def RatioCanvas(canvas_name,
canvas_title,
canw=500,
canh=600,
ratio_size_as_fraction=0.35):
from ROOT import TCanvas, TPad
c = TCanvas(canvas_name, canvas_title, canw, canh)
c.cd()
top = TPad("pad_top", "This is the top pad", 0.0, ratio_size_as_fraction,
1.0, 1.0)
top.SetBottomMargin(0.02 / float(top.GetHNDC()))
top.SetTopMargin(0.04 / float(top.GetHNDC()))
top.SetRightMargin(0.05)
top.SetLeftMargin(0.16)
top.SetFillColor(0)
top.Draw()
tobject_collector.append(top)
c.cd()
bot = TPad("pad_bot", "This is the bottom pad", 0.0, 0.0, 1.0,
ratio_size_as_fraction)
bot.SetBottomMargin(0.11 / float(bot.GetHNDC()))
bot.SetTopMargin(0.02 / float(bot.GetHNDC()))
bot.SetRightMargin(0.05)
bot.SetLeftMargin(0.16)
bot.SetFillColor(0)
bot.Draw()
tobject_collector.append(bot)
return c
def plot_data_vs_refold(args, regularisation_settings, tau):
'''
Plot the differences between the unfolded and refolded distributions
TODO Include also with best tau - redo unfolding with best tau then come here
'''
from ROOT import gStyle
variable = regularisation_settings.variable
channel = regularisation_settings.channel
plot_outpath = regularisation_settings.outpath.replace('tables/', 'plots/')+'tauscan/taus/'
make_folder_if_not_exists(plot_outpath)
# tau as string name for output
tau = str(tau).replace('.', 'p')
outfile = plot_outpath+'data_vs_refold_'+channel+'_'+variable+'_tau_'+tau+'.pdf'
if args.run_measured_as_data:
outfile = plot_outpath+'measured_vs_refold_'+channel+'_'+variable+'_tau_'+tau+'.pdf'
if args.run_smeared_measured_as_data:
outfile = plot_outpath+'smeared_vs_refold_'+channel+'_'+variable+'_tau_'+tau+'.pdf'
if args.unfolded_binning:
outfile = outfile.replace('.pdf', '_unf_binning.pdf')
c = TCanvas('c1','c1',1000,800)
gStyle.SetOptStat(0)
p1 = TPad("pad1", "p1",0.0,0.2,1.0,1.0,21)
p1.SetFillColor(0);
p1.Draw()
p2 = TPad("pad2", "p2",0.0,0.0,1.0,0.2,22)
p2.SetFillColor(0);
p2.Draw()
p1.cd()
regularisation_settings.h_data.SetTitle("Data vs Refolded Data;;NEvents")
regularisation_settings.h_data.Draw()
regularisation_settings.h_refolded.SetLineColor(2)
regularisation_settings.h_refolded.Draw("same")
leg1 = TLegend(0.7, 0.8, 0.9, 0.9)
leg1.SetLineColor(0)
leg1.SetFillColor(0)
leg1.AddEntry(regularisation_settings.h_data, "Data")
leg1.AddEntry(regularisation_settings.h_refolded, "Refolded Data")
leg1.Draw()
p2.cd()
h_ratio = regularisation_settings.h_data.Clone()
h_ratio.Divide(regularisation_settings.h_refolded)
h_ratio.SetTitle(";"+variable+";")
h_ratio.SetLineColor(1);
h_ratio.Draw()
c.SaveAs(outfile)
c.Delete()
print "Written plots to {outfile}".format(outfile = outfile)
return
def makePlot(mds, ds, pdf):
""" Mass fit plot """
frame = mds.frame()
ds.plotOn(frame, DataError(RooAbsData.SumW2), MarkerSize(1))
pdf.plotOn(frame, LineWidth(2))
# pull histogram
pullHist = frame.pullHist()
pullFrame = mds.frame(Title(''))
pullFrame.addPlotable(pullHist, 'P')
pullFrame.GetYaxis().SetRangeUser(-5, 5)
canvas = TCanvas('m(Ds)', 'm(Ds)', 600, 700)
canvas.cd()
pad1 = TPad('pad1', 'pad1', .01, .20, .99, .99)
pad2 = TPad('pad2', 'pad2', .01, .01, .99, .20)
pad1.Draw()
pad2.Draw()
pad1.cd()
pad1.SetLeftMargin(0.15)
pad1.SetFillColor(0)
frame.GetXaxis().SetTitleSize(0.05)
frame.GetXaxis().SetTitleOffset(0.85)
frame.GetXaxis().SetLabelSize(0.04)
frame.GetYaxis().SetTitleOffset(1.6)
frame.Draw()
pad2.cd()
pad2.SetLeftMargin(0.15)
pad2.SetFillColor(0)
pullFrame.SetMarkerSize(0.05)
pullFrame.Draw()
mdsRange = fitRange()['mDs']
lineUp = TLine(mdsRange[0], 3, mdsRange[1], 3)
lineUp.SetLineColor(kBlue)
lineUp.SetLineStyle(2)
lineUp.Draw()
lineCe = TLine(mdsRange[0], 0, mdsRange[1], 0)
lineCe.SetLineColor(kBlue)
lineCe.SetLineStyle(1)
lineCe.SetLineWidth(2)
lineCe.Draw()
lineD0 = TLine(mdsRange[0], -3, mdsRange[0], -3)
lineD0.SetLineColor(kBlue)
lineD0.SetLineStyle(2)
lineD0.Draw()
canvas.Update()
def plot3(key, xsections, histos, names, LogY, weights, outputDIR):
c1=TCanvas(key, key, 800, 600)
pad1 = TPad("pad1", "", 0.00, 0.0, 0.99, 0.99)
pad1.SetGridx()
pad1.SetGridy()
pad1.SetFillColor(0)
pad1.SetLineColor(0)
pad1.SetBottomMargin(0.1)
pad1.Draw()
leg1 = TLegend(0.68,0.55,0.86,0.86)
histos[0].GetXaxis().SetLabelSize(0)
histos[0].SetMarkerStyle(20)
for i in range(0,len(histos)):
#if histos[i].Integral()==0: continue
histos[i].Scale(xsections[i]/weights[i])
histos[i].SetLineColor(i+1)
histos[i].SetLineWidth(2)
pad1.cd()
if LogY:
pad1.SetLogy()
ymax=[]
histos[0].Draw('pe')
for i in range(0, len(histos)):
ymax.append(histos[i].GetMaximum())
ymax.sort(reverse=True)
histos[0].SetMaximum(1.2* ymax[0])
#histos[0].SetMinimum(0.1)
for i in range(1,len(histos)):
histos[i].Draw('same h')
histos[0].GetXaxis().SetTitle(key)
histos[0].GetXaxis().SetTitleSize(0.04)
histos[0].GetXaxis().SetTitleOffset(1.1)
histos[0].GetXaxis().SetLabelSize(0.035)
histos[0].GetYaxis().SetTitle("XS/bin [pb]")
histos[0].GetYaxis().SetTitleSize(0.04)
histos[0].GetYaxis().SetTitleOffset(1.09)
histos[0].GetYaxis().SetLabelSize(0.035)
leg1.AddEntry(histos[0], names[0])
for i in range(1,len(histos)):
leg1.AddEntry(histos[i], names[i])
leg1.SetFillStyle(0)
leg1.SetBorderSize(0)
leg1.Draw()
c1.Update()
if LogY:
c1.SaveAs(outputDIR + '/' + key + '_log.png')
c1.SaveAs(outputDIR + '/' + key + '_log.pdf')
else:
c1.SaveAs(outputDIR + '/' + key + '.png')
c1.SaveAs(outputDIR + '/' + key + '.pdf')
for i in range(0,len(histos)):
histos[i].Scale(weights[i]/xsections[i])
def PlotFakeRatio(ratio):
c = TCanvas("c", "canvas", 800, 800)
gStyle.SetOptStat(0)
gStyle.SetLegendBorderSize(0)
pad = TPad("pad", "pad", 0.01, 0.01, 0.99, 0.99)
pad.Draw()
pad.cd()
pad.SetGrid()
pad.SetFillColor(0)
pad.SetFrameBorderMode(0)
pad.SetBorderMode(0)
xaxis_title = "Photon P_{T} [GeV]"
leg = getLegend(xmin=0.5, ymin=0.7, scale=0.75)
fake_style(ratio)
ratio.SetTitle("")
ratio.GetYaxis().SetTitle("Fake Ratio")
# ratio.GetYaxis().SetTitleOffset(0.5)
ratio.GetXaxis().SetTitle(xaxis_title)
# ratio.GetYaxis().SetRangeUser(0.75,1.2)
print SetBounds([ratio], scale=1)
ratio.Draw("p same")
leg.AddEntry(ratio, "#frac{Data_{ISO}}{Data_{Non-ISO}}", "lp")
leg.Draw()
lumi_label = '%s' % float('%.3g' %
(max(config.lumi.values()) / 1000.)) + " fb^{-1}"
texLumi, texCMS = getCMSText(lumi_label, config.version, scale=0.8)
SaveAs(c,
"fake_ratio_%s" % parser.args.variable,
year=config.version,
sub="GammaPurity/FakeRatio/")
NonuJetpT_mad = TH1D("NonuJetpT madspin", "", 20, 0, 200)
NonuJetpT_mad.SetStats(0)
NonuJetpT_mad.Sumw2()
NonuJetpT_mad.GetYaxis().SetTitle("a.u.")
NonuJetpT_mad.GetYaxis().SetTitleSize(0.05)
NonuJetpT_mad.GetYaxis().SetTitleOffset(0.75)
NonuJetpT_mad.GetXaxis().SetLabelSize(0)
NonuJetpT_mad.SetMinimum(0)
NonuJetpT_nomad = TH1D("NonuJetpT nomadspin", "", 20, 0, 200)
NonuJetpT_nomad.SetStats(0)
NonuJetpT_nomad.Sumw2()
c1 = TCanvas("tauphi", "tauphi", 800, 600)
tauphi_pad1 = TPad("pad1", "", 0.00, 0.20, 0.99, 0.99)
tauphi_pad2 = TPad("pad2", "", 0.00, 0.00, 0.99, 0.20)
tauphi_pad1.SetFillColor(0)
tauphi_pad1.SetLineColor(0)
tauphi_pad2.SetFillColor(0)
tauphi_pad2.SetLineColor(0)
tauphi_pad1.SetBottomMargin(0.03)
tauphi_pad2.SetTopMargin(0.15)
tauphi_pad2.SetBottomMargin(0.3)
tauphi_pad1.Draw()
tauphi_pad2.Draw()
c2 = TCanvas("taueta", "taueta", 800, 600)
taueta_pad1 = TPad("pad1", "", 0.00, 0.20, 0.99, 0.99)
taueta_pad2 = TPad("pad2", "", 0.00, 0.00, 0.99, 0.20)
taueta_pad1.SetFillColor(0)
taueta_pad1.SetLineColor(0)
taueta_pad2.SetFillColor(0)
def makeDiTauStack(outDir,
inFile,
rootDir,
s,
labelX,
units="GeV",
left=False,
channel="",
json="Golden",
log=False,
dndm=False,
doRatio=False,
year=2017,
sign='OS',
LTcut=0.,
cat='mmtt',
wait='wait'):
tdrstyle.setTDRStyle()
writeExtraText = True # if extra text
extraText = "Preliminary" # default extra text is "Preliminary"
lumi_sqrtS = "13 TeV"
if json == "Golden": lumi_13TeV = channel + " 41.8 fb^{-1}, 2017"
iPeriod = 4 # 1=7TeV, 2=8TeV, 3=7+8TeV, 7=7+8+13TeV
xR = 0.65 #legend parameters
xR = 0.2 #legend parameters
H = 600
W = 600
H_ref = 600
W_ref = 600
# references for T, B, L, R
T = 0.08 * H_ref
B = 0.12 * H_ref
L = 0.16 * W_ref
R = 0.04 * W_ref
#margins for inbetween the pads in a ratio plot
B_ratio = 0.1 * H_ref
T_ratio = 0.03 * H_ref
#margin required for lebal on bottom of raito plot
B_ratio_label = 0.3 * H_ref
c = TCanvas('c1', 'c1', 50, 50, W, H)
c.SetFillColor(0)
c.SetBorderMode(0)
c.SetFrameFillStyle(0)
c.SetFrameBorderMode(0)
if not doRatio:
c.SetLeftMargin(L / W)
c.SetRightMargin(R / W)
c.SetTopMargin(T / H)
c.SetBottomMargin(B / H)
c.cd()
ratioPad = TPad("pad2", "", 0.0, 0.0, 1.0, 0.29)
plotPad = TPad("pad1", "", 0.0016, 0.291, 1.0, 1.0)
if doRatio:
plotPad.SetTicks(0, 0)
plotPad.SetLeftMargin(L / W)
plotPad.SetRightMargin(R / W)
plotPad.SetTopMargin(T / H)
plotPad.SetBottomMargin(B_ratio / H)
plotPad.SetFillColor(0)
plotPad.SetBottomMargin(0)
ratioPad.SetLeftMargin(L / W)
ratioPad.SetRightMargin(R / W)
ratioPad.SetTopMargin(T_ratio / H)
ratioPad.SetTopMargin(0.007)
ratioPad.SetBottomMargin(B_ratio_label / H)
ratioPad.SetGridy(1)
ratioPad.SetFillColor(4000)
else:
plotPad = TPad("pad1", "", 0.0, 0.03, 1.0, 1.0)
plotPad.SetLeftMargin(L / W)
plotPad.SetRightMargin(R / W)
plotPad.SetTopMargin(T / H)
plotPad.SetBottomMargin(B / H)
plotPad.Draw()
plotPad.cd()
print("In makeStack inFile={0:s}".format(inFile))
f = TFile(inFile)
groups = ['data', 'Reducible', 'Rare', 'ZZ4L', 'Signal']
histo = {}
colors = {
'data': 0,
'Reducible': kMagenta - 10,
'Rare': kBlue - 8,
'ZZ4L': kAzure - 9,
'Signal': kRed
}
hs = THStack("hs", "")
for group in groups:
if len(cat) == 4:
histo[group] = f.Get("h{0:s}_{1:s}_Mtt".format(group, cat))
else:
histo[group] = f.Get("h{0:s}_ee{1:s}_Mtt".format(group, cat))
histo2 = f.Get("h{0:s}_mm{1:s}_Mtt".format(group, cat))
histo[group].Add(histo2)
if dndm: convertToDNDM(histo[group])
if group == 'data':
applyDATAStyle(histo[group])
else:
applyStyle(histo[group], colors[group], 1, 1001)
if group != 'data': hs.Add(histo[group])
try:
hMax = 1.2 * max(histo['data'].GetMaximum(), hs.GetMaximum())
except KeyError:
hMax = 1.2 * hs.GetMaximum()
hs.SetMaximum(hMax)
hs.Draw("HIST")
try:
histo['data'].Draw("e,SAME")
except KeyError:
pass
if doRatio:
hs.GetXaxis().SetLabelSize(0)
else:
if units != "":
hs.GetXaxis().SetTitle(labelX + " [" + units + "]")
else:
hs.GetXaxis().SetTitle(labelX)
hs.GetYaxis().SetTitle("Events")
hs.GetYaxis().SetTitleOffset(1)
if dndm: hs.GetYaxis().SetTitle("dN/d" + labelX)
c.cd()
if doRatio:
data2 = histo['data'].Clone("data")
mc = histo['Rare']
mc.Add(histo['Reducible'])
mc.Add(histo['ZZ4L'])
xmin = mc.GetXaxis().GetXmin()
xmax = mc.GetXaxis().GetXmax()
line = TLine(xmin, 1.0, xmax, 1.0)
line.SetLineWidth(1)
line.SetLineColor(kBlack)
ratioPad.Draw()
ratioPad.cd()
data2.Divide(data2, mc)
data2.SetMarkerStyle(20)
data2.SetTitleSize(0.12, "Y")
data2.SetTitleOffset(0.40, "Y")
data2.SetTitleSize(0.12, "X")
data2.SetLabelSize(0.10, "X")
data2.SetLabelSize(0.08, "Y")
data2.GetYaxis().SetRangeUser(0.62, 1.38)
data2.GetYaxis().SetNdivisions(305)
data2.GetYaxis().SetTitle("Obs/Exp ")
if units != "":
data2.GetXaxis().SetTitle(labelX + " [" + units + "]")
else:
data2.GetXaxis().SetTitle(labelX)
data2.Draw("P")
line.Draw()
c.cd()
plotPad.cd()
l = TLegend(xR, 0.55, xR + 0.28, 0.9)
for group in groups:
try:
l.AddEntry(histo[group], group, "F")
except KeyError:
continue
l.SetBorderSize(0)
l.SetFillColor(0)
l.SetFillStyle(0)
l.SetTextSize(0.04)
l.Draw()
lTex1 = TLatex(120., 0.97 * hMax, 'Preliminary {0:d}'.format(year))
lTex1.SetTextSize(0.04)
lTex1.Draw()
signText = 'Same Sign'
if sign == 'OS': signText = 'Opposite Sign'
lTex2 = TLatex(120., 0.90 * hMax, '{0:s}'.format(signText))
lTex2.SetTextSize(0.04)
lTex2.Draw()
if len(cat) == 4:
lt = {
'eeet': '#it{l}#it{l}#it{e}#tau',
'eemt': '#it{l}#it{l}#mu#tau',
'eett': '#it{l}#it{l}#tau#tau',
'mmet': '#mu#mu#it{e}#tau',
'mmmt': '#mu#mu#mu#tau',
'mmtt': '#mu#mu#tau#tau'
}
else:
lt = {
'et': '#it{l}#it{l}#it{e}#tau',
'mt': '#it{l}#it{l}#mu#tau',
'tt': '#it{l}#it{l}#tau#tau'
}
lTex3 = TLatex(120., 0.83 * hMax,
'{0:s} H_LT > {1:d} '.format(lt[cat], int(LTcut)))
lTex3.SetTextSize(0.04)
lTex3.Draw()
plotPad.Draw()
#CMS_lumi(plotPad,4,11)
outFileBase = "Stack_{0:d}_{1:s}_{2:s}_LT{3:02d}".format(
year, cat, sign, int(LTcut))
c.SaveAs("{0:s}.png".format(outFileBase))
c.SaveAs("{0:s}.root".format(outFileBase))
if wait == 'wait':
raw_input()
else:
import time
time.sleep(5.)
#exit()
ratioPad = TPad("pad2","",0.0,0.0,1.0,0.29)
exit()
print("After ratioPad")
plotPad = TPad("pad1","",0.0016,0.291,1.0,1.0)
print("After plotPad")
exit()
if doRatio :
plotPad.SetTicks(0,0)
plotPad.SetLeftMargin(L/W)
plotPad.SetRightMargin(R/W)
plotPad.SetTopMargin(T/H)
plotPad.SetBottomMargin(B_ratio/H)
plotPad.SetFillColor(0)
plotPad.SetBottomMargin(0)
ratioPad.SetLeftMargin (L/W)
ratioPad.SetRightMargin (R/W)
ratioPad.SetTopMargin (T_ratio/H)
ratioPad.SetTopMargin (0.007)
ratioPad.SetBottomMargin(B_ratio_label/H)
ratioPad.SetGridy(1)
ratioPad.SetFillColor(4000)
else :
print("L={0:f} W={1:f} R={2:f} H={3:f}".format(L,W,R,H))
plotPad = TPad("pad1","",0.0,0.03,1.0,1.0)
print("After pad1")
plotPad.SetLeftMargin(L/W)
plotPad.SetRightMargin(R/W)
def thresholds(var, title, xtitle, nbin, low, high, region):
cutter = cuts[region]
weight = cutter
can = TCanvas("can", "can", 1000, 900)
can.SetBottomMargin(0.3)
can.SetRightMargin(0.06)
can.cd()
gPad.SetLogy(1)
gStyle.SetOptStat(0)
backs = TH1D('a', 'a', nbin, low, high)
backs.SetFillStyle(3344)
backs.SetFillColor(1)
phojet = TH1D('b', 'b', nbin, low, high)
phojet.SetFillColor(7)
phojet.SetLineColor(7)
qcd = TH1D('c', 'c', nbin, low, high)
qcd.SetFillColor(5)
qcd.SetLineColor(5)
stack = THStack('d', title + ";" + xtitle + ";" + "Events")
Variables = {}
print "Variable: " + var
for tre in List:
histName = var + tre
Variables[tre] = TH1F(histName, ";" + xtitle + ";" + "Events", nbin,
low, high)
# if tre == "dipho":
# weight = cutter+"&& (JetPho_dR<0.1)"
treepj[tre].Draw(var + ">>" + histName, weight)
Variables[tre].Sumw2()
scalable = lumi * crossx[tre] * kFact[tre] / Nevents[tre]
Variables[tre].Scale(scalable)
if tre.startswith("df"):
Variables[tre].SetLineColor(colors[tre])
Variables[tre].SetLineWidth(3)
if tre.startswith("GJets"):
backs.Add(Variables[tre])
phojet.Add(Variables[tre])
if tre.startswith("QCD"):
backs.Add(Variables[tre])
qcd.Add(Variables[tre])
if tre.startswith("DiPhoton"):
Variables[tre].SetFillColor(3)
Variables[tre].SetLineColor(3)
backs.Add(Variables[tre])
Variables['Data'] = TH1F('data', ";" + xtitle + ";" + "Events", nbin, low,
high)
treepj['Data'].Draw(var + ">>data", cutter, "goff")
Variables['Data'].SetLineColor(1)
Variables['Data'].SetLineWidth(2)
stack.Add(Variables['DiPhoton'])
stack.Add(qcd)
stack.Add(phojet)
stack.SetMaximum(1000000.0)
stack.SetMinimum(0.001)
stack.Draw("hist")
stack.GetXaxis().SetLabelSize(0)
backs.Draw("e2same")
Variables['Data'].Draw("e1same")
Variables['df1en0'].Draw("histsame")
Variables['df1en1'].Draw("histsame")
Variables['df1en2'].Draw("histsame")
Variables['df1en3'].Draw("histsame")
pad = TPad("pad", "pad", 0.0, 0.0, 1.0, 1.0)
pad.SetTopMargin(0.7)
pad.SetFillColor(0)
pad.SetGridy(1)
pad.SetFillStyle(0)
pad.Draw()
pad.cd(0)
pad.SetRightMargin(0.06)
Pull = TH1D('Pull', 'Pull', nbin, low, high)
Pull = Variables['Data'].Clone()
Pull.Divide(backs)
Pull.SetMarkerStyle(20)
Pull.SetMaximum(2.0)
Pull.SetMinimum(0.0)
Pull.SetFillColor(2)
Pull.GetXaxis().SetTitle(xtitle)
Pull.GetYaxis().SetTitleSize(0.04)
Pull.GetYaxis().SetTitle('Data/MC')
Pull.SetMarkerSize(0.7)
Pull.GetYaxis().SetNdivisions(5)
line = TF1("line", "1", low, high)
line.SetLineColor(2)
line.SetLineWidth(2)
Pull.Draw("e1")
line.Draw('same')
latex2 = TLatex()
latex2.SetNDC()
latex2.SetTextSize(0.035)
latex2.SetTextAlign(31) # align right
latex2.DrawLatex(
0.87, 0.95,
"Work In Progress, " + str(lumi) + " fb^{-1} at #sqrt{s} = 13 TeV")
led = TLegend(0.7, 0.7, 0.94, 0.9)
led.AddEntry(phojet, "#gamma + Jet", 'f')
led.AddEntry(qcd, "QCD DiJet", 'f')
led.AddEntry(Variables['DiPhoton'], "#gamma + #gamma", 'f')
led.AddEntry(Variables['df1en0'], "f_{D} = 1E0")
led.AddEntry(Variables['df1en1'], "f_{D} = 1E-1")
led.AddEntry(Variables['df1en2'], "f_{D} = 1E-2")
led.AddEntry(Variables['df1en3'], "f_{D} = 1E-3")
led.AddEntry(Variables['Data'], "Data")
led.SetFillColor(0)
led.Draw("same")
can.SaveAs("plots/" + region + "-" + var + ".pdf")
can.Close()
phojet.Delete()
qcd.Delete()
neueta_mad.SetStats(0)
neueta_mad.Sumw2()
neueta_mad.GetYaxis().SetTitle("a.u.")
neueta_mad.GetYaxis().SetTitleSize(0.05)
neueta_mad.GetYaxis().SetTitleOffset(0.75)
neueta_mad.GetXaxis().SetLabelSize(0)
#neueta_mad.SetMaximum(1000)
neueta_mad.SetMinimum(0)
neueta_nomad = TH1D("neu eta nomadspin","",30,-3,3)
neueta_nomad.SetStats(0)
neueta_nomad.Sumw2()
c1= TCanvas("lphi","lphi",800,600)
lphi_pad1 = TPad("pad1", "", 0.00, 0.20, 0.99, 0.99)
lphi_pad2 = TPad("pad2", "", 0.00, 0.00, 0.99, 0.20)
lphi_pad1.SetFillColor(0)
lphi_pad1.SetLineColor(0)
lphi_pad2.SetFillColor(0)
lphi_pad2.SetLineColor(0)
lphi_pad1.SetBottomMargin(0.03);
lphi_pad2.SetTopMargin(0.15);
lphi_pad2.SetBottomMargin(0.3);
lphi_pad1.Draw()
lphi_pad2.Draw()
c2= TCanvas("lpt","lpt",800,600)
lpt_pad1 = TPad("pad1", "", 0.00, 0.20, 0.99, 0.99)
lpt_pad2 = TPad("pad2", "", 0.00, 0.00, 0.99, 0.20)
lpt_pad1.SetFillColor(0)
lpt_pad1.SetLineColor(0)
lpt_pad2.SetFillColor(0)
def eraselabel(pad, h):
pad.cd()
pe = TPad("pe", "pe", 0, 0, pad.GetLeftMargin(), h)
pe.Draw()
pe.SetFillColor(pad.GetFillColor())
pe.SetBorderMode(0)
def DrawOverlap(fileVec,
histVec,
titleVec,
legendtext,
pngname,
logstatus=[0, 0],
xRange=[-99999, 99999, 1]):
gStyle.SetOptTitle(0)
gStyle.SetOptStat(0)
gStyle.SetTitleOffset(1.1, "Y")
gStyle.SetTitleOffset(0.9, "X")
gStyle.SetLineWidth(3)
gStyle.SetFrameLineWidth(3)
i = 0
histList_ = []
histList = []
histList1 = []
maximum = []
## Legend
leg = TLegend(0.65, 0.650, 0.89, 0.85) #,NULL,"brNDC");
leg.SetBorderSize(0)
# leg.SetNColumns(3)
leg.SetLineColor(1)
leg.SetLineStyle(1)
leg.SetLineWidth(1)
leg.SetFillColor(0)
leg.SetFillStyle(0)
leg.SetTextFont(22)
leg.SetTextSize(0.045)
c = TCanvas("c1", "c1", 0, 0, 500, 500)
#c.SetBottomMargin(0.15)
#c.SetLeftMargin(0.15)
#c.SetLogy(0)
#c.SetLogx(0)
c1_2 = TPad("c1_2", "newpad", 0., 0.30, 1, 0.994)
c1_2.Draw()
c1_1 = TPad("c1_1", "newpad1", 0, 0.02, 1, 0.30)
c1_1.Draw()
print("you have provided " + str(len(fileVec)) + " files and " +
str(len(histVec)) + " histograms to make a overlapping plot")
print "opening rootfiles"
c.cd()
c1_2.SetBottomMargin(0.013)
c1_2.SetLogy(logstatus[1])
c1_2.SetLogx(logstatus[0])
c1_2.cd()
ii = 0
inputfile = {}
print str(fileVec[(len(fileVec) - 1)])
for ifile_ in range(len(fileVec)):
print("opening file " + fileVec[ifile_])
inputfile[ifile_] = TFile(fileVec[ifile_])
print "fetching histograms"
for ihisto_ in range(len(histVec)):
print("printing histo " + str(histVec[ihisto_]))
histo = inputfile[ifile_].Get(histVec[ihisto_])
#status_ = type(histo) is TGraphAsymmErrors
histList.append(histo)
# for ratio plot as they should nt be normalize
histList1.append(histo)
print histList[ii].Integral()
histList[ii].Rebin(xRange[2])
print('after', histList[ii].Integral(0, -1))
histList[ii].Scale(1.0 / histList[ii].Integral(0, -1))
maximum.append(histList[ii].GetMaximum())
maximum.sort()
ii = ii + 1
print histList
for ih in range(len(histList)):
tt = type(histList[ih])
if logstatus[1] is 1:
histList[ih].SetMaximum(maximum[(len(maximum) - 1)] *
25) #1.4 for log
histList[ih].SetMinimum(0.001) #1.4 for log
if logstatus[1] is 0:
histList[ih].SetMaximum(maximum[(len(maximum) - 1)] *
1.2) #1.4 for log
histList[ih].SetMinimum(0) #1.4 for log
# print "graph_status =" ,(tt is TGraphAsymmErrors)
# print "hist status =", (tt is TH1D) or (tt is TH1F)
if ih == 0:
if tt is TGraphAsymmErrors:
histList[ih].Draw("AP")
if (tt is TH1D) or (tt is TH1F) or (tt is TH1) or (tt is TH1I):
histList[ih].Draw("hist")
if ih > 0:
#histList[ih].SetLineWidth(2)
if tt is TGraphAsymmErrors:
histList[ih].Draw("P same")
if (tt is TH1D) or (tt is TH1F) or (tt is TH1) or (tt is TH1I):
histList[ih].Draw("hist same")
if tt is TGraphAsymmErrors:
histList[ih].SetMaximum(1.4)
histList[ih].SetMarkerColor(colors[ih])
histList[ih].SetLineColor(colors[ih])
histList[ih].SetMarkerStyle(markerStyle[ih])
histList[ih].SetMarkerSize(1)
leg.AddEntry(histList[ih], legendtext[ih], "PL")
if (tt is TH1D) or (tt is TH1F) or (tt is TH1) or (tt is TH1I):
histList[ih].SetLineStyle(linestyle[ih])
histList[ih].SetLineColor(colors[ih])
histList[ih].SetLineWidth(3)
leg.AddEntry(histList[ih], legendtext[ih], "L")
histList[ih].GetYaxis().SetTitle(titleVec[1])
histList[ih].GetYaxis().SetTitleSize(0.062)
histList[ih].GetYaxis().SetTitleOffset(0.78)
histList[ih].GetYaxis().SetTitleFont(22)
histList[ih].GetYaxis().SetLabelFont(22)
histList[ih].GetYaxis().SetLabelSize(.062)
histList[ih].GetXaxis().SetRangeUser(xRange[0], xRange[1])
histList[ih].GetXaxis().SetLabelSize(0.0000)
histList[ih].GetXaxis().SetTitle(titleVec[0])
histList[ih].GetXaxis().SetLabelSize(0.052)
histList[ih].GetXaxis().SetTitleSize(0.052)
histList[ih].GetXaxis().SetTitleOffset(1.04)
histList[ih].GetXaxis().SetTitleFont(22)
histList[ih].GetXaxis().SetTickLength(0.07)
histList[ih].GetXaxis().SetLabelFont(22)
histList[ih].GetYaxis().SetLabelFont(22)
# histList[ih].GetXaxis().SetNdivisions(508)
#
i = i + 1
pt = TPaveText(0.0877181, 0.91, 0.9580537, 0.95, "brNDC")
pt.SetBorderSize(0)
pt.SetTextAlign(12)
pt.SetFillStyle(0)
pt.SetTextFont(22)
pt.SetTextSize(0.046)
# text = pt.AddText(0.05,0.5,"ATLAS Internal ")
text = pt.AddText(0.65, 1.0, "#sqrt{s} = 13 TeV (36fb^{-1})")
pt.Draw()
t2a = TPaveText(0.277181, 0.81, 0.6780537, 0.89, "brNDC")
t2a.SetBorderSize(0)
t2a.SetFillStyle(0)
t2a.SetTextSize(0.046)
t2a.SetTextAlign(12)
t2a.SetTextFont(22)
histolabel1 = str(fileVec[(len(fileVec) - 1)])
text1 = t2a.AddText(0.065, 0.5, "ATLAS Internal")
t2a.Draw()
leg.Draw()
#
c.cd()
h_inc = histList1[0].Clone()
h_vbs = histList1[1].Clone()
h_qcd = histList1[2].Clone()
h_int = histList1[3].Clone()
h_inc.Add(h_vbs, -1)
h_inc.Add(h_qcd, -1)
## ratio plot
hdivide_1 = h_int.Clone()
hdivide_1.Divide(h_vbs)
# hdivide_1.GetYaxis().SetTitle(str(legendtext[(len(legendtext)-1)]))
hdivide_1.GetYaxis().SetTitleSize(0.11)
hdivide_1.GetYaxis().SetTitle("ratio")
hdivide_1.GetYaxis().SetTitleOffset(0.43)
hdivide_1.GetYaxis().SetTitleFont(22)
hdivide_1.GetYaxis().SetLabelSize(0.13)
hdivide_1.GetYaxis().CenterTitle()
hdivide_1.GetXaxis().SetTitleSize(0.14)
hdivide_1.GetXaxis().SetTitleOffset(0.89)
hdivide_1.GetXaxis().SetTitleFont(22)
hdivide_1.GetXaxis().SetLabelSize(0.14)
hdivide_1.GetYaxis().SetLabelFont(22)
c.cd()
c1_1.cd()
# c1_1.Range(-7.862408,-629.6193,53.07125,486.5489)
c1_1.SetFillColor(0)
c1_1.SetTicky(1)
c1_1.SetTopMargin(0.0510)
c1_1.SetBottomMargin(0.3006666678814)
c1_1.SetFrameFillStyle(0)
c1_1.SetFrameBorderMode(0)
c1_1.SetFrameFillStyle(0)
c1_1.SetFrameBorderMode(0)
c1_1.SetLogy(0)
hdivide_1.GetXaxis().SetRangeUser(xRange[0], xRange[1])
hdivide_1.GetYaxis().SetNdivisions(505)
c1_1.Draw()
c1_1.SetGridy()
hdivide_1.SetMarkerStyle(20)
hdivide_1.SetMarkerColor(2)
hdivide_1.SetMarkerSize(1)
hdivide_1.Draw("P")
hdivide_2 = h_int.Clone()
hdivide_2.Divide(h_qcd)
hdivide_2.SetMarkerStyle(21)
hdivide_2.SetMarkerColor(4)
hdivide_2.SetMarkerSize(1)
hdivide_2.Draw("Psame")
hdivide_3 = h_int.Clone()
hdivide_3.Divide(h_inc)
hdivide_3.SetMarkerStyle(22)
hdivide_3.SetMarkerColor(1)
hdivide_3.SetMarkerSize(1)
hdivide_3.Draw("Psame")
hdivide_1.SetMinimum(-1.01)
hdivide_1.SetMaximum(3.20)
c.cd()
outputdirname = 'plots/'
histname = outputdirname + pngname
c.SaveAs(histname + '.png')
c.SaveAs(histname + '.pdf')
c.SaveAs(histname + '.root')
c.SaveAs(histname + '.C')
class TopPad:
def __init__(self):
# list of plots for this pad
self.plots = []
def AddPlot(self,plot,draw_options='',legend_label=None,legend_draw_options='lp'):
clone = plot.Clone(plot.GetName() + '_clone')
clone.SetDirectory(0)
self.plots.append(Plot(clone,draw_options,legend_label,legend_draw_options))
def Draw(self,
pad_name = 'top_pad',
pad_title = 'Top Pad',
pad_x1 = 0,
pad_y1 = 0,
pad_x2 = 1,
pad_y2 = 1,
pad_border_size = 1,
pad_bottom_margin = 0,
pad_top_margin = 0,
pad_left_margin = 0,
pad_right_margin = 0,
pad_y_ndiv = None,
legend_x1 = None,
legend_y1 = None,
legend_x2 = None,
legend_y2 = None,
legend_border_size = 0,
legend_fill_style = 0,
legend_chi2 = False,
):
# create the pad
self.pad = TPad(pad_name,
pad_title,
pad_x1,
pad_y1,
pad_x2,
pad_y2,
pad_border_size,
0,
)
self.pad.SetMargin(pad_left_margin,pad_right_margin,pad_bottom_margin,pad_top_margin)
self.pad.SetFillColor(0)
self.pad.Draw()
self.pad.cd()
# create the legend
draw_legend = False
if legend_x1 != None and legend_x2 != None and legend_y1 != None and legend_y2 != None:
draw_legend = True
if draw_legend:
self.legend = TLegend(legend_x1,legend_y1,legend_x2,legend_y2)
self.legend.SetBorderSize(legend_border_size)
self.legend.SetFillStyle(legend_fill_style)
# draw the plots
for i in range(len(self.plots)):
plot = self.plots[i]
chi2 = None
if i == 0:
#plot.plot.GetYaxis().SetLabelSize(0)
# can turn off the X-axis labels
plot.plot.GetXaxis().SetLabelSize(0)
plot.plot.GetXaxis().SetTitle('')
if pad_y_ndiv is not None:
plot.plot.GetYaxis().SetNdivisions(pad_y_ndiv)
plot.Draw()
else:
plot.Draw(same=True)
# calculate chi2 between this plot and the first
if legend_chi2:
chi2 = ChiSquared.TH1ChiSquared(self.plots[0].plot,plot.plot)
if draw_legend:
plot.AddToLegend(self.legend,chi2)
if draw_legend:
self.legend.Draw('same')
def plot2(key, xsections, histos, names, LogY, weights, outputDIR):
c1=TCanvas(key, key, 800, 600)
pad1 = TPad("pad1", "", 0.00, 0.20, 0.99, 0.99)
pad2 = TPad("pad2", "", 0.00, 0.00, 0.99, 0.20)
pad1.SetGridx()
pad1.SetGridy()
pad2.SetGridy()
pad1.SetFillColor(0)
pad1.SetLineColor(0)
pad2.SetFillColor(0)
pad2.SetLineColor(0)
pad1.SetBottomMargin(0.03)
pad2.SetTopMargin(0.15)
pad2.SetBottomMargin(0.3)
pad1.Draw()
pad2.Draw()
leg1 = TLegend(0.68,0.55,0.86,0.86)
histos[0].GetXaxis().SetLabelSize(0)
histos[0].SetMarkerStyle(20)
for i in range(0,len(histos)):
#if histos[i].Integral()==0: continue
histos[i].Scale(xsections[i]/weights[i])
histos[i].SetLineColor(i+1)
histos[i].SetLineWidth(2)
histo_ratio=histos[1].Clone()
for i in range(2,len(histos)):
histo_ratio.Add(histos[i])
histo_ratio.SetLineWidth(2)
histo_sum=histo_ratio.Clone()
histo_sum.SetLineColor(49)
histo_sum.SetLineWidth(2)
histo_ratio.SetTitle('')
histo_ratio.Divide(histos[0])
histo_ratio.SetLineColor(49)
histo_ratio.SetMaximum(1.5)
histo_ratio.SetMinimum(0.5)
histo_ratio.GetYaxis().SetNdivisions(4,kFALSE)
histo_ratio.GetXaxis().SetTitle(key)
histo_ratio.GetXaxis().SetTitleSize(0.15)
histo_ratio.GetXaxis().SetTitleOffset(0.75)
histo_ratio.GetXaxis().SetLabelSize(0.13)
histo_ratio.GetYaxis().SetTitle('summed/inc')
histo_ratio.GetYaxis().SetTitleSize(0.1)
histo_ratio.GetYaxis().SetTitleOffset(0.3)
histo_ratio.GetYaxis().SetLabelSize(0.13)
pad1.cd()
if LogY:
pad1.SetLogy()
histos[0].SetMaximum(1.2*histos[0].GetMaximum())
histos[0].SetMinimum(0.0001)
histos[0].Draw('pe')
for i in range(1,len(histos)):
histos[i].Draw('same h')
histo_sum.Draw('same h')
leg1.AddEntry(histos[0], names[0])
leg1.AddEntry(histo_sum, 'MGsummed')
for i in range(1,len(histos)):
leg1.AddEntry(histos[i], names[i])
leg1.SetFillStyle(0)
leg1.SetBorderSize(0)
leg1.Draw()
c1.Update()
pad2.cd()
histo_ratio.Draw()
if LogY:
c1.SaveAs(outputDIR + '/' + key + '_log.png')
c1.SaveAs(outputDIR + '/' + key + '_log.pdf')
else:
c1.SaveAs(outputDIR + '/' + key + '.png')
c1.SaveAs(outputDIR + '/' + key + '.pdf')
for i in range(0,len(histos)):
histos[i].Scale(weights[i]/xsections[i])
def makeDiTauStack(outDir,
inFile,
rootDir,
s,
labelX,
units="GeV",
left=False,
channel="",
json="Golden",
log=False,
dndm=False,
doRatio=False):
cat = 'mmtt'
tdrstyle.setTDRStyle()
writeExtraText = True # if extra text
extraText = "Preliminary" # default extra text is "Preliminary"
lumi_sqrtS = "13 TeV"
if json == "Golden": lumi_13TeV = channel + " 41.8 fb^{-1}, 2017"
iPeriod = 4 # 1=7TeV, 2=8TeV, 3=7+8TeV, 7=7+8+13TeV
xR = 0.65 #legend parameters
xR = 0.2 #legend parameters
H = 600
W = 600
H_ref = 600
W_ref = 600
# references for T, B, L, R
T = 0.08 * H_ref
B = 0.12 * H_ref
L = 0.16 * W_ref
R = 0.04 * W_ref
#margins for inbetween the pads in a ratio plot
B_ratio = 0.1 * H_ref
T_ratio = 0.03 * H_ref
#margin required for lebal on bottom of raito plot
B_ratio_label = 0.3 * H_ref
c = TCanvas('c1', 'c1', 50, 50, W, H)
c.SetFillColor(0)
c.SetBorderMode(0)
c.SetFrameFillStyle(0)
c.SetFrameBorderMode(0)
if not doRatio:
c.SetLeftMargin(L / W)
c.SetRightMargin(R / W)
c.SetTopMargin(T / H)
c.SetBottomMargin(B / H)
c.cd()
ratioPad = TPad("pad2", "", 0.0, 0.0, 1.0, 0.29)
plotPad = TPad("pad1", "", 0.0016, 0.291, 1.0, 1.0)
if doRatio:
plotPad.SetTicks(0, 0)
plotPad.SetLeftMargin(L / W)
plotPad.SetRightMargin(R / W)
plotPad.SetTopMargin(T / H)
plotPad.SetBottomMargin(B_ratio / H)
plotPad.SetFillColor(0)
plotPad.SetBottomMargin(0)
ratioPad.SetLeftMargin(L / W)
ratioPad.SetRightMargin(R / W)
ratioPad.SetTopMargin(T_ratio / H)
ratioPad.SetTopMargin(0.007)
ratioPad.SetBottomMargin(B_ratio_label / H)
ratioPad.SetGridy(1)
ratioPad.SetFillColor(4000)
else:
plotPad = TPad("pad1", "", 0.0, 0.03, 1.0, 1.0)
plotPad.SetLeftMargin(L / W)
plotPad.SetRightMargin(R / W)
plotPad.SetTopMargin(T / H)
plotPad.SetBottomMargin(B / H)
plotPad.Draw()
plotPad.cd()
print("In makeStack inFile={0:s}".format(inFile))
f = TFile(inFile)
groups = ['data', 'Reducible', 'Rare', 'ZZ4L', 'Signal']
histo = {}
colors = {
'data': 0,
'Reducible': kMagenta - 10,
'Rare': kBlue - 8,
'ZZ4L': kAzure - 9,
'Signal': kOrange - 4
}
hs = THStack("hs", "")
for group in groups:
histo[group] = f.Get("h{0:s}_{1:s}_Mtt".format(group, cat))
#print("In makeStack(): histo={0:s} type(histo)={1:s}".format(str(histo[group]),type(histo[group])))
if dndm: convertToDNDM(histo[group])
if group == 'data':
applyDATAStyle(histo[group])
elif group == 'Signal':
applySignalStyle(histo[group])
else:
applyStyle(histo[group], colors[group], 1, 1001)
if group != 'data': hs.Add(histo[group])
hMax = 1.2 * max(histo['data'].GetMaximum(), hs.GetMaximum())
print("hMax={0:f}".format(hMax))
hs.SetMaximum(hMax)
hs.Draw("HIST")
histo['data'].Draw("e,SAME")
if doRatio:
hs.GetXaxis().SetLabelSize(0)
else:
if units != "":
hs.GetXaxis().SetTitle(labelX + " [" + units + "]")
else:
hs.GetXaxis().SetTitle(labelX)
hs.GetYaxis().SetTitle("Events")
hs.GetYaxis().SetTitleOffset(1)
if dndm: hs.GetYaxis().SetTitle("dN/d" + labelX)
c.cd()
if doRatio:
data2 = histo['data'].Clone("data")
mc = histo['Rare']
mc.Add(histo['Reducible'])
mc.Add(histo['ZZ4L'])
xmin = mc.GetXaxis().GetXmin()
xmax = mc.GetXaxis().GetXmax()
line = TLine(xmin, 1.0, xmax, 1.0)
line.SetLineWidth(1)
line.SetLineColor(kBlack)
ratioPad.Draw()
ratioPad.cd()
data2.Divide(data2, mc)
data2.SetMarkerStyle(20)
data2.SetTitleSize(0.12, "Y")
data2.SetTitleOffset(0.40, "Y")
data2.SetTitleSize(0.12, "X")
data2.SetLabelSize(0.10, "X")
data2.SetLabelSize(0.08, "Y")
data2.GetYaxis().SetRangeUser(0.62, 1.38)
data2.GetYaxis().SetNdivisions(305)
data2.GetYaxis().SetTitle("Obs/Exp ")
if units != "":
data2.GetXaxis().SetTitle(labelX + " [" + units + "]")
else:
data2.GetXaxis().SetTitle(labelX)
data2.Draw("P")
line.Draw()
c.cd()
plotPad.cd()
l = TLegend(xR, 0.55, xR + 0.28, 0.9)
for group in groups:
l.AddEntry(histo[group], group, "F")
l.SetBorderSize(0)
l.SetFillColor(0)
l.SetFillStyle(0)
l.Draw()
factor = 1.05
if left: factor = 1. / 2.2
xL = hs.GetXaxis().GetXmin() + (hs.GetXaxis().GetXmax() -
hs.GetXaxis().GetXmin()) * xR * factor
yL = hs.GetMaximum() * 0.35
offsetF = yL - 0.1 * hs.GetMaximum()
offsetFF = yL - 0.2 * hs.GetMaximum()
plotPad.Draw()
#CMS_lumi(plotPad,4,11)
c.SaveAs("stack.png")
c.SaveAs("stack.root")
raw_input()
def plot1(key, xsection1, xsection2, histo1, histo2, name1, name2, LogY, weight1, weight2, outputDIR):
c1=TCanvas(key, key, 800, 600)
pad1 = TPad("pad1", "", 0.00, 0.20, 0.99, 0.99)
pad2 = TPad("pad2", "", 0.00, 0.00, 0.99, 0.20)
pad1.SetGridx()
pad1.SetGridy()
pad2.SetGridy()
pad1.SetFillColor(0)
pad1.SetLineColor(0)
pad2.SetFillColor(0)
pad2.SetLineColor(0)
pad1.SetBottomMargin(0.03)
pad2.SetTopMargin(0.15)
pad2.SetBottomMargin(0.3)
pad1.Draw()
pad2.Draw()
leg1 = TLegend(0.65,0.75,0.86,0.86)
histo1.Scale(xsection1/weight1)
histo1.SetMaximum(1.2*histo1.GetMaximum())
histo1.SetMinimum(0.0001)
histo1.SetLineColor(kRed)
histo1.SetLineWidth(2)
histo1.GetXaxis().SetLabelSize(0)
histo2.Scale(xsection2/weight2)
histo2.SetLineColor(kBlack)
histo2.SetLineWidth(2)
pad1.cd()
if LogY:
pad1.SetLogy()
histo_ratio=histo2.Clone()
histo_ratio.SetTitle('')
histo_ratio.Divide(histo1)
histo_ratio.SetMaximum(1.5)
histo_ratio.SetMinimum(0.5)
histo_ratio.GetYaxis().SetNdivisions(4,kFALSE)
histo_ratio.GetXaxis().SetTitle(key)
histo_ratio.GetXaxis().SetTitleSize(0.15)
histo_ratio.GetXaxis().SetTitleOffset(0.75)
histo_ratio.GetXaxis().SetLabelSize(0.13)
histo_ratio.GetYaxis().SetTitle(name1+'/'+name2)
histo_ratio.GetYaxis().SetTitleSize(0.1)
histo_ratio.GetYaxis().SetTitleOffset(0.3)
histo_ratio.GetYaxis().SetLabelSize(0.13)
histo_ratio.SetLineWidth(2)
histo1.Draw('pe')
histo2.Draw('same pe')
leg1.AddEntry(histo1, name1)
leg1.AddEntry(histo2, name2)
leg1.SetFillStyle(0)
leg1.SetBorderSize(0)
leg1.Draw()
c1.Update()
pad2.cd()
histo_ratio.Draw()
if LogY:
c1.SaveAs(outputDIR + '/' + key + '_log.png')
c1.SaveAs(outputDIR + '/' + key + '_log.pdf')
else:
c1.SaveAs(outputDIR + '/' + key + '.png')
c1.SaveAs(outputDIR + '/' + key + '.pdf')
# renew
histo1.Scale(weight1/xsection1)
histo2.Scale(weight2/xsection2)
def __plot_profiles_in_same_canvas(self, hist_objs, hist_names, legends,
y_limits, **kwargs):
legend_position = retrieve_kw(kwargs, 'legend_position',
(0.36, 0.20, 0.66, 0.36))
legend_prefix = retrieve_kw(kwargs, 'legend_prefix',
'Z#rightarrowee, ')
legend_header = retrieve_kw(kwargs, 'legend_header', 'Trigger step')
ylabel = retrieve_kw(kwargs, 'ylabel', 'Trigger Efficiency')
title = retrieve_kw(kwargs, 'title', 'Trigger Efficiency')
oname = retrieve_kw(kwargs, 'oname', 'plot_efficiencys')
column = retrieve_kw(kwargs, 'column', 2)
doRatio = retrieve_kw(kwargs, 'doRatio', False)
canvas_size = retrieve_kw(kwargs, 'canvas_size', (1800, 1500))
# FIXME: This must be disable for now, there is some problem into the xaxis scale
# The top and bot axis must be match!
tobject_collector = []
ratio_size_as_fraction = 0.35
from ROOT import TCanvas, TLegend, TProfile, TPad
rows = int(round(len(hist_objs) / float(column)))
canvas = TCanvas('canvas', 'canvas', canvas_size[0], canvas_size[1])
canvas.Divide(rows, column)
leg_holder = []
for index, hist_str in enumerate(hist_names):
hists = hist_objs[hist_str]
pad = canvas.cd(index + 1)
# Force disable if != of 2
if len(hists) != 2:
doRatio = False
if doRatio:
drawopt = 'pE1'
pad.cd()
top = TPad("pad_top", "This is the top pad", 0.0,
ratio_size_as_fraction, 1.0, 1.0)
top.SetBottomMargin(0.0)
top.SetBottomMargin(0.06 / float(top.GetHNDC()))
#top.SetTopMargin (0.04/float(top.GetHNDC()))
top.SetRightMargin(0.05)
top.SetLeftMargin(0.16)
top.SetFillColor(0)
top.Draw(drawopt)
tobject_collector.append(top)
pad.cd()
bot = TPad("pad_bot", "This is the bottom pad", 0.0, 0.0, 1.0,
ratio_size_as_fraction)
bot.SetBottomMargin(0.10 / float(bot.GetHNDC()))
#bot.SetTopMargin (0.02/float(bot.GetHNDC()))
bot.SetTopMargin(0.0)
bot.SetRightMargin(0.05)
bot.SetLeftMargin(0.16)
bot.SetFillColor(0)
bot.Draw(drawopt)
tobject_collector.append(bot)
if type(legend_prefix) is not list:
legend_prefix = [legend_prefix] * len(legends)
if doRatio:
top.cd()
leg = TLegend(legend_position[0], legend_position[1],
legend_position[2], legend_position[3])
from AtlasStyle import setLegend1, atlas_template
setLegend1(leg)
leg.SetHeader(legend_header)
for i, eff in enumerate(hists):
eff.SetLineColor(self._curve_color[i])
eff.SetMarkerColor(self._curve_color[i])
eff.SetMarkerStyle(self._marker_style[i])
if type(eff) is TProfile: eff.SetStats(0)
leg.AddEntry(eff, legend_prefix[i] + legends[i], 'p')
if i is 0: eff.Draw()
else: eff.Draw('same')
leg.SetTextSize(0.03)
leg.SetBorderSize(0)
leg.Draw()
if doRatio:
top.Modified()
top.Update
pad.Modified()
pad.Update()
from ROOT import TProfile, TEfficiency, kFALSE
xmin = 0
xmax = 999
if type(hists[0]) is TProfile:
hists[0].GetYaxis().SetRangeUser(y_limits[index][0],
y_limits[index][1])
elif type(hists[0]) is TEfficiency:
hists[0].GetPaintedGraph().GetYaxis().SetRangeUser(
y_limits[index][0], y_limits[index][1])
hists[0].GetPaintedGraph().GetYaxis().SetTitle('A')
# Fix the X axis
nbins = hists[0].GetTotalHistogram().GetNbinsX()
xmin = hists[0].GetTotalHistogram().GetXaxis().GetBinLowEdge(1)
xmax = hists[0].GetTotalHistogram().GetXaxis().GetBinLowEdge(
nbins + 1)
hists[0].GetPaintedGraph().GetXaxis().SetLimits(xmin, xmax)
else:
hists[0].GetYaxis().SetRangeUser(y_limits[index][0],
y_limits[index][1])
pad.Modified()
pad.Update()
tobject_collector.append(leg)
if doRatio:
atlas_template(top, **kwargs)
top.Update()
from ROOT import TH1
divide = ""
drawopt = 'pE1'
bot.cd()
ref = hists[0].GetPassedHistogram().Clone()
h = hists[1].GetPassedHistogram().Clone()
#ref = hists[0].Clone()
#h = hists[1].Clone()
ref.Sumw2()
h.Sumw2()
ref.Divide(hists[0].GetTotalHistogram().Clone())
h.Divide(hists[1].GetTotalHistogram().Clone())
#ratioplot = TEfficiency(h,ref)
ratioplot = h.Clone()
ratioplot.Sumw2()
ratioplot.SetName(h.GetName() + '_ratio')
ratioplot.Divide(h, ref, 1., 1., '')
#ratioplot.Divide(ref)
ratioplot.SetFillColor(0)
ratioplot.SetFillStyle(0)
ratioplot.SetMarkerColor(1)
ratioplot.SetLineColor(kBlack)
ratioplot.SetMarkerStyle(24)
ratioplot.SetMarkerSize(1.2)
ratioplot.GetYaxis().SetTitle('trigger / ref')
ratioplot.GetYaxis().SetTitleSize(0.10)
ratioplot.GetXaxis().SetTitleSize(0.10)
ratioplot.GetXaxis().SetLabelSize(0.10)
ratioplot.GetYaxis().SetLabelSize(0.10)
ratioplot.GetYaxis().SetRangeUser(0.9, 1.07)
ratioplot.Draw(drawopt)
tobject_collector.append(ratioplot)
#atlas_template(bot, **kwargs)
from ROOT import TLine
l1 = TLine(xmin, 1, xmax, 1)
l1.SetLineColor(kRed)
l1.SetLineStyle(2)
l1.Draw()
tobject_collector.append(l1)
bot.Update()
else:
atlas_template(pad, **kwargs)
pad.Update()
canvas.SaveAs(oname + '.pdf')
def makeTwoScalesGraph(file):
print(file)
ch1 = OPData.fromPath('../data/part3/%s' % file, 1)
ch2 = OPData.fromPath('../data/part3/%s' % file, 2)
print('make canvas + pad')
c = TCanvas('c-%s' % file, '', 1280, 720)
pad = TPad('pad-%s' % file, '', 0, 0, 1, 1)
pad.Draw()
pad.cd()
print('frame')
frame = pad.DrawFrame(0,
min(ch1.getY()) * 1.1, 0.051,
max(ch1.getY()) * 1.1)
frame.SetXTitle('Zeit t / s')
frame.GetXaxis().CenterTitle()
frame.SetYTitle('Spannung Spule 2: U_{2} / V')
frame.GetYaxis().CenterTitle()
frame.GetYaxis().SetLabelColor(4)
frame.GetYaxis().SetTitleColor(4)
print('g1')
g1 = ch1.makeGraph('g1-%s' % file)
prepareGraph(g1)
g1.Draw('PX')
print('overlay')
c.cd()
overlay = TPad('overlay-%s' % file, '', 0, 0, 1, 1)
overlay.SetFillStyle(4000) # transparent
overlay.SetFillColor(0) # white
overlay.SetFrameFillStyle(4000) # transparent
overlay.Draw()
overlay.cd()
print('g2')
g2 = ch2.makeGraph('g2-%s' % file)
prepareGraph(g2, 2)
g2ymin = min(ch2.getY())
xmin = pad.GetUxmin()
xmax = pad.GetUxmax()
ymin = 1.1 * g2ymin
ymax = abs(ymin)
if file == '07.tab': # same scale like 06.tab
ymin, ymax = -0.07128, 0.07128
oframe = overlay.DrawFrame(xmin, ymin, xmax, ymax)
oframe.GetXaxis().SetLabelOffset(99)
oframe.GetYaxis().SetLabelOffset(99)
oframe.GetYaxis().SetTickLength(0)
g2.Draw('PX')
print('axis')
axis = TGaxis(xmax, ymin, xmax, ymax, ymin, ymax, 510, "+L")
axis.SetTitle('Spannung Photodiode: U_{ph} / V')
axis.CenterTitle()
axis.SetTitleOffset(1.2)
axis.Draw()
print('print')
c.Update()
c.Print('../img/part3/%s.pdf' % file[:-4], 'pdf')
def plot_BDT(channel, var, massPoint, bin, low, high, ylabel, xlabel, save, nBtags = -1, setLog = False, finalcuts = False):
if (channel == 'electron'):
cut = 'jet_0_pt_WprimeCalc >= 120 && jet_1_pt_WprimeCalc >= 40 && elec_1_pt_WprimeCalc > 32 && abs(elec_1_eta_WprimeCalc) < 2.5 && elec_1_RelIso_WprimeCalc < 0.1 && corr_met_WprimeCalc > 20'
#cut = 'jet_0_pt_WprimeCalc >= 100 && jet_1_pt_WprimeCalc >= 40 && elec_1_pt_WprimeCalc > 30 && abs(elec_1_eta_WprimeCalc) < 2.5 && elec_1_RelIso_WprimeCalc < 0.1 && corr_met_WprimeCalc > 35'
if (channel == 'muon'):
cut = 'jet_0_pt_WprimeCalc >= 120 && jet_1_pt_WprimeCalc >= 40 && muon_1_pt_WprimeCalc > 26 && abs(muon_1_eta_WprimeCalc) < 2.1 && muon_1_RelIso_WprimeCalc < 0.12 && corr_met_WprimeCalc > 20'
#cut = 'jet_0_pt_WprimeCalc >= 100 && jet_1_pt_WprimeCalc >= 40 && muon_1_pt_WprimeCalc > 26 && abs(muon_1_eta_WprimeCalc) < 2.1 && muon_1_RelIso_WprimeCalc < 0.12 && corr_met_WprimeCalc > 35'
if finalcuts: cut+= '&& BestTop_LjetsTopoCalcNew > 130 && BestTop_LjetsTopoCalcNew < 210 && BestTop_Pt_LjetsTopoCalcNew > 75 && Jet1Jet2_Pt_LjetsTopoCalcNew > 100'
njets = ""
if nBtags == -1:
cutbtag = ''
save = save
if nBtags == 0:
cutbtag = ' && ( (jet_0_tag_WprimeCalc + jet_1_tag_WprimeCalc + jet_2_tag_WprimeCalc + jet_3_tag_WprimeCalc + jet_4_tag_WprimeCalc + jet_5_tag_WprimeCalc + jet_6_tag_WprimeCalc + jet_7_tag_WprimeCalc + jet_8_tag_WprimeCalc + jet_9_tag_WprimeCalc) == 0 )'
save = save + '_0bTags'
njets = "N_{b tags} = 0"
if nBtags == 1:
cutbtag = ' && ( (jet_0_tag_WprimeCalc + jet_1_tag_WprimeCalc) == 1)'
save = save + '_1bTags'
njets = "N_{b tags} = 1"
if nBtags == 2:
cutbtag = ' && ( (jet_0_tag_WprimeCalc + jet_1_tag_WprimeCalc) >= 1 ) '
save = save + '_GE1bTags'
njets = "N_{b tags} #geq 1"
cutwbb = ' && n_Bjets_WprimeCalc > 0' # Wb(b)
cutwcc = ' && n_Bjets_WprimeCalc==0 && n_Cjets_WprimeCalc>0' # Wc(c)
cutwjj = ' && n_Bjets_WprimeCalc==0 && n_Cjets_WprimeCalc==0' # W+light
#cutwbb = ' ' # Wb(b)
#cutwcc = ' ' # Wc(c)
#cutwjj = ' ' # W+light
SFWjmu = 1.08*0.85
SFWcmu = 1.06*0.92*1.66
SFWbmu = 1.06*0.92*1.21
#SFWjmu = 1.0
#SFWcmu = 1.0
#SFWbmu = 1.0
WjjHist = TH1D('WjjHist', 'WjjHist', bin,low,high)
WccHist = TH1D('WccHist', 'WccHist', bin,low,high)
WbbHist = TH1D('WbbHist', 'WbbHist', bin,low,high)
Variables = {}
efficiency = {}
BkgList = []
for Type in Samples:
#print channel,' ',Type
if (Type.endswith('_el') and channel == 'muon'): continue
if (Type.endswith('_mu') and channel == 'electron'): continue
if (not Type.startswith(massPoint) ): continue
Variables[Type] = TH1D(Type+var+channel, Type+var+channel, bin, low, high)
histName = Type+var+channel
if (channel == 'electron'): chan = '_el'
if (channel == 'muon'): chan = '_mu'
if (channel == 'electron'): weight = 'weight_PU_ABC_PileUpCalc*weight_ElectronEff_WprimeCalc'
if (channel == 'muon'): weight = 'weight_PU_ABC_PileUpCalc*weight_MuonEff_WprimeCalc'
if ((not Type == massPoint+massPoint+chan) and (not Type == massPoint+'_data'+chan)): BkgList.extend([Type])
if Type.endswith('wjets'+chan):
#print 'Filling ',Type
Trees[Type].Draw(var + " >> " + histName, "("+weight+")*(" + str(SFWjmu) + ")*(" + cut + cutbtag + cutwjj + ")", 'goff')
Trees[Type].Draw(var + " >> " + "WbbHist","("+weight+")*(" + str(SFWbmu) + ")*(" + cut + cutbtag + cutwbb + ")", 'goff')
Trees[Type].Draw(var + " >> " + "WccHist","("+weight+")*(" + str(SFWcmu) + ")*(" + cut + cutbtag + cutwcc + ")", 'goff')
#print 'Raw Wjj ',Variables['WJets'].Integral()
Variables[Type].Add(WbbHist)
#print 'Raw Wjj + Wbb ',Variables['WJets'].Integral()
Variables[Type].Add(WccHist)
#print 'Raw Wjj + Wbb + Wcc',Variables['WJets'].Integral()
elif Type.endswith('data'+chan):
#print 'Filling ',Type
Trees[Type].Draw(var + " >> " + histName, "(" + cut + cutbtag + ")", 'goff')
else:
#print 'Filling ',Type
Trees[Type].Draw(var + " >> " + histName, "("+weight+")*(" + cut + cutbtag + ")", 'goff')
if (not Type.endswith('data'+chan)):
SF = 1.0
if (channel == 'electron'):
lumi = lumi_el
if (channel == 'muon'):
lumi = lumi_mu
if (Type.startswith(massPoint+'_'+massPoint)): SF *= 20
#print 'EVENTS Before Scaling FOR ',Type,' = ',Variables[Type].Integral()
#print 'Pre Events before scaling for ',Type,' = ',VariablesPre[Type].Integral()
#print str(SF),' ',str(lumi),' ',str(xsec_norm[Type]),' ',str(Nevents[Type])
if Variables[Type].Integral() != 0:
#print Type,' Lumi scaling: ',str(SF*lumi*xsec[Type]/Nevents[Type])
Variables[Type].Scale ( SF*Yield[Type]/Variables[Type].Integral() )
efficiency[Type] = Variables[Type].Integral()/Nevents[Type]
else:
efficiency[Type] = 0
Variables[massPoint+'_ttbar'+chan].SetFillColor(ROOT.kRed-7)
Variables[massPoint+'_s'+chan].SetFillColor(ROOT.kRed-7)
Variables[massPoint+'_bs'+chan].SetFillColor(ROOT.kRed-7)
Variables[massPoint+'_t'+chan].SetFillColor(ROOT.kRed-7)
Variables[massPoint+'_bt'+chan].SetFillColor(ROOT.kRed-7)
Variables[massPoint+'_tw'+chan].SetFillColor(ROOT.kRed-7)
Variables[massPoint+'_btw'+chan].SetFillColor(ROOT.kRed-7)
Variables[massPoint+'_s'+chan].SetLineColor(ROOT.kRed-7)
Variables[massPoint+'_bs'+chan].SetLineColor(ROOT.kRed-7)
Variables[massPoint+'_t'+chan].SetLineColor(ROOT.kRed-7)
Variables[massPoint+'_bt'+chan].SetLineColor(ROOT.kRed-7)
Variables[massPoint+'_tw'+chan].SetLineColor(ROOT.kRed-7)
Variables[massPoint+'_btw'+chan].SetLineColor(ROOT.kRed-7)
Variables[massPoint+'_wjets'+chan].SetFillColor(ROOT.kGreen-3)
Variables[massPoint+'_zjets'+chan].SetFillColor(ROOT.kGreen-3)
Variables[massPoint+'_ww'+chan].SetFillColor(ROOT.kGreen-3)
Variables[massPoint+'_zjets'+chan].SetLineColor(ROOT.kGreen-3)
Variables[massPoint+'_ww'+chan].SetLineColor(ROOT.kGreen-3)
Variables[massPoint+'_ttbar'+chan].SetLineWidth(2)
Variables[massPoint+'_wjets'+chan].SetLineWidth(2)
Variables[massPoint+'_'+massPoint+chan].SetLineColor(1)
Variables[massPoint+'_'+massPoint+chan].SetLineWidth(2)
Variables[massPoint+'_'+massPoint+chan].SetLineStyle(6)
stack = THStack('a', 'a')
added = TH1D('a', 'a',bin,low,high)
topadded = TH1D('topadded', 'topadded', bin, low, high)
wjetsadded = TH1D('wjetsadded', 'wjetsadded',bin,low,high)
wjetsadded = Variables[massPoint+'_wjets'+chan].Clone()
wjetsadded.Add(Variables[massPoint+'_ww'+chan])
wjetsadded.Add(Variables[massPoint+'_zjets'+chan])
topadded = Variables[massPoint+'_ttbar'+chan].Clone()
topadded.Add(Variables[massPoint+'_s'+chan])
topadded.Add(Variables[massPoint+'_bs'+chan])
topadded.Add(Variables[massPoint+'_t'+chan])
topadded.Add(Variables[massPoint+'_bt'+chan])
topadded.Add(Variables[massPoint+'_tw'+chan])
topadded.Add(Variables[massPoint+'_btw'+chan])
wjetsadded.SetFillColor(ROOT.kGreen-3)
wjetsadded.SetLineColor(1)
wjetsadded.SetLineWidth(2)
topadded.SetFillColor(ROOT.kRed-7)
topadded.SetLineColor(1)
topadded.SetLineWidth(2)
stack.Add(wjetsadded)
stack.Add(topadded)
added.Add(wjetsadded)
added.Add(topadded)
print 'Data: ',Variables[massPoint+'_data'+chan].Integral(),' Background: ',added.Integral(),' Data/Background: ',Variables[massPoint+'_data'+chan].Integral()/added.Integral()
lumi_error = 0.022
ttbar_error = 0.15
wjets_error = 0.20
other_error = 0.20
uncert_list = []
lumiband = added.Clone();
for hbin in range(0,lumiband.GetNbinsX()+1):
uncert_lumi = 0
uncert_xsec = 0
uncert_stat = 0
for i in BkgList:
error = 0
if i in xsec.keys():
if (i.startswith(massPoint+'_t') or i.startswith(massPoint+'_b') or i.startswith(massPoint+'_s')):
error = ttbar_error
uncert_lumi += (efficiency[i]*xsec[i])**2
uncert_xsec += (Variables[i].GetBinContent(hbin+1)*error)**2
uncert_stat += Variables[i].GetBinError(hbin+1)**2
elif (i.startswith(massPoint+'_w') or i.startswith(massPoint+'_z')):
error = wjets_error
uncert_lumi += (efficiency[i]*xsec[i])**2
uncert_xsec += (Variables[i].GetBinContent(hbin+1)*error)**2
uncert_stat += Variables[i].GetBinError(hbin+1)**2
#print 'uncert_lumi: ',uncert_lumi,' uncert_xsec ',uncert_xsec,' uncert_stat ',uncert_stat
uncert = sqrt( (lumi_error**2)*uncert_lumi + uncert_xsec + uncert_stat )
if lumiband.GetBinContent(hbin+1) != 0:
dummy = 1.0
#print lumiband.GetBinContent(hbin+1),'+/-',uncert,'(',100*uncert/lumiband.GetBinContent(hbin+1),'%)'
lumiband.SetBinError(hbin+1,uncert);
added.SetBinError(hbin+1,uncert);
uncert_list . append(uncert)
#gStyle.SetHatchesSpacing(2.0);
gStyle.SetHatchesLineWidth(1);
lumiband.SetFillStyle(3344);
#lumiband.SetFillStyle(3001);
lumiband.SetFillColor(1);
legend = TLegend(.60,.70,.90,.90)
legend . AddEntry( Variables[massPoint+'_data'+chan], 'Data' , "lp")
legend . AddEntry( Variables[massPoint+'_ttbar'+chan], "t#bar{t} + Single-Top", "f")
legend . AddEntry( Variables[massPoint+'_wjets'+chan], "W#rightarrowl#nu + Z/#gamma*#rightarrowl^{+}l^{-} + VV" , "f")
if (massPoint.endswith('R')): coupling = 'R'
if (massPoint.endswith('L')): coupling = 'L'
if (massPoint.endswith('RL')): coupling = 'RL'
massval = copy.copy(massPoint)
massval = massval.lstrip('wp')
massval = massval.rstrip('00'+coupling)
if (len(massval)==1): massval = '0'+massval
massval = massval[0]+'.'+massval[1]
legend . AddEntry( Variables[massPoint+'_'+massPoint+chan], "W'_{"+coupling+"} x 20, m="+massval+" TeV", "l")
legend . AddEntry( lumiband , "Uncertainty" , "f")
c4 = TCanvas("c4","c4", 1000, 800)
c4.SetBottomMargin(0.3)
c4.SetRightMargin(0.06)
stack.SetMaximum( 2*stack.GetMaximum() )
if setLog:
c4.SetLogy()
stack.SetMaximum( stack.GetMaximum() + 30*stack.GetMaximum() )
stack.SetMinimum(0.1 )
#stack.SetMarkerSize(0)
stack.Draw("")
stack.GetYaxis().CenterTitle()
stack.GetYaxis().SetTitle(ylabel)
stack.GetXaxis().SetLabelSize(0)
#stack.GetXaxis().SetTitle(xlabel)
lumiband.Draw("samee2")
#lumiband.Draw("esame")
legend.SetShadowColor(0);
legend.SetFillColor(0);
legend.SetLineColor(0);
legend.Draw("same")
if (Variables[massPoint+'_data'+chan].GetBinContent(bin+1)>0):
print "Overflow for ",massPoint+"_"+channel," data "
Variables[massPoint+'_data'+chan].SetMarkerStyle(20)
Variables[massPoint+'_data'+chan].Draw('SAMES:E1')
Variables[massPoint+'_'+massPoint+chan].Draw("same")
latex2 = TLatex()
latex2.SetNDC()
latex2.SetTextSize(0.04)
latex2.SetTextAlign(31) # align right
if channel == ('electron'):
latex2.DrawLatex(0.87, 0.95, "CMS Preliminary, "+lumiPlot_el+" fb^{-1} at #sqrt{s} = 8 TeV");
if channel == ('muon'):
latex2.DrawLatex(0.87, 0.95, "CMS Preliminary, "+lumiPlot_mu+" fb^{-1} at #sqrt{s} = 8 TeV");
latex3 = TLatex()
latex3.SetNDC()
latex3.SetTextSize(0.04)
latex3.SetTextAlign(31) # align right
if (channel == 'electron'):
latex3.DrawLatex(0.47, 0.85, "e+jets " + njets);
if (channel == 'muon'):
latex3.DrawLatex(0.47, 0.85, "#mu+jets " + njets);
latex4 = TLatex()
latex4.SetNDC()
latex4.SetTextSize(0.03)
latex4.SetTextAlign(22) # align right
latex4.SetTextAngle(90) # align right
#latex4.DrawLatex(0.905, 0.56, "overflow")
Pull = TH1D('Pull', 'Pull', bin, low, high)
Pull = Variables[massPoint+'_data'+chan].Clone();
Pull.Add(added,-1)
Pull.Divide(added)
for i in range(bin):
i += 1
#print i+1,' ',added.GetBinContent(i+1)
if (Pull.GetBinContent(i+1) != 0 and Pull.GetBinError(i+1) != 0):
Pull.SetBinContent(i+1,Pull.GetBinContent(i+1)/Pull.GetBinError(i+1))
else: Pull.SetBinContent(i+1,0)
pad = TPad("pad", "pad", 0.0, 0.0, 1.0, 1.0)
pad.SetTopMargin(0.7)
pad.SetFillColor(0)
pad.SetGridy(1)
pad.SetFillStyle(0)
pad.Draw()
pad.cd(0)
pad.SetRightMargin(0.06)
Pull.SetMarkerStyle(20)
Pull.SetMaximum(3.0 )
Pull.SetMinimum(-3.0)
Pull.SetFillColor(2)
Pull.GetXaxis().SetTitle(xlabel)
Pull.GetYaxis().SetTitleSize(0.04)
Pull.GetYaxis().SetTitle('#sigma(Data-MC)')
Pull.SetMarkerSize(0.7)
Pull.GetYaxis().SetNdivisions(5);
Pull.Draw("HIST")
c4.SaveAs('Wprime_Plots/StackedHisto_' + save + '.pdf')
del c4
#del pad
del stack
del Variables
frame1 = x.frame()
frame2 = x.frame()
roohistBkg.plotOn(frame1, RooFit.Binning(NBINS))
background.plotOn(frame1)
hpull = frame1.pullHist()
frame2.addPlotable(hpull, 'p')
frame1.SetMinimum(0.5)
frame1.GetXaxis().SetTitle('')
frame1.GetXaxis().SetLabelSize(0.0)
frame1.GetYaxis().SetTickLength(0.06)
frame1.Draw()
pad = TPad('pad', 'pad', 0., 0., 1., 1.)
pad.SetTopMargin(0.6)
pad.SetFillColor(0)
pad.SetFillStyle(0)
pad.Draw()
pad.cd(0)
frame2.SetMinimum(-5)
frame2.SetMaximum(5)
frame2.GetYaxis().SetNdivisions(505)
frame2.GetXaxis().SetTitleOffset(0.9)
frame2.GetYaxis().SetTitleOffset(0.8)
frame2.GetYaxis().SetTickLength(0.06)
frame2.GetYaxis().SetTitleSize(0.05)
frame2.GetYaxis().SetLabelSize(0.03)
frame2.GetYaxis().SetTitle('(Data-Fit)/Error')
frame2.GetXaxis().SetTitle('m_{jj} (GeV)')
frame2.Draw()
class RatioPad:
REFERENCE_IS_DENOMINATOR = 0
REFERENCE_IS_NUMERATOR = 1
def __init__(self):
# reference plot: all other plots will be plotted as a ratio to this plot
self.reference_plot = None
# list of other plots, which will be calculated as a ratio with the reference
self.plots = []
def AddPlot(self,plot,draw_options='',legend_label=None,
legend_draw_options='lp',is_reference=False):
clone = plot.Clone(plot.GetName() + '_clone')
clone.SetDirectory(0)
if is_reference:
self.reference_plot = Plot(clone,draw_options,legend_label,legend_draw_options)
else:
self.plots.append(Plot(clone,draw_options,legend_label,legend_draw_options))
def Draw(self,
pad_name = 'bottom_pad',
pad_title = 'Bottom Pad',
pad_x1 = 0,
pad_y1 = 0,
pad_x2 = 1,
pad_y2 = 1,
pad_border_size = 1,
pad_ratio_order = REFERENCE_IS_DENOMINATOR,
pad_bottom_margin = 0,
pad_top_margin = 0,
pad_left_margin = 0,
pad_right_margin = 0,
yaxis_min = 0.9,
yaxis_max = 1.1,
y_ndiv = None,
y_title = None,
ratio_factor = 2,
):
# create the pad
self.pad = TPad(pad_name,
pad_title,
pad_x1,
pad_y1,
pad_x2,
pad_y2,
pad_border_size,
0
)
self.pad.SetMargin(pad_left_margin,pad_right_margin,pad_bottom_margin,pad_top_margin)
self.pad.SetFillColor(0)
self.pad.Draw()
self.pad.cd()
# create ratio plot for reference
self.reference_plot.CreateRatio(self.reference_plot,pad_ratio_order)
# the ratio plot will be plotted first so it determines the axes
self.reference_plot.ratio.SetMaximum(yaxis_max)
self.reference_plot.ratio.SetMinimum(yaxis_min)
# here I setup the ratio to show up
self.reference_plot.ratio.GetXaxis().SetLabelSize(self.reference_plot.ratio.GetXaxis().GetLabelSize()*ratio_factor)
self.reference_plot.ratio.GetYaxis().SetLabelSize(self.reference_plot.ratio.GetYaxis().GetLabelSize()*ratio_factor)
self.reference_plot.ratio.GetXaxis().SetTitleSize(self.reference_plot.ratio.GetXaxis().GetTitleSize()*ratio_factor)
self.reference_plot.ratio.GetYaxis().SetTitleSize(self.reference_plot.ratio.GetYaxis().GetTitleSize()*ratio_factor)
if y_ndiv is not None:
self.reference_plot.ratio.GetYaxis().SetNdivisions(y_ndiv)
if y_title is not None:
self.reference_plot.ratio.GetYaxis().SetTitle(y_title)
self.reference_plot.DrawRatio()
for plot in self.plots:
plot.CreateRatio(self.reference_plot,pad_ratio_order)
plot.DrawRatio(same=True)
def __plot_quadrant_template2(self, h_oo, h_xo, h_ox, h_xx, alias, xlabel,
plotname, doLogY):
from TrigEgammaDevelopments.plots import AutoFixAxes
from TrigEgammaDevelopments.helper.util import setBoxes
from ROOT import TCanvas, gStyle, TLegend, kRed, kBlue, kGreen, kGray, kBlack, TLine, TPad, TLatex
from TrigEgammaDevelopments.plots.AtlasStyle import AtlasStyle, atlas_template
ratio_size_as_fraction = 0.35
# Internal method
def sortHistograms(hists):
nevents = [o.GetEntries() for o in hists]
from operator import itemgetter
hist_sorted_index = sorted(enumerate(nevents), key=itemgetter(1))
hist_sorted = list()
for index in hist_sorted_index:
hist_sorted.append(hists[index[0]])
hist_sorted.reverse()
return hist_sorted
h_agree = h_xx + h_oo
h_disagree = h_ox + h_xo
hsum = h_agree + h_disagree
gStyle.SetOptStat(111111)
canvas = TCanvas('canvas', 'canvas', 2500, 1600)
drawopt = 'pE1'
canvas.cd()
top = TPad("pad_top", "This is the top pad", 0.0,
ratio_size_as_fraction, 1.0, 1.0)
top.SetBottomMargin(0.0)
top.SetBottomMargin(0.06 / float(top.GetHNDC()))
#top.SetTopMargin (0.04/float(top.GetHNDC()))
top.SetRightMargin(0.05)
top.SetLeftMargin(0.16)
top.SetFillColor(0)
top.Draw(drawopt)
canvas.cd()
bot = TPad("pad_bot", "This is the bottom pad", 0.0, 0.0, 1.0,
ratio_size_as_fraction)
bot.SetBottomMargin(0.10 / float(bot.GetHNDC()))
#bot.SetTopMargin (0.02/float(bot.GetHNDC()))
bot.SetTopMargin(0.0)
bot.SetRightMargin(0.05)
bot.SetLeftMargin(0.16)
bot.SetFillColor(0)
bot.Draw(drawopt)
top.cd()
h_agree.SetLineWidth(1)
h_agree.SetLineColor(kBlack)
h_agree.SetMarkerColor(kBlack)
h_disagree.SetLineWidth(1)
h_disagree.SetLineColor(kRed)
h_disagree.SetMarkerColor(kRed)
h_agree.SetName('Agreement')
h_disagree.SetName('Disagreement')
h_agree.SetStats(1)
h_disagree.SetStats(1)
# top
h1 = sortHistograms([h_agree, h_disagree])
# bot
h2 = sortHistograms([h_agree.Clone(), h_disagree.Clone()])
h1[0].GetXaxis().SetTitle('')
h1[0].GetYaxis().SetTitle('Counts')
#h1[0].GetYaxis().SetTitleOffset(0.5)
#h1[0].GetYaxis().SetLabelSize(0.10)
#h1[0].GetYaxis().SetTitleSize(0.10)
#h1[0].GetXaxis().SetLabelSize(0.10)
h1[0].Draw()
for i in range(1, len(h1)):
h1[i].Draw('sames')
top.Update()
setBoxes(top, h1)
if doLogY:
top.SetLogy()
AutoFixAxes(top, False, False, 9000)
else:
AutoFixAxes(top, False, False, 2)
bot.cd()
if doLogY:
bot.SetLogy()
hsum.Sumw2()
for h in h2:
h.SetStats(0)
h.Sumw2()
h.Divide(h, hsum, 1., 1.)
h2[0].GetYaxis().SetTitle('ratio')
h2[0].GetXaxis().SetTitle(xlabel)
h2[0].GetYaxis().SetTitleOffset(0.5)
h2[0].GetYaxis().SetLabelSize(0.10)
h2[0].GetYaxis().SetTitleSize(0.10)
h2[0].GetXaxis().SetLabelSize(0.10)
h2[0].GetXaxis().SetTitleSize(0.10)
if not doLogY:
h2[0].GetYaxis().SetRangeUser(0, 1.05)
h2[0].Draw('ep1')
for i in range(1, len(h2)):
h2[i].Draw('sames')
if doLogY:
AutoFixAxes(bot, False, False, 1.1)
# Loop over histograms
canvas.SaveAs(plotname)
def sobWeightedPlot(self,
fileName,
datasetName,
channel,
cat,
log,
mass,
tanb,
blind,
sob=False):
# print 'yuta', channel, cat
c = TCanvas(fileName, '', 600, 600)
c.cd()
if log: c.SetLogy(1)
f = self.openTFile('Plot_' + fileName + '.root')
isEMSM = fileName.find('SM') != -1 and fileName.find('em') != -1
isETSM = fileName.find('SM') != -1 and fileName.find('et') != -1
samples = ['ggH', 'Ztt', 'signal', 'data_obs', 'ttbar', 'EWK', 'Fakes']
if isEMSM:
samples.append('ggH_hww')
if isETSM:
samples.append('Zee')
dataGraph = self.tfileGet(f, 'Graph_from_data_obs')
histDict = {}
for sample in samples:
histDict[sample] = self.tfileGet(f, sample)
# print 'check :', sample, histDict[sample].GetSumOfWeights()
if not histDict[sample]:
print 'Missing histogram', sample, 'in file', 'Plot_' + fileName + '.root'
# original for plots
xminInset = 60 # 0
xmaxInset = 179 # 340 (for full range)
# all range
# xminInset = 0 # 0
# xmaxInset = 350 # 340 (for full range)
# xminInset = 40 # 0
# xmaxInset = 200 # 340 (for full range)
# xminInset = 120 # 0
# xmaxInset = 251 # 340 (for full range)
if tanb > 0:
xminInset = mass - 100
xmaxInset = mass + 100
if sob:
xminInset = 0.4
xmaxInset = 0.7
ztt = histDict['Ztt']
ggH = histDict['ggH']
data = histDict['data_obs']
# This is to fix a weird plotting bug
if sob:
new_data = TH1F('new_data', '', ggH.GetNbinsX(), 0., 0.7)
for i in range(1, new_data.GetNbinsX() + 1):
new_data.SetBinContent(i, data.GetBinContent(i))
# print data.GetBinContent(i)
data = new_data
ggH_hww = 0
zee = 0
signal = histDict['signal']
if isEMSM:
ggH_hww = histDict['ggH_hww']
if isETSM:
print 'retrieve Zee'
zee = histDict['Zee']
tt = histDict['ttbar']
ewk = histDict['EWK']
fakes = histDict['Fakes']
ztt.GetYaxis().SetRangeUser(0., 1.3 * self.findMaxY(data, 0))
if log:
ztt.GetYaxis().SetRangeUser(0.001, 50. * self.findMaxY(data, 0))
ztt.GetXaxis().SetTitle('#bf{m_{#tau#tau} [GeV]}')
ztt.GetYaxis().SetTitle('#bf{S/B Weighted dN/dm_{#tau#tau} [1/GeV]}')
if tanb > 0. and not log:
ztt.GetXaxis().SetRangeUser(0., mass + 200.)
if sob:
ztt.GetXaxis().SetTitle('S/(S+B)')
ztt.GetYaxis().SetTitle('Events')
ztt.SetTitleOffset(1.3, 'Y')
ztt.SetTitleOffset(1., 'X')
ztt.GetYaxis().SetNdivisions(505)
ztt.SetNdivisions(505)
for b in range(0, signal.GetNbinsX() + 2):
if signal.GetBinCenter(
b) < xminInset or xmaxInset < signal.GetBinCenter(b):
signal.SetBinContent(b, 0.)
signal.SetBinError(b, 0.)
signal.SetName('sig')
signal.SetFillStyle(3353) # 1001=solid , 3004,3005=diagonal
signal.SetFillColor(2)
signal.SetLineColor(2)
signal.SetLineStyle(1)
signal.SetLineWidth(0)
ggH.SetBinContent(0, 0) # remove red line on top of y axis in plot
ggH.SetBinContent(ggH.GetNbinsX() + 1, 0)
ggH.SetBinError(0, 0)
ggH.SetBinError(ggH.GetNbinsX() + 1, 0)
ggH.SetName('ggH')
ggH.SetFillStyle(3353) # 1001=solid , 3004,3005=diagonal
ggH.SetFillColor(2)
ggH.SetLineColor(2)
ggH.SetLineStyle(1)
ggH.SetLineWidth(0)
if isEMSM:
errorBand = TH1F(ggH_hww)
else:
errorBand = TH1F(ztt)
errorBand.SetName("errorBand")
errorBand.SetMarkerSize(0)
errorBand.SetFillColor(1)
errorBand.SetFillStyle(3013)
errorBand.SetLineWidth(1)
legend = TLegend()
mssmLabel = ''
if tanb > 0:
mssmLabel = "tan#beta={tanb}".format(tanb=tanb)
higgsLabel = "H(125 GeV)#rightarrow#tau#tau"
if tanb > 0:
higgsLabel = "H(125 GeV)#rightarrow#tau#tau"
legend.SetFillStyle(0)
legend.SetFillColor(0)
legend.SetBorderSize(0)
legend.AddEntry(ggH, higgsLabel, "F")
if tanb > 0:
legend.AddEntry(TObject(0), mssmLabel, "")
legend.AddEntry(data, "observed", "LP")
if isEMSM:
legend.AddEntry(ggH_hww, "H(125 GeV)#rightarrowWW", "F")
legend.AddEntry(ztt, "Z#rightarrow#tau#tau", "F")
legend.AddEntry(tt, "t#bar{t}", "F")
if isETSM:
legend.AddEntry(zee, "Z#rightarrowee", "F")
legend.AddEntry(ewk, "electroweak", "F")
legend.AddEntry(fakes, "QCD", "F")
legend.SetX1NDC(0.63)
legend.SetX2NDC(1.05)
legend.SetY1NDC(0.25)
legend.SetY2NDC(0.46)
if log:
legend.SetX1NDC(0.18)
legend.SetX2NDC(0.60)
legend.SetY1NDC(0.17)
legend.SetY2NDC(0.38)
legend.SetTextSize(.028)
legend.SetTextAlign(12)
if isEMSM:
dataDiff = self.diffPlot(data, ggH_hww, 1)
dataDiffGraph = self.diffGraph(dataGraph, ggH_hww, 1)
errBand = self.getErrorBand(ggH_hww)
else:
dataDiff = self.diffPlot(data, ztt, 1)
dataDiffGraph = self.diffGraph(dataGraph, ztt, 1)
errBand = self.getErrorBand(ztt)
errBand.SetFillStyle(
3013
) # 1001=solid , 3004,3005=diagonal, 3013=hatched official for H.tau tau
errBand.SetFillColor(1)
errBand.SetLineStyle(1)
errBand.SetLineColor(1)
errBand.SetLineWidth(1)
errBandFrame = TH1F(
'errBandFrame', '',
int((xmaxInset - xminInset) / dataDiff.GetBinWidth(1)), xminInset,
xmaxInset)
errBandFrame.GetYaxis().SetTitle("")
errBandFrame.GetYaxis().SetRangeUser(
-1.1 * self.findMinY(dataDiff, blind, 0, xminInset, xmaxInset),
2.0 * self.findMaxY(dataDiff, blind, 0, xminInset, xmaxInset))
# errBandFrame.GetYaxis().SetRangeUser(-1.*self.findMinY(dataDiff,blind,0,xminInset,xmaxInset),1.1*self.findMaxY(dataDiff,blind,0,xminInset,xmaxInset)) # good !
# errBandFrame.GetYaxis().SetRangeUser(-0.2*self.findMinY(dataDiff,blind,0,xminInset,xmaxInset),0.5*self.findMaxY(dataDiff,blind,0,xminInset,xmaxInset))
print 'Yuta', channel, cat
if (channel == 'e#tau_{h}' and cat == 'vbf') or (channel == 'e#tau_{h}'
and cat == ''):
print 'enter'
errBandFrame.GetYaxis().SetRangeUser(
-2. * self.findMinY(dataDiff, blind, 0, xminInset, xmaxInset),
2.0 * self.findMaxY(dataDiff, blind, 0, xminInset, xmaxInset))
errBandFrame.GetYaxis().SetNdivisions(5)
errBandFrame.GetYaxis().SetLabelSize(0.06)
errBandFrame.GetXaxis().SetTitle("#bf{m_{#tau#tau} [GeV]} ")
errBandFrame.GetXaxis().SetTitleColor(kBlack)
errBandFrame.GetXaxis().SetTitleSize(0.07)
errBandFrame.GetXaxis().SetTitleOffset(0.85)
errBandFrame.GetXaxis().SetLabelSize(0.06)
errBandFrame.GetXaxis().SetNdivisions(506)
# errBandFrame.SetNdivisions(505)
legendDiff = TLegend()
legendDiff.SetFillStyle(0)
legendDiff.SetFillColor(0)
legendDiff.SetBorderSize(0)
legendDiff.AddEntry(signal, higgsLabel, "F")
if tanb > 0:
legendDiff.AddEntry(TObject(0), mssmLabel,
'') # That might not work in python
# legendDiff.AddEntry(dataDiff,"Data - Background","LP")
legendDiff.AddEntry(dataDiffGraph, "Data - Background", "LEP")
legendDiff.AddEntry(errBand, "Bkg. Uncertainty", "F")
legendDiff.SetX1NDC(0.45)
legendDiff.SetX2NDC(0.88)
legendDiff.SetY1NDC(0.67)
legendDiff.SetY2NDC(0.88)
if dataDiff.GetBinContent(dataDiff.FindBin(mass)) < 0.:
legendDiff.SetX1NDC(0.45)
legendDiff.SetX2NDC(0.88)
legendDiff.SetY1NDC(0.24)
legendDiff.SetY2NDC(0.45)
legendDiff.SetTextSize(.045)
legendDiff.SetTextAlign(12)
padBack = TPad(
"padBack", "padBack", 0.57, 0.58, 0.975,
0.956) # TPad must be created after TCanvas otherwise ROOT crashes
padBack.SetFillColor(0)
pad = TPad(
"diff", "diff", 0.45, 0.5, 0.9765,
0.957) # TPad must be created after TCanvas otherwise ROOT crashes
pad.cd()
pad.SetFillColor(0)
pad.SetFillStyle(0)
errBandFrame.Draw()
errBand.Draw("e2lsame")
signal.Draw("histsame")
line = TLine()
line.DrawLine(xminInset, 0, xmaxInset, 0)
# dataDiff.Draw("pe same")
if blind == False:
self.HideBin(dataDiffGraph)
dataDiffGraph.SetMarkerSize(0.5)
dataDiffGraph.Draw('pe same')
for ibin in range(0, dataDiffGraph.GetN()):
x = Double(0.)
y = Double(0.)
dataDiffGraph.GetPoint(ibin, x, y)
print 'Yuta_bin=', ibin, 'x=', x, 'y=', y, dataDiffGraph.GetErrorYhigh(
ibin), dataDiffGraph.GetErrorYlow(ibin)
print 'Yuta_error=', ibin, errBand.GetXaxis().GetBinCenter(
ibin + 1), errBand.GetBinError(ibin + 1)
legendDiff.Draw()
pad.RedrawAxis()
c.cd()
ztt.Draw("hist")
ggH.Draw("hist same")
if isEMSM:
ggH_hww.Draw("hist same")
ztt.Draw("hist same")
errorBand.Draw("e2 same")
tt.Draw("hist same")
if isETSM:
zee.Draw("hist same")
ewk.Draw("hist same")
fakes.Draw("hist same")
# data.Draw("pe same")
dataGraph.SetMarkerSize(1)
dataGraph.Draw('PE same')
if blind == False:
self.HideBin(dataGraph)
print '#####', data.Integral(), data.GetBinContent(1)
legend.Draw()
c.RedrawAxis()
padBack.Draw() # clear the background axe
pad.Draw()
if log: c.SetLogy(1)
self.CMSPrelim(c, datasetName, channel, cat)
savepath = 'figure/Plot_' + fileName
if cat == '':
savepath = savepath + '.pdf'
else:
savepath = savepath + '_' + cat + '.pdf'
# c.Print('figure/Plot_'+fileName+".eps")
# c.Print('figure/Plot_'+fileName+".png")
# c.Print('figure/Plot_'+fileName+".pdf")
c.Print(savepath)
c.Close()
def PlotSig(templates, sideband_templates):
print "Plotting Signal Template"
data = templates["Data"].histo.Clone()
gjets = templates["GJets"].histo.Clone()
sideband = sideband_templates["Sideband"].histo.Clone()
full = gjets.Clone()
full.Add(sideband)
c = TCanvas("c", "canvas", 800, 800)
gStyle.SetOptStat(0)
gStyle.SetLegendBorderSize(0)
# c.SetLeftMargin(0.15);
# c.SetLogy();
#c.cd();
pad1 = TPad("pad1", "pad1", 0.01, 0.25, 0.99, 0.99)
pad1.SetBottomMargin(0.)
pad1.Draw()
pad1.cd()
pad1.SetLogy()
pad1.SetFillColor(0)
pad1.SetFrameBorderMode(0)
pad1.SetBorderMode(0)
temp_style(gjets, kGreen + 2)
temp_style(sideband, kRed)
temp_style(full, kBlue + 2)
DataStyle(data)
leg = getLegend(xmax=0.7, ymin=0.55, ymax=0.75)
gjets.Draw("hist")
gjets.SetTitle("")
gjets.GetYaxis().SetTitle("Events")
if templates.variable.xaxis_title == "":
templates.variable.xaxis_title = next(
(vartitle for var, vartitle in xaxismap.items()
if var in templates.variable.variable), "")
gjets.GetXaxis().SetTitle(templates.variable.xaxis_title)
sideband.Draw("hist same")
full.Draw("hist same")
data.Draw("pex0 same")
hslist = [data, gjets, sideband]
leg.AddEntry(data, "Data", "lp")
leg.AddEntry(gjets, "Real GJets", "l")
leg.AddEntry(sideband, "QCD Fake Template", "l")
leg.AddEntry(full, "Full", "l")
VarBounds(templates.variable.variable, hslist)
leg.Draw()
lumi_label = '%s' % float('%.3g' % (templates.lumi / 1000.)) + " fb^{-1}"
texLumi, texCMS = getCMSText(lumi_label, templates.year)
if re.search("(\d+to\d+|\d+toInf)", templates.variable.variable):
ptrange = templates.variable.variable.split("_")[1].split("to")
rtext = PtRangeText(ptrange=ptrange)
c.cd()
pad2 = TPad("pad2", "pad2", 0.01, 0.01, 0.99, 0.25)
pad2.SetGridy()
pad2.Draw()
pad2.cd()
pad2.SetFillColor(0)
pad2.SetFrameBorderMode(0)
pad2.SetBorderMode(0)
pad2.SetTopMargin(0)
pad2.SetBottomMargin(0.35)
ratio = GetRatio(data, full)
RatioStyle(ratio,
rymin=-0.25,
rymax=2.25,
xname=templates.variable.xaxis_title,
yname="Data/Full")
ratio.Draw("pex0")
line = getRatioLine(data.GetXaxis().GetXmin(), data.GetXaxis().GetXmax())
line.Draw("same")
SaveAs(c,
"real_template_%s" % templates.varname,
year=templates.year,
sub="GammaPurity")
def plot(self, **kw):
from ROOT import kRed
dirname = retrieve_kw(kw, 'dirname', 'Distribution')
basecolor = retrieve_kw(kw, 'basecolor', kRed - 7)
pdftitle = retrieve_kw(kw, 'pdftitle', 'Distributions')
pdfoutput = retrieve_kw(kw, 'pdfoutput', 'distributions')
import os
# Organize outputs (.py and .pdf)
prefix = self._basepath.split('/')[-1]
localpath = os.getcwd() + '/' + dirname + '/' + prefix
try:
if not os.path.exists(localpath):
os.makedirs(localpath)
except:
self._logger.warning('The director %s exist.', localpath)
hist_names = [
'et', 'eta', 'mu', 'nvtx', 'reta', 'eratio', 'weta2', 'rhad',
'rphi', 'f1', 'f3'
]
hist_labels = [
'E_{T}', "#eta", "<#mu>", 'N_{vtx}', 'R_{eta}', 'E_{ratio}',
'W_{eta2}', 'R_{had}', 'R_{phi}', 'f_{1}', 'f_{3}'
]
from ROOT import TCanvas, TH1F, gStyle, TLegend, TPad
from ROOT import kGreen, kRed, kBlue, kBlack, kGray, gPad, kAzure
from TrigEgammaDevelopments.plots.AtlasStyle import AtlasStyle, atlas_template, setLegend1
canvas1 = TCanvas('canvas1', 'canvas1', 2500, 1600)
canvas1.Divide(4, 3)
# Concatenate distributions for all regions
def sumAllRegions(histname):
h = None
for etBinIdx in range(len(self._etBins) - 1):
for etaBinIdx in range(len(self._etaBins) - 1):
binningname = ('et%d_eta%d') % (etBinIdx, etaBinIdx)
path = self._basepath + '/' + self.currentDir(
) + '/' + binningname
if h:
h += self.storeSvc().histogram(path + '/' + histname)
else:
h = self.storeSvc().histogram(path + '/' +
histname).Clone()
return h
collector = []
figures = {
'rings': [],
'rnnOutput': [],
'ringer_profile': str(),
'shower_shapes': str()
}
"""
Plot all shower shapes distributins
"""
for idx, histname in enumerate(hist_names):
self.setDir('Data')
h_data = sumAllRegions(histname)
self.setDir('MonteCarlo')
h_mc = sumAllRegions(histname)
#h_mc, h_data = self.__scale_histograms(h_mc, h_data, 100, 0.01, 0.01)
pad = canvas1.cd(idx + 1)
gStyle.SetOptStat(110011)
collector.append(pad)
h_mc.SetFillColor(basecolor)
h_mc.SetLineColor(basecolor)
h_data.SetLineColor(kBlack)
h_mc.Scale(1. / h_mc.GetMaximum())
h_data.Scale(1. / h_data.GetMaximum())
h_mc.Draw()
h_data.Draw('same')
leg1 = TLegend(0.2, 0.75, 0.5, 0.95)
setLegend1(leg1)
leg1.AddEntry(h_mc, 'MC')
leg1.AddEntry(h_data, 'Data')
leg1.Draw()
collector[-1].Update()
collector.append(h_mc)
collector.append(h_data)
collector.append(leg1)
canvas1.SaveAs(localpath + '/shower_shapes_distributions.pdf')
figures[
'shower_shapes'] = localpath + '/shower_shapes_distributions.pdf'
"""
Plot all shower ringer shapes for each ring
"""
ratio_size_as_fraction = 0.35
from RingerCore import progressbar
rings_localpath = []
for r in progressbar(range(100),
100,
step=1,
logger=self._logger,
prefix="Looping over rings (Plotting...) "):
canvas2 = TCanvas('canvas2', 'canvas2', 2500, 1600)
drawopt = 'pE1'
canvas2.cd()
top = TPad("pad_top", "This is the top pad", 0.0,
ratio_size_as_fraction, 1.0, 1.0)
top.SetBottomMargin(0.0)
top.SetBottomMargin(0.06 / float(top.GetHNDC()))
#top.SetTopMargin (0.04/float(top.GetHNDC()))
top.SetRightMargin(0.05)
top.SetLeftMargin(0.16)
top.SetFillColor(0)
top.Draw(drawopt)
canvas2.cd()
bot = TPad("pad_bot", "This is the bottom pad", 0.0, 0.0, 1.0,
ratio_size_as_fraction)
bot.SetBottomMargin(0.10 / float(bot.GetHNDC()))
#bot.SetTopMargin (0.02/float(bot.GetHNDC()))
bot.SetTopMargin(0.0)
bot.SetRightMargin(0.05)
bot.SetLeftMargin(0.16)
bot.SetFillColor(0)
bot.Draw(drawopt)
self.setDir('MonteCarlo')
h_mc = sumAllRegions('rings/ring_' + str(r))
self.setDir('Data')
h_data = sumAllRegions('rings/ring_' + str(r))
gStyle.SetOptStat(000000)
h_mc, h_data = self.__scale_histograms(h_mc, h_data, 100, 0.0001,
0.025)
h_mc.Scale(1. / h_mc.GetMaximum())
h_data.Scale(1. / h_data.GetMaximum())
from ROOT import TH1, kGray
divide = ""
drawopt = 'pE1'
bot.cd()
ref = h_mc.Clone()
h = h_data.Clone()
ref.Sumw2()
h.Sumw2()
ratioplot = h.Clone()
ratioplot.Sumw2()
ratioplot.SetName(h.GetName() + '_ratio')
ratioplot.Divide(h, ref, 1., 1., '')
ratioplot.SetFillColor(0)
ratioplot.SetFillStyle(0)
ratioplot.SetMarkerColor(1)
ratioplot.SetLineColor(kGray)
ratioplot.SetMarkerStyle(24)
ratioplot.SetMarkerSize(1.2)
ratioplot.GetYaxis().SetTitleSize(0.10)
ratioplot.GetXaxis().SetTitleSize(0.10)
ratioplot.GetXaxis().SetLabelSize(0.10)
ratioplot.GetYaxis().SetLabelSize(0.10)
ratioplot.GetYaxis().SetRangeUser(-1.6, 3.7)
ratioplot.GetYaxis().SetTitleOffset(0.7)
ratioplot.GetYaxis().SetTitle('Data/MC')
ratioplot.GetXaxis().SetTitle('Ring #' + str(r + 1) + ' [MeV]')
ratioplot.Draw(drawopt)
from ROOT import TLine
nbins = h_data.GetNbinsX()
xmin = h_data.GetXaxis().GetBinLowEdge(1)
xmax = h_data.GetXaxis().GetBinLowEdge(nbins + 1)
l1 = TLine(xmin, 1, xmax, 1)
l1.SetLineColor(kRed)
l1.SetLineStyle(2)
l1.Draw()
bot.Update()
top.cd()
h_mc.SetFillColor(basecolor)
h_mc.SetLineWidth(1)
h_mc.SetLineColor(basecolor)
h_data.SetLineColor(kBlack)
h_data.SetLineWidth(1)
h_mc.GetYaxis().SetTitle('Count')
h_mc.Draw()
h_data.Draw('same')
leg1 = TLegend(0.8, 0.70, 0.95, 0.95)
setLegend1(leg1)
leg1.AddEntry(h_mc, 'MC')
leg1.AddEntry(h_data, 'Data')
leg1.Draw()
atlas_template(top)
top.Update()
canvas2.SaveAs(localpath + '/distribution_ring_' + str(r + 1) +
'.pdf')
figures['rings'].append(localpath + '/distribution_ring_' +
str(r + 1) + '.pdf')
"""
Plot ringer mean shapes
"""
h_mean_data = TH1F('h_mean_data', '', 100, 0, 100)
h_mean_mc = TH1F('h_mean_mc', '', 100, 0, 100)
for bin in range(100):
self.setDir('MonteCarlo')
h_mc = sumAllRegions('rings/ring_' + str(bin))
self.setDir('Data')
h_data = sumAllRegions('rings/ring_' + str(bin))
h_mean_data.SetBinContent(bin + 1, h_data.GetMean())
h_mean_mc.SetBinContent(bin + 1, h_mc.GetMean())
canvas3 = TCanvas('canvas3', 'canvas3', 2500, 1600)
drawopt = 'pE1'
canvas3.cd()
top = TPad("pad_top", "This is the top pad", 0.0,
ratio_size_as_fraction, 1.0, 1.0)
top.SetBottomMargin(0.0)
top.SetBottomMargin(0.06 / float(top.GetHNDC()))
#top.SetTopMargin (0.04/float(top.GetHNDC()))
top.SetRightMargin(0.05)
top.SetLeftMargin(0.16)
top.SetFillColor(0)
top.Draw(drawopt)
canvas3.cd()
bot = TPad("pad_bot", "This is the bottom pad", 0.0, 0.0, 1.0,
ratio_size_as_fraction)
bot.SetBottomMargin(0.10 / float(bot.GetHNDC()))
#bot.SetTopMargin (0.02/float(bot.GetHNDC()))
bot.SetTopMargin(0.0)
bot.SetRightMargin(0.05)
bot.SetLeftMargin(0.16)
bot.SetFillColor(0)
bot.Draw(drawopt)
gStyle.SetOptStat(000000)
from ROOT import TH1, kGray
divide = ""
drawopt = 'pE1'
bot.cd()
ref = h_mean_mc.Clone()
h = h_mean_data.Clone()
ref.Sumw2()
h.Sumw2()
ratioplot = h.Clone()
ratioplot.Sumw2()
ratioplot.SetName(h.GetName() + '_ratio')
ratioplot.Divide(h, ref, 1., 1., '')
ratioplot.SetFillColor(0)
ratioplot.SetFillStyle(0)
ratioplot.SetMarkerColor(1)
ratioplot.SetLineColor(kGray)
ratioplot.SetMarkerStyle(24)
ratioplot.SetMarkerSize(1.2)
ratioplot.GetYaxis().SetTitleSize(0.10)
ratioplot.GetXaxis().SetTitleSize(0.10)
ratioplot.GetXaxis().SetLabelSize(0.10)
ratioplot.GetYaxis().SetLabelSize(0.10)
ratioplot.GetYaxis().SetRangeUser(-1.6, 3.7)
ratioplot.GetYaxis().SetTitleOffset(0.7)
ratioplot.GetYaxis().SetTitle('Data/MC')
ratioplot.GetXaxis().SetTitle('Rings')
ratioplot.Draw(drawopt)
from ROOT import TLine
nbins = h_mean_data.GetNbinsX()
xmin = h_mean_data.GetXaxis().GetBinLowEdge(1)
xmax = h_mean_data.GetXaxis().GetBinLowEdge(nbins + 1)
l1 = TLine(xmin, 1, xmax, 1)
l1.SetLineColor(kRed)
l1.SetLineStyle(2)
l1.Draw()
bot.Update()
top.cd()
h_mean_mc.SetFillColor(basecolor)
h_mean_mc.SetLineWidth(1)
h_mean_mc.SetLineColor(basecolor)
h_mean_data.SetLineColor(kBlack)
h_mean_data.SetLineWidth(1)
#h_mean_mc.Scale( 1./h_mean_mc.GetEntries() )
#h_mean_data.Scale( 1./h_mean_data.GetEntries() )
if h_mean_mc.GetMaximum() > h_mean_data.GetMaximum():
ymin = h_mean_mc.GetMinimum()
ymax = h_mean_mc.GetMaximum()
h_mean_mc.Draw()
h_mean_mc.GetYaxis().SetTitle('E[Ring] MeV')
h_mean_data.Draw('same')
else:
ymin = h_mean_data.GetMinimum()
ymax = h_mean_data.GetMaximum()
h_mean_data.GetYaxis().SetTitle('E[Ring] MeV')
h_mean_data.Draw()
h_mean_mc.Draw('same')
h_mean_data.Draw('same')
# prepare ringer lines
def gen_line_90(x, ymin, ymax, text):
from ROOT import TLine, TLatex
ymax = 1.05 * ymax
l = TLine(x, ymin, x, ymax)
l.SetLineStyle(2)
l.Draw()
txt = TLatex()
txt.SetTextFont(12)
txt.SetTextAngle(90)
txt.SetTextSize(0.04)
txt.DrawLatex(x - 1, (ymax - ymin) / 2., text)
return l, txt
l_ps, t_ps = gen_line_90(8, ymin, ymax, 'presampler')
l_em1, t_em1 = gen_line_90(72, ymin, ymax, 'EM.1')
l_em2, t_em2 = gen_line_90(80, ymin, ymax, 'EM.2')
l_em3, t_em3 = gen_line_90(88, ymin, ymax, 'EM.3')
l_had1, t_had1 = gen_line_90(92, ymin, ymax, 'Had.1')
l_had2, t_had2 = gen_line_90(96, ymin, ymax, 'Had.2')
l_had3, t_had3 = gen_line_90(100, ymin, ymax, 'Had.3')
leg1 = TLegend(0.8, 0.70, 0.95, 0.95)
setLegend1(leg1)
leg1.AddEntry(h_mean_mc, 'MC')
leg1.AddEntry(h_mean_data, 'Data')
leg1.Draw()
atlas_template(top)
top.Update()
canvas3.SaveAs(localpath + '/ringer_profile.pdf')
figures['ringer_profile'] = localpath + '/ringer_profile.pdf'
"""
Plot all NN distributions for each calo region
"""
for algname in self._discrList:
for etBinIdx in range(len(self._etBins) - 1):
for etaBinIdx in range(len(self._etaBins) - 1):
binningname = ('et%d_eta%d') % (etBinIdx, etaBinIdx)
path = self._basepath + '/MonteCarlo/' + binningname
h_mc = self.storeSvc().histogram(
path + '/' + algname +
'/discriminantVsMu').ProjectionX().Clone()
path = self._basepath + '/Data/' + binningname
h_data = self.storeSvc().histogram(
path + '/' + algname +
'/discriminantVsMu').ProjectionX().Clone()
h_mc.Rebin(10)
h_data.Rebin(10)
h_mc.Scale(1. / h_mc.GetMaximum())
h_data.Scale(1. / h_data.GetMaximum())
canvas4 = TCanvas('canvas4', 'canvas4', 2500, 1600)
drawopt = 'pE1'
canvas4.cd()
top = TPad("pad_top", "This is the top pad", 0.0,
ratio_size_as_fraction, 1.0, 1.0)
top.SetBottomMargin(0.0)
top.SetBottomMargin(0.06 / float(top.GetHNDC()))
#top.SetTopMargin (0.04/float(top.GetHNDC()))
top.SetRightMargin(0.05)
top.SetLeftMargin(0.16)
top.SetFillColor(0)
top.Draw(drawopt)
canvas4.cd()
bot = TPad("pad_bot", "This is the bottom pad", 0.0, 0.0,
1.0, ratio_size_as_fraction)
bot.SetBottomMargin(0.10 / float(bot.GetHNDC()))
bot.SetTopMargin(0.0)
bot.SetRightMargin(0.05)
bot.SetLeftMargin(0.16)
bot.SetFillColor(0)
bot.Draw(drawopt)
gStyle.SetOptStat(000000)
from ROOT import TH1, kGray
divide = ""
drawopt = 'pE1'
bot.cd()
ref = h_mc.Clone()
h = h_data.Clone()
ref.Sumw2()
h.Sumw2()
ratioplot = h.Clone()
ratioplot.Sumw2()
ratioplot.SetName(h.GetName() + '_ratio')
ratioplot.Divide(h, ref, 1., 1., '')
ratioplot.SetFillColor(0)
ratioplot.SetFillStyle(0)
ratioplot.SetMarkerColor(1)
ratioplot.SetLineColor(kGray)
ratioplot.SetMarkerStyle(24)
ratioplot.SetMarkerSize(1.2)
ratioplot.GetYaxis().SetTitleSize(0.10)
ratioplot.GetXaxis().SetTitleSize(0.10)
ratioplot.GetXaxis().SetLabelSize(0.10)
ratioplot.GetYaxis().SetLabelSize(0.10)
ratioplot.GetYaxis().SetRangeUser(-1.6, 3.7)
ratioplot.GetYaxis().SetTitleOffset(0.7)
ratioplot.GetYaxis().SetTitle('Data/MC')
ratioplot.GetXaxis().SetTitle(
'Neural Network (Discriminant)')
ratioplot.Draw(drawopt)
from ROOT import TLine
nbins = h_data.GetNbinsX()
xmin = h_data.GetXaxis().GetBinLowEdge(1)
xmax = h_data.GetXaxis().GetBinLowEdge(nbins + 1)
l1 = TLine(xmin, 1, xmax, 1)
l1.SetLineColor(kRed)
l1.SetLineStyle(2)
l1.Draw()
bot.Update()
top.cd()
h_mc.SetFillColor(basecolor)
h_mc.SetLineWidth(1)
h_mc.SetLineColor(basecolor)
h_data.SetLineColor(kBlack)
h_data.SetLineWidth(1)
h_mc.Scale(1. / h_mc.GetMaximum())
h_data.Scale(1. / h_data.GetMaximum())
h_mc.GetYaxis().SetTitle(
('Counts (%s)') % (binningname.replace('_', ',')))
h_mc.Draw()
h_data.Draw('same')
leg1 = TLegend(0.8, 0.70, 0.95, 0.95)
setLegend1(leg1)
leg1.AddEntry(h_mc, 'MC')
leg1.AddEntry(h_data, 'Data')
leg1.Draw()
atlas_template(top)
top.Update()
canvas4.SaveAs(localpath + '/' + algname + '_rnnOutput_' +
binningname + '.pdf')
figures['rnnOutput'].append(localpath + '/' + algname +
'_rnnOutput_' + binningname +
'.pdf')
#from RingerCore.tex.TexAPI import *
from RingerCore.tex.BeamerAPI import BeamerTexReportTemplate1, BeamerSection, BeamerMultiFigureSlide, BeamerFigureSlide
with BeamerTexReportTemplate1(theme='Berlin',
_toPDF=True,
title=pdftitle,
outputFile=pdfoutput,
font='structurebold'):
with BeamerSection(name='Shower Shapes'):
BeamerMultiFigureSlide(
title='Shower Shapes (MC and Data)',
paths=[figures['shower_shapes']],
nDivWidth=1 # x
,
nDivHeight=1 # y
,
texts=None,
fortran=False,
usedHeight=0.8,
usedWidth=1.1)
with BeamerSection(name='Ringer Shapes Profile'):
BeamerMultiFigureSlide(
title='Ringer Profile (MC and Data)',
paths=[figures['ringer_profile']],
nDivWidth=1 # x
,
nDivHeight=1 # y
,
texts=None,
fortran=False,
usedHeight=0.8,
usedWidth=1.1)
with BeamerSection(name='Ringer Shapes'):
for s in range(4):
paths1 = [
path for path in figures['rings'][s * 25:s * 25 + 25]
]
BeamerMultiFigureSlide(
title='Ringer Shapes (MC and Data)',
paths=paths1,
nDivWidth=5 # x
,
nDivHeight=5 # y
,
texts=None,
fortran=False,
usedHeight=0.8,
usedWidth=1.1)
for algname in self._discrList:
with BeamerSection(name=('%s Neural Network Output') %
(algname.replace('_', '\_'))):
paths2 = []
for etBinIdx in range(len(self._etBins) - 1):
for etaBinIdx in range(len(self._etaBins) - 1):
binningname = ('et%d_eta%d') % (etBinIdx,
etaBinIdx)
paths2.append(localpath + '/' + algname +
'_rnnOutput_' + binningname + '.pdf')
BeamerMultiFigureSlide(
title=algname.replace('_', '\_'),
paths=paths2,
nDivWidth=len(self._etaBins) # x
,
nDivHeight=len(self._etBins) # y
,
texts=None,
fortran=False,
usedHeight=1.0,
usedWidth=1.1)
return StatusCode.SUCCESS
def main():
from optparse import OptionParser
parser = OptionParser()
parser.add_option("-i", "--inputfile", dest="inputfile")
parser.add_option("-N", "--multiplicity", dest="N", type="int", default=3)
parser.add_option("-x", "--exclusive", action="store_true",\
dest="isExclusive", default=False)
parser.add_option("-l", "--label", dest="label", type="string", default="")
parser.add_option("-z",
"--zeyneplabel",
action="store_true",
dest="zeynep",
default=True)
(options, args) = parser.parse_args()
N = options.N
isExclusive = options.isExclusive
label_text = options.label
zeynep = options.zeynep
if isExclusive and not (N == 2 or N == 3):
parser.error("Exclusive plot only for N =2 or 3")
import configurations as config
from ROOT import TFile, TCanvas, THStack, TLegend, TPaveText, gStyle, TPad, TH1F, TGraphAsymmErrors, TMath
from ModelParser import ModelKey
gStyle.SetPadTopMargin(0.05)
gStyle.SetPadRightMargin(0.05)
gStyle.SetPadBottomMargin(0.20)
gStyle.SetErrorX(0.)
suffix = ""
if not isExclusive:
suffix = "up"
sm_files = []
for model in config.sm_models:
f = TFile("%s/%s.root" % (config.sm_dir, model), "READ")
sm_files.append(f)
bh_weights = []
bh_files = []
from BHXsec import BHXsec
xsec = BHXsec()
for model in config.bh_showcase:
f = TFile("%s/%s.root" % (config.bh_dir, model), "READ")
bh_files.append(f)
h = f.Get("plotsNoCut/ST")
nEvents = h.GetEntries()
bh_weights.append(
xsec.get(model) / nEvents * config.integrated_luminosity)
c = TCanvas("ST_Mul%d%s" % (N, suffix), "ST_Mul%d%s" % (N, suffix), 500,
600)
hs = THStack()
hs1 = THStack()
infile = TFile(options.inputfile, "READ")
hBkg = infile.Get("Background_N%d%s" % (N, suffix))
#hnewBkg = infile.Get("histoTemplateN3_0")
hnewBkg = infile.Get("ReferenceTemplateN3_0")
gBkg = infile.Get("BackgroundGraph_N%d%s" % (N, suffix))
hData = infile.Get("Data_N%d%s" % (N, suffix))
hBkg = infile.Get("Background_N%d%s" % (N, suffix))
hBkg.SetMarkerSize(0)
hBkg_ = hBkg.Clone("BkgLine")
hBkg.SetFillColor(33)
hBkg.SetLineColor(33)
hBkg_.SetLineWidth(3)
hBkg_.SetLineColor(862)
hs.Add(hBkg, "e3")
hnewBkg.SetLineWidth(3)
hnewBkg.Scale(10 * 3.407)
hs.Add(hnewBkg, "l")
legend = TLegend(0.2826613, 0.4819492, 0.6094355,
0.9416102) # - only for N >= 2 and 3
#legend = TLegend(0.3026613,0.5519492,0.6094355,0.9416102) # was 0.4919...zeynep
#legend = TLegend(0.3526613,0.5519492,0.6094355,0.9416102) # was 0.4919...
#legend.SetTextSize(0.041); #was 0.02966102
legend.SetTextSize(0.037)
legend.SetTextFont(42)
legend.SetFillColor(0)
legend.SetLineColor(0)
if isExclusive:
legend.SetHeader("Multiplicity N = %d" % N)
else:
legend.SetHeader("Multiplicity N #geq %d" % N)
legend.AddEntry(hData, "Data", "lep")
#legend.AddEntry(hnewBkg, "N=3 Fit Rescaled","l")
legend.AddEntry(hBkg_, "Background", "l")
legend.AddEntry(hBkg, "Uncertainty", "f")
legend_sm = TLegend(0.6471774, 0.7069492, 0.8508065, 0.8471186)
# legend_sm = TLegend(0.6271774,0.7369492,0.8308065,0.8771186)
# legend_sm.SetTextSize(0.037);
legend_sm.SetTextSize(0.037)
legend_sm.SetTextFont(42)
legend_sm.SetFillColor(0)
legend_sm.SetLineColor(0)
for i, f in enumerate(bh_files):
h = f.Get("plotsN%d%s/ST" % (N, suffix))
h.Rebin(config.rebin)
h.Scale(bh_weights[i])
# Add background
for ibin in range(h.GetNbinsX()):
h.SetBinContent(ibin+1,\
h.GetBinContent(ibin+1)\
+ hBkg.GetBinContent(ibin+1))
h.SetLineWidth(3)
#h.SetLineColor(i+2)
h.SetLineStyle(i + 2)
#if i == 0:
#h.SetLineColor(814)
if i == 0:
h.SetLineStyle(5)
h.SetLineColor(899)
if i == 1:
h.SetLineStyle(9)
h.SetLineColor(4)
if i == 2:
h.SetLineStyle(3)
h.SetLineColor(614)
hs.Add(h, "hist")
model = ModelKey(config.bh_showcase[i])
bh_legend = "M_{D} = %.1f TeV, M_{BH}^{ min} = %.1f TeV, n = %d" % (\
model.parameter["MD"],
model.parameter["M"],
model.parameter["n"])
if i == 3:
bh_legend = "M_{D} = 3.0 TeV, M_{QBH}^{ min} = 4.0 TeV, n = 4"
legend.AddEntry(h, bh_legend, "l")
# qbh_legend = "M_{D} = 4.0 TeV, M_{QBH}^{ min} = 5.0 TeV, n = 5"
# legend.AddEntry(h, qbh_legend, "l")
#if isExclusive:
zeynep = True
if zeynep:
for i, f in enumerate(sm_files):
h = f.Get("plotsN%d%s/ST" % (N, suffix))
h.Rebin(config.rebin)
h.Scale(config.integrated_luminosity)
h.SetFillColor(config.sm_colors[i])
h.SetLineColor(config.sm_colors[i])
hs1.Add(h, "hist")
legend_sm.AddEntry(h, config.sm_models[i], "f")
#hs.Add(hData, "e")
hs.Draw("nostack")
hs1.Draw("same")
c.SetLogy(1)
hs.GetXaxis().SetTitle("S_{T} (GeV)")
hs.GetYaxis().SetTitle(hData.GetYaxis().GetTitle())
hs.GetYaxis().SetTitleOffset(1.25)
hs.GetYaxis().SetTitleSize(0.04)
hs.GetYaxis().SetLabelSize(0.04)
hs.GetXaxis().SetTitleSize(0.01)
hs.GetXaxis().SetLabelSize(0.01)
ibin = 0
#if isExclusive:
# hs.GetXaxis().SetRangeUser(config.fit_range[0], config.maxST)
# ibin = hData.FindBin(config.fit_range[0])
#else:
# hs.GetXaxis().SetRangeUser(config.norm_range[0], config.maxST)
# ibin = hData.FindBin(config.norm_range[0])
if isExclusive:
hs.GetXaxis().SetRangeUser(1800, config.maxST)
ibin = hData.FindBin(1800)
else:
hs.GetXaxis().SetRangeUser(config.norm_range[0], config.maxST)
ibin = hData.FindBin(config.norm_range[0])
from Styles import formatUncertainty
formatUncertainty(gBkg)
gBkg.Draw("LX")
hData.Draw("sameex0")
hs.SetMinimum(5e-1)
if isExclusive:
hs.SetMaximum(1e7)
# hs.SetMaximum(hData.GetBinContent(ibin) * 40)
else:
#hs.SetMaximum(1e8)
hs.SetMaximum(hData.GetBinContent(ibin) *
20) # or 1e7 for N>=3 and use 4 models
legend.Draw("plain")
#if isExclusive:
if zeynep:
legend_sm.Draw("plain")
if isExclusive:
cmslabel = TPaveText(0.45, 0.96, 0.60, 0.99, "brNDC")
else:
cmslabel = TPaveText(0.45, 0.96, 0.60, 0.99, "brNDC")
cmslabel.AddText(config.cmsTitle)
#cmslabel.AddText(config.cmsSubtitle)
cmslabel.SetFillColor(0)
cmslabel.SetTextSize(0.041)
cmslabel.Draw("plain")
label = TPaveText(0.8891129, 0.8644068, 0.9435484, 0.9258475, "brNDC")
label.SetFillColor(0)
#label.SetTextSize(0.0529661);
label.SetTextSize(0.0529661)
label.AddText(label_text)
label.Draw("plain")
c.RedrawAxis()
#Divide
ibin = hData.FindBin(config.norm_range[0])
#print ibin
fbin = hData.FindBin(config.maxST)
#print fbin
hData.Sumw2()
hBkg_.Sumw2()
Pull = TH1F("", "", fbin - ibin + 1, (ibin - 1) * 100, fbin * 100)
Pull2 = TH1F("", "", fbin - ibin + 1, (ibin - 1) * 100, fbin * 100)
Ratio = hData.Clone()
Ratio.Add(hBkg_, -1)
#Ratio.Divide(hBkg_)
Band = TGraphAsymmErrors(fbin - ibin + 1)
for i in range(ibin - 1, fbin + 1):
i += 1
if hData.GetBinContent(i) != 0:
value = hData.GetBinContent(i) + (hBkg_.GetBinError(i) *
hBkg_.GetBinError(i))
#print Ratio.GetBinError(i), value**(0.5)
#print i-19,i,(i)*100, hData.GetBinContent(i) , hBkg_.GetBinContent(i),hData.GetBinContent(i) - hBkg_.GetBinContent(i)
Pull.SetBinContent(
i - 19, (hData.GetBinContent(i) - hBkg_.GetBinContent(i)) /
Ratio.GetBinError(i))
#print Ratio.GetBinError(i), abs(Ratio.GetBinContent(i))*0.05
#Pull.SetBinContent(i-19,(hData.GetBinContent(i) - hBkg_.GetBinContent(i))/ Ratio.GetBinError(i))
#Pull.SetBinContent(i-19,(hData.GetBinContent(i) / hBkg_.GetBinContent(i)))
Pull.SetBinError(i - 19, Ratio.GetBinError(i))
#Pull.SetBinError(i-19,hData.GetBinError(i)/gBkg.GetErrorY(i))
if (hBkg_.GetBinContent(i) * 0.05 > hBkg_.GetBinError(i)):
#print "bin error too small changing the error to: ", hBkg_.GetBinContent(i)*0.05
Pull2.SetBinContent(
i - 19,
(hnewBkg.GetBinContent(i) - hBkg_.GetBinContent(i)) /
(hBkg_.GetBinContent(i) * 0.05))
else:
Pull2.SetBinContent(
i - 19,
(hnewBkg.GetBinContent(i) - hBkg_.GetBinContent(i)) /
hBkg_.GetBinError(i))
#print hBkg_.GetBinError(i), hBkg_.GetBinContent(i)*0.05
#print i, " Pull2: ", Pull2.GetBinContent(i-19), "hnewBkg.GetBinContent(i-1): " , hnewBkg.GetBinContent(i-1), "hBkg_.GetBinContent(i): ", hBkg_.GetBinContent(i)
else:
Pull.SetBinContent(i - 19, 0)
Pull2.SetBinContent(
i - 19,
(hnewBkg.GetBinContent(i - 1) - hBkg_.GetBinContent(i)) /
hBkg_.GetBinError(i))
Band.SetPoint(i, hBkg_.GetBinCenter(i), 1.0)
#print hBkg_.GetBinContent(i), hBkg_.GetBinError(i)
up = abs(1. - ((hBkg_.GetBinContent(i) + hBkg_.GetBinError(i)) /
hBkg_.GetBinContent(i)))
down = abs(1. - ((hBkg_.GetBinContent(i) - hBkg_.GetBinError(i)) /
hBkg_.GetBinContent(i)))
Band.SetPointError(i, 0., 0., down, up)
#Band.Print()
pad = TPad("pad", "pad", 0.0, 0.0, 1.0, 1.0)
pad.SetTopMargin(0.799999)
pad.SetRightMargin(0.05)
pad.SetBottomMargin(0.09)
pad.SetFillColor(0)
#pad.SetGridy(1)
pad.SetFillStyle(0)
pad.Draw("same")
pad.cd(0)
Ratio.SetMarkerStyle(20)
Pull.SetMarkerStyle(20)
Pull.SetLineColor(1)
Pull.SetMarkerSize(0.9)
#Pull.SetMaximum(3)
#Pull.SetMinimum(-1)
Pull.SetMaximum(2.5)
Pull.SetMinimum(-2.5)
Pull.GetYaxis().SetNdivisions(5, 1)
Pull.GetXaxis().SetTitle('S_{T} (GeV)')
Pull.GetXaxis().SetLabelSize(0.04)
Pull.GetYaxis().SetTitleOffset(1.05)
Pull.GetYaxis().SetLabelSize(0.02)
Pull.GetYaxis().SetTitleSize(0.025)
Pull.GetYaxis().CenterTitle(1)
Pull.GetYaxis().SetTitle('#sigma(Data-Bkg)')
Pull.SetFillColor(2)
Pull.Draw("HIST")
Pull2.SetLineColor(862)
Pull2.SetLineWidth(3)
Pull2.SetLineStyle(2)
#Pull2.Draw("SAME")
formatUncertainty(Band)
Band.SetFillStyle(3001)
# Band.Draw("le3")
# Pull.Draw("ex0same")
pad.RedrawAxis()
gStyle.SetOptStat(0)
#block1 =TPaveText(0.370,0.84,0.351,0.86,"brNDC"); # for N>=2 and >=3 only
#block1 =TPaveText(0.361,0.85,0.377,0.87,"brNDC");
#block1 =TPaveText(0.333,0.88,0.354,0.85,"brNDC") #for n = 2 only
block1 = TPaveText(0.331, 0.82, 0.357, 0.85, "brNDC")
#FOR n=3 only
block1.SetFillColor(0)
block1.Draw("plain")
#block2 =TPaveText(0.305,0.84,0.333,0.86,"brNDC"); # for N>=2 and >=3 only
#block2 =TPaveText(0.395,0.85,0.41,0.87,"brNDC");
#block2 =TPaveText(0.296,0.88,0.316,0.85,"brNDC"); for n =2 only
block2 = TPaveText(0.295, 0.82, 0.317, 0.85, "brNDC")
#FOR n=3 only
block2.SetFillColor(0)
block2.Draw("plain")
if isExclusive:
c.Print("ST_Mul%d.pdf" % N)
c.Print("ST_Mul%d.png" % N)
else:
c.Print("ST_Mul%dup.pdf" % N)
c.Print("ST_Mul%dup.png" % N)
c.Update()
raw_input("Press Enter to continue...")
]
for i in range(len(h)):
read_hist(hist_name, h[i], indir, which_year, which_channel,
setting_for_h[i][1], which_region, barrel_or_endcap,
setting_for_h[i][0])
set_hist(h[i], setting_for_h[i][0], setting_for_h[i][1],
setting_for_h[i][2])
h[10].Add(h[12], -1)
h[11].Add(h[12], -1)
cv = TCanvas("cv_", "cv_", 900, 900)
fPads1 = TPad("pad1", "", 0.00, 0.225, 1.00, 1.00)
fPads2 = TPad("pad2", "", 0.00, 0.00, 1.00, 0.23)
fPads1.SetFillColor(0)
fPads1.SetLineColor(1)
fPads2.SetFillColor(0)
fPads2.SetLineColor(5)
fPads1.SetLineWidth(15)
fPads2.SetLineWidth(13)
fPads1.SetBottomMargin(0.02)
fPads1.SetTicks(1, 1)
fPads1.SetTicks(1, 1)
fPads2.SetTopMargin(0.02)
fPads2.SetBottomMargin(0.4)
fPads1.Draw()
fPads2.Draw()
#cv.SetLogy()
hs = THStack(" ", " ")
t.SetTextSize(0.026)
t.DrawText(3, 17, r'>>> x, y = 5, 7')
t.DrawText(3, 16, r'>>> import math; x*math.sqrt(y)')
t.DrawText(
3, 14,
r'>>> for i in range(2,7): print "sqrt(%d) = %f" % (i,math.sqrt(i))')
t.DrawText(3, 10,
r'>>> import ROOT; f1 = ROOT.TF1( "f1", "sin(x)/x", 0, 10 )')
t.DrawText(3, 9, r'>>> f1.Draw()')
t.SetTextFont(81)
t.SetTextSize(0.018)
t.DrawText(4, 15, '13.228756555322953')
t.DrawText(4, 13.3, 'sqrt(2) = 1.414214')
t.DrawText(4, 12.7, 'sqrt(3) = 1.732051')
t.DrawText(4, 12.1, 'sqrt(4) = 2.000000')
t.DrawText(4, 11.5, 'sqrt(5) = 2.236068')
t.DrawText(4, 10.9, 'sqrt(6) = 2.449490')
pad = TPad('pad', 'pad', .2, .05, .8, .35)
pad.SetFillColor(42)
pad.SetFrameFillColor(33)
pad.SetBorderSize(10)
pad.Draw()
pad.cd()
pad.SetGrid()
f1 = TF1('f1', 'sin(x)/x', 0, 10)
f1.Draw()
nut.cd()
nut.Update()
c.SetRightMargin(R / W)
c.SetTopMargin(T / H)
c.SetBottomMargin(B / H)
c.SetTickx(0)
c.SetTicky(0)
c.Draw()
c.cd()
pad1 = TPad("zxc_p1", "zxc_p1", 0, padRatio - padOverlap, 1, 1)
pad2 = TPad("qwe_p2", "qwe_p2", 0, 0, 1, padRatio + padOverlap)
pad1.SetLeftMargin(L / W)
pad1.SetRightMargin(R / W)
pad1.SetTopMargin(T / H / (1 - padRatio + padOverlap))
pad1.SetBottomMargin(
(padOverlap + padGap) / (1 - padRatio + padOverlap))
pad1.SetFillColor(0)
pad1.SetBorderMode(0)
pad1.SetFrameFillStyle(0)
pad1.SetFrameBorderMode(0)
pad1.SetTickx(0)
pad1.SetTicky(0)
pad2.SetLeftMargin(L / W)
pad2.SetRightMargin(R / W)
pad2.SetTopMargin((padOverlap) / (padRatio + padOverlap))
pad2.SetBottomMargin(B / H / (padRatio + padOverlap))
pad2.SetFillColor(0)
pad2.SetFillStyle(4000)
pad2.SetBorderMode(0)
pad2.SetFrameFillStyle(0)
pad2.SetFrameBorderMode(0)
def makeRatioPlot(hNum,
hDen,
hDen2="",
nameNum="num",
nameDen="den",
nameDen2="",
xtitle="pt",
ytitle="Entries",
ratiotitle="Ratio",
norm=False,
log=True,
plotName="ratio",
outDir='out',
ratioyrange=(0, 2)):
TH1.SetDefaultSumw2()
# prepare settings of histos
hNum.SetLineColor(kBlack)
hNum.SetLineWidth(2)
hNum.SetMarkerStyle(20)
#hNum.SetMarkerStyle(1)
hNum.SetMarkerColor(kBlack)
hNum.GetYaxis().SetTitle(ytitle)
hDen.SetLineColor(kOrange + 1)
hDen.SetMarkerColor(kOrange + 1)
hDen.SetLineWidth(2)
hDen.SetMarkerStyle(21)
#hDen.SetMarkerStyle(1)
if nameDen2 != "":
hDen2.SetLineColor(kBlue)
hDen2.SetMarkerColor(kBlue)
hDen2.SetLineWidth(2)
hDen2.SetMarkerStyle(22)
#hDen2.SetMarkerStyle(1)
makeHistSettings(hDen2) #
makeHistSettings(hNum)
makeHistSettings(hDen)
# prepare canva
canvas = TCanvas(plotName, plotName, 600, 600)
ROOT.SetOwnership(
canvas, False
) # Crucial to avoid crashes due to the way python deletes the objects
canvas.cd()
yMinP1 = 0.305
bottomMarginP1 = 0.005
pad1 = TPad('pad1', 'pad1', 0, yMinP1, 0.99, 1)
if log: pad1.SetLogy()
pad1.SetBottomMargin(bottomMarginP1)
pad1.SetFillColor(kWhite)
pad1.SetTickx()
pad1.SetTicky()
pad2 = TPad('pad2', 'pad2', 0., 0.01, .99, 0.300)
pad2.SetTopMargin(0.033)
pad2.SetBottomMargin(0.40)
pad2.SetFillColor(kWhite)
pad2.SetGridy()
pad1.SetNumber(1)
pad2.SetNumber(2)
pad1.Draw()
pad2.Draw()
# prepare legend
#leg = TLegend(0.75,0.68,0.82,0.88,'')
#leg.SetBorderSize(0)
#leg.SetTextSize(0.05)
leg = defaultLegend(x1=0.15, y1=0.7, x2=0.95, y2=0.95, mult=1.5)
# Draw
pad1.cd()
histo_saver = []
opt = 'histE'
#hNumNorm = hNum.Clone()
if norm:
hNumNorm = hNum.DrawNormalized('histE')
histo_saver.append(hNumNorm)
else:
hNum.Draw('histE')
# hNum.SetMaximum(hNum.GetMaximum()*4)
#leg.Draw('same')
ymax = max(hNum.GetMaximum(), hDen.GetMaximum())
if log == True:
hNum.SetMaximum(ymax * 30)
else:
hNum.SetMaximum(ymax * 1.7)
#hDenNorm = hDen.Clone()
if norm:
hDenNorm = hDen.DrawNormalized('samehistE')
histo_saver.append(hDenNorm)
else:
hDen.Draw('samehistE')
#hDenNorm2 = hDen2.Clone()
if nameDen2 != "":
if norm:
hDenNorm2 = hDen2.DrawNormalized('samehistE')
histo_saver.append(hDenNorm2)
else:
hDen2.Draw('samehistE')
leg.AddEntry(hDen2, nameDen2, 'LP')
leg.AddEntry(hDen, nameDen, 'LP')
leg.AddEntry(hNum, nameNum, 'LP')
leg.Draw('same')
#print hNumNorm.Integral(), hDenNorm.Integral(), hDenNorm2.Integral()
#print hNum.Integral(), hDen.Integral(), hDen2.Integral()
#######################################################
### RATIO PAD
#######################################################
pad2.cd()
hRatio = hNum.Clone()
if nameDen2 != "": hRatio2 = hNum.Clone()
if norm:
hRatio = hNumNorm.Clone()
hRatio2 = hNumNorm.Clone()
#print 'Ratio integral before division'
#print hRatio.Integral(), hRatio2.Integral()
hRatio.Divide(hDenNorm)
if nameDen2 != "": hRatio2.Divide(hDenNorm2)
#print 'Ratio integral after division'
#print hRatio.Integral(), hRatio2.Integral()
else:
hRatio.Divide(hDen)
if nameDen2 != "": hRatio2.Divide(hDen2)
#hRatio.SetLineColor(kRed+2)
if nameDen2 != "": hRatio2.SetLineColor(kBlue)
#print hRatio.Integral()
makeRatioSettings(hRatio)
if nameDen2 != "": makeRatioSettings(hRatio2)
hRatio.GetYaxis().SetRangeUser(ratioyrange[0], ratioyrange[1])
hRatio.GetXaxis().SetTitle(xtitle)
hRatio.GetYaxis().SetTitle(ratiotitle)
hRatio.SetTitle('')
hRatio.Draw('histE')
if nameDen2 != "": hRatio2.Draw('histEsame')
#hRatio.GetXaxis().SetRangeUser(200.,2000.)
canvas.SaveAs('{d}/{name}.pdf'.format(d=outDir, name=plotName))
canvas.SaveAs('{d}/{name}.png'.format(d=outDir, name=plotName))
