if [masspoint,i,j] in codes:
contour.SetLineWidth(703)
contour.SetFillStyle(3005)
contour.SetFillColor(2)
#contour.Draw('c')
tutti.append(contour.Clone())
if masspoint in [3,4]:
xcont=array('d',[0,1])
ycont=array('d',[1,0])
allcont=TGraph(2,ycont,xcont)
allcont.SetLineWidth(706)
allcont.SetFillStyle(3005)
allcont.SetFillColor(2)
allcont.SetLineColor(2)
#allcont.Draw('c')
tutti.append(allcont.Clone())
if masspoint in [2]:
xcont=array('d',[0])
ycont=array('d',[0])
allcont=TGraph(1,ycont,xcont)
allcont.SetLineWidth(706)
allcont.SetFillStyle(3005)
allcont.SetFillColor(2)
allcont.SetLineColor(2)
#allcont.Draw('c')
tutti.append(allcont.Clone())
#print conts
#print conts.GetSize()
def plotUpperLimits(model, lambdas, helicity):
N = len(lambdas)
#yellow = TGraph(2*N) # yellow band
#green = TGraph(2*N) # green band
#median = TGraph(N) # median line
Mmin = [100 + i * 100 for i in range(40)]
graphs = []
for i in range(N):
thislam = TGraph(len(Mmin))
thislimit = []
for mm in range(len(Mmin)):
file_name = "./%sdataCards/ee_signif%s/higgsCombine%d.Significance.mH%d.root" % (
model, helicity, Mmin[mm], lambdas[i])
limit = getLimits(file_name)
thislam.SetPoint(mm, Mmin[mm], limit[0])
thislam.SetLineColor(i + 2)
thislam.SetLineWidth(2)
thislimit.append(limit[0])
graphs.append(thislam.Clone())
print "this minimum mass cut is %d" % Mmin[mm]
print thislimit
#yellow.SetPoint( i, values[i], limit[4] ) # + 2 sigma
#green.SetPoint( i, values[i], limit[3] ) # + 1 sigma
#median.SetPoint( i, labels[i], limit[0] ) # 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()
if model == "ADD": frame = c.DrawFrame(100, 0.01, 4000, 22)
elif "Con" in helicity: frame = c.DrawFrame(100, 0.01, 4000, 15)
else: frame = c.DrawFrame(100, 0.01, 4000, 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("Significance")
frame.GetXaxis().SetTitle("M_{min} [GeV]")
frame.SetMinimum(0)
#frame.SetMaximum(max(up2s)*1.05)
#frame.GetXaxis().SetLimits(min(values),max(values))
for gf in graphs:
gf.Draw('Lsame')
'''
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 = 0.75
x2 = x1 + 0.24
y2 = 0.86
y1 = 0.60
legend = TLegend(x1, y1, x2, y2)
legend.SetFillStyle(0)
legend.SetBorderSize(0)
legend.SetTextSize(0.041)
legend.SetTextFont(42)
for i in range(N):
legend.AddEntry(graphs[i], "#Lambda = %d" % lambdas[i], 'l')
#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("%slimits/%sSignificance_ee%s.png" % (model, model, helicity))
c.Close()
else:
gr1 = TGraph()
dumb = drawlik(options.input, gr = gr1, color = 53, second = False, Folder = options.outFolder)
gr1 = dumb.Clone()
gr1.GetYaxis().SetRangeUser(0.,3.)
gr1.Draw("Ap")
mg.Add(gr1)
colorset(gr = gr1, color = 53)
leg.AddEntry(gr1, options.label, 'Lp')
entries += 1
if options.input2 != "none" :
gr2 = TGraph()
dumb = TGraph()
dumb = drawlik(options.input2, gr = gr2, color = 8, second = False, Folder = options.outFolder2)
gr2 = dumb.Clone()
gr2.GetYaxis().SetRangeUser(0.,3.)
gr2.Draw("p, same")
mg.Add(gr2)
colorset(gr = gr2, color = 6)
leg.AddEntry(gr2, options.label2, 'Lp')
entries += 1
if options.input3 != "none" :
gr3 = TGraph()
dumb = drawlik(options.input3, gr = gr3, color = 93, second = False, Folder = options.outFolder3)
gr3 = dumb.Clone()
gr3.GetYaxis().SetRangeUser(0.,3.)
gr3.Draw("p, same")
#gr3.Draw("p, same")
mg.Add(gr3)
x_1110_2 = array('d', x1110[nwa1110:])
y_theory1110 = array('d', theory1110[:nwa1110 + 1])
y_theory1110_2 = array('d', theory1110[nwa1110:])
theory_curve_1110 = TGraph(len(theory1110[:nwa1110 + 1]), x_1110, y_theory1110)
theory_curve_1110_2 = TGraph(len(theory1110[nwa1110:]), x_1110_2,
y_theory1110_2)
#theory_curve_1410=TGraph(len(theory1410),x_1410,y_theory1410)
theory_curve_1110.SetLineWidth(3)
theory_curve_1110.SetLineColor(kAzure)
theory_curve_1110.SetMarkerColor(kAzure)
theory_curve_1110_2.SetLineWidth(3)
theory_curve_1110_2.SetLineColor(kAzure)
theory_curve_1110_2.SetMarkerColor(kAzure)
theory_curve_1110_2.SetLineStyle(7)
theory_curve_1110_33 = theory_curve_1110_2.Clone()
theory_curve_1110_33.SetLineColor(1)
theory_curve_1110_33.SetMarkerColor(1)
theory_curve_1410.SetLineWidth(3)
theory_curve_1410.SetLineColor(kGreen + 3)
theory_curve_1410.SetMarkerColor(kGreen + 3)
theory_curve_1410_2.SetLineWidth(3)
theory_curve_1410_2.SetLineColor(kGreen + 3)
theory_curve_1410_2.SetMarkerColor(kGreen + 3)
theory_curve_1410_2.SetLineStyle(7)
zeros_theory = array('d', [0 for i in range(len(theory_values[1]))])
theory_sigma = TGraphAsymmErrors(len(theory_values[1]), x_theory, y_theory,
zeros_theory, zeros_theory, y_theory_down,
y_theory_up)
g_width.GetYaxis().SetTitleSize(0.05)
g_width.GetYaxis().SetLabelSize(0.05)
g_width.GetYaxis().SetTitleOffset(0.8)
g_width.GetYaxis().SetRangeUser(0., mass * 0.12)
g_width.GetXaxis().SetTitleSize(0.05)
g_width.GetXaxis().SetLabelSize(0.05)
g_width.GetXaxis().SetTitleOffset(0.88)
g_partial_width.SetLineColor(4)
g_partial_width.SetLineWidth(3003)
g_partial_width.SetFillStyle(3002)
g_partial_width.Draw('C')
legend = TLegend(0.15, 0.6, 0.4, 0.85)
legend.AddEntry(g_width, 'Total width', 'l')
legend.AddEntry(g_partial_width, 'Partial width (t#bar{t})', 'l')
g_partial_width_excl = g_partial_width.Clone('g_partial_width_excl')
g_partial_width_excl.SetLineWidth(0)
g_partial_width_excl.SetLineColor(0)
legend.AddEntry(g_partial_width_excl, 'Forbidden', 'f')
legend.AddEntry(p_25percent, 'Sample (2.5% width)', 'p')
legend.AddEntry(p_5percent, 'Sample (5% width)', 'p')
legend.AddEntry(p_10percent, 'Sample (10% width)', 'p')
legend.SetBorderSize(0)
legend.Draw()
c.Print('width_vs_tanb_mA{mass}.pdf'.format(mass=int(mass)))
zeros = array('d', [0] * len(lines_exp))
print lumi
for i in range(len(lines_exp)):
print masses[i], '&', rounding(lines_exp[i][2]), '&', rounding(
lines_exp[i][4]), '&', rounding(lines_exp[i][1]), '&', rounding(
lines_exp[i][5]), '&', rounding(lines_exp[i][3]), '\\\\'
exp1sigma = ROOT.TGraphAsymmErrors(5, x, y_exp, zeros, zeros, y_err1down,
y_err1up)
exp2sigma = ROOT.TGraphAsymmErrors(5, x, y_exp, zeros, zeros, y_err2down,
y_err2up)
explim = TGraph(5, x, y_exp)
explim.SetLineWidth(2)
explim.SetLineStyle(2)
explim.SetTitle('')
limits.append(explim.Clone())
exp2sigma.SetTitle('')
exp1sigma.SetTitle('')
exp1sigma.SetFillColor(ROOT.kGreen + 1)
exp2sigma.SetFillColor(ROOT.kOrange)
exp2sigma.SetMaximum(10000)
exp2sigma.SetMinimum(0.0007)
exp2sigma.Draw('a3lp')
exp2sigma.GetXaxis().SetTitle("g_{KK} mass [TeV]")
exp2sigma.GetXaxis().SetRangeUser(1500, 6500)
exp2sigma.GetYaxis().SetTitle("Upper cross section limit [pb]")
sizefactor = 1.5
exp2sigma.GetXaxis().SetTitleSize(sizefactor *
exp2sigma.GetXaxis().GetTitleSize())
