def lumiDependency(path, plotName, selection, runRange, cmsExtra, bins):
plot = getPlot(plotName)
plot.addRegion(selection)
plot.cleanCuts()
plot.cuts = plot.cuts % runRange.runCut
label = ""
if "Forward" in selection.name:
label = "forward"
elif "Central" in selection.name:
label = "central"
else:
label = "inclusive"
corr = getattr(rSFOF, label).val
corrUncert = getattr(rSFOF, label).err
runCuts = [[190645, 194643], [194644, 195868], [195915, 198955],
[198969, 200075], [200091, 201669], [201671, 202972],
[202973, 205344], [205515, 206512], [206513, 207491],
[207492, 208686]]
#~ runCuts = [[190645,194897]]
#~ xValues = [2,4,6,8,10,12,14,16,18,19.4]
if bins:
xValues = [0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5, 8.5, 9.5]
xValuesUncert = [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5]
else:
xValues = [1, 3, 5, 7, 9, 11, 13, 15, 17, 18.7]
xValuesUncert = [1, 1, 1, 1, 1, 1, 1, 1, 1, 0.7]
yValues = []
yValuesUncert = []
yValuesBTagged = []
yValuesUncertBTagged = []
yValuesBVeto = []
yValuesUncertBVeto = []
sfList = []
ofList = []
sfValuesUncert = []
ofValuesUncert = []
sfListBTagged = []
ofListBTagged = []
sfValuesUncertBTagged = []
ofValuesUncertBTagged = []
sfListBVeto = []
ofListBVeto = []
sfValuesUncertBVeto = []
ofValuesUncertBVeto = []
eeList = []
mmList = []
eeValuesUncert = []
mmValuesUncert = []
cuts = plot.cuts
for cutPair in runCuts:
if bins:
plot.cuts = plot.cuts + "*(runNr >= %d && runNr <= %d)" % (
cutPair[0], cutPair[1])
else:
plot.cuts = plot.cuts + "*(runNr >= %d && runNr <= %d)" % (
runCuts[0][0], cutPair[1])
eeHist, mmHist, emHist = getHistograms(path, plot, runRange, False, [],
label)
plot.cuts = cuts
if bins:
plot.cuts = plot.cuts + "*(runNr >= %d && runNr <= %d)" % (
cutPair[0], cutPair[1]) + "*(nBJets == 0)"
else:
plot.cuts = plot.cuts + "*(runNr >= %d && runNr <= %d)" % (
runCuts[0][0], cutPair[1]) + "*(nBJets == 0)"
eeHistBVeto, mmHistBVeto, emHistBVeto = getHistograms(
path, plot, runRange, False, [], label)
plot.cuts = cuts
if bins:
plot.cuts = plot.cuts + "*(runNr >= %d && runNr <= %d)" % (
cutPair[0], cutPair[1]) + "*(nBJets >= 1)"
else:
plot.cuts = plot.cuts + "*(runNr >= %d && runNr <= %d)" % (
runCuts[0][0], cutPair[1]) + "*(nBJets >= 1)"
eeHistBTagged, mmHistBTagged, emHistBTagged = getHistograms(
path, plot, runRange, False, [], label)
plot.cuts = cuts
ee = eeHist.Integral()
mm = mmHist.Integral()
sf = eeHist.Integral() + mmHist.Integral()
of = emHist.Integral() * corr
eeBTagged = eeHistBTagged.Integral()
mmBTagged = mmHistBTagged.Integral()
sfBTagged = eeHistBTagged.Integral() + mmHistBTagged.Integral()
ofBTagged = emHistBTagged.Integral()
eeBVeto = eeHistBVeto.Integral()
mmBVeto = mmHistBVeto.Integral()
sfBVeto = eeHistBVeto.Integral() + mmHistBVeto.Integral()
ofBVeto = emHistBVeto.Integral()
yValues.append(sf - of)
yValuesUncert.append(getUncert(sf, of, corrUncert))
sfList.append(sf)
ofList.append(of)
sfValuesUncert.append(sf**0.5)
ofValuesUncert.append((of + (of * corrUncert)**2)**0.5)
yValuesBTagged.append(sfBTagged - ofBTagged)
yValuesUncertBTagged.append(getUncert(sfBTagged, ofBTagged,
corrUncert))
sfListBTagged.append(sfBTagged)
ofListBTagged.append(ofBTagged)
sfValuesUncertBTagged.append(sfBTagged**0.5)
ofValuesUncertBTagged.append(ofBTagged**0.5)
yValuesBVeto.append(sfBVeto - ofBVeto)
yValuesUncertBVeto.append(getUncert(sfBVeto, ofBVeto, corrUncert))
sfListBVeto.append(sfBVeto)
ofListBVeto.append(ofBVeto)
sfValuesUncertBVeto.append(sfBVeto**0.5)
ofValuesUncertBVeto.append(ofBVeto**0.5)
eeList.append(ee)
mmList.append(mm)
eeValuesUncert.append(ee**0.5)
mmValuesUncert.append(mm**0.5)
hCanvas = TCanvas("hCanvas", "Distribution", 800, 800)
plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0, 1, 1)
style = setTDRStyle()
style.SetTitleYOffset(1.25)
plotPad.UseCurrentStyle()
plotPad.Draw()
plotPad.cd()
if bins:
legend = TLegend(0.45, 0.6, 0.9, 0.95)
else:
legend = TLegend(0.19, 0.5, 0.55, 0.85)
legend.SetFillStyle(0)
legend.SetBorderSize(0)
ROOT.gStyle.SetOptStat(0)
#~ if label == "forward":
#~ hCanvas.DrawFrame(0,-20,20,200,"; %s ; %s" %("integrated luminosity [fb^{-1}]","Events"))
#~
#~ else:
yMax = sfList[-1] + 150
yMin = min(min(yValues) - max(yValuesUncert) * 1.25, -10)
if bins:
hCanvas.DrawFrame(
0, yMin, 10, yMax,
"; %s ; %s" % ("bin number", "Events / approx. 2 fb^{-1}"))
else:
hCanvas.DrawFrame(
0, yMin, 20, yMax,
"; %s ; %s" % ("integrated luminosity [fb^{-1}]", "Events"))
zeroLine = ROOT.TLine(0, 0., 20, 0.)
zeroLine.SetLineWidth(1)
zeroLine.SetLineColor(ROOT.kBlue)
zeroLine.SetLineStyle(2)
zeroLine.Draw("same")
arg2 = numpy.array(xValues, "d")
arg4 = numpy.array(xValuesUncert, "d")
arg3 = numpy.array(yValues, "d")
arg5 = numpy.array(yValuesUncert, "d")
sfArray = numpy.array(sfList, "d")
ofArray = numpy.array(ofList, "d")
sfUncertArray = numpy.array(sfValuesUncert, "d")
ofUncertArray = numpy.array(ofValuesUncert, "d")
arg3BTagged = numpy.array(yValuesBTagged, "d")
arg5BTagged = numpy.array(yValuesUncertBTagged, "d")
sfArrayBTagged = numpy.array(sfListBTagged, "d")
ofArrayBTagged = numpy.array(ofListBTagged, "d")
sfUncertArrayBTagged = numpy.array(sfValuesUncertBTagged, "d")
ofUncertArrayBTagged = numpy.array(ofValuesUncertBTagged, "d")
arg3BVeto = numpy.array(yValuesBVeto, "d")
arg5BVeto = numpy.array(yValuesUncertBVeto, "d")
sfArrayBVeto = numpy.array(sfListBVeto, "d")
ofArrayBVeto = numpy.array(ofListBVeto, "d")
sfUncertArrayBVeto = numpy.array(sfValuesUncertBVeto, "d")
ofUncertArrayBVeto = numpy.array(ofValuesUncertBVeto, "d")
eeArray = numpy.array(eeList, "d")
mmArray = numpy.array(mmList, "d")
eeUncertArray = numpy.array(eeValuesUncert, "d")
mmUncertArray = numpy.array(mmValuesUncert, "d")
#~ graph1jet = ROOT.TGraphErrors(6,METvalues,Rinout1Jets,METErrors,ErrRinout1Jets)
graph = ROOT.TGraphErrors(10, arg2, arg3, arg4, arg5)
graphSF = ROOT.TGraphErrors(10, arg2, sfArray, arg4, sfUncertArray)
graphOF = ROOT.TGraphErrors(10, arg2, ofArray, arg4, ofUncertArray)
graphBTagged = ROOT.TGraphErrors(10, arg2, arg3BTagged, arg4, arg5BTagged)
graphSFBTagged = ROOT.TGraphErrors(10, arg2, sfArrayBTagged, arg4,
sfUncertArrayBTagged)
graphOFBTagged = ROOT.TGraphErrors(10, arg2, ofArrayBTagged, arg4,
ofUncertArrayBTagged)
graphBVeto = ROOT.TGraphErrors(10, arg2, arg3BVeto, arg4, arg5BVeto)
graphSFBVeto = ROOT.TGraphErrors(10, arg2, sfArrayBVeto, arg4,
sfUncertArrayBVeto)
graphOFBVeto = ROOT.TGraphErrors(10, arg2, ofArrayBVeto, arg4,
ofUncertArrayBVeto)
graphEE = ROOT.TGraphErrors(10, arg2, eeArray, arg4, eeUncertArray)
graphMM = ROOT.TGraphErrors(10, arg2, mmArray, arg4, mmUncertArray)
graph.Draw("Psame")
graphSF.Draw("Psame")
graphSF.SetLineColor(ROOT.kRed)
graphSF.SetMarkerColor(ROOT.kRed)
graphOF.Draw("Psame")
graphOF.SetLineColor(ROOT.kBlue)
graphOF.SetMarkerColor(ROOT.kBlue)
from ROOT import TH1F, kWhite
legendHistDing = TH1F()
legendHistDing.SetFillColor(kWhite)
if "Signal" in selection.name:
legend.AddEntry(legendHistDing, "Signal region %s" % label, "h")
else:
legend.AddEntry(legendHistDing, "Control region %s" % label, "h")
legend.AddEntry(graphSF, "Same Flavour", "p")
legend.AddEntry(graphOF, "Prediction from Opposite Flavour", "p")
legend.AddEntry(graph, "N_{SF}-N_{prediction}", "p")
legend.Draw("same")
latex = ROOT.TLatex()
latex.SetTextFont(42)
latex.SetTextAlign(31)
latex.SetTextSize(0.04)
latex.SetNDC(True)
latexCMS = ROOT.TLatex()
latexCMS.SetTextFont(61)
latexCMS.SetTextSize(0.06)
latexCMS.SetNDC(True)
latexCMSExtra = ROOT.TLatex()
latexCMSExtra.SetTextFont(52)
latexCMSExtra.SetTextSize(0.045)
latexCMSExtra.SetNDC(True)
latex.DrawLatex(0.95, 0.96, "%s fb^{-1} (8 TeV)" % runRange.printval)
latexCMS.DrawLatex(0.19, 0.89, "CMS")
if "Simulation" in cmsExtra:
yLabelPos = 0.82
else:
yLabelPos = 0.85
latexCMSExtra.DrawLatex(0.19, yLabelPos, "%s" % (cmsExtra))
if bins:
hCanvas.Print("fig/YieldvsLumi_Bins_%s" %
(plot.filename % runRange.label))
else:
hCanvas.Print("fig/YieldvsLumi_%s" % (plot.filename % runRange.label))
#~ if label == "forward":
#~ hCanvas.DrawFrame(0,-20,20,200,"; %s ; %s" %("integrated luminosity [fb^{-1}]","Events"))
#~
#~ else:
yMax = sfListBTagged[-1] + 150
yMin = min(min(yValuesBTagged) - max(yValuesUncertBTagged) * 1.25, -10)
if bins:
hCanvas.DrawFrame(
0, yMin, 10, yMax,
"; %s ; %s" % ("bin number", "Events / approx. 2 fb^{-1}"))
else:
hCanvas.DrawFrame(
0, yMin, 20, yMax,
"; %s ; %s" % ("integrated luminosity [fb^{-1}]", "Events"))
zeroLine.Draw("same")
legend.Clear()
graphBTagged.Draw("Psame")
graphSFBTagged.Draw("Psame")
graphSFBTagged.SetLineColor(ROOT.kRed)
graphSFBTagged.SetMarkerColor(ROOT.kRed)
graphOFBTagged.Draw("Psame")
graphOFBTagged.SetLineColor(ROOT.kBlue)
graphOFBTagged.SetMarkerColor(ROOT.kBlue)
from ROOT import TH1F, kWhite
legendHistDing = TH1F()
legendHistDing.SetFillColor(kWhite)
if "Signal" in selection.name:
legend.AddEntry(legendHistDing, "Signal region %s - b tagged" % label,
"h")
else:
legend.AddEntry(legendHistDing, "Control region %s - b tagged" % label,
"h")
legend.AddEntry(graphSFBTagged, "Same Flavour", "p")
legend.AddEntry(graphOFBTagged, "Prediction from Opposite Flavour", "p")
legend.AddEntry(graphBTagged, "N_{SF}-N_{prediction}", "p")
legend.Draw("same")
latex = ROOT.TLatex()
latex.SetTextFont(42)
latex.SetTextAlign(31)
latex.SetTextSize(0.04)
latex.SetNDC(True)
latexCMS = ROOT.TLatex()
latexCMS.SetTextFont(61)
latexCMS.SetTextSize(0.06)
latexCMS.SetNDC(True)
latexCMSExtra = ROOT.TLatex()
latexCMSExtra.SetTextFont(52)
latexCMSExtra.SetTextSize(0.045)
latexCMSExtra.SetNDC(True)
latex.DrawLatex(0.95, 0.96, "%s fb^{-1} (8 TeV)" % runRange.printval)
latexCMS.DrawLatex(0.19, 0.89, "CMS")
if "Simulation" in cmsExtra:
yLabelPos = 0.82
else:
yLabelPos = 0.85
latexCMSExtra.DrawLatex(0.19, yLabelPos, "%s" % (cmsExtra))
if bins:
hCanvas.Print("fig/YieldvsLumi_Bins_BTagged_%s" %
(plot.filename % runRange.label))
else:
hCanvas.Print("fig/YieldvsLumi_BTagged_%s" %
(plot.filename % runRange.label))
#~ if label == "forward":
#~ hCanvas.DrawFrame(0,-20,20,200,"; %s ; %s" %("integrated luminosity [fb^{-1}]","Events"))
#~
#~ else:
yMax = sfListBVeto[-1] + 150
yMin = min(min(yValuesBVeto) - max(yValuesUncertBVeto) * 1.25, -10)
if bins:
hCanvas.DrawFrame(
0, yMin, 10, yMax,
"; %s ; %s" % ("bin number", "Events / approx. 2 fb^{-1}"))
else:
hCanvas.DrawFrame(
0, yMin, 20, yMax,
"; %s ; %s" % ("integrated luminosity [fb^{-1}]", "Events"))
zeroLine.Draw("same")
legend.Clear()
graphBVeto.Draw("Psame")
graphSFBVeto.Draw("Psame")
graphSFBVeto.SetLineColor(ROOT.kRed)
graphSFBVeto.SetMarkerColor(ROOT.kRed)
graphOFBVeto.Draw("Psame")
graphOFBVeto.SetLineColor(ROOT.kBlue)
graphOFBVeto.SetMarkerColor(ROOT.kBlue)
from ROOT import TH1F, kWhite
legendHistDing = TH1F()
legendHistDing.SetFillColor(kWhite)
if "Signal" in selection.name:
legend.AddEntry(legendHistDing, "Signal region %s - b veto" % label,
"h")
else:
legend.AddEntry(legendHistDing, "Control region %s - b veto" % label,
"h")
legend.AddEntry(graphSFBVeto, "Same Flavour", "p")
legend.AddEntry(graphOFBVeto, "Prediction from Opposite Flavour", "p")
legend.AddEntry(graphBTagged, "N_{SF}-N_{prediction}", "p")
#~ legend.AddEntry(graph,"SF - OF","p")
legend.Draw("same")
latex = ROOT.TLatex()
latex.SetTextFont(42)
latex.SetTextAlign(31)
latex.SetTextSize(0.04)
latex.SetNDC(True)
latexCMS = ROOT.TLatex()
latexCMS.SetTextFont(61)
latexCMS.SetTextSize(0.06)
latexCMS.SetNDC(True)
latexCMSExtra = ROOT.TLatex()
latexCMSExtra.SetTextFont(52)
latexCMSExtra.SetTextSize(0.045)
latexCMSExtra.SetNDC(True)
latex.DrawLatex(0.95, 0.96, "%s fb^{-1} (8 TeV)" % runRange.printval)
latexCMS.DrawLatex(0.19, 0.89, "CMS")
if "Simulation" in cmsExtra:
yLabelPos = 0.82
else:
yLabelPos = 0.85
latexCMSExtra.DrawLatex(0.19, yLabelPos, "%s" % (cmsExtra))
if bins:
hCanvas.Print("fig/YieldvsLumi_Bins_BVeto_%s" %
(plot.filename % runRange.label))
else:
hCanvas.Print("fig/YieldvsLumi_BVeto_%s" %
(plot.filename % runRange.label))
def DrawBazil(diagonal=175, doData=False, pname='limits'):
import numpy as np
# 'mstop','mlsp','sm2','sm1','central','sp1','sp2', 'data'
d = GetDic(pname + '.p', diagonal)
x = np.array(d['mstop'])
e = np.array(d['exp'])
y1max = np.array(d['s+1'])
y2max = np.array(d['s+2'])
y1min = np.array(d['s-1'])
y2min = np.array(d['s-2'])
# observed
if (doData): o = np.array(d['obs'])
else: o = np.array(d['exp'])
c1 = TCanvas("c1", "CL", 10, 10, 800, 600)
#c1.SetGrid();
ymax = 7.5
ymin = 0.3
if (diagonal == 'down' or diagonal == 'Down' or diagonal == 'DOWN'):
ymax = 3.1
ymin = 0.30
elif (diagonal == 'up' or diagonal == 'Up' or diagonal == 'UP'):
ymax = 2.5
ymin = 0.15
#c1.DrawFrame(min(x)-2,min(d['sp2']+d['sm2'])-0.2,max(x)+2,max(d['sp2']+d['sm2'])+0.2);
c1.DrawFrame(min(x), ymin, max(x), ymax)
n = len(e)
gr1min = TGraph(n, x, y1min)
gr1max = TGraph(n, x, y1max)
gr2min = TGraph(n, x, y2min)
gr2max = TGraph(n, x, y2max)
gro = TGraph(n, x, o)
gre = TGraph(n, x, e)
gh = TGraph(n, x, np.linspace(0.999, 1, n))
gr1shade = TGraph(2 * n)
gr2shade = TGraph(2 * n)
#color1shade = 3; color2shade = 5;
color1shade = kOrange
color2shade = kGreen + 1
for i in range(n):
gr1shade.SetPoint(i, x[i], y1max[i] * scalefact)
gr1shade.SetPoint(n + i, x[n - i - 1], y1min[n - i - 1] * scalefact)
gr2shade.SetPoint(i, x[i], y2max[i] * scalefact)
gr2shade.SetPoint(n + i, x[n - i - 1], y2min[n - i - 1] * scalefact)
gre.SetPoint(i, x[i], e[i] * scalefact)
gh.SetPoint(i, x[i], np.linspace(0.999, 1, n)[i] * scalefact)
gro.SetPoint(i, x[i], o[i] * scalefact if doData else e[i] * scalefact)
gr2shade.SetFillColor(color2shade)
gr2shade.Draw("f")
gr1shade.SetFillColor(color1shade)
gr1shade.Draw("f")
gh.SetLineWidth(2)
gh.SetMarkerStyle(0)
gh.SetLineColor(46)
gh.SetLineStyle(2)
gh.Draw("LP")
gro.SetLineWidth(2)
gro.SetMarkerStyle(20)
gro.SetMarkerSize(0.7)
gro.SetLineColor(1)
if doData: gro.Draw("LP")
gre.SetLineWidth(2)
gre.SetMarkerStyle(0)
gre.SetLineColor(1)
gre.SetLineStyle(6)
gre.Draw("LP")
gre.SetTitle("Expected")
gro.SetTitle("Observed")
gr1shade.SetTitle("Expected 1#sigma")
gr2shade.SetTitle("Expected 2#sigma")
leg = TLegend(.1, .65, .4, .9)
leg.AddEntry(gro)
leg.AddEntry(gre)
leg.AddEntry(gr1shade, '', 'f')
leg.AddEntry(gr2shade, '', 'f')
leg.SetFillColor(0)
leg.Draw("same")
gre.SetFillColor(0)
gro.SetFillColor(0)
gr1shade.SetLineColor(color1shade)
gr2shade.SetLineColor(color2shade)
tit = "m_{#tilde{t}_{1}} - m_{#tilde{#chi}_{1}^{0}} = "
dm = "0"
ymax = 4.1
ymin = 0.3
if (diagonal == 'down' or diagonal == 'Down' or diagonal == 'DOWN'):
tit += "182.5 GeV" #" + 7.5 GeV"
dm = "m7p5"
ymax = 2.2
ymin = 0.15
elif (diagonal == 'up' or diagonal == 'Up' or diagonal == 'UP'):
tit += "167.5 GeV" #" - 7.5 GeV"
dm = "7p5"
ymax = 3.3
ymin = 0.30
else:
tit += "175 GeV"
Title = TLatex()
Title.SetTextSize(0.060)
Title.DrawLatexNDC(.42, .84, tit)
Xaxis = TLatex()
Xaxis.SetTextFont(42)
Xaxis.DrawLatexNDC(0.8, 0.03, "m_{#tilde{t}_{1}} (GeV)")
Yaxis = TLatex()
Yaxis.SetTextFont(42)
Yaxis.SetTextAngle(90)
Yaxis.DrawLatexNDC(0.05, 0.15, "95% CL limit on signal strength")
textCMS = TLatex()
textCMS.SetTextSize(0.06)
textCMS.SetTextSizePixels(22)
textCMS.SetTextAlign(12)
textCMS.DrawLatexNDC(.12, .93, "CMS")
textLumi = TLatex()
textLumi.SetTextFont(42)
textLumi.SetTextSize(0.06)
textLumi.SetTextSizePixels(22)
textLumi.DrawLatexNDC(.58, .91, "%1.1f fb^{-1} (13 TeV)" % (lumi)) #35.9
name = "brazil_%i" % diagonal
name = "brazil_%s" % pname
for form in ['pdf', 'png']:
c1.Print(outputdir + name + '.%s' % form)
def plotUpperLimits(labels, values):
# see CMS plot guidelines: https://ghm.web.cern.ch/ghm/plots/
N = len(labels)
yellow = TGraph(2 * N) # yellow band
green = TGraph(2 * N) # green band
median = TGraph(N) # median line
up2s = []
for i in range(N):
file_name = "../model/higgsCombine." + labels[
i] + ".AsymptoticLimits.mH120.root"
limit = getLimits(file_name)
up2s.append(limit[4])
yellow.SetPoint(i, values[i], limit[4]) # + 2 sigma
green.SetPoint(i, values[i], limit[3]) # + 1 sigma
median.SetPoint(i, values[i], limit[2]) # median
green.SetPoint(2 * N - 1 - i, values[i], limit[1]) # - 1 sigma
yellow.SetPoint(2 * N - 1 - i, values[i], limit[0]) # - 2 sigma
W = 800
H = 600
T = 0.08 * H
B = 0.12 * H
L = 0.12 * W
R = 0.04 * W
c = TCanvas("c", "c", 100, 100, W, H)
c.SetFillColor(0)
c.SetBorderMode(0)
c.SetFrameFillStyle(0)
c.SetFrameBorderMode(0)
c.SetLeftMargin(L / W)
c.SetRightMargin(R / W)
c.SetTopMargin(T / H)
c.SetBottomMargin(B / H)
c.SetTickx(0)
c.SetTicky(0)
c.SetGrid()
c.cd()
frame = c.DrawFrame(1.4, 0.001, 4.1, 10)
frame.GetYaxis().CenterTitle()
frame.GetYaxis().SetTitleSize(0.05)
frame.GetXaxis().SetTitleSize(0.05)
frame.GetXaxis().SetLabelSize(0.04)
frame.GetYaxis().SetLabelSize(0.04)
frame.GetYaxis().SetTitleOffset(0.9)
frame.GetXaxis().SetNdivisions(508)
frame.GetYaxis().CenterTitle(True)
frame.GetYaxis().SetTitle("95% upper limit on signal strength")
# frame.GetYaxis().SetTitle("95% upper limit on #sigma / #sigma_{SM}")
# frame.GetYaxis().SetTitle("95% upper limit on #sigma #times BR / (#sigma #times BR)_{SM}")
# frame.GetXaxis().SetTitle("background systematic uncertainty [%]")
frame.GetXaxis().SetTitle("c#tau [mm]")
frame.SetMinimum(0)
frame.SetMaximum(max(up2s) * 1.05)
frame.GetXaxis().SetLimits(min(values), max(values))
yellow.SetFillColor(ROOT.kOrange)
yellow.SetLineColor(ROOT.kOrange)
yellow.SetFillStyle(1001)
yellow.Draw('F')
green.SetFillColor(ROOT.kGreen + 1)
green.SetLineColor(ROOT.kGreen + 1)
green.SetFillStyle(1001)
green.Draw('Fsame')
median.SetLineColor(1)
median.SetLineWidth(2)
median.SetLineStyle(2)
median.Draw('Lsame')
#CMS_lumi.CMS_lumi(c,14,11)
ROOT.gPad.SetTicks(1, 1)
ROOT.gPad.SetLogx()
frame.Draw('sameaxis')
x1 = 0.15
x2 = x1 + 0.24
y2 = 0.76
y1 = 0.60
legend = TLegend(x1, y1, x2, y2)
legend.SetFillStyle(0)
legend.SetBorderSize(0)
legend.SetTextSize(0.041)
legend.SetTextFont(42)
legend.AddEntry(median, "Asymptotic CL_{s} expected", 'L')
legend.AddEntry(green, "#pm 1 std. deviation", 'f')
# legend.AddEntry(green, "Asymptotic CL_{s} #pm 1 std. deviation",'f')
legend.AddEntry(yellow, "#pm 2 std. deviation", 'f')
# legend.AddEntry(green, "Asymptotic CL_{s} #pm 2 std. deviation",'f')
legend.Draw()
print " "
c.SaveAs("UpperLimit.png")
c.Close()
def illustration(name):
if "Forward" in name:
label = "forward"
else:
if "Central" in name:
label = "central"
else:
label = "inclusive"
hCanvas = TCanvas("hCanvas", "Distribution", 800, 800)
plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0, 1, 1)
style = setTDRStyle()
plotPad.UseCurrentStyle()
plotPad.Draw()
plotPad.cd()
hCanvas.DrawFrame(0, 0, 3, 2, "; %s ; %s" % ("r_{#mu e}", "R_{SF/OF}"))
legend = TLegend(0.55, 0.18, 0.9, 0.525)
legend.SetFillStyle(0)
legend.SetBorderSize(0)
ROOT.gStyle.SetOptStat(0)
x = array("f", [
getattr(rMuE, label).val - getattr(rMuE, label).err,
getattr(rMuE, label).val + getattr(rMuE, label).err
])
y = array("f", [1., 1.])
ey = array("f", [1, 1])
ex = array("f", [0, 0])
ge = ROOT.TGraphErrors(2, x, y, ex, ey)
ge.SetFillColor(ROOT.kGreen + 3)
ge.SetLineColor(ROOT.kGreen + 3)
ge.SetFillStyle(3001)
ge.Draw("SAME 3")
x = array("f", [0, 3])
#~ y= array("f", [1.175, 1.175]) # 1.237
#~ y= array([rMuEs[region], rMuEs[region]],"f") # 1.237
y = array(
"f",
[getattr(rSFOFFact, label).SF.val,
getattr(rSFOFFact, label).SF.val])
ey = array(
"f",
[getattr(rSFOFFact, label).SF.err,
getattr(rSFOFFact, label).SF.err])
ex = array("f", [0.0, 0.0])
ge2 = ROOT.TGraphErrors(2, x, y, ex, ey)
ge2.SetFillColor(ROOT.kBlue - 3)
ge2.SetLineColor(ROOT.kBlue - 3)
ge2.SetFillStyle(3002)
ge2.Draw("SAME 3")
#~ print 0.5*((1+getattr(rMuE,label).val-1)+ 1./(1+getattr(rMuE,label).val-1))*getattr(rSFOFTrig,label).val
#~ print getattr(rSFOFFact,label).SF.val
#~ print 0.5*((getattr(rMuE,label).val-0.183218)+1./(getattr(rMuE,label).val-0.183218))*1.084055
#~ print "0.5*((x-%f)+1./(x-%f))*%f"%(getattr(rMuE,label).val-1,getattr(rMuE,label).val-1,getattr(rSFOFTrig,label).val)
#~ rSFOFLine = TF1("rSFOF%s"%label,"0.5*((x-%f)+1./(x-%f))*%f"%(getattr(rMuE,label).val-1,getattr(rMuE,label).val-1,getattr(rSFOFTrig,label).val),0.,3.)
rSFOFLine = TF1("rSFOF%s" % label,
"0.5*((x)+1./(x))*%f" % (getattr(rSFOFTrig, label).val),
0., 3.)
rSFOFLine.SetLineColor(ROOT.kRed)
rSFOFLine.SetLineWidth(2)
#~ rSFOFTrigUp = TF1("rSFOFUp%s"%label,"0.5*((x-%f)+1./(x-%f))*%f"%(getattr(rMuE,label).val-1,getattr(rMuE,label).val-1,getattr(rSFOFTrig,label).val+getattr(rSFOFTrig,label).err),0.,3.)
rSFOFTrigUp = TF1(
"rSFOFUp%s" % label, "0.5*((x)+1./(x))*%f" %
(getattr(rSFOFTrig, label).val + getattr(rSFOFTrig, label).err), 0.,
3.)
rSFOFTrigUp.SetLineColor(ROOT.kBlack)
rSFOFTrigUp.SetLineWidth(2)
rSFOFTrigUp.SetLineStyle(ROOT.kDashed)
#~ rSFOFTrigDown = TF1("rSFOFDown%s"%label,"0.5*((x-%f)+1./(x-%f))*%f"%(getattr(rMuE,label).val-1,getattr(rMuE,label).val-1,getattr(rSFOFTrig,label).val-getattr(rSFOFTrig,label).err),0.,3.)
rSFOFTrigDown = TF1(
"rSFOFDown%s" % label, "0.5*((x)+1./(x))*%f" %
(getattr(rSFOFTrig, label).val - getattr(rSFOFTrig, label).err), 0.,
3.)
rSFOFTrigDown.SetLineColor(ROOT.kBlack)
rSFOFTrigDown.SetLineWidth(2)
rSFOFTrigDown.SetLineStyle(ROOT.kDashed)
rmueline = ROOT.TF1("rmueline", "%s" % getattr(rSFOFFact, label).SF.val, 0,
3)
rmueline.SetLineColor(ROOT.kBlue)
rmueline.SetLineWidth(3)
rmueline.SetLineStyle(2)
rmueline.Draw("SAME")
line1 = ROOT.TLine(
getattr(rMuE, label).val, 0,
getattr(rMuE, label).val, 2)
line1.Draw("Same")
line1.SetLineWidth(2)
line1.SetLineColor(ROOT.kGreen + 3)
legendHistDing = ROOT.TH1F()
legendHistDing.SetFillColor(ROOT.kWhite)
legend.AddEntry(legendHistDing, "Factorization method:", "h")
legend.AddEntry(rSFOFLine, "R_{SF/OF} (r_{#mu e})", "l")
legend.AddEntry(rSFOFTrigDown,
"R_{SF/OF} (r_{#mu e}) #pm 1 #sigma on R_{T} ", "l")
legend.AddEntry(ge, "measured r_{#mu e} #pm 1 #sigma", "fl")
legend.AddEntry(ge2, "measured R_{SF/OF} #pm 1 #sigma", "fl")
legend.Draw("SAME")
rSFOFLine.Draw("SAME")
rSFOFTrigUp.Draw("SAME")
rSFOFTrigDown.Draw("SAME")
latex = ROOT.TLatex()
latex.SetTextSize(0.04)
latex.SetNDC(True)
latex.DrawLatex(0.15, 0.96, "%s dilepton selection" % label.title())
hCanvas.Print("fig/rMuEPropaganda_%s.pdf" % label)
def plotBlockComparison(treeBlockA,
treeBlockB,
variable,
additionalCut,
nBins,
firstBin,
lastBin,
labelX,
labelY,
suffix,
log=False,
signal=False):
hCanvas = TCanvas("hCanvas", "Distribution", 800, 800)
plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0.3, 1, 1)
ratioPad = ROOT.TPad("ratioPad", "ratioPad", 0, 0., 1, 0.3)
setTDRStyle()
plotPad.UseCurrentStyle()
ratioPad.UseCurrentStyle()
plotPad.Draw()
ratioPad.Draw()
plotPad.cd()
legend = TLegend(0.7, 0.55, 0.95, 0.95)
legend.SetFillStyle(0)
legend.SetBorderSize(1)
minMll = 20
ROOT.gStyle.SetOptStat(0)
Cutlabel = ROOT.TLatex()
Cutlabel.SetTextAlign(12)
Cutlabel.SetTextSize(0.03)
Labelin = ROOT.TLatex()
Labelin.SetTextAlign(12)
Labelin.SetTextSize(0.07)
Labelin.SetTextColor(ROOT.kRed + 2)
Labelout = ROOT.TLatex()
Labelout.SetTextAlign(12)
Labelout.SetTextSize(0.07)
Labelout.SetTextColor(ROOT.kBlack)
EMuhistBlockA = createHistoFromTree(treeBlockA, variable, additionalCut,
nBins, firstBin, lastBin, -1)
EMuhistBlockB = createHistoFromTree(treeBlockB, variable, additionalCut,
nBins, firstBin, lastBin, -1)
EMuhistBlockB.Scale(9.2 / 10.4)
print EMuhistBlockA.Integral()
print EMuhistBlockB.Integral()
EMuhistBlockA.SetMarkerStyle(21)
EMuhistBlockB.SetMarkerStyle(22)
EMuhistBlockA.SetMarkerColor(ROOT.kGreen + 3)
EMuhistBlockB.SetMarkerColor(ROOT.kBlack)
EMuhistBlockA.SetLineColor(ROOT.kGreen + 3)
EMuhistBlockB.SetLineColor(ROOT.kBlack)
if log:
yMin = 0.1
yMax = max(EMuhistBlockA.GetBinContent(EMuhistBlockA.GetMaximumBin()),
EMuhistBlockB.GetBinContent(
EMuhistBlockB.GetMaximumBin())) * 10
plotPad.SetLogy()
else:
yMin = 0
yMax = max(EMuhistBlockA.GetBinContent(EMuhistBlockA.GetMaximumBin()),
EMuhistBlockB.GetBinContent(
EMuhistBlockB.GetMaximumBin())) * 1.5
hCanvas.DrawFrame(firstBin, yMin, lastBin, yMax,
"; %s ; %s" % (labelX, labelY))
EMuhistBlockA.Draw("samep")
EMuhistBlockB.Draw("samep")
legend.AddEntry(EMuhistBlockA, "First 9.2 fb^{-1}", "p")
legend.AddEntry(EMuhistBlockB, "Second 10.4 fb^{-1} scaled", "p")
#~
latex = ROOT.TLatex()
latex.SetTextSize(0.043)
latex.SetTextFont(42)
latex.SetNDC(True)
latex.DrawLatex(
0.13, 0.95,
"CMS Preliminary, #sqrt{s} = 8 TeV, #scale[0.6]{#int}Ldt = 9.2-10.4 fb^{-1}"
)
#~
legend.Draw("same")
ratioPad.cd()
ratioGraphs = ratios.RatioGraph(EMuhistBlockA,
EMuhistBlockB,
firstBin,
lastBin,
title="Bl. A / Bl. B",
yMin=0.0,
yMax=2,
ndivisions=10,
color=ROOT.kGreen + 3,
adaptiveBinning=0.25)
ratioGraphs.draw(ROOT.gPad, True, False, True, chi2Pos=0.8)
if signal:
name = "OFUnblinding_SignalRegion_%s_%s.pdf"
else:
name = "OFUnblinding_Inclusive_%s_%s.pdf"
if variable == "p4.M()":
hCanvas.Print(name % (suffix, "Mll"))
else:
hCanvas.Print(name % (suffix, variable))
hCanvas.Clear()
iPt) * fDataOverFONLL['min'].GetParameter(0) * 1.e-6 - extrapCross
hCrossSecExtrap.SetBinContent(iPt, extrapCross)
hCrossSecExtrap.SetBinError(iPt, 0.)
gCrossSecExtrap.SetPoint(iPt - 1, ptCent, extrapCross)
gCrossSecExtrapSyst.SetPoint(iPt - 1, ptCent, extrapCross)
gCrossSecExtrap.SetPointError(iPt - 1, 0.4, 0.4, systLow, systHigh)
gCrossSecExtrapSyst.SetPointError(iPt - 1, 0.4, 0.4, systLow, systHigh)
legFit = TLegend(0.2, 0.7, 0.4, 0.9)
legFit.SetTextSize(0.045)
legFit.SetBorderSize(0)
legFit.SetFillStyle(0)
cFit = TCanvas('cFit', '', 500, 500)
hFrame = cFit.DrawFrame(ptMinMeas, 0., ptMaxMeas,
hDataOverFONLL['min'].GetMaximum() * 2,
';#it{p}_{T} (GeV/#it{c});data/FONLL')
hFrame.GetYaxis().SetDecimals()
for var in ['cent', 'min', 'max']:
hDataOverFONLL[var].Draw('same')
fDataOverFONLL[var].Draw('same')
legFit.AddEntry(hDataOverFONLL[var], f'{legNamesFONLL[var]}', 'p')
legFit.Draw()
leg = TLegend(0.3, 0.7, 0.7, 0.9)
leg.SetTextSize(0.045)
leg.SetBorderSize(0)
leg.SetFillStyle(0)
leg.AddEntry(hCrossSec, f'measured', 'p')
leg.AddEntry(hCrossSecExtrap, f'extrapolated', 'p')
leg.AddEntry(hFONLL['cent'], f'FONLL + PYTHIA8 decayer', 'f')
else:
effAcc = hEffAccFD.GetBinContent(iPt + 1)
frac = fFD
crossSec, crossSecUnc = ComputeCrossSection(rawYield, rawYieldUnc, effAcc,
1., ptMax - ptMin, 1., sigmaMB,
nEv, BR)
hCrossSection.SetBinContent(iPt + 1, crossSec)
hCrossSection.SetBinError(iPt + 1, crossSecUnc)
SetGlobalStyle()
cCrossSec = TCanvas('cCrossSec', '', 700, 800)
hCrossSection.Draw()
cFrac = TCanvas('cFrac', '', 800, 800)
cFrac.DrawFrame(hPromptFrac.GetBinLowEdge(1), 0., ptMax, 1.,
';#it{p}_{T} (GeV/#it{c}); fraction')
hPromptFrac.Draw('same')
hFDFrac.Draw('same')
cEff = TCanvas('cEff', '', 800, 800)
cEff.DrawFrame(hPromptFrac.GetBinLowEdge(1), 1.e-4, ptMax, 1.,
';#it{p}_{T} (GeV/#it{c}); (Acc#times#font[152]{e})')
hEffAccPrompt.Draw('same')
hEffAccFD.Draw('same')
outFile = TFile(args.outFileName)
hCrossSection.Write()
hRawYields.Write()
hEffAccPrompt.Write()
hEffAccFD.Write()
hPromptFrac.Write()
PtMin, 0., PtMax, hSignal[1].GetMaximum() * 2,
';#it{p}_{T} (GeV/#it{c}); raw yields / #it{N}_{events}')
for iFile, _ in enumerate(inputfilenames):
hSignal[iFile].Draw('same')
leg.Draw()
cSignal.cd(2).DrawFrame(
PtMin, 0., PtMax, hRatioSignal[1].GetMaximum() * 2,
';#it{p}_{T} (GeV/#it{c}); ratio of raw yields / #it{N}_{events}')
for iFile, _ in enumerate(inputfilenames):
if iFile == 0:
continue
hRatioSignal[iFile].Draw('same')
cRatioSignal = TCanvas('cRatioSignal', '', 800, 800)
cRatioSignal.DrawFrame(
PtMin, 0.5, PtMax, hRatioSignal[1].GetMaximum() * 2,
';#it{p}_{T} (GeV/#it{c}); ratio of raw yields / #it{N}_{events}')
for iFile, _ in enumerate(inputfilenames):
hRatioSignal[iFile].Draw('same')
leg.Draw()
cBkg = TCanvas('cBkg', '', 1000, 500)
cBkg.Divide(2, 1)
cBkg.cd(1).DrawFrame(
PtMin, hBackground[0].GetMinimum() * 0.5, PtMax,
hBackground[0].GetMaximum() * 2,
';#it{p}_{T} (GeV/#it{c}); background(3#sigma) / #it{N}_{events}')
cBkg.cd(1).SetLogy()
for iFile, _ in enumerate(inputfilenames):
hBackground[iFile].Draw('same')
leg.Draw()
def crossSectionValuePlot(group,groups,keys_no_comb,
sigmas,stats,systs,lumis,tots):
delChars = '#\\/+.~${}><,?[]|&^_!@%*()-`;:\'\"'
sigmas_lcl = array('d',sigmas[:])
stats_lcl = array('d',stats[:])
systs_lcl = array('d',systs[:])
tots_lcl = array('d',tots[:])
lumis_lcl = array('d',lumis[:])
if 'combined' in groups[group]:
sig, sta, sys, tot = getCSInfo(groups[group]['combined'])
sigmas_lcl.insert(0,sig)
stats_lcl.insert(0,sta)
systs_lcl.insert(0,sys)
tots_lcl.insert(0,tot)
lumis_lcl.insert(0,sig*lumi_err/100.0)
sigmas_lcl.insert(0,mc_info['sigma'])
stats_lcl.insert(0,mc_info['theory_err'])
systs_lcl.insert(0,mc_info['theory_err'])
tots_lcl.insert(0,mc_info['theory_err'])
lumis_lcl.insert(0,mc_info['theory_err'])
for i in range(1,len(sigmas_lcl)):
tots_lcl[i] = hypot(tots_lcl[i],lumis_lcl[i])
yvals = array('d',[i*2 for i in range(1,len(sigmas_lcl)+1)])
yerrs = array('d',[0 for i in range(len(sigmas_lcl))])
toterrs = array('d',stats_lcl[0:1] +tots_lcl[1:len(tots_lcl)])
gStats = TGraphErrors(len(sigmas_lcl),sigmas_lcl,yvals,stats_lcl,yerrs)
gTotes = TGraphErrors(len(sigmas_lcl),sigmas_lcl,yvals,toterrs,yerrs)
canv = TCanvas(group+'val','',500,500)
canv.cd()
frame = canv.DrawFrame(1,0,1.35*mc_info['sigma'],2*(len(sigmas_lcl)+1))
frame.GetXaxis().SetTitle("Cross Section (pb)")
unshitify(frame)
gTotes.SetMarkerColor(2)
gTotes.SetMarkerStyle(20)
gTotes.SetLineColor(4)
gTotes.SetLineWidth(2)
gTotes.Draw("PE1")
gStats.SetMarkerColor(2)
gStats.SetMarkerStyle(20)
gStats.SetLineColor(1)
gStats.SetLineWidth(2)
gStats.Draw("PE1")
tex1 = TLatex()
tex1.SetTextSize(0.04)
tex2 = TLatex()
tex2.SetTextSize(0.03)
xmin = 1
xmax = 1.30*mc_info['sigma']
xscale = xmax - xmin
xpad = xmin + (xmax-xmin)*xpadfactor
ymin = 0
ymax = 2*(len(sigmas_lcl)+1)
yscale = ymax-ymin
ypad = ymin + yscale*ypadfactor
for i in range(len(sigmas_lcl)):
if i == 0:
tex1.DrawLatex(xpad,yvals[i]-0.009*yscale,
"#font[132]{Theory Prediction}")
tex2.DrawLatex(xpad,yvals[i]-0.065*yscale,
"#font[132]{%.2f #pm %.2f pb}"%(sigmas_lcl[i],
stats_lcl[i]))
else:
if('combined' in groups[group]):
if( i == 1 ):
tex1.DrawLatex(xpad,yvals[i]-0.009*yscale,
"#font[132]{BLUE Combination}")
else:
tex1.DrawLatex(xpad,yvals[i]-0.009*yscale,
"#font[132]{%s: %s}"%(group,
keys_no_comb[i-2]))
else:
if 'combined' in group:
tex1.DrawLatex(xpad,yvals[i]-0.009*yscale,
"#font[132]{BLUE Comb.: %s}"%keys_no_comb[i-1])
else:
tex1.DrawLatex(xpad,yvals[i]-0.009*yscale,
"#font[132]{%s: %s}"%(group,
keys_no_comb[i-1]))
tex2.DrawLatex(xpad,yvals[i]-0.065*yscale,
"#font[132]{%.2f #pm "%sigmas_lcl[i]+
"%.2f (stat.) #pm "%stats_lcl[i]+
"%.2f (syst.) #pm "%systs_lcl[i]+
"%.2f (lumi.) pb}"%lumis_lcl[i])
#flavor text
tex1.DrawLatex(0.85*xpad,yvals[-1] + 0.95*ypad,
"#font[132]{%s}"%luminosity)
for i,flav in enumerate(flavor_text.split('\\')):
tex1.DrawLatex(3.7*xpad,
yvals[-1] + (1.20-0.50*i)*ypad,
"#font[132]{%s}"%flav)
tex1.DrawLatex(xmin,ymax+0.08,
"#font[132]{CMS Preliminary 2011}")
tex1.DrawLatex(xmin+0.78*xscale,
ymax+0.08,
"#font[132]{#sqrt{s} = 7 TeV}")
saneName = group.translate(None,delChars)
valName = saneName+"_CS_value_plot"
canv.Print(valName+".png")
canv.Print(valName+".eps")
canv.Print(valName+".pdf")
def main():
from sys import argv
from ROOT import TCanvas, TPad, TH1F, TH2F, TH1I, THStack, TLegend, TF1, TGraphErrors, TTree
from numpy import array
import numpy as n
from setTDRStyle import setTDRStyle
region = "SignalNonRectCombinedConstrained"
hCanvas = TCanvas("hCanvas", "Distribution", 800, 800)
plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0, 1, 1)
style = setTDRStyle()
plotPad.UseCurrentStyle()
plotPad.Draw()
plotPad.cd()
#~ result=([name,0., parameters,parametersError,parametersMass,parametersChi2,parametersLogLH0,parametersLogLH1, project, region, title, name])
bckgOnlyPkl = loadToysForBackgroundOnly(region)
bckgOnlyHist = TH1F("bckgOnlyHist", "bckgOnlyHist", 50, -1, 22)
nTest = 0
nTestLarger = 0
nominatorHist = ROOT.TH1F("nominatorHist", "nominatorHist", 1, 0, 1)
nominatorHistFull = ROOT.TH1F("nominatorHist", "nominatorHist", 1, 0, 1)
denominatorHist = ROOT.TH1F("denominatorHist", "denominatorHist", 1, 0, 1)
denominatorHistFull = ROOT.TH1F("denominatorHist", "denominatorHist", 1, 0,
1)
for index, value in bckgOnlyPkl[2].iteritems():
if not index == "38ed30c9":
if bckgOnlyPkl[4][index] > 0:
denominatorHistFull.Fill(0.5)
if -2 * (bckgOnlyPkl[7][index] -
bckgOnlyPkl[6][index]) >= 2 * 4.3808:
nominatorHistFull.Fill(0.5)
if bckgOnlyPkl[4][index] < 90 and bckgOnlyPkl[4][index] > 0:
bckgOnlyHist.Fill(
-2 * (bckgOnlyPkl[7][index] - bckgOnlyPkl[6][index]))
nTest = nTest + 1
denominatorHist.Fill(0.5)
if -2 * (bckgOnlyPkl[7][index] -
bckgOnlyPkl[6][index]) >= 2 * 4.3808:
nTestLarger = nTestLarger + 1
nominatorHist.Fill(0.5)
print nTest, nTestLarger
hCanvas.Clear()
plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0, 1, 1)
plotPad.UseCurrentStyle()
plotPad.Draw()
plotPad.cd()
hCanvas.DrawFrame(
-1, 0, 18,
bckgOnlyHist.GetBinContent(bckgOnlyHist.GetMaximumBin()) + 20,
"; %s ; %s" % ("-2*(log(L_{1})-log(L_{0}))", "N_{Results}"))
chi2Shape = ROOT.TF1("chi2Shape", "[2]*TMath::GammaDist(x,[0],[1],2)", 0,
18)
chi2Shape.SetParameters(1.5, 0, 200)
#~ chi2Shape.Draw("same")
#~ bckgOnlyHist.Fit("chi2Shape")
hCanvas.DrawFrame(
-1, 0, 22,
bckgOnlyHist.GetBinContent(bckgOnlyHist.GetMaximumBin()) + 20,
"; %s ; %s" % ("-2*(log(L_{1})-log(L_{0}))", "N_{Results}"))
latex = ROOT.TLatex()
latex.SetTextSize(0.04)
latex.SetNDC(True)
latex.DrawLatex(
0.15, 0.96,
"CMS Simulation #sqrt{s} = 8 TeV, #scale[0.6]{#int}Ldt = %s fb^{-1}"
% 19.4)
latex = ROOT.TLatex()
latex.SetTextSize(0.04)
latex.SetNDC(True)
#~ latex.DrawLatex(0.6, 0.6, "#splitline{fit of #chi^{2} dist., NDF = %.2f}{#chi^{2}/N_{dof} %.2f}"%(chi2Shape.GetParameter(0)*2,chi2Shape.GetChisquare()/chi2Shape.GetNDF()))
observedLine = ROOT.TLine(
2 * 4.3808, 0, 2 * 4.3808,
bckgOnlyHist.GetBinContent(bckgOnlyHist.GetMaximumBin()) + 20)
observedLine.SetLineColor(ROOT.kRed)
observedLine.SetLineStyle(2)
observedLine.Draw("same")
bckgOnlyHist.Draw("samepe")
#~ chi2Shape.Draw("same")
ROOT.gStyle.SetOptStat(0)
ROOT.gStyle.SetOptFit(0)
legend = ROOT.TLegend(0.5, 0.75, 0.95, 0.95)
legend.SetFillStyle(0)
legend.SetBorderSize(0)
legend.SetTextFont(42)
legend.AddEntry(observedLine, "observed", "l")
hist = ROOT.TH1F()
hist.SetLineColor(ROOT.kWhite)
#~ efficiencyObject = ROOT.TEfficiency(nominatorHist,denominatorHist)
#~ uncertaintyUp = efficiencyObject.Wilson(nTestLarger,nTest,0.69,ROOT.kTRUE)
#~ uncertaintyDown = efficiencyObject.Wilson(nTestLarger,nTest,0.69,ROOT.kFALSE)
#~ print uncertaintyUp
pValue = getEffciency(nominatorHist, denominatorHist)
pValueFull = getEffciency(nominatorHistFull, denominatorHistFull)
#~ legend.AddEntry(hist,"p-Value low mass: %.3f + %.3f - %.3f (%.2f #sigma)"%(pValue[0],pValue[1],pValue[2], ROOT.TMath.NormQuantile(1.0-pValue[0]/2)))
legend.AddEntry(
hist, "p-Value: %.3f + %.3f - %.3f (%.2f #sigma)" %
(pValueFull[0], pValueFull[1], pValueFull[2],
ROOT.TMath.NormQuantile(1.0 - pValue[0] / 2)))
legend.Draw("same")
hCanvas.Print("significanceStudy_BackgroundOnly.pdf")
hCanvas.Print("significanceStudy_BackgroundOnly.root")
print nTest, nTestLarger
hYieldPromptReco.SetBinContent(iPt + 1, nRecoPromptWeighted)
hYieldPromptReco.SetBinError(iPt + 1,
nRecoPromptWeighted / math.sqrt(nRecoPrompt))
hYieldFDReco.SetBinContent(iPt + 1, nRecoFDWeighted)
hYieldFDReco.SetBinError(iPt + 1, nRecoFDWeighted / math.sqrt(nRecoFD))
leg = TLegend(0.6, 0.2, 0.8, 0.4)
leg.SetTextSize(0.045)
leg.SetFillStyle(0)
leg.AddEntry(hEffPrompt, "Prompt", "p")
leg.AddEntry(hEffFD, "Feed-down", "p")
hEffPrompt.SetDirectory(0)
hEffFD.SetDirectory(0)
cEff = TCanvas('cEff', '', 800, 800)
cEff.DrawFrame(PtMin[0], 1.e-5, PtMax[nPtBins - 1], 1.,
';#it{p}_{T} (GeV/#it{c});(Acc #times #epsilon);')
cEff.SetLogy()
hEffPrompt.Draw('same')
hEffFD.Draw('same')
leg.Draw()
outFile = TFile(args.outFileName, 'recreate')
hEffPrompt.Write()
hEffFD.Write()
hYieldPromptGen.Write()
hYieldFDGen.Write()
hYieldPromptReco.Write()
hYieldFDReco.Write()
outFile.Close()
if not args.batch:
"higgsCombineExpectedMuNoSys.MultiDimFit.mH120.root"
],
'both': [
"higgsCombineExpectedBothFullUncertainty.MultiDimFit.mH120.root",
"higgsCombineExpectedBothNoTau.MultiDimFit.mH120.root",
"higgsCombineExpectedBothNoSys.MultiDimFit.mH120.root"
],
}
gROOT.SetBatch()
gStyle.SetOptStat(0)
c1 = TCanvas("c1", "Expected Bias Band Graph", 200, 10, 800, 800)
#c1.SetGrid();
c1.DrawFrame(0.85, 0.75, 1.15, 1.25)
c1.cd()
leg = TLegend(0.6, 0.7, 0.89, 0.89)
file_full_el_exp = TFile(
"higgsCombineExpectedElFullUncertainty.MultiDimFit.mH120.root")
file_full_mu_exp = TFile(
"higgsCombineExpectedMuFullUncertainty.MultiDimFit.mH120.root")
file_full_both_exp = TFile(
"higgsCombineExpectedBothFullUncertainty.MultiDimFit.mH120.root")
file_full_el_obs = TFile(
"higgsCombineElFullUncertainty.MultiDimFit.mH120.root")
file_full_mu_obs = TFile(
"higgsCombineMuFullUncertainty.MultiDimFit.mH120.root")
from ROOT import TTree, TFile, gROOT, gStyle, TCanvas, TGraph, TLegend
from array import array
f = TFile('mleak_chk.no_leak.root')
tr = f.Get('tr')
gROOT.SetStyle('Plain')
c = TCanvas('c', 'c', 640, 480)
c.SetTopMargin(0.05)
c.SetRightMargin(0.05)
gStyle.SetGridStyle(1)
gStyle.SetGridColor(16)
c.SetGrid()
h = c.DrawFrame(0, 0, 8000, 1200)
N = tr.GetEntries()
tr.Draw('committed_AS/1000:Entry$', '', 'goff')
g1 = TGraph(tr.GetSelectedRows(), tr.GetV2(), tr.GetV1())
g1.SetLineWidth(2)
g1.Draw('')
tr.Draw('memFree/1000:Entry$', '', 'goff')
g2 = TGraph(tr.GetSelectedRows(), tr.GetV2(), tr.GetV1())
g2.SetLineWidth(2)
g2.SetLineStyle(2)
g2.Draw('')
tr.Draw('swapFree/1000:Entry$', '', 'goff')
g3 = TGraph(tr.GetSelectedRows(), tr.GetV2(), tr.GetV1())
def main(): #pylint: disable=too-many-statements
SetGlobalStyle(padleftmargin=0.18, padbottommargin=0.14, titleoffsety=1.6, maxdigits=2, optstat=0)
inFileFONLL = TFile.Open('fonll/feeddown/DmesonLcPredictions_502TeV_y05_FFee_BRpythia8_SepContr_PDG2020.root')
hFONLLPromptD0 = inFileFONLL.Get('hD0Kpipred_max')
hFONLLPromptDplus = inFileFONLL.Get('hDpluskpipipred_max')
hFONLLPromptDs = inFileFONLL.Get('hDsPhipitoKkpipred_max')
hFONLLNonPromptD0 = inFileFONLL.Get('hD0KpifromBpred_central_corr')
hFONLLNonPromptDplus = inFileFONLL.Get('hDpluskpipifromBpred_central_corr')
hFONLLNonPromptDs = inFileFONLL.Get('hDsPhipitoKkpifromBpred_central_corr')
binLims = np.array([0., 1., 2., 3., 4., 5., 6., 7., 8., 10., 12., 16., 24.], 'd')
nBins = 12
hFONLLPromptD0 = hFONLLPromptD0.Rebin(nBins, 'hFONLLPromptD0', binLims)
hFONLLPromptDplus = hFONLLPromptDplus.Rebin(nBins, 'hFONLLPromptDplus', binLims)
hFONLLPromptDs = hFONLLPromptDs.Rebin(nBins, 'hFONLLPromptDs', binLims)
hFONLLNonPromptD0 = hFONLLNonPromptD0.Rebin(nBins, 'hFONLLNonPromptD0', binLims)
hFONLLNonPromptDplus = hFONLLNonPromptDplus.Rebin(nBins, 'hFONLLNonPromptDplus', binLims)
hFONLLNonPromptDs = hFONLLNonPromptDs.Rebin(nBins, 'hFONLLNonPromptDs', binLims)
hFONLLNPfracD0 = hFONLLPromptD0.Clone('hFONLLNPfracD0')
hFONLLNPfracD0.Divide(hFONLLNonPromptD0, hFONLLNPfracD0)
hFONLLNPfracDplus = hFONLLPromptDplus.Clone('hFONLLNPfracDplus')
hFONLLNPfracDplus.Divide(hFONLLNonPromptDplus, hFONLLNPfracDplus)
hFONLLNPfracDs = hFONLLPromptDs.Clone('hFONLLNPfracDs')
hFONLLNPfracDs.Divide(hFONLLNonPromptDs, hFONLLNPfracDs)
SetObjectStyle(hFONLLNPfracD0, color=kRed, linewitdh=2, markerstyle=0, fillstyle=0)
SetObjectStyle(hFONLLNPfracDplus, color=kGreen, linewitdh=2, markerstyle=0, fillstyle=0)
SetObjectStyle(hFONLLNPfracDs, color=kOrange, linewitdh=2, markerstyle=0, fillstyle=0)
mesonList = ['D0', 'D+', 'Ds']
histoList = [hFONLLNPfracD0, hFONLLNPfracDplus, hFONLLNPfracDs]
print(*binLims, sep=' ')
for meson, histo in zip(mesonList, histoList):
valueList = []
for iBin in range(1, nBins + 1):
valueList.append(f'{histo.GetBinContent(iBin):.3f}')
print(meson)
print(*valueList, sep=' ')
legMeson = TLegend(0.65, 0.6, 0.85, 0.8)
legMeson.SetTextSize(0.04)
legMeson.SetFillStyle(0)
legMeson.AddEntry(hFONLLNPfracD0, 'D^{0}', 'l')
legMeson.AddEntry(hFONLLNPfracDplus, 'D^{+}', 'l')
legMeson.AddEntry(hFONLLNPfracDs, 'D_{s}^{+}', 'l')
cFrac = TCanvas('cFrac', '', 500, 500)
hFrame = cFrac.DrawFrame(0., 0.01, 24., 1.05, ';#it{p}_{T} (GeV/#it{c}); #it{f}_{non-prompt}')
hFrame.GetYaxis().SetDecimals()
hFrame.Draw('axis same')
hFONLLNPfracD0.Draw('same')
hFONLLNPfracDplus.Draw('same')
hFONLLNPfracDs.Draw('same')
legMeson.Draw('same')
cFrac.Update()
TFile('./NaturalNonPromptFrac_FONLL_FFee_BRpythia8.root', 'recreate')
hFONLLNPfracD0.Write()
hFONLLNPfracDplus.Write()
hFONLLNPfracDs.Write()
cFrac.Write()
input('Press enter to exit')
updatemgrsvc.newEvent( gauditime )
#updatemgrsvc.update()
globalcenter = element.geometry().toGlobal( origin )
#print timeiter, ' ', \
# gauditime.format(True,"%D %T"), " --> ", \
# '(', globalcenter.x() , ",", globalcenter.y(), ",", globalcenter.z(), ")"
#print timeiter, gauditime.nanoformat(True), gauditime.year(False)
timeiter += timeinterval
xgraph.SetPoint( ipoint, timeiter - roottimeoffset, globalcenter.x() )
if abs( globalcenter.x() ) > xmax:
xmax = abs( globalcenter.x() )
ipoint +=1
canvas = TCanvas('c1')
frame = canvas.DrawFrame(timebegin- roottimeoffset,-1.1*xmax,timeend- roottimeoffset,1.1*xmax)
frame.SetTitle(element.name())
frame.GetXaxis().SetTimeDisplay(True)
period = timeend - timebegin
if period < 25*3600:
frame.GetXaxis().SetTimeFormat("%H:%M")
else:
frame.GetXaxis().SetTimeFormat("%d/%m")
xgraph.SetMarkerStyle(20)
xgraph.SetMarkerSize(0.5)
xgraph.Draw("P")
canvas.Print('globalposition.eps')
def crossSectionRatioPlot(group,groups,keys_no_comb,
sigmas,stats,systs,lumis,tots):
delChars = '#\\/+.~${}><,?[]|&^_!@%*()-`;:\'\"'
sigmas_lcl = array('d',sigmas[:])
stats_lcl = array('d',stats[:])
systs_lcl = array('d',systs[:])
tots_lcl = array('d',tots[:])
lumis_lcl = array('d',lumis[:])
tots_theory = array('d')
if 'combined' in groups[group]:
sig, sta, sys, tot = getCSInfo(groups[group]['combined'])
sigmas_lcl.insert(0,sig)
stats_lcl.insert(0,sta)
systs_lcl.insert(0,sys)
tots_lcl.insert(0,tot)
lumis_lcl.insert(0,sig*lumi_err/100.0)
for i in range(len(sigmas_lcl)):
tots_lcl[i] = tots_lcl[i]/sigmas_lcl[i]
sigmas_lcl[i] = sigmas_lcl[i]/mc_info['sigma']
tots_theory.append(hypot(tots_lcl[i],
mc_info['theory_err']/mc_info['sigma']))
yvals = array('d',[i*2 for i in range(1,len(sigmas_lcl)+1)])
xones = array('d',[1 for i in range(len(sigmas_lcl))])
x1serrs = array('d',[lumi_err/100.0 for i in range(len(sigmas_lcl))])
yerrs = array('d',[0 for i in range(len(sigmas_lcl))])
y1serrs = array('d',[2 for i in range(len(sigmas_lcl))])
gStats = TGraphErrors(len(sigmas_lcl),sigmas_lcl,yvals,tots_lcl,yerrs)
gTotes = TGraphErrors(len(sigmas_lcl),sigmas_lcl,yvals,tots_theory,yerrs)
gLine = TGraphErrors(len(sigmas_lcl),xones,yvals,x1serrs,y1serrs)
lOne = TLine(1,0,1,2*(len(sigmas_lcl)+1))
canv = TCanvas(group+'val','',500,500)
canv.cd()
frame = canv.DrawFrame(0.1,0,2,2*(len(sigmas_lcl)+1))
frame.GetXaxis().SetTitle("Ratio (CMS/Theory)")
unshitify(frame)
gLine.SetFillColor(6)
gLine.SetFillStyle(3004)
gLine.Draw("E2")
lOne.SetLineWidth(2)
lOne.SetLineColor(6)
lOne.Draw()
gTotes.SetMarkerColor(2)
gTotes.SetMarkerStyle(20)
gTotes.SetLineColor(4)
gTotes.SetLineWidth(2)
gTotes.Draw("PE1")
gStats.SetMarkerColor(2)
gStats.SetMarkerStyle(20)
gStats.SetLineColor(1)
gStats.SetLineWidth(2)
gStats.Draw("PE1")
tex1 = TLatex()
tex1.SetTextSize(0.04)
tex2 = TLatex()
tex2.SetTextSize(0.03)
xmin = 0.1
xmax = 2.0
xscale = xmax - xmin
xpad = xmin + xscale*xpadfactor
ymin = 0
ymax = 2*(len(sigmas_lcl)+1)
yscale = ymax-ymin
ypad = ymin + yscale*ypadfactor
for i in range(len(sigmas_lcl)):
if('combined' in groups[group]):
if( i == 0 ):
tex2.DrawLatex(0.75*xpad,yvals[i]-0.009*yscale,
"#font[132]{BLUE Combination}")
else:
tex2.DrawLatex(0.75*xpad,yvals[i]-0.009*yscale,
"#font[132]{%s: %s}"%(group,
keys_no_comb[i-1]))
else:
if 'combined' in group:
tex2.DrawLatex(0.75*xpad,yvals[i]-0.009*yscale,
"#font[132]{BLUE Comb.: %s}"%keys_no_comb[i])
else:
tex2.DrawLatex(0.75*xpad,yvals[i]-0.009*yscale,
"#font[132]{%s: %s}"%(group,
keys_no_comb[i]))
tex2.DrawLatex(4.60*xpad,yvals[i]-0.009*yscale,
"#font[132]{%.2f #pm "%sigmas_lcl[i]+
"%.2f_{exp} #pm "%tots_lcl[i]+
"%.2f_{theo}}"%(mc_info['theory_err']/mc_info['sigma']))
#flavor text
tex1.DrawLatex(0.85*xpad,yvals[-1] + 0.95*ypad,
"#font[132]{%s}"%luminosity)
for i,flav in enumerate(flavor_text.split('\\')):
tex1.DrawLatex(3.7*xpad,
yvals[-1] + (1.40-0.50*i)*ypad,
"#font[132]{%s}"%flav)
tex1.DrawLatex(xmin,ymax+0.08,
"#font[132]{CMS Preliminary 2011}")
tex1.DrawLatex(xmin+0.78*xscale,
ymax+0.08,
"#font[132]{#sqrt{s} = 7 TeV}")
#lumi uncertainty
tex1.SetTextColor(6)
tex1.DrawLatex(3.7*xpad,
yvals[0] - 1.5*ypad,
"#font[132]{lumi. uncertainty %.1f}"%lumi_err
+ "%")
saneName = group.translate(None,delChars)
valName = saneName+"_CS_ratio_plot"
canv.Print(valName+".png")
canv.Print(valName+".eps")
canv.Print(valName+".pdf")
SetObjectStyle(gRatioFDOverFONLL, color=kBlack, fillstyle=0)
lineFONLLFD = TLine(ptMinFD, 1., ptMaxFD, 1.)
lineFONLLFD.SetLineColor(kAzure + 4)
lineFONLLFD.SetLineWidth(2)
# protection for log scale
if sigmaMin <= 0:
sigmaMin = 1.e-3
if args.logx and ptMin <= 0:
print('WARNING: disabling log scale for x axis because minimum pT <= 0!')
args.logx = False
cCrossSec = TCanvas('cCrossSec', '', 700, 800)
hFrame = cCrossSec.DrawFrame(
ptMin, sigmaMin, ptMax, sigmaMax,
';#it{p}_{T} (GeV/#it{c});#frac{d#sigma}{d#it{p}_{T}} (#mub GeV^{-1} #it{c})'
)
hFrame.GetXaxis().SetMoreLogLabels()
cCrossSec.SetLogy()
if args.logx:
cCrossSec.SetLogx()
if args.logx:
legPrompt = TLegend(0.65, 0.75, 0.85, 0.9)
legFD = TLegend(0.25, 0.2, 0.45, 0.35)
else:
legPrompt = TLegend(0.6, 0.8, 0.8, 0.95)
legFD = TLegend(0.6, 0.62, 0.8, 0.77)
legPrompt.SetTextSize(0.045)
legPrompt.SetBorderSize(0)
legPrompt.SetFillStyle(0)
metavar='text',
default='FONLL.txt',
help='input FONLL txt file name')
args = parser.parse_args()
SetGlobalStyle(padleftmargin=0.16, padbottommargin=0.14)
dfModel = pd.read_csv(args.infileFONLL, sep=' ')
gFONLL = TGraphAsymmErrors(len(dfModel))
for iPt, (ptMin, ptMax, crossSec, crossSecMin, crossSecMax) in enumerate(zip(\
dfModel['ptmin'].values, dfModel['ptmax'].values, dfModel['central'].values, dfModel['min'].values, dfModel['max'].values)):
print((ptMin + ptMax) / 2, crossSec)
gFONLL.SetPoint(iPt, (ptMin + ptMax) / 2, crossSec / (ptMax - ptMin))
gFONLL.SetPointError(iPt, (ptMax - ptMin) / 2, (ptMax - ptMin) / 2,
(crossSec - crossSecMin) / (ptMax - ptMin),
(crossSecMax - crossSec) / (ptMax - ptMin))
SetObjectStyle(gFONLL, color=864, fillalpha=0.2, markerstyle=20)
cFONLL = TCanvas('cFONLL', '', 500, 500)
cFONLL.DrawFrame(
0., 1.e4, 24., 1.e8,
';d#it{p}_{T} (GeV/#it{c});(d^{2}#sigma/d#it{p}_{T}d#it{y}) (pb^{-1} GeV^{-1} #it{c})'
)
cFONLL.SetLogy()
gFONLL.Draw('2')
gFONLL.Draw('PX')
input()
def plotLimits(model, lambdas, helicity):
Mmin = [400 + i * 100 for i in range(29)]
if model == "CI": Mmin = [800 + i * 100 for i in range(25)]
N = len(Mmin)
yellow = TGraph(2*N) # yellow band
green = TGraph(2*N) # green band
median = TGraph(N) # median
for i in range(N):
limit = getCross(Mmin[i], model, lambdas, helicity)
print Mmin[i], limit[0], limit[1], limit[2], limit[3], limit[4]
yellow.SetPoint( i, Mmin[i], limit[4]) # + 2 sigma
green.SetPoint( i, Mmin[i], limit[3]) # + 1 sigma
median.SetPoint( i, Mmin[i], limit[2]) # median
green.SetPoint( 2*N-1-i, Mmin[i], limit[1]) # - 1 sigma
yellow.SetPoint( 2*N-1-i, Mmin[i], limit[0]) # - 2 sigma
W = 800
H = 600
T = 0.08*H
B = 0.12*H
L = 0.12*W
R = 0.04*W
c = TCanvas("c","c",100,100,W,H)
c.SetFillColor(0)
c.SetBorderMode(0)
c.SetFrameFillStyle(0)
c.SetFrameBorderMode(0)
c.SetLeftMargin( L/W )
c.SetRightMargin( R/W )
c.SetTopMargin( T/H )
c.SetBottomMargin( B/H )
c.SetTickx(0)
c.SetTicky(0)
c.SetGrid()
c.cd()
if model == "ADD":
frame = c.DrawFrame(Mmin[0], 2, Mmin[-1], 10)
else:
frame = c.DrawFrame(Mmin[0], 2, Mmin[-1], 50)
frame.GetYaxis().CenterTitle()
frame.GetYaxis().SetTitleSize(0.05)
frame.GetXaxis().SetTitleSize(0.05)
frame.GetXaxis().SetLabelSize(0.04)
frame.GetYaxis().SetLabelSize(0.04)
frame.GetYaxis().SetTitleOffset(0.9)
frame.GetXaxis().SetNdivisions(508)
frame.GetYaxis().CenterTitle(True)
frame.GetYaxis().SetTitle("95% limit of #Lambda_{T}")
if model == "CI": frame.GetYaxis().SetTitle("95% limit of #Lambda")
frame.GetXaxis().SetTitle("M_{#font[12]{l}#font[12]{l}}^{min} (GeV)")
#frame.SetMinimum(0)
#frame.SetMaximum(max(up2s)*1.05)
#frame.GetXaxis().SetLimits(min(values),max(values))
yellow.SetFillColor(ROOT.kOrange)
yellow.SetLineColor(ROOT.kOrange)
yellow.SetFillStyle(1001)
yellow.Draw('F')
green.SetFillColor(ROOT.kGreen+1)
green.SetLineColor(ROOT.kGreen+1)
green.SetFillStyle(1001)
green.Draw('Fsame')
median.SetLineColor(1)
median.SetLineWidth(2)
median.SetLineStyle(2)
median.Draw('Lsame')
CMS_lumi.CMS_lumi(c,13,11)
ROOT.gPad.SetTicks(1,1)
frame.Draw('sameaxis')
x1 = 0.42
x2 = x1 + 0.24
y2 = 0.86
y1 = 0.70
legend = TLegend(x1,y1,x2,y2)
legend.SetFillStyle(0)
legend.SetBorderSize(0)
legend.SetTextSize(0.041)
legend.SetTextFont(42)
legend.AddEntry(median, "Asymptotic CL_{s} expected of %s%s"%(model, helicity),'L')
legend.AddEntry(green, "#pm 1 std. deviation",'f')
legend.AddEntry(yellow,"#pm 2 std. deviation",'f')
legend.Draw()
c.SaveAs("%slimits/%sLimit_ee_LimitVsMmin%s.png"%(model, model, helicity))
c.Close()
def plotUpperLimits(labels, values):
# see CMS plot guidelines: https://ghm.web.cern.ch/ghm/plots/
N = len(labels)
yellow = TGraph(2 * N) # yellow band
green = TGraph(2 * N) # green band
median = TGraph(N) # median line
up2s = []
for i in range(N):
# file_name = "higgsCombine"+labels[i]+"AsymptoticLimits.mH125.root"
file_name = "higgsCombine.AsymptoticLimits.mH125." + labels[i] + ".root"
limit = getLimits(file_name)
# print'limit = ',limit
# print'values[i] = ',values[i]
up2s.append(limit[4])
yellow.SetPoint(i, values[i], limit[4]) # + 2 sigma
green.SetPoint(i, values[i], limit[3]) # + 1 sigma
median.SetPoint(i, values[i], limit[2]) # median
green.SetPoint(2 * N - 1 - i, values[i], limit[1]) # - 1 sigma
yellow.SetPoint(2 * N - 1 - i, values[i], limit[0]) # - 2 sigma
W = 800
H = 600
T = 0.08 * H
B = 0.12 * H
L = 0.12 * W
R = 0.04 * W
c = TCanvas("c", "c", 100, 100, W, H)
c.SetFillColor(0)
c.SetBorderMode(0)
c.SetFrameFillStyle(0)
c.SetFrameBorderMode(0)
c.SetLeftMargin(L / W)
c.SetRightMargin(R / W)
c.SetTopMargin(T / H)
c.SetBottomMargin(B / H)
c.SetTickx(0)
c.SetTicky(0)
c.SetGrid()
# c.SetLogy()
# gPad.SetLogy()
c.cd()
# ROOT.gPad.SetLogy()
# c.SetLogy()
frame = c.DrawFrame(1.4, 0.001, 4.1, 10)
frame.GetYaxis().CenterTitle()
frame.GetYaxis().SetTitleSize(0.05)
frame.GetXaxis().SetTitleSize(0.05)
frame.GetXaxis().SetLabelSize(0.04)
frame.GetYaxis().SetLabelSize(0.04)
frame.GetYaxis().SetTitleOffset(0.9)
frame.GetXaxis().SetNdivisions(508)
frame.GetYaxis().CenterTitle(True)
# frame.GetYaxis().SetTitle("95% upper limit on #sigma / #sigma_{SM}")
if (args.atlas_compare):
frame.GetYaxis().SetTitle(
"95% CL limits on #sigma(gg#rightarrow X)#times B(X#rightarrow HH) [pb]"
)
elif (args.CMS_compare):
frame.GetYaxis().SetTitle(
"95% CL limit on #sigma(gg#rightarrow X#rightarrow HH) (fb)")
# frame.GetYaxis().SetTitle("95% upper limit on #sigma #times BR / (#sigma #times BR)_{SM}")
# frame.GetXaxis().SetTitle("background systematic uncertainty [%]")
#if(args.SM_Radion): frame.GetXaxis.SetTitle("Standard Model")
#else: frame.GetXaxis().SetTitle("Radion Mass (GeV)")
# frame.SetMinimum(0)
# frame.SetMinimum(1) # need Minimum > 0 for log scale
frame.SetMinimum(1.000001) # need Minimum > 0 for log scale
# frame.SetMaximum(max(up2s)*1.05)
# frame.SetMaximum(max(up2s)*2)
# frame.SetMaximum(1000.)
if (args.atlas_compare):
frame.SetMaximum(7 * 1e2) # ATLAS
elif (args.CMS_compare):
frame.SetMaximum(8 * 1e4) # CMS HH
#frame.GetXaxis().SetLimits(min(values),max(values))
# frame.SetLogy()
frame.GetXaxis().SetLimits(min(values) - 10, max(values) + 10)
yellow.SetFillColor(ROOT.kOrange)
yellow.SetLineColor(ROOT.kOrange)
yellow.SetFillStyle(1001)
yellow.Draw('F')
green.SetFillColor(ROOT.kGreen + 1)
green.SetLineColor(ROOT.kGreen + 1)
green.SetFillStyle(1001)
green.Draw('Fsame')
median.SetLineColor(1)
median.SetLineWidth(2)
median.SetLineStyle(2)
median.Draw('Lsame')
CMS_lumi.CMS_lumi(c, 4, 11)
ROOT.gPad.SetTicks(1, 1)
frame.Draw('sameaxis')
# yboost = 0.075
yboost = -0.2
x1 = 0.15
x2 = x1 + 0.24
y2 = 0.76 + yboost
y1 = 0.60 + yboost
legend = TLegend(x1, y1, x2, y2)
legend.SetFillStyle(0)
legend.SetBorderSize(0)
legend.SetTextSize(0.041)
legend.SetTextFont(42)
legend.AddEntry(median, "AsymptoticLimits CL_{s} expected", 'L')
legend.AddEntry(green, "#pm 1 std. deviation", 'f')
# legend.AddEntry(green, "AsymptoticLimits CL_{s} #pm 1 std. deviation",'f')
legend.AddEntry(yellow, "#pm 2 std. deviation", 'f')
# legend.AddEntry("","STAT Only","")
# legend.AddEntry(green, "AsymptoticLimits CL_{s} #pm 2 std. deviation",'f')
legend.Draw()
label = TLatex()
label.SetNDC()
label.SetTextAngle(0)
label.SetTextColor(kBlack)
label.SetTextFont(42)
label.SetTextSize(0.045)
label.SetLineWidth(2)
label.DrawLatex(0.7, 0.7 + yboost, "STAT only")
print " "
# c.SaveAs("UpperLimit.png")
outFile = ''
if (args.CMS_compare):
outFile += "CMS_Compare_"
if (args.atlas_compare):
outFile += "atlas_Compare_"
if args.SM_Radion: outFile += "SM_"
c.SaveAs(outFile + "UpperLimit.pdf")
c.SaveAs(outFile + "UpperLimit.C")
c.Close()
legAbs = TLegend(0.18, 0.815, 0.45, 0.965)
legAbs.SetTextSize(0.045)
legAbs.SetBorderSize(1)
legAbs.SetFillColor(kWhite)
legAbs.SetHeader(f'#rho = {gAbsVar.GetCorrelationFactor():0.3f}')
if removeOutliersRel:
legAbs.AddEntry(gRelVar, 'considered', 'p')
legAbs.AddEntry(gRelVarOutliers, 'outliers', 'p')
if doRelVar:
cRelVar = TCanvas('cRelVar', '', 800, 800)
minVals = np.min(relVar, axis=0)
maxVals = np.max(relVar, axis=0)
hFrameRel = cRelVar.DrawFrame(
minVals[0] - 0.5 * abs(minVals[0]), minVals[1] - 0.5 * abs(minVals[1]),
maxVals[0] + 0.5 * abs(maxVals[0]), maxVals[1] + 0.5 * abs(maxVals[1]),
f";relative variation of {varName['var1']};relative variation of {varName['var2']}"
)
hFrameRel.GetYaxis().SetDecimals()
hFrameRel.GetYaxis().SetNdivisions(505)
hFrameRel.GetXaxis().SetNdivisions(505)
SetObjectStyle(gRelVar, color=kAzure + 4, markerstyle=kFullCircle)
gRelVar.Draw('P')
if removeOutliersRel:
SetObjectStyle(gRelVarOutliers,
color=kRed + 1,
markerstyle=kFullCircle)
gRelVarOutliers.Draw('P')
legRel.Draw()
cRelVar.SaveAs(f'{outFileName}_RelativeVariation.pdf')
if doAbsVar:
def limit_canvas(limits_, signal_, oname_):
m = [mp.mass for mp in limits_]
exp = [mp.exp for mp in limits_]
exp68up = [mp.exp68up for mp in limits_]
exp68dn = [mp.exp68dn for mp in limits_]
exp95up = [mp.exp95up for mp in limits_]
exp95dn = [mp.exp95dn for mp in limits_]
obs = [mp.obs for mp in limits_]
N = len(limits_)
gExp = TGraph()
g68 = TGraph(2*N)
g95 = TGraph(2*N)
gObs = TGraph()
gTH = get_theory_XsecBR_graph(signal_)
for a in range(0,N):
gExp.SetPoint(a,m[a],exp[a])
gObs.SetPoint(a,m[a],obs[a])
g68.SetPoint(a,m[a],exp68dn[a])
g95.SetPoint(a,m[a],exp95dn[a])
g68.SetPoint(N+a,m[N-a-1],exp68up[N-a-1])
g95.SetPoint(N+a,m[N-a-1],exp95up[N-a-1])
trans = 0
up = 0
if signal_ == 'n':
trans = 0.770776
up = 3
if signal_ == 'w':
trans = 0.836432
up = 10
if signal_ == 'r':
trans = 0.899902
up = 4
gExp.SetLineStyle(2)
gExp.SetLineWidth(4)
gExp.SetLineColor(TColor.GetColor('#112288'))
#gExp.Print()
g68.SetLineStyle(1)
g68.SetLineWidth(0)
g68.SetLineColor(kBlack)
g68.SetFillColor(TColor.GetColor('#4488dd'))
g95.SetLineStyle(1)
g95.SetLineWidth(0)
g95.SetLineColor(kBlack)
g95.SetFillColor(TColor.GetColor('#99bbff'))
gObs.SetLineStyle(1)
gObs.SetLineWidth(4)
gObs.SetLineColor(kBlack)
gObs.SetMarkerStyle(21)
gObs.SetMarkerSize(0.8)
gTH.SetLineStyle(7)
gTH.SetLineWidth(4)
gTH.SetMarkerSize(0)
gTH.SetMarkerColor(kRed+1)
gTH.SetLineColor(kRed+1)
leg = TLegend(0.58,0.633,0.969,0.908)
leg.SetFillColor(0)
leg.SetBorderSize(0)
leg.AddEntry(gExp,'Expected (95% CL)','l')
leg.AddEntry(gObs,'Observed (95% CL)','l')
leg.AddEntry(gTH,signal_dict[signal_][1],'l')
leg.AddEntry(g68,'#pm1#sigma Expected','f')
leg.AddEntry(g95,'#pm2#sigma Expected','f')
text_TL = TPaveText(0.18,0.830,0.44,0.900,'NDC')
text_TL.AddText(label_TL)
text_TL.SetFillColor(0)
text_TL.SetTextAlign(12)
text_TL.SetTextSize(0.06)
text_TL.SetTextFont(42)
text_TR = TPaveText(0.586,0.923,0.999,0.997,'NDC')
text_TR.AddText(label_TR)
text_TR.SetFillColor(0)
text_TR.SetTextAlign(32)
text_TR.SetTextSize(0.055)
text_TR.SetTextFont(42)
c = TCanvas('c','c',950,750)
c.SetTopMargin(0.08)
c.SetRightMargin(0.02)
c.SetBottomMargin(0.135)
c.SetLeftMargin(0.11)
#c.SetGrid()
c.SetLogy()
#hr = c.DrawFrame(0.401,0.001,3.999,1000)
#hr = c.DrawFrame(0.401,0.001,4.199,1000)
hr = c.DrawFrame(0.401,0.001,5.199,1000)
gExp.Sort()
gTH.Print()
g95.Draw('f')
g95.Print()
g68.Draw('f')
gTH.Draw('L')
gExp.Draw('L')
#Don't draw observed for blind analysis
# gObs.Sort()
# gObs.Draw('L')
hr.GetXaxis().SetTitle('M_{'+signal_dict[signal_][0]+'} [TeV]')
hr.GetYaxis().SetTitle('Upper limit on #sigma_{'+signal_dict[signal_][0]+'} #times B('+signal_dict[signal_][0]+' #rightarrow t#bar{t}) [pb]')
#hr.GetYaxis().SetTitle('\\mathrm{Upper~limit~on~}\\sigma_{'+signal_dict[signal_][0]+'}\\times\\mathscr{B}('+signal_dict[signal_][0]+' \\rightarrow t\\bar{t}) [pb]')
hr.GetXaxis().SetTitleSize(0.055)
hr.GetYaxis().SetTitleSize(0.055)
hr.GetXaxis().SetTitleFont(42)
hr.GetYaxis().SetTitleFont(42)
hr.GetXaxis().SetTitleOffset(1.00)
hr.GetYaxis().SetTitleOffset(0.98)
hr.GetXaxis().SetLabelSize(0.045)
hr.GetYaxis().SetLabelSize(0.045)
name = TString(oname_)
if name.Contains("com"):
tl = TLine(trans, 1e-3, trans, up)
tl.SetLineStyle(ROOT.kDashed)
tl.SetLineColor(kGray+1)
tl.SetLineWidth(3)
tl.Draw()
c.Update()
text_TL.Draw('same')
text_TR.Draw('same')
leg.Draw()
c.SaveAs(oname_+'.pdf')
c.Close()
setTDRStyle()
plotPad.UseCurrentStyle()
ratioPad.UseCurrentStyle()
plotPad.Draw()
ratioPad.Draw()
plotPad.cd()
legend = TLegend(0.7, 0.55, 0.95, 0.95)
legend.SetFillStyle(0)
legend.SetBorderSize(0)
yMin = 0
yMax = max(eeHist.GetBinContent(eeHist.GetMaximumBin()),
mmHist.GetBinContent(mmHist.GetMaximumBin())) * 1.5
hCanvas.DrawFrame(
0, yMin, 2.5, yMax,
"; %s ; %s" % ("|#eta^{leading}|", "N_{events} / 0.1 [a.u.]"))
ROOT.gStyle.SetOptStat(0)
eeHist.SetLineColor(ROOT.kRed)
eeHist.SetLineWidth(2)
eeHist.SetLineStyle(2)
#~ eeHist.SetLineColor(ROOT.kRed)
fakeHist = ROOT.TH1F()
fakeHist.SetLineColor(ROOT.kWhite)
legend.SetHeader("t#bar{t} Simulation")
legend.AddEntry(eeHist, "e^{#pm}e^{#mp}", "l")
legend.AddEntry(mmHist, "#mu^{#pm}#mu^{#mp}", "l")
eeHist.Draw("samehist")
mmHist.Draw("samehist")
def plotUpperLimits(labels, masses, **kwargs):
print color("plotUpperLimits()", color="magenta", prepend=">>>\n>>> ")
# https://raw.githubusercontent.com/nucleosynthesis/HiggsAnalysis-CombinedLimit/combine_tutorial_SWAN/combine_tutorials_2016/combine_intro/plotPvalue.py
# SIGNAL strength & mass
extralabel = kwargs.get('extralabel', "")
# LOOP over LABELS
for label in labels:
print color("plotUpperLimits - %s" % (label),
color="grey",
prepend="\n>>> ")
N = len(masses)
yellow = TGraph(2 * N) # yellow band
green = TGraph(2 * N) # green band
median = TGraph(N) # median line
up2s = []
down2s = []
for i, mass in enumerate(masses):
filename = getOutputFilename(label, mass, extralabel=extralabel)
limits = getLimits(filename)
yellow.SetPoint(i, mass, limits[4]) # + 2 sigma
green.SetPoint(i, mass, limits[3]) # + 1 sigma
median.SetPoint(i, mass, limits[2]) # median
green.SetPoint(2 * N - 1 - i, mass, limits[1]) # - 1 sigma
yellow.SetPoint(2 * N - 1 - i, mass, limits[0]) # - 2 sigma
down2s.append(limits[0])
up2s.append(limits[4])
ymax = max(up2s) * 1.20
ymin = min(down2s)
doLog = ymin and ymax / min(down2s) > 4
xtitle = "m_{X} [GeV]"
ytitle = "95% upper limit on #sigma#timesBR(X #rightarrow #tau#tau) [pb]"
if "bbA" in extralabel:
xtitle = "m_{A} [GeV]"
ytitle = "95% upper limit on #sigma#timesBR(A #rightarrow #tau#tau) [pb]"
W, H = 800, 600
T, B = 0.08 * H, 0.12 * H
L, R = 0.12 * W, 0.04 * W
canvas = TCanvas("canvas", "canvas", 100, 100, W, H)
canvas.SetFillColor(0)
canvas.SetBorderMode(0)
canvas.SetFrameFillStyle(0)
canvas.SetFrameBorderMode(0)
canvas.SetTopMargin(T / H)
canvas.SetBottomMargin(B / H)
canvas.SetLeftMargin(L / W)
canvas.SetRightMargin(R / W)
canvas.SetTickx(0)
canvas.SetTicky(0)
canvas.SetGrid()
canvas.cd()
if doLog:
ymin = 0.1 #10**(floor(log(ymin,10))-1)
ymax = 1000 #10**(ceil(log(ymax,10))+1)
#ymin, ymax = 0.1, 1000
canvas.SetLogy()
else:
ymin *= 0 if ymin > 0 else 1.20
frame = canvas.DrawFrame(min(masses), ymin, max(masses), ymax)
frame.GetYaxis().SetTitleSize(0.055)
frame.GetXaxis().SetTitleSize(0.055)
frame.GetXaxis().SetLabelSize(0.044)
frame.GetYaxis().SetLabelSize(0.044)
frame.GetXaxis().SetLabelOffset(0.010)
frame.GetXaxis().SetTitleOffset(1.04)
frame.GetYaxis().SetTitleOffset(1.08)
frame.GetXaxis().SetNdivisions(508)
frame.GetYaxis().CenterTitle(True)
frame.GetYaxis().SetTitle(ytitle)
frame.GetXaxis().SetTitle(xtitle)
yellow.SetFillColor(kOrange)
yellow.SetLineColor(kOrange)
yellow.SetFillStyle(1001)
yellow.Draw('F')
green.SetFillColor(kGreen + 1)
green.SetLineColor(kGreen + 1)
green.SetFillStyle(1001)
green.Draw('Fsame')
median.SetLineColor(1)
median.SetLineWidth(2)
median.SetLineStyle(2)
median.Draw('Lsame')
CMS_lumi.CMS_lumi(canvas, 13, 0)
gPad.SetTicks(1, 1)
gPad.Modified()
frame.Draw('sameaxis')
width = 0.28
height = 0.20
#x1 = 0.16; x2 = x1 + width # Left
x2 = 0.80
x1 = x2 - width # Right
x2 = x1 + width
y1 = 0.68
y2 = y1 + height
legend = TLegend(x1, y1, x2, y2)
legend.SetFillStyle(0)
legend.SetBorderSize(0)
legend.SetTextSize(0.040)
legend.SetTextFont(62)
legend.SetHeader("%s" % (label_dict[label + extralabel]))
legend.SetTextFont(42)
legend.AddEntry(median, "Asymptotic CL_{s} expected", 'L')
legend.AddEntry(green, "#pm 1 std. deviation", 'f')
#legend.AddEntry(green, "Asymptotic CL_{s} #pm 1 std. deviation",'f')
legend.AddEntry(yellow, "#pm 2 std. deviation", 'f')
#legend.AddEntry(green, "Asymptotic CL_{s} #pm 2 std. deviation",'f')
legend.Draw()
print " "
canvas.SaveAs("%s/upperLimit-%s%s.png" %
(PLOTS_DIR, label, extralabel))
canvas.SaveAs("%s/upperLimit-%s%s%s.pdf" %
(PLOTS_DIR, label, extralabel))
canvas.Close()
hRho00Charm.SetBinError(iPt + 1,
ciRho00VsNonPromptFrac[iPt].GetBinError(1))
hRho00Beauty.SetBinContent(iPt + 1,
ciRho00VsNonPromptFrac[iPt].GetBinContent(1000))
hRho00Beauty.SetBinError(iPt + 1,
ciRho00VsNonPromptFrac[iPt].GetBinError(1000))
cRho00VsPromptFrac.Modified()
cRho00VsPromptFrac.Update()
cRho00VsNonPromptFrac.Modified()
cRho00VsNonPromptFrac.Update()
cRho00vsPt = TCanvas('cRho00vsPt', '', 500, 500)
cRho00vsPt.DrawFrame(ptMins[0], 0., ptMaxs[-1], 0.6,
';#it{p}_{T} (GeV/#it{c});#it{#rho}_{00}')
lineNoPolVsPt.Draw('same')
hRho00Charm.DrawCopy('same')
hRho00Beauty.DrawCopy('same')
leg = TLegend(0.2, 0.2, 0.5, 0.35)
leg.SetTextSize(0.045)
leg.SetFillStyle(0)
leg.SetBorderSize(0)
leg.AddEntry(hRho00Charm, 'c #rightarrow D*^{+}', 'pl')
leg.AddEntry(hRho00Beauty, 'b #rightarrow D*^{+}', 'pl')
leg.Draw()
# output
outFileName = inputCfg['output']['file']
def plotPValues(labels, masses0, **kwargs):
print color("plotPValues()", color="magenta", prepend=">>>\n>>> ")
# SIGNAL strength & mass
bins = kwargs.get('bins', [])
ymin = 0.00005
# LOOP over LABELS
for label in labels:
print color("plotPValues - %s" % (label),
color="grey",
prepend="\n>>> ")
masses = array('d', [])
zeros = array('d', [])
limitObs = array('d', [])
limitExps = []
up2s = []
for i, mass in enumerate(masses0):
bin = -1
if bins: bin = bins[i]
filename = getOutputFilename(label,
mass,
method="ProfileLikelihood",
bin=bin,
extralabel=".SignifObs")
limitObs.append(getLimits(filename, brazilian=False))
masses.append(mass)
zeros.append(0.0)
v_masses = TVectorD(len(masses), masses)
v_zeros = TVectorD(len(zeros), zeros)
v_limitObs = TVectorD(len(limitObs), limitObs)
v_limitExps = []
for limitExp in limitExps:
v_limitExps.append(TVectorD(len(limitExp), limitExp))
W = 800
H = 600
T = 0.08 * H
B = 0.12 * H
L = 0.12 * W
R = 0.04 * W
canvas = TCanvas("canvas", "canvas", 100, 100, W, H)
canvas.SetFillColor(0)
canvas.SetBorderMode(0)
canvas.SetFrameFillStyle(0)
canvas.SetFrameBorderMode(0)
canvas.SetLeftMargin(L / W)
canvas.SetRightMargin(R / W)
canvas.SetTopMargin(T / H)
canvas.SetBottomMargin(B / H)
canvas.SetTickx(0)
canvas.SetTicky(0)
canvas.SetGrid()
canvas.SetLogy() # log
canvas.cd()
frame = canvas.DrawFrame(1.4, 0.001, 4.1, 10)
frame.GetYaxis().CenterTitle()
frame.GetYaxis().SetTitleSize(0.05)
frame.GetXaxis().SetTitleSize(0.05)
frame.GetXaxis().SetLabelSize(0.04)
frame.GetYaxis().SetLabelSize(0.04)
frame.GetYaxis().SetTitleOffset(1.14)
frame.GetXaxis().SetNdivisions(508)
frame.GetYaxis().CenterTitle(False)
frame.GetYaxis().SetTitle("local p-value")
#frame.GetYaxis().SetTitle("95% upper limit on #sigma / #sigma_{SM}")
frame.GetXaxis().SetTitle("X#rightarrow#tau#tau mass [GeV]")
frame.SetMinimum(ymin)
frame.SetMaximum(1.5)
frame.GetXaxis().SetLimits(min(masses), max(masses))
latex = TLatex()
latex.SetTextSize(0.4 * canvas.GetTopMargin())
latex.SetTextColor(2)
f1 = TF1("f1", "0.15866", min(masses), max(masses))
f1.SetLineColor(2)
f1.SetLineWidth(2)
f1.Draw("lsame")
latex.DrawLatex(min(masses) + 1, 0.15866 * 1.1, "1#sigma")
f2 = TF1("f2", "0.02275", min(masses), max(masses))
f2.SetLineColor(2)
f2.SetLineWidth(2)
f2.Draw("lsame")
latex.DrawLatex(min(masses) + 1, 0.02275 * 1.1, "2#sigma")
f3 = TF1("f3", "0.0013499", min(masses), max(masses))
f3.SetLineColor(2)
f3.SetLineWidth(2)
f3.Draw("lsame")
latex.DrawLatex(min(masses) + 1, 0.0013499 * 1.1, "3#sigma")
graph_limitExps = []
colors = [4, 2, 3, 6, 7, 8]
for i, v_limitExp in enumerate(v_limitExps):
graph_limitExps.append(
TGraphAsymmErrors(v_masses, v_limitExp, v_zeros, v_zeros,
v_zeros, v_zeros))
graph_limitExps[-1].SetLineColor(colors[i])
graph_limitExps[-1].SetLineWidth(2)
graph_limitExps[-1].SetLineStyle(2)
graph_limitExps[-1].Draw("Lsame")
graph_limitObs = TGraphAsymmErrors(v_masses, v_limitObs, v_zeros,
v_zeros, v_zeros, v_zeros)
graph_limitObs.SetLineColor(1)
graph_limitObs.SetLineWidth(2)
graph_limitObs.Draw("Csame")
CMS_lumi.CMS_lumi(canvas, 13, 0)
gPad.SetTicks(1, 1)
frame.Draw('sameaxis')
x1 = 0.62
x2 = x1 + 0.24
y1 = 0.15
y2 = y1 + 0.20
legend = TLegend(x1, y1, x2, y2)
legend.SetFillStyle(0)
legend.SetBorderSize(0)
legend.SetTextSize(0.041)
legend.SetTextFont(42)
legend.SetHeader("%s" % (label_dict[label]))
legend.AddEntry(graph_limitObs, "observed", 'L') #p-value
legend.Draw("same")
gPad.RedrawAxis()
print " "
canvas.SaveAs("%s/p-value-local-%s.png" % (PLOTS_DIR, label))
canvas.SaveAs("%s/p-value-local-%s.pdf" % (PLOTS_DIR, label))
canvas.Close()
gr_d30 = TGraph(3, energyArr, dummyDoubleArr)
iAngle = 40
dummyDoubleArr = array('d')
dummyDoubleArr.append(ratioDict[iAngle][0])
dummyDoubleArr.append(ratioDict[iAngle][1])
dummyDoubleArr.append(ratioDict[iAngle][2])
gr_d40 = TGraph(3, energyArr, dummyDoubleArr)
styleGraph(gr_d20, 1)
styleGraph(gr_d30, 2)
styleGraph(gr_d40, 3)
c1 = TCanvas('c1', 'A Simple Graph Example', 0, 0, 800, 600)
myFrame = c1.DrawFrame(0, 1, 110, 1.03)
myFrame.GetXaxis().SetLabelSize(0.03)
myFrame.GetXaxis().SetTitle("Energy [GeV]")
myFrame.GetYaxis().SetTitle("Correction")
gr_d20.Draw("P2 same")
gr_d30.Draw("P2 same")
gr_d40.Draw("P2 same")
leg = TLegend(0.35, 0.14, 0.64, 0.36)
leg.SetBorderSize(0)
leg.SetTextSize(0.03)
leg.AddEntry(gr_d20, "20 degree", "p")
leg.AddEntry(gr_d30, "30 degree", "p")
leg.AddEntry(gr_d40, "40 degree", "p")
';#it{p}_{T} (GeV/#it{c});mean (GeV/#it{c}^{2})')
hFrameMean.GetYaxis().SetNdivisions(505)
hFrameMean.GetYaxis().SetDecimals()
hMeanMC.DrawCopy('same')
hMeanData.DrawCopy('same')
legPars.Draw()
cMeanSigma.cd(2).DrawFrame(ptLims[0], 0, ptLims[-1], 0.015,
';#it{p}_{T} (GeV/#it{c});FWHM (GeV/#it{c}^{2})')
hFWHMMC.DrawCopy('same')
hFWHMData.DrawCopy('same')
legPars.Draw()
cMeanSigma.Modified()
cMeanSigma.Update()
cEfficiency = TCanvas('cEfficiency', '', 800, 800)
hFrameEff = cEfficiency.DrawFrame(ptLims[0], 0., ptLims[-1], 1.,
';#it{p}_{T} (GeV/#it{c});efficiency')
hFrameEff.GetYaxis().SetDecimals()
for cut in hEffMC:
hEffMC[cut].DrawCopy('epsame')
hEffData[cut].DrawCopy('epsame')
legEff.Draw()
cEfficiency.Modified()
cEfficiency.Update()
cPtInt = TCanvas('cPtInt', '', 800, 800)
cPtInt.Divide(2, 2)
cPtInt.cd(1)
hMassKKSigRegionMC[-1].DrawCopy('E')
hSideBandsMC[-1].DrawCopy('hist same')
fMassKKwoPhiMC[-1].Draw('same')
legMassKK.Draw()
def plotUpperLimits(sample_limits):
# adapted from: https://wiki.physik.uzh.ch/cms/limits:brazilianplotexample
# see CMS plot guidelines: https://ghm.web.cern.ch/ghm/plots/
labels = list(sample_limits.keys())
print(labels)
values = [float(label.replace('p','.')) for label in labels]
N = len(labels)
yellow = TGraph(2*N) # yellow band
green = TGraph(2*N) # green band
median = TGraph(N) # median line
up2s = [ ]
for i in range(N):
#file_name = "higgsCombine"+labels[i]+"Asymptotic.mH125.root"
#limit = getLimits(file_name)
limit = sample_limits[labels[i]]
up2s.append(limit['up2'])
yellow.SetPoint( i, values[i], limit['up2'] ) # + 2 sigma
green.SetPoint( i, values[i], limit['up1'] ) # + 1 sigma
median.SetPoint( i, values[i], limit['nom'] ) # median
green.SetPoint( 2*N-1-i, values[i], limit['dn1'] ) # - 1 sigma
yellow.SetPoint( 2*N-1-i, values[i], limit['dn2'] ) # - 2 sigma
W = 800
H = 600
T = 0.08*H
B = 0.12*H
L = 0.12*W
R = 0.04*W
c = TCanvas("c","c",100,100,W,H)
c.SetFillColor(0)
c.SetBorderMode(0)
c.SetFrameFillStyle(0)
c.SetFrameBorderMode(0)
c.SetLeftMargin( L/W )
c.SetRightMargin( R/W )
c.SetTopMargin( T/H )
c.SetBottomMargin( B/H )
c.SetTickx(0)
c.SetTicky(0)
c.SetGrid()
c.cd()
frame = c.DrawFrame(1.4,0.001, 4.1, 10)
frame.GetYaxis().CenterTitle()
frame.GetYaxis().SetTitleSize(0.05)
frame.GetXaxis().SetTitleSize(0.05)
frame.GetXaxis().SetLabelSize(0.04)
frame.GetYaxis().SetLabelSize(0.04)
frame.GetYaxis().SetTitleOffset(1.1)
frame.GetYaxis().SetMaxDigits(3)
#frame.GetXaxis().SetNdivisions(508)
frame.GetYaxis().CenterTitle(True)
#frame.GetYaxis().SetTitle("95% upper limit on #sigma / #sigma_{SM}")
#frame.GetYaxis().SetTitle("95% upper limit on #sigma #times BR / (#sigma #times BR)_{SM}")
frame.GetYaxis().SetTitle("95% upper limit on #sigma_{h} #times BR / #sigma_{h}")
#frame.GetXaxis().SetTitle("background systematic uncertainty [%]")
frame.GetXaxis().SetTitle("m_{a} [GeV]")
frame.SetMinimum(0)
#frame.SetMaximum(max(up2s)*1.05)
frame.SetMaximum(max(up2s)*1.4)
#frame.SetMinimum(1.e-4)
#frame.SetMaximum(1.e-2)
#ROOT.gPad.SetLogy()
#frame.GetXaxis().SetLimits(min(values),max(values))
frame.GetXaxis().SetLimits(0., 1.2) # GeV
yellow.SetFillColor(ROOT.kOrange)
yellow.SetLineColor(ROOT.kOrange)
yellow.SetFillStyle(1001)
yellow.Draw('F')
green.SetFillColor(ROOT.kGreen+1)
green.SetLineColor(ROOT.kGreen+1)
green.SetFillStyle(1001)
green.Draw('Fsame')
median.SetLineColor(1)
median.SetLineWidth(2)
median.SetLineStyle(2)
median.Draw('Lsame')
#CMS_lumi.CMS_lumi(c,14,11)
#ROOT.gPad.SetTicks(1,1)
#frame.Draw('sameaxis')
x1 = 0.15
x2 = x1 + 0.24
y2 = 0.86
y1 = 0.70
legend = TLegend(x1,y1,x2,y2)
legend.SetFillStyle(0)
legend.SetBorderSize(0)
legend.SetTextSize(0.041)
legend.SetTextFont(42)
legend.AddEntry(median, "Asymptotic CL_{s} expected",'L')
legend.AddEntry(green, "#pm 1 std. deviation",'f')
#legend.AddEntry(green, "Asymptotic CL_{s} #pm 1 std. deviation",'f')
legend.AddEntry(yellow,"#pm 2 std. deviation",'f')
#legend.AddEntry(green, "Asymptotic CL_{s} #pm 2 std. deviation",'f')
legend.Draw()
print " "
c.Draw()
c.Update()
c.Print("Plots/UpperLimits%s.eps"%(''))
setTDRStyle()
plotPad.UseCurrentStyle()
#~ ratioPad.UseCurrentStyle()
plotPad.Draw()
#~ ratioPad.Draw()
#~ plotPad.cd()
legend = TLegend(0.7, 0.75, 0.95, 0.95)
legend.SetFillStyle(0)
legend.SetBorderSize(0)
yMin=0
yMax = max(eeHist.GetBinContent(eeHist.GetMaximumBin()),eeHist.GetBinContent(mmHist.GetMaximumBin()))*1.5
hCanvas.DrawFrame(0,yMin,30,yMax,"; %s ; %s" %("m(ll) [GeV]","N_{events} / 0.5 GeV"))
ROOT.gStyle.SetOptStat(0)
#~ eeHist.SetLineColor(ROOT.kRed)
#~ eeHist.SetLineColor(ROOT.kRed)
fakeHist = ROOT.TH1F()
fakeHist.SetLineColor(ROOT.kWhite)
legend.SetHeader("Data")
legend.AddEntry(eeHist,"e^{#pm}e^{#mp} + #mu^{#pm}#mu^{#mp}","p")
#~ legend.AddEntry(mmHist,"e^{#pm}#mu^{#mp}","l")
eeHist.Draw("same")
#~ emHist.Draw("samehist")
legend.Draw("same")
line1 = ROOT.TLine(20,0,20,yMax)