal[Types] = helpers.round_sig(
masterdic[Types][tag][region], 2)
nominal[Types + "_err"] = helpers.round_sig(
masterdic[Types][tag][region + "_err"], 2)
#print masterdic, tag
for Types in column_key_lst:
value = (masterdic[Types][tag][region] / nominal[Types] - 1) * 100
error = helpers.ratioerror(masterdic[Types][tag][region],
nominal[Types],
masterdic[Types][tag][region + "_err"],
nominal[Types + "_err"]) * 100
outstr += add_entry(value, error, percent=True)
#finish up
del (masterdic)
f1.close()
#finish the current entry
outstr += "\\\\"
if (syst != syst_lst[0]):
tableList.append(outstr)
#finish the table
add_table_tail(tableList, column_lst)
#return the table
for line in tableList:
print line
outFile.write(line + " \n")
def Dump_BKGCompare(tag="FourTag", title="SR_Varations", region="Signal"):
column_lst = ["Prediction", "Diff", "QCD", "ttbar"]
column_key_lst = ["data_est", "data_est", "qcd_est", "ttbar_est"] #for looping through the objects
texoutpath = inputpath + inputdir + "/" + "Plot/Tables/"
if not os.path.exists(texoutpath):
os.makedirs(texoutpath)
outFile = open( texoutpath + tag + "_" + title + ".tex", "w")
###
tableList = []
###
#start the table
add_table_head(tableList, column_lst, title=" " + tag)
##save a temp value
nominal = {}
for i, syst in enumerate(syst_lst):
#get the corresponding region
outstr = ""
outstr += syst.replace("_", " ") if syst is not "" else "Nominal"
systpath = "_" + syst if syst is not "" else reweightpath
inputtex = inputpath + inputdir + (systpath + "/" + "sum_" + inputdir + systpath + ".txt")
f1 = open(inputtex, 'r')
masterdic = json.load(f1)
#save the noiminal values
if (syst is ""):
for Types in column_key_lst:
nominal[Types] = helpers.round_sig(masterdic[Types][tag][region], 2)
nominal[Types+"_err"] = helpers.round_sig(masterdic[Types][tag][region+"_err"], 2)
#print masterdic, tag
for j, Types in enumerate(column_key_lst):
if j == 0: ##for the first entry
value = masterdic[Types][tag][region]
error = masterdic[Types][tag][region+"_err"]
outstr += add_entry(value, error, percent=True)
else: ##do percentage
value = (masterdic[Types][tag][region]/nominal[Types] - 1) * 100
error = helpers.ratioerror(masterdic[Types][tag][region], nominal[Types],
masterdic[Types][tag][region+"_err"], nominal[Types+"_err"]) * 100
outstr += add_entry(value, error, percent=True)
#finish up
del(masterdic)
f1.close()
#finish the current entry
outstr+="\\\\"
if (syst!=syst_lst[-1]):
tableList.append(outstr)
#finish the table
add_table_tail(tableList, column_lst)
#return the table
for line in tableList:
print line
outFile.write(line+" \n")
def find_syst(masterdic, c, systag, col):
sys_lst = {}
#loopoing throught the dictionary
for key1 in masterdic:#get to the 2b/3b/4b region; containes the systemtaic info as well
if (c in key1) and (systag in key1):
for key2 in masterdic[key1]:#get to the qcd/ttbar/rsg region
if col in key2:
value_def = abs(masterdic[key1][key2]["int"] / masterdic[c][key2]["int"] - 1)
value_def_err = abs(helpers.ratioerror(masterdic[key1][key2]["int"], masterdic[c][key2]["int"], masterdic[key1][key2]["int_err"], masterdic[c][key2]["int_err"]))
sys_lst.update({key1: (value_def, value_def_err)})
if debug:
print systag, col, key1, key2, value_def
return sys_lst
def find_syst(masterdic, c, systag, col):
debug = False
sys_lst = {}
#loopoing throught the dictionary
for key1 in masterdic:#get to the 2b/3b/4b region; containes the systemtaic info as well
if (c in key1) and (systag in key1):
for key2 in masterdic[key1]:#get to the qcd/ttbar/rsg region
if col in key2:
if debug:
print systag, col, key1, key2
value_def = abs(masterdic[key1][key2]["int"] / masterdic[c][key2]["int"] - 1)
value_def_err = abs(helpers.ratioerror(masterdic[key1][key2]["int"], masterdic[c][key2]["int"], masterdic[key1][key2]["int_err"], masterdic[c][key2]["int_err"]))
sys_lst.update({key1: (value_def, value_def_err)})
return sys_lst
def GetDiff(dic1, dic2, histname=""):
result = {}
for i, cut in enumerate(cut_lst):
#get the corresponding region
cutcounts = {}
for j, region in enumerate(region_lst):
if dic2[cut][region]!= 0:
cutcounts[region] = (dic1[cut][region] - dic2[cut][region])/dic2[cut][region] * 100
cutcounts[region + "_err"] = helpers.ratioerror(dic1[cut][region], dic2[cut][region], \
dic1[cut][region + "_err"], dic2[cut][region + "_err"]) * 100
else:
cutcounts[region] = 0
cutcounts[region + "_err"] = 0
result[cut] = cutcounts
return {histname:result}
def DrawMulticomparison(inputlst, keyword="", prename="", Xrange=[0, 0], Yrange=[0, 0], norm=True, Logy=0, Rebin=1):
#print inputdir
tempname = "directcompare" + "_" + keyword + ("" if Logy == 0 else "_" + str(Logy))
canv = ROOT.TCanvas(tempname, tempname, 800, 800)
# 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()
xleg, yleg = 0.5, 0.6
legend = ROOT.TLegend(xleg, yleg, xleg+0.2, yleg+0.3)
counter = 0
maxbincontent = (0.05 if Logy ==0 else 10)
temphst_lst = []
graph_lst = []
tempratio_lst = []
for i, dic in enumerate(inputlst):
#print dic["file"], dic["path"] ##?????
refroot = ROOT.TFile.Open(inputpath + dic["file"])
temphst_lst.append(refroot.Get(dic["path"]).Clone())
tempratio_lst.append(refroot.Get(dic["path"]).Clone(dic["path"] + "_ratio"))
temphst_lst[i].SetDirectory(0) #otherwise the hist lives in the current open file
tempratio_lst[i].SetDirectory(0) #otherwise the hist lives in the current open file
if Rebin != 1:
temphst_lst[i].Rebin(Rebin)
tempratio_lst[i].Rebin(Rebin)
if norm:
if Xrange != [0, 0]:
temphst_lst[i].Scale(temphst_lst[0].Integral(temphst_lst[0].GetXaxis().FindBin(Xrange[0]), temphst_lst[0].GetXaxis().FindBin(Xrange[1] + 1))/temphst_lst[i].Integral(temphst_lst[0].GetXaxis().FindBin(Xrange[0]), temphst_lst[0].GetXaxis().FindBin(Xrange[1] + 1)))
else:
temphst_lst[i].Scale(temphst_lst[0].Integral(0, temphst_lst[0].GetXaxis().GetNbins()+1)/temphst_lst[i].Integral(0, temphst_lst[i].GetXaxis().GetNbins()+1))
for j in range(1, temphst_lst[0].GetNbinsX()+1):
try:
tempratio_lst[i].SetBinContent(j, temphst_lst[i].GetBinContent(j) / temphst_lst[0].GetBinContent(j))
tempratio_lst[i].SetBinError(j, helpers.ratioerror(\
temphst_lst[i].GetBinContent(j), temphst_lst[0].GetBinContent(j), \
temphst_lst[i].GetBinError(j), temphst_lst[0].GetBinError(j)))
except ZeroDivisionError:
pass
#print "Divide by zero! Check bin content in", canv.GetName()
maxbincontent = max(maxbincontent, temphst_lst[i].GetMaximum())
#graph_lst.append(helpers.TH1toTAsym(temphst_lst[i], efficiency=False))
temphst_lst[i].SetLineColor(1 if i == 0 else CONF.clr_lst[i])
#temphst_lst[i].SetLineStyle(1 + i)
temphst_lst[i].SetMarkerStyle(20 + i)
temphst_lst[i].SetMarkerColor(1 if i == 0 else CONF.clr_lst[i])
temphst_lst[i].SetMarkerSize(1)
temphst_lst[i].SetMaximum(maxbincontent * (1.5 if Logy == 0 else 150))
temphst_lst[i].SetMinimum(0.001 if Logy == 0 else 0.02)
if Xrange != [0, 0]:
#print Xrange
temphst_lst[i].GetXaxis().SetRangeUser(Xrange[0], Xrange[1])
chi2 = temphst_lst[i].Chi2Test(temphst_lst[0], "QU CHI2/NDF")
#legend.AddEntry(temphst_lst[i], dic["leg"] + " KS: " + str(('%.3g' % temphst_lst[i].KolmogorovTest(temphst_lst[0], "QU"))), "pl")
legend.AddEntry(temphst_lst[i], dic["leg"] + " chi2: " + str(('%.3g' % (chi2))), "pl")
temphst_lst[i].Draw("EP" if i==0 else "hist same")
refroot.Close()
legend.SetBorderSize(0)
legend.SetMargin(0.3)
legend.SetTextSize(0.04)
legend.Draw()
# draw watermarks
xatlas, yatlas = 0.28, 0.87
atlas = ROOT.TLatex(xatlas, yatlas, "ATLAS Internal")
hh4b = ROOT.TLatex(xatlas, yatlas-0.06, "Simulations")
lumi = ROOT.TLatex(xatlas, yatlas-0.12, "MC #sqrt{s} = 13 TeV")
info = ROOT.TLatex(xatlas, yatlas-0.06, keyword.replace("data_est_", "").replace("_mHH_l", "").replace("_", " "))
watermarks = [atlas, info]
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 i, dic in enumerate(inputlst):
tempratio_lst[i].SetLineColor(1 if i == 0 else CONF.clr_lst[i])
#tempratio_lst[i].SetLineStyle(1 + i)
tempratio_lst[i].SetMarkerStyle(20 + i)
tempratio_lst[i].SetMarkerColor(1 if i == 0 else CONF.clr_lst[i])
tempratio_lst[i].SetMarkerSize(1)
tempratio_lst[i].GetYaxis().SetTitleFont(43)
tempratio_lst[i].GetYaxis().SetTitleSize(28)
tempratio_lst[i].GetYaxis().SetLabelFont(43)
tempratio_lst[i].GetYaxis().SetLabelSize(28)
tempratio_lst[i].GetYaxis().SetTitle("ratio to ref")
tempratio_lst[i].GetYaxis().SetRangeUser(0.6, 1.5) #set range for ratio plot
tempratio_lst[i].GetYaxis().SetNdivisions(405)
tempratio_lst[i].GetXaxis().SetTitleFont(43)
tempratio_lst[i].GetXaxis().SetTitleOffset(3.5)
tempratio_lst[i].GetXaxis().SetTitleSize(28)
tempratio_lst[i].GetXaxis().SetLabelFont(43)
tempratio_lst[i].GetXaxis().SetLabelSize(28)
if Xrange != [0, 0]:
tempratio_lst[i].GetXaxis().SetRangeUser(Xrange[0], Xrange[1])
if i > 0:
tempratio_lst[i].Draw("ep" if i == 1 else "ep same")
# draw the ratio 1 line
line = ROOT.TLine(Xrange[0], 1.0, Xrange[1], 1.0)
line.SetLineStyle(1)
line.Draw()
#save and clean up
canv.SaveAs(outputpath + (prename + "_" if prename is not "" else "") + canv.GetName() + ".pdf")
pad0.Close()
pad1.Close()
canv.Close()
del(tempratio_lst)
del(temphst_lst)
del(graph_lst)
def DrawTrigEff(cut_lst, inputdir, outputname="", normalization="All"):
### 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 + "_" + "Efficiency" + "_" + normalization,
"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 = []
maxbincontent = 1
minbincontent = -0.01
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))
eff_lst[i].SetLineColor(2 + i)
eff_lst[i].SetMarkerStyle(20 + i)
eff_lst[i].SetMarkerColor(2 + i)
eff_lst[i].SetMarkerSize(1)
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") #notice here we use no weight for now!
totevt_mc = 0
totevt_mc = cutflow_mc.GetBinContent(
cutflow_mc.GetXaxis().FindBin(normalization))
maxbincontent = 1
cutevt_mc = cutflow_mc.GetBinContent(
cutflow_mc.GetXaxis().FindBin(cut))
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))
# print ratioerror(cutevt_mc, totevt_mc)
input_mc.Close()
eff_lst[i].SetMaximum(maxbincontent * 1.5)
eff_lst[i].SetMinimum(minbincontent)
legend.AddEntry(
eff_lst[i],
cut.replace("_", " ") if cut is not "PassTrig" else "PassJ420 lcw",
"apl")
canv.cd()
if cut == cut_lst[0]:
eff_lst[i].Draw("epl")
else:
eff_lst[i].Draw("same epl")
legend.SetBorderSize(0)
legend.SetMargin(0.3)
legend.SetTextSize(0.04)
legend.Draw()
# draw reference lines
xline90 = ROOT.TLine(lowmass, 0.9, highmass, 0.9)
xline90.SetLineStyle(3)
xline90.Draw()
xline95 = ROOT.TLine(lowmass, 0.95, highmass, 0.95)
xline95.SetLineStyle(4)
xline95.Draw()
xline98 = ROOT.TLine(lowmass, 0.98, highmass, 0.98)
xline98.SetLineStyle(5)
xline98.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()
# finish up
canv.SaveAs(outputpath + outputname + "_" + canv.GetName() + ".pdf")
canv.Close()
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 fitestimation(histname="", inputdic={}, weight=False):
'''weight controls whether the a/b tag ratio is applied'''
#now do the real work
print "***** estimation *****"
#do a dump fill first
outroot.cd()
est = {}
for i, cut in enumerate(cut_lst):
#get the corresponding region
cutcounts = {}
for j, region in enumerate(region_lst):
#start the histogram as a dumb holder
Ftransfer = 1.0
Ftransfer_err = 0.0
Ftransfer_corr = 0.0
Ntransfer = 1.0
#define where the qcd come from
ref_cut = "NoTag"
if cut in bkgest_dict.keys():
ref_cut = bkgest_dict[cut]
#reset for top, use the correct MCs
if "ttbar" in histname:
ref_cut = cut
#print ref_cut, histname, cut, region
#start the temp calculation of Ftransfer
#print fitresult
if fitresult and cut in word_dict.keys():
if word_dict[cut] < len(
fitresult["mu" + histname.replace("_est", "")]):
Ftransfer = fitresult["mu" + histname.replace("_est", "")][
word_dict[cut]]
Ftransfer_err = fitresult["mu" +
histname.replace("_est", "") +
"_e"][word_dict[cut]]
corr_temp = fitresult["corr_m"][word_dict[cut]]
Ftransfer_corr = corr_temp[
word_dict[cut] +
len(corr_temp) / 2] if not useOneTop else corr_temp[-1]
#print "cor is, ", fitresult["corr_m"], Ftransfer_corr, cut, histname, word_dict[cut]
else:
Ftransfer = inputdic["qcd"][cut]["Sideband"] / inputdic[
"qcd"][ref_cut]["Sideband"]
Ftransfer_err = helpers.ratioerror(
inputdic["qcd"][cut]["Sideband"],
inputdic["qcd"][ref_cut]["Sideband"])
#print histname, Ftransfer
for hst in plt_lst:
htemp_qcd = outroot.Get(
histname.replace("_est", "") + "_" + ref_cut + "_" +
region + "_" + hst).Clone()
#for ttbar, for mscale and mll, use 3b instead of 4b
if "ttbar" in histname and ("FourTag" in cut
or "ThreeTag" in cut):
#print ref_cut, histname, cut, region, htemp_qcd.Integral(0, htemp_qcd.GetNbinsX()+1)
hist_temp = outroot.Get(
histname.replace("_est", "") + "_" + "TwoTag_split" +
"_" + region + "_" + hst).Clone()
hist_temp.Scale(
htemp_qcd.Integral(0,
htemp_qcd.GetNbinsX() + 1) /
hist_temp.Integral(0,
hist_temp.GetNbinsX() + 1))
#print ref_cut, histname, cut, region, hist_temp.Integral(0, hist_temp.GetNbinsX()+1)
htemp_qcd = hist_temp.Clone()
del (hist_temp)
#proceed!
Ntransfer = htemp_qcd.Integral(0, htemp_qcd.GetNbinsX() + 1)
htemp_qcd.SetName(histname + "_" + cut + "_" + region + "_" +
hst)
htemp_qcd.Scale(Ftransfer)
## add weight!
if weight:
#print ref_cut, histname, cut, region
if cut in weight_dict.keys():
hist_temp_base = outroot.Get(
histname.replace("_est", "") + "_" +
weight_dict[cut][0] + "_" + "Sideband" + "_" +
hst).Clone("base")
hist_temp_model = outroot.Get(
histname.replace("_est", "") + "_" +
weight_dict[cut][1] + "_" + "Sideband" + "_" +
hst).Clone("model")
hist_temp_base.Scale(hist_temp_model.Integral() /
hist_temp_base.Integral())
hist_temp_model.Divide(hist_temp_base)
htemp_qcd.Multiply(hist_temp_model)
hist_temp_model.SetName(histname + "_" + cut + "_" +
region + "_" + hst + "_weight")
hist_temp_model.Write()
del (hist_temp_model)
del (hist_temp_base)
else:
pass
## end of add weight
htemp_qcd.Write()
del (htemp_qcd)
#get the notag sideband for the current version
plttemp = outroot.Get(histname + "_" + cut + "_" + region + "_" +
plt_m)
err = ROOT.Double(0.)
cutcounts[region] = plttemp.IntegralAndError(
0,
plttemp.GetXaxis().GetNbins() + 1, err)
cutcounts[region + "_err"] = float(err)
cutcounts[region +
"_syst_muqcd_fit_up"] = Ftransfer_err * Ntransfer
cutcounts[region +
"_syst_muqcd_fit_down"] = -Ftransfer_err * Ntransfer
cutcounts[region + "_scale_factor"] = Ftransfer
cutcounts[region + "_corr"] = Ftransfer_corr
#print plttemp.GetName(), cut, region, cutcounts[region], cutcounts[region + "_err"], cutcounts[region + "_syst_muqcd_fit_up"]
del (plttemp)
est[cut] = cutcounts
return {histname: est}
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 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 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 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 = 0.52, 0.7
legend = ROOT.TLegend(xleg, yleg, xleg + 0.3, yleg + 0.2)
# setup basic plot parameters
# load input MC file
eff_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))
eff_lst[i].SetLineColor(CONF.clr_lst[i])
eff_lst[i].SetMarkerStyle(20 + i)
eff_lst[i].SetMarkerColor(CONF.clr_lst[i])
eff_lst[i].SetMarkerSize(1)
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") #notice here we use no weight for now!
cutflow_mc_w = input_mc.Get("CutFlowWeight")
if dorel:
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()
eff_lst[i].SetMaximum(maxbincontent * 1.5)
eff_lst[i].SetMinimum(minbincontent)
legend.AddEntry(eff_lst[i], cut.replace("_", " "), "apl")
canv.cd()
if cut == cut_lst[0]:
eff_lst[i].Draw("epl")
else:
eff_lst[i].Draw("same epl")
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")
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 DrawMuqcd_split(prename="", qcdmc=True):
input_data = ROOT.TFile.Open(inputpath + "data_test/hist.root", "read")
input_ttbar = ROOT.TFile.Open(inputpath + "ttbar_comb_test/hist.root",
"read")
input_zjet = ROOT.TFile.Open(inputpath + "zjets_test/hist.root", "read")
outputroot.cd()
if (qcdmc):
input_qcd = ROOT.TFile.Open(inputpath + "signal_QCD/hist.root", "read")
for j, cut in enumerate(tag_lst):
for i in range(4): #4 regions
data_muqcd = ROOT.TH1D(
str(i) + "_" + "data_" + cut + "_" + "muqcd", "muqcd", 1, 1, 2)
data_muqcd.GetYaxis().SetTitle("#mu qcd")
if (qcdmc):
mc_muqcd = ROOT.TH1D(
str(i) + "_" + "mc_" + cut + "_" + "muqcd", "muqcd", 1, 1,
2)
mc_muqcd.GetYaxis().SetTitle("#mu qcd")
#very stupid protection to distinguish 2b and 2bs
for k, ch in enumerate(channels):
aftercutname = "_" + "r" + str(i) + "_" + ch + "/mHH_l"
histname = cut + aftercutname
#print histname
hist_data = input_data.Get(histname).Clone()
hist_ttbar = input_ttbar.Get(histname).Clone()
hist_zjet = input_zjet.Get(histname).Clone()
hist_temp = hist_data.Clone()
hist_temp.Add(hist_ttbar, -1)
hist_temp.Add(hist_zjet, -1)
Nqcd_err = ROOT.Double(0.)
Nqcd = hist_temp.IntegralAndError(
0,
hist_temp.GetXaxis().GetNbins() + 1, Nqcd_err)
#get the 0 tag numbers
refname = "NoTag" + aftercutname
ref_data = input_data.Get(refname).Clone()
ref_ttbar = input_ttbar.Get(refname).Clone()
ref_zjet = input_zjet.Get(refname).Clone()
ref_temp = ref_data.Clone()
ref_temp.Add(ref_ttbar, -1)
ref_temp.Add(ref_zjet, -1)
refqcd_err = ROOT.Double(0.)
refqcd = ref_temp.IntegralAndError(
0,
ref_temp.GetXaxis().GetNbins() + 1, refqcd_err)
#print cut, ch, Nmcqcd, refmcqcd
#compute mu qcd
if refqcd > 0:
data_muqcd.Fill(ch, Nqcd / refqcd)
data_muqcd.SetBinError(
data_muqcd.GetXaxis().FindBin(ch),
helpers.ratioerror(Nqcd,
refqcd,
ea=Nqcd_err,
eb=refqcd_err))
else:
#print refqcd, histname
data_muqcd.Fill(ch, 0)
data_muqcd.SetBinError(data_muqcd.GetXaxis().FindBin(ch),
0)
if (qcdmc):
hist_mcqcd = input_qcd.Get(histname).Clone()
Nmcqcd_err = ROOT.Double(0.)
Nmcqcd = hist_mcqcd.IntegralAndError(
0,
hist_mcqcd.GetXaxis().GetNbins() + 1, Nmcqcd_err)
ref_mcqcd = input_qcd.Get(refname).Clone()
refmcqcd_err = ROOT.Double(0.)
refmcqcd = ref_mcqcd.IntegralAndError(
0,
ref_mcqcd.GetXaxis().GetNbins() + 1, refmcqcd_err)
if refmcqcd > 0:
mc_muqcd.Fill(ch, Nmcqcd / refmcqcd)
mc_muqcd.SetBinError(
mc_muqcd.GetXaxis().FindBin(ch),
helpers.ratioerror(Nmcqcd,
refmcqcd,
ea=Nmcqcd_err,
eb=refmcqcd_err))
outputroot.cd()
data_muqcd.SetMaximum(data_muqcd.GetMaximum() * 1.5)
data_muqcd.Write()
if (qcdmc):
mc_muqcd.SetMaximum(data_muqcd.GetMaximum() * 1.5)
mc_muqcd.Write()
input_data.Close()
input_ttbar.Close()
input_zjet.Close()
if (qcdmc):
input_qcd.Close()
#make the plot from the saved macro, it is stupid
for j, cut in enumerate(tag_lst):
drawsplit_overlayed("data_" + cut + "_" + "muqcd",
cut + "_" + "mustudy",
labelname=cut + " data")
if (qcdmc):
drawsplit_overlayed("mc_" + cut + "_" + "muqcd",
cut + "_" + "mc_mustudy",
labelname=cut + " MC")
def DrawMuqcd_split(prename="", qcdmc=True):
input_data = ROOT.TFile.Open(inputpath + "data_test/hist.root", "read")
input_ttbar = ROOT.TFile.Open(inputpath + "ttbar_comb_test/hist.root", "read")
input_zjet = ROOT.TFile.Open(inputpath + "zjets_test/hist.root", "read")
outputroot.cd()
if (qcdmc):
input_qcd = ROOT.TFile.Open(inputpath + "signal_QCD/hist.root", "read")
for j, cut in enumerate(tag_lst):
for i in range(4):#4 regions
data_muqcd = ROOT.TH1D(str(i) + "_" + "data_" + cut + "_" + "muqcd", "muqcd",1,1,2)
data_muqcd.GetYaxis().SetTitle("#mu qcd")
if (qcdmc):
mc_muqcd = ROOT.TH1D(str(i) + "_" + "mc_" + cut + "_" + "muqcd","muqcd",1,1,2)
mc_muqcd.GetYaxis().SetTitle("#mu qcd")
#very stupid protection to distinguish 2b and 2bs
for k, ch in enumerate(channels):
aftercutname = "_" + "r" + str(i) + "_" + ch + "/mHH_l"
histname = cut + aftercutname
#print histname
hist_data = input_data.Get(histname).Clone()
hist_ttbar = input_ttbar.Get(histname).Clone()
hist_zjet = input_zjet.Get(histname).Clone()
hist_temp = hist_data.Clone()
hist_temp.Add(hist_ttbar, -1)
hist_temp.Add(hist_zjet, -1)
Nqcd_err = ROOT.Double(0.)
Nqcd = hist_temp.IntegralAndError(0, hist_temp.GetXaxis().GetNbins()+1, Nqcd_err)
#get the 0 tag numbers
refname = "NoTag" + aftercutname
ref_data = input_data.Get(refname).Clone()
ref_ttbar = input_ttbar.Get(refname).Clone()
ref_zjet = input_zjet.Get(refname).Clone()
ref_temp = ref_data.Clone()
ref_temp.Add(ref_ttbar, -1)
ref_temp.Add(ref_zjet, -1)
refqcd_err = ROOT.Double(0.)
refqcd = ref_temp.IntegralAndError(0, ref_temp.GetXaxis().GetNbins()+1, refqcd_err)
#print cut, ch, Nmcqcd, refmcqcd
#compute mu qcd
if refqcd > 0:
data_muqcd.Fill(ch, Nqcd/refqcd)
data_muqcd.SetBinError(data_muqcd.GetXaxis().FindBin(ch), helpers.ratioerror(Nqcd, refqcd, ea=Nqcd_err, eb=refqcd_err))
else:
#print refqcd, histname
data_muqcd.Fill(ch, 0)
data_muqcd.SetBinError(data_muqcd.GetXaxis().FindBin(ch), 0)
if (qcdmc):
hist_mcqcd = input_qcd.Get(histname).Clone()
Nmcqcd_err = ROOT.Double(0.)
Nmcqcd = hist_mcqcd.IntegralAndError(0, hist_mcqcd.GetXaxis().GetNbins()+1, Nmcqcd_err)
ref_mcqcd = input_qcd.Get(refname).Clone()
refmcqcd_err = ROOT.Double(0.)
refmcqcd = ref_mcqcd.IntegralAndError(0, ref_mcqcd.GetXaxis().GetNbins()+1, refmcqcd_err)
if refmcqcd > 0:
mc_muqcd.Fill(ch, Nmcqcd/refmcqcd)
mc_muqcd.SetBinError(mc_muqcd.GetXaxis().FindBin(ch), helpers.ratioerror(Nmcqcd, refmcqcd, ea=Nmcqcd_err, eb=refmcqcd_err))
outputroot.cd()
data_muqcd.SetMaximum(data_muqcd.GetMaximum() * 1.5)
data_muqcd.Write()
if (qcdmc):
mc_muqcd.SetMaximum(data_muqcd.GetMaximum() * 1.5)
mc_muqcd.Write()
input_data.Close()
input_ttbar.Close()
input_zjet.Close()
if (qcdmc):
input_qcd.Close()
#make the plot from the saved macro, it is stupid
for j, cut in enumerate(tag_lst):
drawsplit_overlayed("data_" + cut + "_" + "muqcd", cut + "_" + "mustudy", labelname=cut + " data")
if (qcdmc):
drawsplit_overlayed("mc_" + cut + "_" + "muqcd", cut + "_" + "mc_mustudy", labelname=cut + " MC")
def DrawMuqcd(qcdmc=False):
outputroot.cd()
input_data = ROOT.TFile.Open(inputpath + "data_test/hist.root", "read")
input_ttbar = ROOT.TFile.Open(inputpath + "ttbar_comb_test/hist.root", "read")
input_zjet = ROOT.TFile.Open(inputpath + "zjets_test/hist.root", "read")
if (qcdmc):
input_qcd = ROOT.TFile.Open(inputpath + "signal_QCD/hist.root", "read")
for j, cut in enumerate(tag_lst):
canv = ROOT.TCanvas(cut + "_" + "mustudy", "mustudy", 800, 800)
xleg, yleg = 0.52, 0.67
legend = ROOT.TLegend(xleg, yleg, xleg+0.3, yleg+0.2)
data_muqcd = ROOT.TH1D("data_" + cut + "_" + "muqcd","muqcd",1,1,2)
data_muqcd.SetMarkerStyle(20)
data_muqcd.SetMarkerColor(1)
data_muqcd.SetLineColor(1)
data_muqcd.SetMarkerSize(1)
data_muqcd.GetYaxis().SetTitle("#mu qcd")
legend.AddEntry(data_muqcd, "Data Est", "apl")
if (qcdmc):
mc_muqcd = ROOT.TH1D("mc_" + cut + "_" + "muqcd","muqcd",1,1,2)
mc_muqcd.SetMarkerStyle(20)
mc_muqcd.SetMarkerColor(2)
mc_muqcd.SetLineColor(2)
mc_muqcd.SetMarkerSize(1)
mc_muqcd.GetYaxis().SetTitle("#mu qcd")
legend.AddEntry(mc_muqcd, "Dijet MC", "apl")
#very stupid protection to distinguish 2b and 2bs
for k, ch in enumerate(channels):
histname = cut + "_" + ch + "/mHH_l"
#print histname
hist_data = input_data.Get(histname).Clone()
hist_ttbar = input_ttbar.Get(histname).Clone()
hist_zjet = input_zjet.Get(histname).Clone()
hist_temp = hist_data.Clone()
hist_temp.Add(hist_ttbar, -1)
hist_temp.Add(hist_zjet, -1)
Nqcd_err = ROOT.Double(0.)
Nqcd = hist_temp.IntegralAndError(0, hist_temp.GetXaxis().GetNbins()+1, Nqcd_err)
#get the 0 tag numbers
refname = "NoTag" + "_" + ch + "/mHH_l"
ref_data = input_data.Get(refname).Clone()
ref_ttbar = input_ttbar.Get(refname).Clone()
ref_zjet = input_zjet.Get(refname).Clone()
ref_temp = ref_data.Clone()
ref_temp.Add(ref_ttbar, -1)
ref_temp.Add(ref_zjet, -1)
refqcd_err = ROOT.Double(0.)
refqcd = ref_temp.IntegralAndError(0, ref_temp.GetXaxis().GetNbins()+1, refqcd_err)
#print cut, ch, Nmcqcd, refmcqcd
#compute mu qcd
if refqcd > 0:
data_muqcd.Fill(ch, Nqcd/refqcd)
data_muqcd.SetBinError(data_muqcd.GetXaxis().FindBin(ch), helpers.ratioerror(Nqcd, refqcd, ea=Nqcd_err, eb=refqcd_err))
#for QCD MC
if (qcdmc):
hist_mcqcd = input_qcd.Get(histname).Clone()
Nmcqcd_err = ROOT.Double(0.)
Nmcqcd = hist_mcqcd.IntegralAndError(0, hist_mcqcd.GetXaxis().GetNbins()+1, Nmcqcd_err)
ref_mcqcd = input_qcd.Get(refname).Clone()
refmcqcd_err = ROOT.Double(0.)
refmcqcd = ref_mcqcd.IntegralAndError(0, ref_mcqcd.GetXaxis().GetNbins()+1, refmcqcd_err)
if refmcqcd > 0:
mc_muqcd.Fill(ch, Nmcqcd/refmcqcd)
mc_muqcd.SetBinError(mc_muqcd.GetXaxis().FindBin(ch), helpers.ratioerror(Nmcqcd, refmcqcd, ea=Nmcqcd_err, eb=refmcqcd_err))
data_muqcd.SetMaximum(data_muqcd.GetMaximum() * 2.5)
data_muqcd.Draw("EPL")
#canv.SaveAs(outputpath + data_muqcd.GetName() + ".pdf")
#canv.Clear()
if (qcdmc):
mc_muqcd.SetMaximum(mc_muqcd.GetMaximum() * 2.5)
mc_muqcd.Draw("EPL SAME")
myText(0.5, 0.87, 1, "Region: %s" % cut, 42)
legend.SetBorderSize(0)
legend.SetMargin(0.3)
legend.SetTextSize(0.04)
legend.Draw()
canv.SaveAs(outputpath + data_muqcd.GetName() + ".pdf")
canv.Close()
input_data.Close()
input_ttbar.Close()
input_zjet.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 = 0.52, 0.7
legend = ROOT.TLegend(xleg, yleg, xleg+0.3, yleg+0.2)
# setup basic plot parameters
# load input MC file
eff_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) )
eff_lst[i].SetLineColor(CONF.clr_lst[i])
eff_lst[i].SetMarkerStyle(20 + i)
eff_lst[i].SetMarkerColor(CONF.clr_lst[i])
eff_lst[i].SetMarkerSize(1)
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") #notice here we use no weight for now!
cutflow_mc_w = input_mc.Get("CutFlowWeight")
if dorel:
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()
eff_lst[i].SetMaximum(maxbincontent * 1.5)
eff_lst[i].SetMinimum(minbincontent)
legend.AddEntry(eff_lst[i], cut.replace("_", " "), "apl")
canv.cd()
if cut==cut_lst[0]:
eff_lst[i].Draw("epl")
else:
eff_lst[i].Draw("same epl")
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")
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 DrawTrigEff(cut_lst, inputdir, outputname="", normalization="All"):
### 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 + "_" + "Efficiency" + "_" + normalization, "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 = []
maxbincontent = 1
minbincontent = -0.01
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) )
eff_lst[i].SetLineColor(2 + i)
eff_lst[i].SetMarkerStyle(20 + i)
eff_lst[i].SetMarkerColor(2 + i)
eff_lst[i].SetMarkerSize(1)
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") #notice here we use no weight for now!
totevt_mc = 0
totevt_mc = cutflow_mc.GetBinContent(cutflow_mc.GetXaxis().FindBin(normalization))
maxbincontent = 1
cutevt_mc = cutflow_mc.GetBinContent(cutflow_mc.GetXaxis().FindBin(cut))
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))
# print ratioerror(cutevt_mc, totevt_mc)
input_mc.Close()
eff_lst[i].SetMaximum(maxbincontent * 1.5)
eff_lst[i].SetMinimum(minbincontent)
legend.AddEntry(eff_lst[i], cut.replace("_", " ") if cut is not "PassTrig" else "PassJ420 lcw", "apl")
canv.cd()
if cut==cut_lst[0]:
eff_lst[i].Draw("epl")
else:
eff_lst[i].Draw("same epl")
legend.SetBorderSize(0)
legend.SetMargin(0.3)
legend.SetTextSize(0.04)
legend.Draw()
# draw reference lines
xline90 = ROOT.TLine(lowmass, 0.9, highmass, 0.9)
xline90.SetLineStyle(3)
xline90.Draw()
xline95 = ROOT.TLine(lowmass, 0.95, highmass, 0.95)
xline95.SetLineStyle(4)
xline95.Draw()
xline98 = ROOT.TLine(lowmass, 0.98, highmass, 0.98)
xline98.SetLineStyle(5)
xline98.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()
# finish up
canv.SaveAs(outputpath + outputname + "_" + canv.GetName() + ".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 fitestimation_test(histname="", inputdic={}):
#now do the real work
print "***** estimation *****"
#do a dump fill first
outroot.cd()
est = {}
for i, cut in enumerate(cut_lst):
#get the corresponding region
cutcounts = {}
for j, region in enumerate(region_lst):
#start the histogram as a dumb holder
Ftransfer = 1.0
Ftransfer_err = 0.0
Ftransfer_OneTag = 1.0
Ftransfer_OneTag_err = 0.0
Ftransfer_NoTag = 1.0
Ftransfer_NoTag_err = 0.0
Ftransfer_corr = 0.0
Ntransfer = 1.0
#define where the qcd come from
ref_cut = "NoTag"
ref_cut_NoTag = "NoTag"
ref_cut_OneTag = "NoTag"
if cut in bkgest_dict.keys():
ref_cut = bkgest_dict[cut]
ref_cut_NoTag = bkgest_dict_NoTag[cut]
ref_cut_OneTag = bkgest_dict_OneTag[cut]
#reset for top, use the correct MCs
if "ttbar" in histname:
ref_cut = cut
#start the temp calculation of Ftransfer
#print ref_cut, histname, cut, region
#print fitresult
if fitresult and cut in word_dict.keys():
if word_dict[cut] < len(fitresult["mu" + histname.replace("_est", "")]):
Ftransfer = fitresult["mu" + histname.replace("_est", "")][word_dict[cut]]
Ftransfer_err = fitresult["mu" + histname.replace("_est", "") + "_e"][word_dict[cut]]
Ftransfer_NoTag = fitresult_NoTag["mu" + histname.replace("_est", "")][word_dict[cut]]
Ftransfer_NoTag_err = fitresult_NoTag["mu" + histname.replace("_est", "") + "_e"][word_dict[cut]]
Ftransfer_OneTag = fitresult_OneTag["mu" + histname.replace("_est", "")][word_dict[cut]]
Ftransfer_OneTag_err = fitresult_OneTag["mu" + histname.replace("_est", "") + "_e"][word_dict[cut]]
corr_temp = fitresult["corr_m"][word_dict[cut]]
Ftransfer_corr = corr_temp[word_dict[cut] + len(corr_temp)/2] if not useOneTop else corr_temp[-1]
#print "cor is, ", fitresult["corr_m"], Ftransfer_corr, cut, histname, word_dict[cut]
else:
Ftransfer = inputdic["qcd"][cut]["Sideband"]/inputdic["qcd"][ref_cut]["Sideband"]
Ftransfer_err = helpers.ratioerror(inputdic["qcd"][cut]["Sideband"], inputdic["qcd"][ref_cut]["Sideband"])
#print histname, cut, Ftransfer, Ftransfer_NoTag, Ftransfer_OneTag
for hst in plt_lst:
htemp_qcd = outroot.Get(histname.replace("_est", "") + "_" + ref_cut + "_" + region + "_" + hst).Clone()
htemp_qcd_NoTag = outroot.Get(histname.replace("_est", "") + "_" + ref_cut_NoTag + "_" + region + "_" + hst).Clone()
htemp_qcd_OneTag = outroot.Get(histname.replace("_est", "") + "_" + ref_cut_OneTag + "_" + region + "_" + hst).Clone()
#for ttbar, for mscale and mll, use 2bs instead of 3/4b
if "ttbar" in histname and ("FourTag" in cut or ("ThreeTag" in cut and "Signal" in region)):
hist_temp = outroot.Get(histname.replace("_est", "") + "_" + "TwoTag_split" + "_" + region + "_" + hst).Clone()
hist_temp.Scale(htemp_qcd.Integral(0, htemp_qcd.GetNbinsX()+1)/hist_temp.Integral(0, hist_temp.GetNbinsX()+1))
htemp_qcd = hist_temp.Clone()
del(hist_temp)
#proceed!
Ntransfer = htemp_qcd.Integral(0, htemp_qcd.GetNbinsX()+1)
htemp_qcd.SetName(histname + "_" + cut + "_" + region + "_" + hst)
htemp_qcd.Scale(Ftransfer)
##this is nasty for now
if "qcd" in histname:
if ("split" in cut): ##2bs; this works wonderfully
htemp_qcd_NoTag.Scale(Ftransfer_NoTag)
htemp_qcd_OneTag.Scale(Ftransfer_OneTag)
htemp_qcd.Add(htemp_qcd_OneTag, 1)
htemp_qcd.Add(htemp_qcd_NoTag, -1)
elif ("ThreeTag" in cut):
htemp_qcd_NoTag.Scale(Ftransfer_NoTag)
htemp_qcd_OneTag.Scale(Ftransfer_OneTag)
htemp_qcd.Add(htemp_qcd_OneTag, 1)
htemp_qcd.Add(htemp_qcd_NoTag, -1)
#htemp_qcd.Add(htemp_qcd_NoTag, -1)
elif ("FourTag" in cut):
htemp_qcd_NoTag.Scale(Ftransfer_NoTag)
htemp_qcd_OneTag.Scale(Ftransfer_OneTag)
htemp_qcd.Add(htemp_qcd_OneTag, 1)
htemp_qcd.Add(htemp_qcd_NoTag, -1)
##directly scale from 2tag
# htemp_qcd.Scale(2)
# htemp_qcd.Add(htemp_qcd_NoTag, -1)
elif "ttbar" in histname:
htemp_qcd.Scale(1/Ftransfer)#unscale
if ("split" in cut): ##2bs; this works wonderfully
htemp_qcd.Scale(Ftransfer + Ftransfer_OneTag - Ftransfer_NoTag)
elif ("ThreeTag" in cut):
htemp_qcd.Scale(Ftransfer + Ftransfer_OneTag - Ftransfer_NoTag )
elif ("FourTag" in cut):
htemp_qcd.Scale(Ftransfer + Ftransfer_OneTag - Ftransfer_NoTag) #htemp_qcd.Scale(2 * Ftransfer - Ftransfer_NoTag)
htemp_qcd.Write()
del(htemp_qcd)
del(htemp_qcd_NoTag)
del(htemp_qcd_OneTag)
#get the notag sideband for the current version
plttemp = outroot.Get(histname + "_" + cut + "_" + region + "_" + plt_m)
err = ROOT.Double(0.)
cutcounts[region] = plttemp.IntegralAndError(0, plttemp.GetXaxis().GetNbins()+1, err)
cutcounts[region + "_err"] = float(err)
cutcounts[region + "_syst_muqcd_fit_up"] = Ftransfer_err * Ntransfer
cutcounts[region + "_syst_muqcd_fit_down"] = -Ftransfer_err * Ntransfer
cutcounts[region + "_scale_factor"] = Ftransfer
cutcounts[region + "_corr"] = Ftransfer_corr
#print cut, region, Ntransfer, Ftransfer_err, cutcounts[region + "_syst_muqcd_fit_up"]
del(plttemp)
est[cut] = cutcounts
return {histname:est}
def DrawMuqcd(qcdmc=False):
outputroot.cd()
input_data = ROOT.TFile.Open(inputpath + "data_test/hist.root", "read")
input_ttbar = ROOT.TFile.Open(inputpath + "ttbar_comb_test/hist.root",
"read")
input_zjet = ROOT.TFile.Open(inputpath + "zjets_test/hist.root", "read")
if (qcdmc):
input_qcd = ROOT.TFile.Open(inputpath + "signal_QCD/hist.root", "read")
for j, cut in enumerate(tag_lst):
canv = ROOT.TCanvas(cut + "_" + "mustudy", "mustudy", 800, 800)
xleg, yleg = 0.52, 0.67
legend = ROOT.TLegend(xleg, yleg, xleg + 0.3, yleg + 0.2)
data_muqcd = ROOT.TH1D("data_" + cut + "_" + "muqcd", "muqcd", 1, 1, 2)
data_muqcd.SetMarkerStyle(20)
data_muqcd.SetMarkerColor(1)
data_muqcd.SetLineColor(1)
data_muqcd.SetMarkerSize(1)
data_muqcd.GetYaxis().SetTitle("#mu qcd")
legend.AddEntry(data_muqcd, "Data Est", "apl")
if (qcdmc):
mc_muqcd = ROOT.TH1D("mc_" + cut + "_" + "muqcd", "muqcd", 1, 1, 2)
mc_muqcd.SetMarkerStyle(20)
mc_muqcd.SetMarkerColor(2)
mc_muqcd.SetLineColor(2)
mc_muqcd.SetMarkerSize(1)
mc_muqcd.GetYaxis().SetTitle("#mu qcd")
legend.AddEntry(mc_muqcd, "Dijet MC", "apl")
#very stupid protection to distinguish 2b and 2bs
for k, ch in enumerate(channels):
histname = cut + "_" + ch + "/mHH_l"
#print histname
hist_data = input_data.Get(histname).Clone()
hist_ttbar = input_ttbar.Get(histname).Clone()
hist_zjet = input_zjet.Get(histname).Clone()
hist_temp = hist_data.Clone()
hist_temp.Add(hist_ttbar, -1)
hist_temp.Add(hist_zjet, -1)
Nqcd_err = ROOT.Double(0.)
Nqcd = hist_temp.IntegralAndError(
0,
hist_temp.GetXaxis().GetNbins() + 1, Nqcd_err)
#get the 0 tag numbers
refname = "NoTag" + "_" + ch + "/mHH_l"
ref_data = input_data.Get(refname).Clone()
ref_ttbar = input_ttbar.Get(refname).Clone()
ref_zjet = input_zjet.Get(refname).Clone()
ref_temp = ref_data.Clone()
ref_temp.Add(ref_ttbar, -1)
ref_temp.Add(ref_zjet, -1)
refqcd_err = ROOT.Double(0.)
refqcd = ref_temp.IntegralAndError(
0,
ref_temp.GetXaxis().GetNbins() + 1, refqcd_err)
#print cut, ch, Nmcqcd, refmcqcd
#compute mu qcd
if refqcd > 0:
data_muqcd.Fill(ch, Nqcd / refqcd)
data_muqcd.SetBinError(
data_muqcd.GetXaxis().FindBin(ch),
helpers.ratioerror(Nqcd,
refqcd,
ea=Nqcd_err,
eb=refqcd_err))
#for QCD MC
if (qcdmc):
hist_mcqcd = input_qcd.Get(histname).Clone()
Nmcqcd_err = ROOT.Double(0.)
Nmcqcd = hist_mcqcd.IntegralAndError(
0,
hist_mcqcd.GetXaxis().GetNbins() + 1, Nmcqcd_err)
ref_mcqcd = input_qcd.Get(refname).Clone()
refmcqcd_err = ROOT.Double(0.)
refmcqcd = ref_mcqcd.IntegralAndError(
0,
ref_mcqcd.GetXaxis().GetNbins() + 1, refmcqcd_err)
if refmcqcd > 0:
mc_muqcd.Fill(ch, Nmcqcd / refmcqcd)
mc_muqcd.SetBinError(
mc_muqcd.GetXaxis().FindBin(ch),
helpers.ratioerror(Nmcqcd,
refmcqcd,
ea=Nmcqcd_err,
eb=refmcqcd_err))
data_muqcd.SetMaximum(data_muqcd.GetMaximum() * 2.5)
data_muqcd.Draw("EPL")
#canv.SaveAs(outputpath + data_muqcd.GetName() + ".pdf")
#canv.Clear()
if (qcdmc):
mc_muqcd.SetMaximum(mc_muqcd.GetMaximum() * 2.5)
mc_muqcd.Draw("EPL SAME")
myText(0.5, 0.87, 1, "Region: %s" % cut, 42)
legend.SetBorderSize(0)
legend.SetMargin(0.3)
legend.SetTextSize(0.04)
legend.Draw()
canv.SaveAs(outputpath + data_muqcd.GetName() + ".pdf")
canv.Close()
input_data.Close()
input_ttbar.Close()
input_zjet.Close()
def fitestimation(histname="", inputdic={}, weight=False):
'''weight controls whether the a/b tag ratio is applied'''
#now do the real work
print "***** estimation *****"
#do a dump fill first
outroot.cd()
est = {}
for i, cut in enumerate(cut_lst):
#get the corresponding region
cutcounts = {}
for j, region in enumerate(region_lst):
#start the histogram as a dumb holder
Ftransfer = 1.0
Ftransfer_err = 0.0
Ftransfer_corr = 0.0
Ntransfer = 1.0
#define where the qcd come from
ref_cut = "NoTag"
if cut in bkgest_dict.keys():
ref_cut = bkgest_dict[cut]
#reset for top, use the correct MCs
if "ttbar" in histname:
ref_cut = cut
#print ref_cut, histname, cut, region
#start the temp calculation of Ftransfer
#print fitresult
if fitresult and cut in word_dict.keys():
if word_dict[cut] < len(fitresult["mu" + histname.replace("_est", "")]):
Ftransfer = fitresult["mu" + histname.replace("_est", "")][word_dict[cut]]
Ftransfer_err = fitresult["mu" + histname.replace("_est", "") + "_e"][word_dict[cut]]
corr_temp = fitresult["corr_m"][word_dict[cut]]
Ftransfer_corr = corr_temp[word_dict[cut] + len(corr_temp)/2] if not useOneTop else corr_temp[-1]
#print "cor is, ", fitresult["corr_m"], Ftransfer_corr, cut, histname, word_dict[cut]
else:
Ftransfer = inputdic["qcd"][cut]["Sideband"]/inputdic["qcd"][ref_cut]["Sideband"]
Ftransfer_err = helpers.ratioerror(inputdic["qcd"][cut]["Sideband"], inputdic["qcd"][ref_cut]["Sideband"])
#print histname, Ftransfer
for hst in plt_lst:
htemp_qcd = outroot.Get(histname.replace("_est", "") + "_" + ref_cut + "_" + region + "_" + hst).Clone()
#for ttbar, for mscale and mll, use 2bs instead of 3/4b
if "ttbar" in histname and ("FourTag" in cut or ("ThreeTag" in cut and "Signal" in region)):
#print ref_cut, histname, cut, region, htemp_qcd.Integral(0, htemp_qcd.GetNbinsX()+1)
hist_temp = outroot.Get(histname.replace("_est", "") + "_" + "TwoTag_split" + "_" + region + "_" + hst).Clone()
hist_temp.Scale(htemp_qcd.Integral(0, htemp_qcd.GetNbinsX()+1)/hist_temp.Integral(0, hist_temp.GetNbinsX()+1))
#print ref_cut, histname, cut, region, hist_temp.Integral(0, hist_temp.GetNbinsX()+1)
htemp_qcd = hist_temp.Clone()
del(hist_temp)
#proceed!
Ntransfer = htemp_qcd.Integral(0, htemp_qcd.GetNbinsX()+1)
htemp_qcd.SetName(histname + "_" + cut + "_" + region + "_" + hst)
htemp_qcd.Scale(Ftransfer)
## add weight!
if weight:
#print ref_cut, histname, cut, region
if cut in weight_dict.keys():
hist_temp_base = outroot.Get(histname.replace("_est", "") + "_" + weight_dict[cut][0] + "_" + "Sideband" + "_" + hst).Clone("base")
hist_temp_model = outroot.Get(histname.replace("_est", "") + "_" + weight_dict[cut][1] + "_" + "Sideband" + "_" + hst).Clone("model")
hist_temp_base.Scale(hist_temp_model.Integral()/hist_temp_base.Integral())
hist_temp_model.Divide(hist_temp_base)
htemp_qcd.Multiply(hist_temp_model)
hist_temp_model.SetName(histname + "_" + cut + "_" + region + "_" + hst + "_weight")
hist_temp_model.Write()
del(hist_temp_model)
del(hist_temp_base)
else:
pass
## end of add weight
htemp_qcd.Write()
del(htemp_qcd)
#get the notag sideband for the current version
plttemp = outroot.Get(histname + "_" + cut + "_" + region + "_" + plt_m)
err = ROOT.Double(0.)
cutcounts[region] = plttemp.IntegralAndError(0, plttemp.GetXaxis().GetNbins()+1, err)
cutcounts[region + "_err"] = float(err)
cutcounts[region + "_syst_muqcd_fit_up"] = Ftransfer_err * Ntransfer
cutcounts[region + "_syst_muqcd_fit_down"] = -Ftransfer_err * Ntransfer
cutcounts[region + "_scale_factor"] = Ftransfer
cutcounts[region + "_corr"] = Ftransfer_corr
#print plttemp.GetName(), cut, region, cutcounts[region], cutcounts[region + "_err"], cutcounts[region + "_syst_muqcd_fit_up"]
del(plttemp)
est[cut] = cutcounts
return {histname:est}
def fitestimation_test(histname="", inputdic={}):
#now do the real work
print "***** estimation *****"
#do a dump fill first
outroot.cd()
est = {}
for i, cut in enumerate(cut_lst):
#get the corresponding region
cutcounts = {}
for j, region in enumerate(region_lst):
#start the histogram as a dumb holder
Ftransfer = 1.0
Ftransfer_err = 0.0
Ftransfer_OneTag = 1.0
Ftransfer_OneTag_err = 0.0
Ftransfer_NoTag = 1.0
Ftransfer_NoTag_err = 0.0
Ftransfer_corr = 0.0
Ntransfer = 1.0
#define where the qcd come from
ref_cut = "NoTag"
ref_cut_NoTag = "NoTag"
ref_cut_OneTag = "NoTag"
if cut in bkgest_dict.keys():
ref_cut = bkgest_dict[cut]
ref_cut_NoTag = bkgest_dict_NoTag[cut]
ref_cut_OneTag = bkgest_dict_OneTag[cut]
#reset for top, use the correct MCs
if "ttbar" in histname:
ref_cut = cut
#start the temp calculation of Ftransfer
#print ref_cut, histname, cut, region
#print fitresult
if fitresult and cut in word_dict.keys():
if word_dict[cut] < len(
fitresult["mu" + histname.replace("_est", "")]):
Ftransfer = fitresult["mu" + histname.replace("_est", "")][
word_dict[cut]]
Ftransfer_err = fitresult["mu" +
histname.replace("_est", "") +
"_e"][word_dict[cut]]
Ftransfer_NoTag = fitresult_NoTag[
"mu" + histname.replace("_est", "")][word_dict[cut]]
Ftransfer_NoTag_err = fitresult_NoTag[
"mu" + histname.replace("_est", "") +
"_e"][word_dict[cut]]
Ftransfer_OneTag = fitresult_OneTag[
"mu" + histname.replace("_est", "")][word_dict[cut]]
Ftransfer_OneTag_err = fitresult_OneTag[
"mu" + histname.replace("_est", "") +
"_e"][word_dict[cut]]
corr_temp = fitresult["corr_m"][word_dict[cut]]
Ftransfer_corr = corr_temp[
word_dict[cut] +
len(corr_temp) / 2] if not useOneTop else corr_temp[-1]
#print "cor is, ", fitresult["corr_m"], Ftransfer_corr, cut, histname, word_dict[cut]
else:
Ftransfer = inputdic["qcd"][cut]["Sideband"] / inputdic[
"qcd"][ref_cut]["Sideband"]
Ftransfer_err = helpers.ratioerror(
inputdic["qcd"][cut]["Sideband"],
inputdic["qcd"][ref_cut]["Sideband"])
#print histname, cut, Ftransfer, Ftransfer_NoTag, Ftransfer_OneTag
for hst in plt_lst:
htemp_qcd = outroot.Get(
histname.replace("_est", "") + "_" + ref_cut + "_" +
region + "_" + hst).Clone()
htemp_qcd_NoTag = outroot.Get(
histname.replace("_est", "") + "_" + ref_cut_NoTag + "_" +
region + "_" + hst).Clone()
htemp_qcd_OneTag = outroot.Get(
histname.replace("_est", "") + "_" + ref_cut_OneTag + "_" +
region + "_" + hst).Clone()
#for ttbar, for mscale and mll, use 3b instead of 4b
if "ttbar" in histname and ("FourTag" in cut
or "ThreeTag" in cut):
hist_temp = outroot.Get(
histname.replace("_est", "") + "_" + "TwoTag_split" +
"_" + region + "_" + hst).Clone()
hist_temp.Scale(
htemp_qcd.Integral(0,
htemp_qcd.GetNbinsX() + 1) /
hist_temp.Integral(0,
hist_temp.GetNbinsX() + 1))
htemp_qcd = hist_temp.Clone()
del (hist_temp)
#proceed!
Ntransfer = htemp_qcd.Integral(0, htemp_qcd.GetNbinsX() + 1)
htemp_qcd.SetName(histname + "_" + cut + "_" + region + "_" +
hst)
htemp_qcd.Scale(Ftransfer)
##this is nasty for now
if "qcd" in histname:
if ("split" in cut): ##2bs; this works wonderfully
htemp_qcd_NoTag.Scale(Ftransfer_NoTag)
htemp_qcd_OneTag.Scale(Ftransfer_OneTag)
htemp_qcd.Add(htemp_qcd_OneTag, 1)
htemp_qcd.Add(htemp_qcd_NoTag, -1)
elif ("ThreeTag" in cut):
htemp_qcd_NoTag.Scale(Ftransfer_NoTag)
htemp_qcd_OneTag.Scale(Ftransfer_OneTag)
htemp_qcd.Add(htemp_qcd_OneTag, 1)
htemp_qcd.Add(htemp_qcd_NoTag, -1)
#htemp_qcd.Add(htemp_qcd_NoTag, -1)
elif ("FourTag" in cut):
htemp_qcd_NoTag.Scale(Ftransfer_NoTag)
htemp_qcd_OneTag.Scale(Ftransfer_OneTag)
htemp_qcd.Add(htemp_qcd_OneTag, 1)
htemp_qcd.Add(htemp_qcd_NoTag, -1)
##directly scale from 2tag
# htemp_qcd.Scale(2)
# htemp_qcd.Add(htemp_qcd_NoTag, -1)
elif "ttbar" in histname:
htemp_qcd.Scale(1 / Ftransfer) #unscale
if ("split" in cut): ##2bs; this works wonderfully
htemp_qcd.Scale(Ftransfer + Ftransfer_OneTag -
Ftransfer_NoTag)
elif ("ThreeTag" in cut):
htemp_qcd.Scale(Ftransfer + Ftransfer_OneTag -
Ftransfer_NoTag)
elif ("FourTag" in cut):
htemp_qcd.Scale(
Ftransfer + Ftransfer_OneTag - Ftransfer_NoTag
) #htemp_qcd.Scale(2 * Ftransfer - Ftransfer_NoTag)
htemp_qcd.Write()
del (htemp_qcd)
del (htemp_qcd_NoTag)
del (htemp_qcd_OneTag)
#get the notag sideband for the current version
plttemp = outroot.Get(histname + "_" + cut + "_" + region + "_" +
plt_m)
err = ROOT.Double(0.)
cutcounts[region] = plttemp.IntegralAndError(
0,
plttemp.GetXaxis().GetNbins() + 1, err)
cutcounts[region + "_err"] = float(err)
cutcounts[region +
"_syst_muqcd_fit_up"] = Ftransfer_err * Ntransfer
cutcounts[region +
"_syst_muqcd_fit_down"] = -Ftransfer_err * Ntransfer
cutcounts[region + "_scale_factor"] = Ftransfer
cutcounts[region + "_corr"] = Ftransfer_corr
#print cut, region, Ntransfer, Ftransfer_err, cutcounts[region + "_syst_muqcd_fit_up"]
del (plttemp)
est[cut] = cutcounts
return {histname: est}
def DrawSignalEff(cut_lst, inputdir="b77", outputname="", normalization="All", doint=False, donormint=False, dorel=False, dosum=False, signal="G_hh_c10"):
### 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, 600)
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)/0.1), lowmass, highmass) )
for mass in mass_lst:
if signal == "G_hh_c20" and mass == 2750:
continue
#here could be changed to have more options
input_mc = ROOT.TFile.Open(inputpath + "signal_" + signal + "_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/1000.), cutevt_mc/totevt_mc)
eff_lst[i].SetBinError(eff_lst[i].GetXaxis().FindBin(mass/1000.), helpers.ratioerror(cutevt_mc, totevt_mc))
# for j in range(1, eff_lst[i].GetNbinsX() + 1):
# eff_lst[i].GetXaxis().SetBinLabel(j, str(eff_lst[i].GetXaxis().GetBinLowEdge(j)/1000.))
if signal == "G_hh_c10":
eff_lst[i].GetXaxis().SetTitle("m(G_{kk}) [TeV]")
if signal == "G_hh_c20":
eff_lst[i].GetXaxis().SetTitle("m(G_{kk}) [TeV]")
if signal == "X_hh":
eff_lst[i].GetXaxis().SetTitle("m(Scalar) [TeV]")
maxbincontent = max(maxbincontent, eff_content)
# print ratioerror(cutevt_mc, totevt_mc)
input_mc.Close()
if dosum:##add in a sum curve
eff_lst.append( ROOT.TH1F(inputdir + "_" + "sum", "%s; Mass [GeV]; Acceptance x Efficiency" %cut, int((highmass-lowmass)/0.1), lowmass, highmass) )
for i, cut in enumerate(cut_lst):
eff_lst[-1].Add(eff_lst[i])
maxbincontent = eff_lst[-1].GetMaximum()
for i, cut in enumerate(eff_lst):
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]
if i < len(cut_lst):
legend.AddEntry(graph_lst[i], cut_dic[cut_lst[i]], "apl")
else: ##of corse this is do sum as well
legend.AddEntry(graph_lst[i], "All of above", "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.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 + 0.1, yatlas, "Simulation")
#status.SetTextAlign(22)
status.SetTextSize(0.04)
status.SetTextFont(42)
status.SetNDC()
status.Draw()
if signal == "G_hh_c10":
signal_leg = "G_{kk} k/#bar{M}_{Pl} = 1,"
if signal == "G_hh_c20":
signal_leg = "G_{kk} k/#bar{M}_{Pl} = 2,"
if signal == "X_hh":
signal_leg = "Scalar,"
myText(xatlas, yatlas-0.05, 1, signal_leg + " #sqrt{s} = 13 TeV", CONF.paperlegsize)
myText(xatlas, yatlas-0.1, 1, "Boosted", CONF.paperlegsize)
# finish up
canv.SaveAs(outputpath + signal + "_" + outputname + "_" + canv.GetName() + ".pdf")
canv.SaveAs(outputpath + signal + "_" + outputname + "_" + canv.GetName() + ".eps")
canv.SaveAs(outputpath + signal + "_" + outputname + "_" + canv.GetName() + ".png")
canv.SaveAs(outputpath + signal + "_" + outputname + "_" + canv.GetName() + ".C")
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()
