def getGraph(self):
from array import array
from ROOT import TMultiGraph, TLegend, TGraphAsymmErrors
n = len(self.__x)
if n != len(self.__y) or n != len(self.__yErrLow) or n != len(
self.__yErrHigh):
raise StandardError, "The length of the x(%s), y(%s) and y error(%s,%s) lists does not match" % (
len(self.__x), len(self.__y), len(
self.__yErrLow), len(self.__yErrHigh))
result = TMultiGraph()
legendPosition = [
float(i) for i in self.__getStyleOption("legendPosition").split()
]
legend = TLegend(*legendPosition)
legend.SetFillColor(0)
result.SetTitle("%s;%s;%s" %
(self.__title, self.__xTitle, self.__yTitle))
#(refArrays, refLabel) = self.__getRefernceGraphArrays()
#refGraph = TGraphAsymmErrors(*refArrays)
#refGraph.SetLineWidth(2)
#refGraph.SetLineColor(int(self.__config.get("reference","lineColor")))
#refGraph.SetFillColor(int(self.__config.get("reference","fillColor")))
#result.Add(refGraph,"L3")
#legend.AddEntry(refGraph,self.__config.get("reference","name"))
xErr = array("d", [0 for i in range(n)])
print "__x = ", self.__x
print "__y = ", self.__y
graph = TGraphAsymmErrors(n, self.__x, self.__y, xErr, xErr,
self.__yErrLow, self.__yErrHigh)
graph.SetLineWidth(2)
graph.SetFillColor(0)
graph.SetLineColor(int(self.__getStyleOption("lineColor")))
graph.SetMarkerColor(int(self.__getStyleOption("markerColor")))
graph.SetMarkerStyle(int(self.__getStyleOption("markerStyle")))
graph.SetMarkerSize(float(self.__getStyleOption("markerSize")))
sysGraph = TGraphAsymmErrors(n, self.__x, self.__y, xErr, xErr,
self.__ySysErrLow, self.__ySysErrHigh)
sysGraph.SetLineWidth(1)
sysGraph.SetFillColor(0)
sysGraph.SetLineColor(int(self.__getStyleOption("lineColor")))
sysGraph.SetMarkerColor(int(self.__getStyleOption("markerColor")))
sysGraph.SetMarkerStyle(int(self.__getStyleOption("markerStyle")))
sysGraph.SetMarkerSize(float(self.__getStyleOption("markerSize")))
result.Add(sysGraph, "[]")
result.Add(graph, "P")
# result.SetName("MultiPlots")
# result.SetTitle("%s;%s;%s"%(self.__title,self.__xTitle,self.__yTitle))
result.SetName("MG_%s" % (self.__title))
legend.AddEntry(graph, self.__getStyleOption("name"))
#for (x,y,yErr) in zip(self.__x, self.__y, zip(self.__yErrLow,self.__yErrHigh)):
# self.__addAnnotaion("hallo",x,y,yErr)
return (result, legend)
def draw_limits_per_category(nchannels, xmin, xmax, obs, expect, upper1sig,
lower1sig, upper2sig, lower2sig):
channel = np.array(
[3. * nchannels - 1.5 - 3. * i for i in range(0, nchannels)])
ey = np.array([0.8 for i in range(0, nchannels)])
zero = np.zeros(nchannels)
gexpect1sig = TGraphAsymmErrors(nchannels, expect, channel, lower1sig,
upper1sig, ey, ey)
gexpect1sig.SetFillColor(kGreen)
gexpect1sig.SetLineWidth(2)
gexpect1sig.SetLineStyle(2)
gexpect2sig = TGraphAsymmErrors(nchannels, expect, channel, lower2sig,
upper2sig, ey, ey)
gexpect2sig.SetFillColor(kYellow)
gexpect2sig.SetLineWidth(2)
gexpect2sig.SetLineStyle(2)
gexpect2sig.Draw("2")
gexpect1sig.Draw("2")
gobs = TGraphErrors(nchannels, obs, channel, zero, ey)
gobs.SetMarkerStyle(21)
gobs.SetMarkerSize(1.5)
gobs.SetLineWidth(2)
gobs.Draw("pz")
# dashed line at median expected limits
l = TLine()
l.SetLineStyle(2)
l.SetLineWidth(2)
for bin in range(nchannels):
l.DrawLine(expect[bin], channel[bin] - ey[bin], expect[bin],
channel[bin] + ey[bin])
# line to separate individual and combined limits
l.SetLineStyle(1)
l.SetLineWidth(1)
l.DrawLine(xmin, 0, xmax, 0)
# legend
x1 = gStyle.GetPadLeftMargin() + 0.01
y2 = 1 - gStyle.GetPadTopMargin() - 0.01
leg = TLegend(x1, y2 - 0.17, x1 + 0.25, y2)
leg.SetFillColor(4000)
leg.AddEntry(gexpect1sig, "Expected #pm1#sigma", "FL")
leg.AddEntry(gexpect2sig, "Expected #pm2#sigma", "FL")
leg.AddEntry(gobs, "Observed", "pl")
leg.Draw()
return gobs, gexpect1sig, gexpect2sig, leg
def draw_limits_per_category(nchannels, xmin, xmax, obs, expect, upper1sig,
lower1sig, upper2sig, lower2sig):
channel = np.array(
[nchannels - 1.5 - float(i) for i in range(0, nchannels)])
ey = np.full(nchannels, 0.494)
zero = np.zeros(nchannels)
gexpect1sig = TGraphAsymmErrors(nchannels, expect, channel, lower1sig,
upper1sig, ey, ey)
gexpect1sig.SetFillColor(kGreen)
gexpect1sig.SetLineWidth(2)
gexpect1sig.SetLineStyle(2)
gexpect2sig = TGraphAsymmErrors(nchannels, expect, channel, lower2sig,
upper2sig, ey, ey)
gexpect2sig.SetFillColor(kYellow)
gexpect2sig.SetLineWidth(2)
gexpect2sig.SetLineStyle(2)
gexpect2sig.Draw("2")
gexpect1sig.Draw("2")
gobs = TGraphErrors(nchannels, obs, channel, zero, ey)
gobs.SetMarkerStyle(21)
gobs.SetMarkerSize(1.5)
gobs.SetLineWidth(2)
#gobs.Draw("pz")
# dashed line at median expected limits
l = TLine()
l.SetLineStyle(2)
l.SetLineWidth(2)
for bin in range(nchannels):
l.DrawLine(expect[bin], channel[bin] - ey[bin], expect[bin],
channel[bin] + ey[bin])
# line to separate individual and combined limits
l.SetLineStyle(1)
l.SetLineWidth(1)
l.DrawLine(xmin, 0, xmax, 0)
# legend
leg = TLegend(0.75, 0.75, 0.95, 0.9)
leg.SetFillColor(4000)
leg.AddEntry(gexpect1sig, "Expected #pm1#sigma", "FL")
leg.AddEntry(gexpect2sig, "Expected #pm2#sigma", "FL")
#leg.AddEntry( gobs, "Observed", "pl" )
leg.Draw()
return gobs, gexpect1sig, gexpect2sig, leg
def getGraphSimple(self):
from array import array
from ROOT import TMultiGraph, TLegend, TGraphAsymmErrors
n = len(self.__x)
if n != len(self.__y) or n != len(self.__yErrLow) or n != len(self.__yErrHigh):
raise StandardError, "The length of the x(%s), y(%s) and y error(%s,%s) lists does not match"%(len(self.__x), len(self.__y), len(self.__yErrLow), len(self.__yErrHigh))
legendPosition = [float(i) for i in self.__getStyleOption("legendPosition").split()]
legend = TLegend(*legendPosition)
legend.SetFillColor(0)
xErr = array("d",[0 for i in range(n)])
print "__x = ", self.__x
print "__y = ", self.__y
graph = TGraphAsymmErrors(n, self.__x, self.__y, xErr, xErr, self.__yErrLow,self.__yErrHigh)
graph.SetTitle("%s;%s;%s"%(self.__title,self.__xTitle,self.__yTitle))
graph.SetLineWidth(2)
graph.SetFillColor(0)
graph.SetLineColor(int(self.__getStyleOption("lineColor")))
graph.SetMarkerColor(int(self.__getStyleOption("markerColor")))
graph.SetMarkerStyle(int(self.__getStyleOption("markerStyle")))
graph.SetMarkerSize(float(self.__getStyleOption("markerSize")))
graph.SetDrawOption("AP")
return (graph, legend)
def convertHistToGraph(hist, useGarwood=False):
alpha = 1 - 0.6827
graph = TGraphAsymmErrors(hist.GetNbinsX())
if useGarwood:
lastEvent = False
for i in reversed(range(hist.GetNbinsX())):
N = hist.GetBinContent(i + 1)
if not lastEvent and N > 0: lastEvent = True
if lastEvent and N <= 0.: N = 1.e-6
L = 0 if N == 0 else ROOT.Math.gamma_quantile(alpha / 2, N, 1.)
U = ROOT.Math.gamma_quantile_c(alpha / 2, N + 1, 1)
graph.SetPoint(i,
hist.GetXaxis().GetBinCenter(i + 1),
N if not N == 0 else -1.e99)
graph.SetPointError(i, 0., 0., N - L, U - N)
else:
for i in range(hist.GetNbinsX()):
graph.SetPoint(i,
hist.GetXaxis().GetBinCenter(i + 1),
hist.GetBinContent(i + 1))
graph.SetPointError(i,
hist.GetXaxis().GetBinWidth(i + 1) / 2.,
hist.GetXaxis().GetBinWidth(i + 1) / 2.,
hist.GetBinError(i + 1),
hist.GetBinError(i + 1))
graph.SetLineWidth(hist.GetLineWidth())
graph.SetLineStyle(hist.GetLineStyle())
graph.SetLineColor(hist.GetLineColor())
graph.SetMarkerSize(hist.GetMarkerSize())
graph.SetMarkerStyle(hist.GetMarkerStyle())
graph.SetMarkerColor(hist.GetMarkerColor())
graph.SetFillStyle(hist.GetFillStyle())
graph.SetFillColor(hist.GetFillColor())
return graph
def makeResidHist(data, bkg):
pulls = TGraphAsymmErrors(data.GetN())
pulls.SetName("Pulls")
pulls.SetLineWidth(data.GetLineWidth())
pulls.SetLineStyle(data.GetLineStyle())
pulls.SetLineColor(data.GetLineColor())
pulls.SetMarkerSize(data.GetMarkerSize())
pulls.SetMarkerStyle(data.GetMarkerStyle())
pulls.SetMarkerColor(data.GetMarkerColor())
pulls.SetFillStyle(data.GetFillStyle())
pulls.SetFillColor(data.GetFillColor())
# Add histograms, calculate Poisson confidence interval on sum value
for i in range(data.GetN()):
x = data.GetX()[i]
dyl = data.GetErrorYlow(i)
dyh = data.GetErrorYhigh(i)
yy = data.GetY()[i] - bkg.Interpolate(x) #bkg.GetBinContent(i+1)
norm = dyl if yy > 0. else dyh
if norm == 0.:
yy, dyh, dyl = 0., 0., 0.
else:
yy /= norm
dyh /= norm
dyl /= norm
pulls.SetPoint(i, x, yy)
pulls.SetPointEYhigh(i, dyh)
pulls.SetPointEYlow(i, dyl)
return pulls
def convertHistToGraph(hist):
graph = TGraphAsymmErrors(hist.GetNbinsX())
for i in range(hist.GetNbinsX()):
graph.SetPoint(i,
hist.GetXaxis().GetBinCenter(i), hist.GetBinContent(i))
graph.SetPointError(i,
hist.GetXaxis().GetBinWidth(i) / 2.,
hist.GetXaxis().GetBinWidth(i) / 2.,
hist.GetBinError(i), hist.GetBinError(i))
graph.SetLineWidth(hist.GetLineWidth())
graph.SetLineStyle(hist.GetLineStyle())
graph.SetLineColor(hist.GetLineColor())
graph.SetMarkerSize(hist.GetMarkerSize())
graph.SetMarkerStyle(hist.GetMarkerStyle())
graph.SetMarkerColor(hist.GetMarkerColor())
graph.SetFillStyle(hist.GetFillStyle())
graph.SetFillColor(hist.GetFillColor())
return graph
def histToGraph(hist, name='', keepErrors=True, poissonErrors=True):
## Helper method to convert a histogram to a corresponding graph
# @hist TH1 object
# @name name of the graph (default is name of histogram)
# @keepErrors decide if the y-errors should be propagated to the graph
# @poissonErrors decide if the y-errors should be calculated as Poisson errors
# @return graph
if not name:
name = 'g%s' % (hist.GetName())
from ROOT import TGraphAsymmErrors
nBins = hist.GetNbinsX()
graph = TGraphAsymmErrors(nBins)
graph.SetNameTitle(name, hist.GetTitle())
xAxis = hist.GetXaxis()
for i in xrange(nBins):
xVal = xAxis.GetBinCenter(i + 1)
yVal = hist.GetBinContent(i + 1)
graph.SetPoint(i, xVal, yVal)
graph.SetPointEXlow(i, abs(xVal - xAxis.GetBinLowEdge(i + 1)))
graph.SetPointEXhigh(i, abs(xVal - xAxis.GetBinUpEdge(i + 1)))
if keepErrors:
if poissonErrors:
lo, hi = calculatePoissonErrors(yVal)
graph.SetPointEYlow(i, lo)
graph.SetPointEYhigh(i, hi)
else:
graph.SetPointEYlow(i, hist.GetBinErrorLow(i + 1))
graph.SetPointEYhigh(i, hist.GetBinErrorUp(i + 1))
# copy the style
graph.SetMarkerStyle(hist.GetMarkerStyle())
graph.SetMarkerColor(hist.GetMarkerColor())
graph.SetMarkerSize(hist.GetMarkerSize())
graph.SetLineStyle(hist.GetLineStyle())
graph.SetLineColor(hist.GetLineColor())
graph.SetLineWidth(hist.GetLineWidth())
graph.SetFillColor(hist.GetFillColor())
graph.SetFillStyle(hist.GetFillStyle())
return graph
exh_c = np.array(LC_dict['tpr_e_h'])
eyh_c = np.array(LC_dict['fpr_e_h'])
# somehow if you call one of the variables before the Draw() method the graph won't work properly
gr = GAE(n_bins, x, y, exl, exh, eyl, eyh)
gr_s = GAE(n_bins, x, y, exl, exh, eyl, eyh)
gr_LC = GAE(1, x_c, y_c, exl_c, exh_c, eyl_c, eyh_c)
gr_c = gr.Clone()
gr_sc = gr_s.Clone()
gr.SetTitle('ROC(zoomed in)')
#gr.SetMarkerColor(8)
#gr.SetMarkerStyle(21)
gr.SetFillColor(632 - 9)
gr_s.SetTitle('ROC')
gr_s.SetFillColor(632 - 9)
gr_sc.SetLineColor(4)
c1.cd(1)
gr.GetXaxis().SetRangeUser(0, 0.5)
gr.GetYaxis().SetRangeUser(0.00001, 0.01)
gr_c.GetXaxis().SetRangeUser(0, 0.5)
gr_c.GetXaxis().SetRangeUser(0.00001, 0.01)
gr_LC.GetXaxis().SetRangeUser(0, 0.5)
gr_LC.GetYaxis().SetRangeUser(0.00001, 0.01)
gr_c.SetLineColor(4)
def limit():
method = ''
channel = "bb"
particleP = "Z'"
particle = channel
multF = ZPTOBB
THEORY = ['A1', 'B3']
suffix = "_" + BTAGGING
if ISMC: suffix += "_MC"
if SY: suffix += "_comb"
#if method=="cls": suffix="_CLs"
if SY:
filename = "./combine/limits/MANtag_study/" + BTAGGING + "/combined_run2/" + YEAR + "_M%d.txt"
else:
filename = "./combine/limits/MANtag_study/" + BTAGGING + "/" + YEAR + "_M%d.txt"
if CATEGORY != "":
filename = filename.replace(
BTAGGING + "/", BTAGGING + "/single_category/" + CATEGORY + "_")
suffix += "_" + CATEGORY
if ISMC: filename = filename.replace(".txt", "_MC.txt")
mass, val = fillValues(filename)
#print "mass =",mass
#print "val =", val
Obs0s = TGraph()
Exp0s = TGraph()
Exp1s = TGraphAsymmErrors()
Exp2s = TGraphAsymmErrors()
Sign = TGraph()
pVal = TGraph()
Best = TGraphAsymmErrors()
Theory = {}
for i, m in enumerate(mass):
if not m in val:
print "Key Error:", m, "not in value map"
continue
n = Exp0s.GetN()
Obs0s.SetPoint(n, m, val[m][0] * multF)
Exp0s.SetPoint(n, m, val[m][3] * multF)
Exp1s.SetPoint(n, m, val[m][3] * multF)
Exp1s.SetPointError(n, 0., 0., val[m][3] * multF - val[m][2] * multF,
val[m][4] * multF - val[m][3] * multF)
Exp2s.SetPoint(n, m, val[m][3] * multF)
Exp2s.SetPointError(n, 0., 0., val[m][3] * multF - val[m][1] * multF,
val[m][5] * multF - val[m][3] * multF)
if len(val[m]) > 6: Sign.SetPoint(n, m, val[m][6])
if len(val[m]) > 7: pVal.SetPoint(n, m, val[m][7])
if len(val[m]) > 8: Best.SetPoint(n, m, val[m][8])
if len(val[m]) > 10:
Best.SetPointError(n, 0., 0., abs(val[m][9]), val[m][10])
for t in THEORY:
Theory[t] = TGraphAsymmErrors()
addXZH = True
for m in sorted(HVT[t]['W']['XS'].keys()):
if m < mass[0] or m > mass[-1]: continue
if m > 4500:
continue ## for now because I don't have the higher mass xs FIXME
XsZ, XsZ_Up, XsZ_Down = 0., 0., 0.
if addXZH:
XsZ = 1000. * HVT[t]['Z']['XS'][
m] * 0.12 #temporary BR value set to 0.12 FIXME
XsZ_Up = XsZ * (1. + math.hypot(HVT[t]['Z']['QCD'][m][0] - 1.,
HVT[t]['Z']['PDF'][m][0] - 1.))
XsZ_Down = XsZ * (1. -
math.hypot(1. - HVT[t]['Z']['QCD'][m][0],
1. - HVT[t]['Z']['PDF'][m][0]))
n = Theory[t].GetN()
Theory[t].SetPoint(n, m, XsZ)
Theory[t].SetPointError(n, 0., 0., (XsZ - XsZ_Down),
(XsZ_Up - XsZ))
Theory[t].SetLineColor(theoryLineColor[t])
Theory[t].SetFillColor(theoryFillColor[t])
Theory[t].SetFillStyle(theoryFillStyle[t])
Theory[t].SetLineWidth(2)
#Theory[t].SetLineStyle(7)
Exp2s.SetLineWidth(2)
Exp2s.SetLineStyle(1)
Obs0s.SetLineWidth(3)
Obs0s.SetMarkerStyle(0)
Obs0s.SetLineColor(1)
Exp0s.SetLineStyle(2)
Exp0s.SetLineWidth(3)
Exp1s.SetFillColor(417) #kGreen+1
Exp1s.SetLineColor(417) #kGreen+1
Exp2s.SetFillColor(800) #kOrange
Exp2s.SetLineColor(800) #kOrange
Exp2s.GetXaxis().SetTitle("m_{" + particleP + "} (GeV)")
Exp2s.GetXaxis().SetTitleSize(Exp2s.GetXaxis().GetTitleSize() * 1.25)
Exp2s.GetXaxis().SetNoExponent(True)
Exp2s.GetXaxis().SetMoreLogLabels(True)
Exp2s.GetYaxis().SetTitle("#sigma(" + particleP + ") #bf{#it{#Beta}}(" +
particleP + " #rightarrow " + particle +
") (fb)")
Exp2s.GetYaxis().SetTitleOffset(1.5)
Exp2s.GetYaxis().SetNoExponent(True)
Exp2s.GetYaxis().SetMoreLogLabels()
Sign.SetLineWidth(2)
Sign.SetLineColor(629)
Sign.GetXaxis().SetTitle("m_{" + particleP + "} (GeV)")
Sign.GetXaxis().SetTitleSize(Sign.GetXaxis().GetTitleSize() * 1.1)
Sign.GetYaxis().SetTitle("Significance")
pVal.SetLineWidth(2)
pVal.SetLineColor(629)
pVal.GetXaxis().SetTitle("m_{" + particleP + "} (GeV)")
pVal.GetXaxis().SetTitleSize(pVal.GetXaxis().GetTitleSize() * 1.1)
pVal.GetYaxis().SetTitle("local p-Value")
Best.SetLineWidth(2)
Best.SetLineColor(629)
Best.SetFillColor(629)
Best.SetFillStyle(3003)
Best.GetXaxis().SetTitle("m_{" + particleP + "} (GeV)")
Best.GetXaxis().SetTitleSize(Best.GetXaxis().GetTitleSize() * 1.1)
Best.GetYaxis().SetTitle("Best Fit (pb)")
c1 = TCanvas("c1", "Exclusion Limits", 800, 600)
c1.cd()
#SetPad(c1.GetPad(0))
c1.GetPad(0).SetTopMargin(0.06)
c1.GetPad(0).SetRightMargin(0.05)
c1.GetPad(0).SetLeftMargin(0.12)
c1.GetPad(0).SetTicks(1, 1)
#c1.GetPad(0).SetGridx()
#c1.GetPad(0).SetGridy()
c1.GetPad(0).SetLogy()
Exp2s.Draw("A3")
Exp1s.Draw("SAME, 3")
for t in THEORY:
Theory[t].Draw("SAME, L3")
Theory[t].Draw("SAME, L3X0Y0")
Exp0s.Draw("SAME, L")
if not options.blind: Obs0s.Draw("SAME, L")
#setHistStyle(Exp2s)
Exp2s.GetXaxis().SetTitleSize(0.050)
Exp2s.GetYaxis().SetTitleSize(0.050)
Exp2s.GetXaxis().SetLabelSize(0.045)
Exp2s.GetYaxis().SetLabelSize(0.045)
Exp2s.GetXaxis().SetTitleOffset(0.90)
Exp2s.GetYaxis().SetTitleOffset(1.25)
Exp2s.GetYaxis().SetMoreLogLabels(True)
Exp2s.GetYaxis().SetNoExponent(True)
Exp2s.GetYaxis().SetRangeUser(0.1, 5.e3)
#else: Exp2s.GetYaxis().SetRangeUser(0.1, 1.e2)
#Exp2s.GetXaxis().SetRangeUser(mass[0], min(mass[-1], MAXIMUM[channel] if channel in MAXIMUM else 1.e6))
Exp2s.GetXaxis().SetRangeUser(SIGNALS[0], SIGNALS[-1])
#drawAnalysis(channel)
drawAnalysis("")
#drawRegion(channel, True)
drawRegion("", True)
#drawCMS(LUMI, "Simulation Preliminary") #Preliminary
drawCMS(LUMI, "Work in Progress", suppressCMS=True)
# legend
top = 0.9
nitems = 4 + len(THEORY)
leg = TLegend(0.55, top - nitems * 0.3 / 5., 0.98, top)
#leg = TLegend(0.45, top-nitems*0.3/5., 0.98, top)
leg.SetBorderSize(0)
leg.SetFillStyle(0) #1001
leg.SetFillColor(0)
leg.SetHeader("95% CL upper limits")
leg.AddEntry(Obs0s, "Observed", "l")
leg.AddEntry(Exp0s, "Expected", "l")
leg.AddEntry(Exp1s, "#pm 1 std. deviation", "f")
leg.AddEntry(Exp2s, "#pm 2 std. deviation", "f")
for t in THEORY:
leg.AddEntry(Theory[t], theoryLabel[t], "fl")
leg.Draw()
latex = TLatex()
latex.SetNDC()
latex.SetTextSize(0.045)
latex.SetTextFont(42)
#latex.DrawLatex(0.66, leg.GetY1()-0.045, particleP+" #rightarrow "+particle+"h")
leg2 = TLegend(0.12, 0.225 - 2 * 0.25 / 5., 0.65, 0.225)
leg2.SetBorderSize(0)
leg2.SetFillStyle(0) #1001
leg2.SetFillColor(0)
c1.GetPad(0).RedrawAxis()
leg2.Draw()
if not options.blind: Obs0s.Draw("SAME, L")
c1.GetPad(0).Update()
if not gROOT.IsBatch(): raw_input("Press Enter to continue...")
c1.Print("combine/plotsLimit/ExclusionLimits/MANtag_study/" + YEAR +
suffix + ".png")
c1.Print("combine/plotsLimit/ExclusionLimits/MANtag_study/" + YEAR +
suffix + ".pdf")
if 'ah' in channel or 'sl' in channel:
c1.Print("combine/plotsLimit/ExclusionLimits/MANtag_study/" + YEAR +
suffix + ".C")
c1.Print("combine/plotsLimit/ExclusionLimits/MANtag_study/" + YEAR +
suffix + ".root")
for t in THEORY:
print "Model", t, ":",
for m in range(mass[0], mass[-1], 1):
if not (Theory[t].Eval(m) > Obs0s.Eval(m)) == (
Theory[t].Eval(m + 1) > Obs0s.Eval(m + 1)):
print m,
print ""
return
def makePlot(finname,foutname,plottitle='',masstitle='',scale=False):
xsecs = resonantXsecs if 'resonant' in finname else fcncXsecs
points = {}
if BLIND:
cls = [2.5, 16, 50, 84, 97.5]
else:
cls = [2.5, 16, 50, 84, 97.5,'Observed']
xaxis = []
for cl in cls:
points[cl] = []
xsec=1
for l in open(finname):
try:
if l.strip()[0]=='#':
continue
if 'MASS' in l:
if scale:
xsec = xsecs[int(l.split()[1])]
if VERBOSE:
print ''
stdout.write('$%6s$ & $%7.3g$'%(l.split()[1],xsec/(0.667)))
xaxis.append(float(l.split()[1]))
else:
cl,val = parseLine(l)
points[cl].append(val/xsec)
if VERBOSE and (cl==50 or cl=='Observed'):
stdout.write(' & $%10.4g$'%(val/xsec))
except:
pass
if VERBOSE:
print ''
N = len(xaxis)
up1Sigma=[]; up2Sigma=[]
down1Sigma=[]; down2Sigma=[]
for iM in xrange(N):
up1Sigma.append(points[84][iM]-points[50][iM])
up2Sigma.append(points[97.5][iM]-points[50][iM])
down1Sigma.append(-points[16][iM]+points[50][iM])
down2Sigma.append(-points[2.5][iM]+points[50][iM])
up1Sigma = array('f',up1Sigma)
up2Sigma = array('f',up2Sigma)
down1Sigma = array('f',down1Sigma)
down2Sigma = array('f',down2Sigma)
cent = array('f',points[50])
if not BLIND:
obs = array('f',points['Observed'])
xarray = array('f',xaxis)
xsecarray = array('f',[xsecs[xx] for xx in xaxis])
xsecarrayLow = array('f',[0.0625*xsecs[xx] for xx in xaxis])
onearray = array('f',[1 for xx in xaxis])
graphXsec = TGraph(N,xarray,xsecarray)
graphXsecLow = TGraph(N,xarray,xsecarrayLow)
graphOne = TGraph(N,xarray,onearray)
zeros = array('f',[0 for i in xrange(N)])
graphCent = TGraph(N,xarray,cent)
if not BLIND:
graphObs = TGraph(N,xarray,obs)
graph1Sigma = TGraphAsymmErrors(N,xarray,cent,zeros,zeros,down1Sigma,up1Sigma)
graph2Sigma = TGraphAsymmErrors(N,xarray,cent,zeros,zeros,down2Sigma,up2Sigma)
c = TCanvas('c','c',700,600)
c.SetLogy()
c.SetLeftMargin(.15)
graph2Sigma.GetXaxis().SetTitle(masstitle+' [GeV]')
if scale:
graph2Sigma.GetYaxis().SetTitle('Upper limit [#sigma/#sigma_{theory}]')
else:
graph2Sigma.GetYaxis().SetTitle("Upper limit [#sigma] [pb]")
graph2Sigma.SetLineColor(5)
graph1Sigma.SetLineColor(3)
graph2Sigma.SetFillColor(5)
graph1Sigma.SetFillColor(3)
graph2Sigma.SetMinimum(0.5*min(points[2.5]))
if scale:
graph2Sigma.SetMaximum(10*max(max(points[97.5]),max(xsecarray),4))
else:
graph2Sigma.SetMaximum(10*max(max(points[97.5]),max(xsecarray)))
graphCent.SetLineWidth(2)
graphCent.SetLineStyle(2)
if not BLIND:
graphObs.SetLineColor(1)
graphObs.SetLineWidth(3)
graph1Sigma.SetLineStyle(0)
graph2Sigma.SetLineStyle(0)
leg = TLegend(0.55,0.7,0.9,0.9)
leg.AddEntry(graphCent,'Expected','L')
if not BLIND:
leg.AddEntry(graphObs,'Observed','L')
leg.AddEntry(graph1Sigma,'1 #sigma','F')
leg.AddEntry(graph2Sigma,'2 #sigma','F')
leg.SetFillStyle(0)
leg.SetBorderSize(0)
graph2Sigma.Draw('A3')
graph1Sigma.Draw('3 same')
graphCent.Draw('same L')
if not BLIND:
graphObs.Draw('same L')
if scale:
graphOne.SetLineColor(2)
graphOne.SetLineWidth(2)
graphOne.SetLineStyle(2)
graphOne.Draw('same L')
else:
graphXsec.SetLineColor(2)
graphXsecLow.SetLineColor(4)
subscript = 'SR' if 'Resonant' in plottitle else 'FC'
if 'Resonant' in plottitle:
leg.AddEntry(graphXsec,'Theory #splitline{a_{%s}=b_{%s}=0.1}{m_{#chi}=100 GeV}'%(subscript,subscript),'l')
else:
leg.AddEntry(graphXsec,'Theory a_{%s}=b_{%s}=0.1'%(subscript,subscript),'l')
# leg.AddEntry(graphXsecLow,'Theory a_{%s}=b_{%s}=0.025'%(subscript,subscript),'l')
for g in [graphXsec]:
g.SetLineWidth(2)
g.SetLineStyle(2)
g.Draw('same L')
leg.Draw()
label = TLatex()
label.SetNDC()
label.SetTextFont(62)
label.SetTextAlign(11)
label.DrawLatex(0.19,0.85,"CMS")
label.SetTextFont(52)
label.DrawLatex(0.28,0.85,"Preliminary")
label.SetTextFont(42)
label.SetTextSize(0.6*c.GetTopMargin())
label.DrawLatex(0.19,0.77,plottitle)
if scale:
if 'Resonant' in plottitle:
label.DrawLatex(0.19,0.7,"a_{SR} = b_{SR} = 0.1")
label.DrawLatex(0.19,0.64,"m_{#chi}=100 GeV")
else:
label.DrawLatex(0.19,0.7,"a_{FC} = b_{FC} = 0.1")
label.SetTextSize(0.5*c.GetTopMargin())
label.SetTextFont(42)
label.SetTextAlign(31) # align right
label.DrawLatex(0.9, 0.94,"%.1f fb^{-1} (13 TeV)"%(plotConfig.lumi))
c.SaveAs(foutname+'.pdf')
c.SaveAs(foutname+'.png')
def limit(method, channel):
particle = channel[1:2]
particleP = particle + "'" if channel.startswith('X') else channel[0]
THEORY = ['A1', 'B3'] if channel.startswith('X') else []
suffix = ""
if method == "hvt": suffix = "_HVT"
if method == "cls": suffix = "_CLs"
if method == "monoH": suffix = "_monoH"
filename = "./combine/" + method + "/" + channel + "_M%d.txt"
mass, val = fillValues(filename)
Obs0s = TGraph()
Exp0s = TGraph()
Exp1s = TGraphAsymmErrors()
Exp2s = TGraphAsymmErrors()
Sign = TGraph()
pVal = TGraph()
Best = TGraphAsymmErrors()
Theory = {}
for i, m in enumerate(mass):
if not m in val:
print "Key Error:", m, "not in value map"
continue
n = Exp0s.GetN()
Obs0s.SetPoint(n, m, val[m][0])
Exp0s.SetPoint(n, m, val[m][3])
Exp1s.SetPoint(n, m, val[m][3])
Exp1s.SetPointError(n, 0., 0., val[m][3] - val[m][2],
val[m][4] - val[m][3])
Exp2s.SetPoint(n, m, val[m][3])
Exp2s.SetPointError(n, 0., 0., val[m][3] - val[m][1],
val[m][5] - val[m][3])
if len(val[m]) > 6: Sign.SetPoint(n, m, val[m][6])
if len(val[m]) > 7: pVal.SetPoint(n, m, val[m][7])
if len(val[m]) > 8: Best.SetPoint(n, m, val[m][8])
if len(val[m]) > 10:
Best.SetPointError(n, 0., 0., abs(val[m][9]), val[m][10])
for t in THEORY:
Theory[t] = TGraphAsymmErrors()
for m in sorted(HVT[t]['Z']['XS'].keys()):
if m < mass[0] or m > mass[-1]: continue
XsW, XsW_Up, XsW_Down, XsZ, XsZ_Up, XsZ_Down = 0., 0., 0., 0., 0., 0.
XsZ = 1000. * HVT[t]['Z']['XS'][m] * HVT[t]['Z']['BR'][m]
XsZ_Up = XsZ * (1. + math.hypot(HVT[t]['Z']['QCD'][m][0] - 1.,
HVT[t]['Z']['PDF'][m][0] - 1.))
XsZ_Down = XsZ * (1. - math.hypot(1. - HVT[t]['Z']['QCD'][m][0],
1. - HVT[t]['Z']['PDF'][m][0]))
n = Theory[t].GetN()
Theory[t].SetPoint(n, m, XsW + XsZ)
Theory[t].SetPointError(n, 0., 0.,
(XsW - XsW_Down) + (XsZ - XsZ_Down),
(XsW_Up - XsW) + (XsZ_Up - XsZ))
Theory[t].SetLineColor(theoryLineColor[t])
Theory[t].SetFillColor(theoryFillColor[t])
Theory[t].SetFillStyle(theoryFillStyle[t])
Theory[t].SetLineWidth(2)
#Theory[t].SetLineStyle(7)
Exp2s.SetLineWidth(2)
Exp2s.SetLineStyle(1)
Obs0s.SetLineWidth(3)
Obs0s.SetMarkerStyle(0)
Obs0s.SetLineColor(1)
Exp0s.SetLineStyle(2)
Exp0s.SetLineWidth(3)
Exp1s.SetFillColor(417) #kGreen+1
Exp1s.SetLineColor(417) #kGreen+1
Exp2s.SetFillColor(800) #kOrange
Exp2s.SetLineColor(800) #kOrange
Exp2s.GetXaxis().SetTitle("m_{" + particleP + "} (GeV)")
Exp2s.GetXaxis().SetTitleSize(Exp2s.GetXaxis().GetTitleSize() * 1.25)
Exp2s.GetXaxis().SetNoExponent(True)
Exp2s.GetXaxis().SetMoreLogLabels(True)
Exp2s.GetYaxis().SetTitle("#sigma(" + particleP + ") #bf{#it{#Beta}}(" +
particleP + " #rightarrow " + particle +
"h) (fb)")
Exp2s.GetYaxis().SetTitleOffset(1.5)
Exp2s.GetYaxis().SetNoExponent(True)
Exp2s.GetYaxis().SetMoreLogLabels()
Sign.SetLineWidth(2)
Sign.SetLineColor(629)
Sign.GetXaxis().SetTitle("m_{" + particleP + "} (GeV)")
Sign.GetXaxis().SetTitleSize(Sign.GetXaxis().GetTitleSize() * 1.1)
Sign.GetYaxis().SetTitle("Significance")
pVal.SetLineWidth(2)
pVal.SetLineColor(629)
pVal.GetXaxis().SetTitle("m_{" + particleP + "} (GeV)")
pVal.GetXaxis().SetTitleSize(pVal.GetXaxis().GetTitleSize() * 1.1)
pVal.GetYaxis().SetTitle("local p-Value")
Best.SetLineWidth(2)
Best.SetLineColor(629)
Best.SetFillColor(629)
Best.SetFillStyle(3003)
Best.GetXaxis().SetTitle("m_{" + particleP + "} (GeV)")
Best.GetXaxis().SetTitleSize(Best.GetXaxis().GetTitleSize() * 1.1)
Best.GetYaxis().SetTitle("Best Fit (pb)")
c1 = TCanvas("c1", "Exclusion Limits", 800, 600)
c1.cd()
#SetPad(c1.GetPad(0))
c1.GetPad(0).SetTopMargin(0.06)
c1.GetPad(0).SetRightMargin(0.05)
c1.GetPad(0).SetLeftMargin(0.12)
c1.GetPad(0).SetTicks(1, 1)
#c1.GetPad(0).SetGridx()
#c1.GetPad(0).SetGridy()
c1.GetPad(0).SetLogy()
Exp2s.Draw("A3")
Exp1s.Draw("SAME, 3")
for t in THEORY:
Theory[t].Draw("SAME, L3")
Theory[t].Draw("SAME, L3X0Y0")
Exp0s.Draw("SAME, L")
if not options.blind: Obs0s.Draw("SAME, L")
#setHistStyle(Exp2s)
Exp2s.GetXaxis().SetTitleSize(0.050)
Exp2s.GetYaxis().SetTitleSize(0.050)
Exp2s.GetXaxis().SetLabelSize(0.045)
Exp2s.GetYaxis().SetLabelSize(0.045)
Exp2s.GetXaxis().SetTitleOffset(0.90)
Exp2s.GetYaxis().SetTitleOffset(1.25)
Exp2s.GetYaxis().SetMoreLogLabels(True)
Exp2s.GetYaxis().SetNoExponent(True)
Exp2s.GetYaxis().SetRangeUser(0.01, 5.e3)
#else: Exp2s.GetYaxis().SetRangeUser(0.1, 1.e2)
Exp2s.GetXaxis().SetRangeUser(
mass[0], min(mass[-1],
MAXIMUM[channel] if channel in MAXIMUM else 1.e6))
drawAnalysis(channel)
drawRegion(channel, True)
drawCMS(LUMI, YEAR, "Preliminary") #Preliminary
# legend
top = 0.9
nitems = 4 + len(THEORY)
leg = TLegend(0.55, top - nitems * 0.3 / 5., 0.98, top)
leg.SetBorderSize(0)
leg.SetFillStyle(0) #1001
leg.SetFillColor(0)
leg.SetHeader("95% CL upper limits")
leg.AddEntry(Obs0s, "Observed", "l")
leg.AddEntry(Exp0s, "Expected", "l")
leg.AddEntry(Exp1s, "#pm 1 std. deviation", "f")
leg.AddEntry(Exp2s, "#pm 2 std. deviation", "f")
for t in THEORY:
leg.AddEntry(Theory[t], theoryLabel[t], "fl")
leg.Draw()
latex = TLatex()
latex.SetNDC()
latex.SetTextSize(0.045)
latex.SetTextFont(42)
#latex.DrawLatex(0.66, leg.GetY1()-0.045, particleP+" #rightarrow "+particle+"h")
leg2 = TLegend(0.12, 0.225 - 2 * 0.25 / 5., 0.65, 0.225)
leg2.SetBorderSize(0)
leg2.SetFillStyle(0) #1001
leg2.SetFillColor(0)
c1.GetPad(0).RedrawAxis()
"""
if True and channel.endswith('sl'):
mass, val = fillValues("./combine/alpha/X"+particle+"Hbonly_M%d.txt")
Exp, Obs = TGraphAsymmErrors(), TGraphAsymmErrors()
for i, m in enumerate(mass):
if not m in val: continue
Exp.SetPoint(Exp.GetN(), m, val[m][3])
Obs.SetPoint(Obs.GetN(), m, val[m][0])
Exp.SetLineWidth(3)
Exp.SetLineColor(602) #602
Exp.SetLineStyle(5)
Obs.SetLineWidth(3)
Obs.SetLineColor(602)
Exp.Draw("SAME, L")
Obs.Draw("SAME, L")
mass15, val15 = fillValues("./combine/Vh_2015/X"+particle+"h_M%d.txt")
Exp15, Obs15 = TGraphAsymmErrors(), TGraphAsymmErrors()
for i, m in enumerate(mass15):
if not m in val: continue
Exp15.SetPoint(Exp15.GetN(), m, val15[m][3]*multF*Theory['B3'].GetY()[i]*(0.625 if particle=='V' and m>3000 else 1.))
Obs15.SetPoint(Obs15.GetN(), m, val15[m][0]*multF*Theory['B3'].GetY()[i]*(0.625 if particle=='V' and m>3000 else 1.))
Exp15.SetLineWidth(3)
Exp15.SetLineColor(856) #602
Exp15.SetLineStyle(6)
Obs15.SetLineWidth(3)
Obs15.SetLineColor(856)
Exp15.Draw("SAME, L")
#Obs15.Draw("SAME, L")
leg2.AddEntry(Exp, "1+2 b-tag", "l")
"""
if True and channel == 'AZh':
massLL, valLL = fillValues("./combine/AZh/AZhll_M%d.txt")
ExpLL, ObsLL = TGraphAsymmErrors(), TGraphAsymmErrors()
for i, m in enumerate(massLL):
if not m in val: continue
ExpLL.SetPoint(ExpLL.GetN(), m, valLL[m][3] * multF)
ObsLL.SetPoint(ObsLL.GetN(), m, valLL[m][0] * multF)
ExpLL.SetLineWidth(3)
ExpLL.SetLineColor(833) #602
ExpLL.SetLineStyle(5)
ObsLL.SetLineWidth(3)
ObsLL.SetLineColor(833)
ExpLL.Draw("SAME, L")
#ObsLL.Draw("SAME, L")
massNN, valNN = fillValues("./combine/AZh/AZhnn_M%d.txt")
ExpNN, ObsNN = TGraphAsymmErrors(), TGraphAsymmErrors()
for i, m in enumerate(massNN):
if not m in val: continue
ExpNN.SetPoint(ExpNN.GetN(), m, valNN[m][3] * multF)
ObsNN.SetPoint(ObsNN.GetN(), m, valNN[m][0] * multF)
ExpNN.SetLineWidth(3)
ExpNN.SetLineColor(855) #602
ExpNN.SetLineStyle(6)
ObsNN.SetLineWidth(3)
ObsNN.SetLineColor(855)
ExpNN.Draw("SAME, L")
#ObsNN.Draw("SAME, L")
leg2.AddEntry(ExpLL,
"Expected, A #rightarrow Zh #rightarrow llb#bar{b}", "l")
leg2.AddEntry(ExpNN,
"Expected, A #rightarrow Zh #rightarrow #nu#nub#bar{b}",
"l")
if method == 'combo':
massAH, valAH = fillValues("./combine/dijet/X" + particle +
"Hah_M%d.txt")
ExpAH = TGraphAsymmErrors()
for i, m in enumerate(massAH):
if not m in val: continue
ExpAH.SetPoint(ExpAH.GetN(), m, valAH[m][3] * multF)
ExpAH.SetLineWidth(2)
ExpAH.SetLineColor(602) #602
ExpAH.SetLineStyle(4)
ExpAH.Draw("SAME, L")
massSL, valSL = fillValues("./combine/alpha/X" + particle +
"Hsl_M%d.txt")
ExpSL = TGraphAsymmErrors()
for i, m in enumerate(massSL):
if not m in val: continue
ExpSL.SetPoint(ExpSL.GetN(), m, valSL[m][3] * multF)
ExpSL.SetLineWidth(3)
ExpSL.SetLineColor(860 - 9) #602
ExpSL.SetLineStyle(7)
ExpSL.Draw("SAME, L")
leg2.AddEntry(ExpAH, "B2G-17-002", "l")
leg2.AddEntry(ExpSL, "B2G-17-004", "l")
leg2.Draw()
if not options.blind: Obs0s.Draw("SAME, L")
c1.GetPad(0).Update()
if not gROOT.IsBatch(): raw_input("Press Enter to continue...")
c1.Print("plotsLimit/Exclusion/" + channel + suffix + ".png")
c1.Print("plotsLimit/Exclusion/" + channel + suffix + ".pdf")
if 'ah' in channel or 'sl' in channel:
c1.Print("plotsLimit/Exclusion/" + channel + suffix + ".C")
c1.Print("plotsLimit/Exclusion/" + channel + suffix + ".root")
for t in THEORY:
print "Model", t, ":",
for m in range(mass[0], mass[-1], 1):
if not (Theory[t].Eval(m) > Obs0s.Eval(m)) == (
Theory[t].Eval(m + 1) > Obs0s.Eval(m + 1)):
print m,
print ""
print "p1s[",
for i in range(Exp0s.GetN()):
print Exp0s.GetY()[i] + Exp1s.GetErrorYhigh(i), ",",
print "],"
print "m1s[",
for i in range(Exp0s.GetN()):
print Exp0s.GetY()[i] - Exp1s.GetErrorYlow(i), ",",
print "],"
print "[",
for i in range(Exp0s.GetN()):
print Exp0s.GetY()[i], ",",
print "]"
#if not 'ah' in channel and not 'sl' in channel: return
# ---------- Significance ----------
c2 = TCanvas("c2", "Significance", 800, 600)
c2.cd()
c2.GetPad(0).SetTopMargin(0.06)
c2.GetPad(0).SetRightMargin(0.05)
c2.GetPad(0).SetTicks(1, 1)
c2.GetPad(0).SetGridx()
c2.GetPad(0).SetGridy()
Sign.GetYaxis().SetRangeUser(0., 5.)
Sign.Draw("AL3")
drawCMS(LUMI, YEAR, "Preliminary")
drawAnalysis(channel[1:3])
c2.Print("plotsLimit/Significance/" + channel + suffix + ".png")
c2.Print("plotsLimit/Significance/" + channel + suffix + ".pdf")
# c2.Print("plotsLimit/Significance/"+channel+suffix+".root")
# c2.Print("plotsLimit/Significance/"+channel+suffix+".C")
# ---------- p-Value ----------
c3 = TCanvas("c3", "p-Value", 800, 600)
c3.cd()
c3.GetPad(0).SetTopMargin(0.06)
c3.GetPad(0).SetRightMargin(0.05)
c3.GetPad(0).SetTicks(1, 1)
c3.GetPad(0).SetGridx()
c3.GetPad(0).SetGridy()
c3.GetPad(0).SetLogy()
pVal.Draw("AL3")
pVal.GetYaxis().SetRangeUser(2.e-7, 0.5)
ci = [
1., 0.317310508, 0.045500264, 0.002699796, 0.00006334, 0.000000573303,
0.000000001973
]
line = TLine()
line.SetLineColor(922)
line.SetLineStyle(7)
text = TLatex()
text.SetTextColor(922)
text.SetTextSize(0.025)
text.SetTextAlign(12)
for i in range(1, len(ci) - 1):
line.DrawLine(pVal.GetXaxis().GetXmin(), ci[i] / 2,
pVal.GetXaxis().GetXmax(), ci[i] / 2)
text.DrawLatex(pVal.GetXaxis().GetXmax() * 1.01, ci[i] / 2,
"%d #sigma" % i)
drawCMS(LUMI, YEAR, "Preliminary")
drawAnalysis(channel[1:3])
c3.Print("plotsLimit/pValue/" + channel + suffix + ".png")
c3.Print("plotsLimit/pValue/" + channel + suffix + ".pdf")
# c3.Print("plotsLimit/pValue/"+channel+suffix+".root")
# c3.Print("plotsLimit/pValue/"+channel+suffix+".C")
# --------- Best Fit ----------
c4 = TCanvas("c4", "Best Fit", 800, 600)
c4.cd()
c4.GetPad(0).SetTopMargin(0.06)
c4.GetPad(0).SetRightMargin(0.05)
c4.GetPad(0).SetTicks(1, 1)
c4.GetPad(0).SetGridx()
c4.GetPad(0).SetGridy()
Best.Draw("AL3")
drawCMS(LUMI, YEAR, "Preliminary")
drawAnalysis(channel[1:3])
c4.Print("plotsLimit/BestFit/" + channel + suffix + ".png")
c4.Print("plotsLimit/BestFit/" + channel + suffix + ".pdf")
# c4.Print("plotsLimit/BestFit/"+channel+suffix+".root")
# c4.Print("plotsLimit/BestFit/"+channel+suffix+".C")
if not gROOT.IsBatch(): raw_input("Press Enter to continue...")
if 'ah' in channel:
outFile = TFile("bands.root", "RECREATE")
outFile.cd()
pVal.Write("graph")
Best.Write("best")
outFile.Close()
0,
] * len(brazil_data))
rms = array("d", list(map(itemgetter(2), brazil_data)))
rms2 = array("d", [2 * r for r in rms])
low_2sigma = array("d", list(map(itemgetter(3), brazil_data)))
low_1sigma = array("d", list(map(itemgetter(4), brazil_data)))
high_1sigma = array("d", list(map(itemgetter(5), brazil_data)))
high_2sigma = array("d", list(map(itemgetter(6), brazil_data)))
mg = TMultiGraph()
#mg.SetTitle(title)
mg.SetTitle(job_id)
brazil_yellow = TGraphAsymmErrors(len(brazil_data), x, mean, xerr, xerr,
low_2sigma, high_2sigma)
brazil_yellow.SetFillColor(5)
brazil_yellow.SetFillStyle(1001)
brazil_yellow.SetLineColor(3)
brazil_yellow.SetLineWidth(10)
brazil_yellow.SetMarkerColor(3)
brazil_green = TGraphAsymmErrors(len(brazil_data), x, mean, xerr, xerr,
low_1sigma, high_1sigma)
brazil_green.SetFillColor(3)
brazil_green.SetFillStyle(1001)
brazil_green.SetLineColor(3)
brazil_green.SetLineWidth(3)
mg.Add(brazil_yellow)
mg.Add(brazil_green)
mg.Draw("a3")
def make1DLimitPlot(xtitle, xvals, obs, exp, exp1plus, exp1minus, exp2plus, exp2minus, theory):
gStyle.SetOptTitle(0)
axisTitleSize = 0.041
axisTitleOffset = 1.2
axisTitleSizeRatioX = 0.18
axisLabelSizeRatioX = 0.12
axisTitleOffsetRatioX = 0.94
axisTitleSizeRatioY = 0.15
axisLabelSizeRatioY = 0.108
axisTitleOffsetRatioY = 0.32
leftMargin = 0.15
rightMargin = 0.12
topMargin = 0.05
bottomMargin = 0.14
bottomMargin2 = 0.22
#c1 = TCanvas() #'c1', '', 200, 10, 700, 500 )
c1 = TCanvas( "c1", "c2", 200, 10, 700, 600 )
c1.SetHighLightColor(2)
c1.SetFillColor(0)
c1.SetBorderMode(0)
c1.SetBorderSize(2)
c1.SetLeftMargin(leftMargin)
c1.SetRightMargin(rightMargin)
c1.SetTopMargin(topMargin)
c1.SetBottomMargin(bottomMargin)
c1.SetFrameBorderMode(0)
c1.SetFrameBorderMode(0)
c1.SetLogy(1)
#c1.SetLogx(1)
c1.SetTickx(1)
c1.SetTicky(1)
#c1.SetGridx(True);
#c1.SetGridy(True);
if "c#tau" in xtitle:
c1.SetLogx(1);
exp2sigma_xsec = TGraphAsymmErrors(len(xvals), array('d', xvals), array('d', exp), \
array('d', [0]), array('d', [0]), array('d', exp2minus), array('d', exp2plus))
exp2sigma_xsec.Sort()
exp2sigma_xsec.Draw('A3')
exp2sigma_xsec.SetFillStyle(1001);
exp2sigma_xsec.SetFillColor(kOrange);
exp2sigma_xsec.SetLineColor(kOrange);
exp2sigma_xsec.GetYaxis().SetRangeUser(0.001,100);
exp2sigma_xsec.GetXaxis().SetLimits(0.8*min(xvals),1.1*max(xvals));
#exp2sigma_xsec.GetXaxis().SetTitle('m_{1} [GeV]')
#exp2sigma_xsec.GetXaxis().SetTitle('c#tau [cm]')
exp2sigma_xsec.GetXaxis().SetTitle(xtitle)
exp2sigma_xsec.GetXaxis().SetTitleOffset(axisTitleOffset)
exp2sigma_xsec.GetYaxis().SetTitle('95% C.L. #sigma(pp #rightarrow #chi_{1} #chi_{1} #mu^{+} #mu^{-}) [pb]')
exp2sigma_xsec.GetYaxis().SetTitleOffset(axisTitleOffset+0.1)
exp1sigma_xsec = TGraphAsymmErrors(len(xvals), array('d', xvals), array('d', exp), \
array('d', [0]), array('d', [0]), array('d', exp1minus), array('d', exp1plus))
exp1sigma_xsec.Sort()
exp1sigma_xsec.SetFillStyle(1001);
exp1sigma_xsec.SetFillColor(kGreen+1);
exp1sigma_xsec.SetLineColor(kGreen+1);
exp1sigma_xsec.Draw('3 SAME')
exp_xsec = TGraph(len(xvals), array('d', xvals), array('d', exp))
exp_xsec.Sort()
exp_xsec.SetLineWidth(2)
exp_xsec.SetLineStyle(1)
exp_xsec.SetLineColor(kRed)
exp_xsec.Draw('C SAME')
obs_xsec = TGraph(len(xvals), array('d', xvals), array('d', obs))
obs_xsec.Sort()
obs_xsec.SetLineWidth(3)
obs_xsec.SetLineColor(kBlack)
obs_xsec.SetMarkerColor(kBlack)
obs_xsec.SetMarkerStyle(20)
obs_xsec.SetMarkerSize(1)
obs_xsec.Draw('PC SAME')
theory_xsec = TGraph(len(xvals), array('d', xvals), array('d', theory))
theory_xsec.Sort()
theory_xsec.SetLineWidth(2)
theory_xsec.SetLineStyle(8)
theory_xsec.SetLineColor(kBlue)
theory_xsec.Draw('C SAME')
leg = TLegend(0.50,0.70,0.8,0.90);
leg.SetBorderSize(0);
leg.SetFillStyle(0);
leg.AddEntry(theory_xsec, "Theory", "l");
leg.AddEntry(obs_xsec, "Observed Limit", "pl");
leg.AddEntry(exp_xsec, "Expected Limit", "l");
leg.AddEntry(exp1sigma_xsec, "#pm 1 std. dev.", "f");
leg.AddEntry(exp2sigma_xsec, "#pm 2 std. dev.", "f");
leg.Draw()
drawCMSLogo(c1, 13, 122450)
# TCanvas.Update() draws the frame, after which one can change it
# c1.Update()
# c1.Modified()
# c1.Update()
c1.RedrawAxis()
c1.Draw()
wait(True)
800)
can_HV_scan_SL1_L1.SetGrid()
can_HV_scan_SL1_L1.cd()
##Prepare summary TGraph
graph_HV_L1 = TGraphAsymmErrors()
n = 0
for a in sorted(HV_scan_L1):
#for a in sorted(run_parameters):
##Fill the TGraph with threshold (x-axis) and rate (y-axis)
#######graph.SetPoint(n,int(run_parameters[a]['VTHR']),float(run_parameters[a]['RATE_SL1_L1']))
graph_HV_L1.SetPoint(n, int(a), float(HV_scan_L1[a]))
n = n + 1
graph_HV_L1.SetMarkerSize(1.)
graph_HV_L1.SetMarkerStyle(21)
graph_HV_L1.SetMarkerColor(418)
graph_HV_L1.SetFillColor(868)
graph_HV_L1.SetFillStyle(3844)
graph_HV_L1.SetLineColor(418 - 1)
graph_HV_L1.SetLineWidth(2)
graph_HV_L1.SetLineStyle(2)
graph_HV_L1.GetXaxis().SetTitle("HV [V]")
graph_HV_L1.GetYaxis().SetTitleOffset(1.2)
graph_HV_L1.GetYaxis().SetTitle("efficiency")
graph_HV_L1.GetYaxis().SetRangeUser(0, 1.01)
graph_HV_L1.Draw("APL")
latex = TLatex()
latex.SetNDC()
latex.SetTextSize(0.04)
latex.SetTextColor(1)
latex.SetTextFont(42)
latex.SetTextAlign(33)
def make_ratioplot(name,
ttbar_file=0,
qcd_file=0,
signal_files=[],
histo=0,
rebin=1,
minx=0,
maxx=0,
miny=0,
maxy=0,
logy=False,
xtitle='',
ytitle='',
textsizefactor=1,
signal_legend=[],
outfile=0,
signal_colors=[],
signal_zoom=1,
qcd_zoom=1,
ttbar_zoom=1,
ttbar_legend='t#bar{t}',
qcd_legend='QCD from MC',
dosys=False,
docms=True,
legendtitle=''):
###canvas setting up
canvas = 0
canvas = TCanvas(name, '', 0, 0, 600, 600)
canvas.SetLeftMargin(0.15)
canvas.SetRightMargin(0.05)
canvas.SetTopMargin(0.10)
canvas.SetBottomMargin(0.10)
charsize = 0.04
offset = 1.9
###latex label
latex = 0
latex = TLatex(0.6, 0.7, '13 TeV, 2.69 fb^{-1}')
latex.SetTextSize(charsize)
latex.SetNDC(1)
latex.SetTextFont(42)
###legend setting up
#legend=TLegend(0.0,0.75,0.99,1.04)
legend = TLegend(0.4, 0.6, 0.94, 0.95)
legend.SetNColumns(2)
legend.SetHeader('')
legend.SetFillStyle(0)
legend.SetBorderSize(0)
###mc stack
stack = THStack(name + '_stack', '')
qcd_histo = qcd_file.Get(histo).Clone(name + '_make_plot')
qcd_histo.Rebin(rebin)
ttbar_histo = ttbar_file.Get(histo).Clone()
ttbar_histo.Rebin(rebin)
ttbar_histo.SetFillColor(kRed - 9)
ttbar_histo.SetLineColor(kRed - 9)
ttbar_histo.SetMarkerColor(kRed - 9)
if ttbar_zoom != 1:
ttbar_histo.Scale(ttbar_zoom)
legend.AddEntry(ttbar_histo, ttbar_legend, 'f')
qcd_histo.SetFillColor(kOrange - 5)
qcd_histo.SetLineColor(kOrange - 5)
qcd_histo.SetMarkerColor(kOrange - 5)
if qcd_zoom != 1:
qcd_histo.Scale(qcd_zoom)
legend.AddEntry(qcd_histo, qcd_legend, 'f')
sum_mc = qcd_histo.Clone(histo + 'tmp')
sum_mc.Add(ttbar_histo)
stack.Add(ttbar_histo)
stack.Add(qcd_histo)
sum_mc.SetLineColor(kBlack)
sum_mc.SetFillStyle(0)
err = TGraphAsymmErrors(sum_mc)
legend.AddEntry(err, 'Total uncertainty', 'f')
if legendtitle == '':
legend.AddEntry(0, "", '')
legend.AddEntry(0, "g_{RS} #rightarrow t#bar{t} (2pb)", '')
else:
legend.AddEntry(0, "", '')
legend.AddEntry(0, legendtitle, '')
###signal setting up
signal_histos = []
colors = [
kBlack, kRed, kOrange, kBlue, kGreen + 3, 44, 45, 46, 47, 48, 49, 50,
51, 52, 53, 54, 55, 56, 57, 58, 59, 60
]
styles = [
1, 3, 5, 7, 7, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1
]
if signal_colors != []:
colors = signal_colors
for i in range(len(signal_files)):
signal_histos.append(signal_files[i].Get(histo).Clone())
signal_histos[i].SetLineWidth(3)
signal_histos[i].SetLineStyle(styles[i])
signal_histos[i].SetLineColor(colors[i])
signal_histos[i].SetMarkerColor(colors[i])
signal_histos[i].Rebin(rebin)
if signal_zoom != 1:
signal_histos[i].Scale(signal_zoom)
legend.AddEntry(signal_histos[i], signal_legend[i], 'l')
###mc shape line
ttbar_line = 0
ttbar_line = ttbar_histo.Clone()
ttbar_line.SetLineColor(kBlack)
ttbar_line.SetFillStyle(0)
###mc errors
if dosys:
sys_diff_qcd = []
sys_diff_ttbar = []
for imtt in range(1, ttbar_histo.GetNbinsX() + 1):
sys_diff_qcd.append([])
sys_diff_ttbar.append([])
#adding stat uncertainties <--removed
# for imtt in range(1,ttbar_histo.GetNbinsX()+1):
# sys_diff_ttbar[imtt-1].append(ttbar_histo.GetBinError(imtt))
# sys_diff_ttbar[imtt-1].append(-ttbar_histo.GetBinError(imtt))
# sys_diff_qcd[imtt-1].append(qcd_histo.GetBinError(imtt))
# sys_diff_qcd[imtt-1].append(-qcd_histo.GetBinError(imtt))
#adding flat uncertainties
for imtt in range(1, ttbar_histo.GetNbinsX() + 1):
#ttbar
for i in [
2.4, #pdf
10.0, #mu
3.0, #xsec
6.0, #toppt
1.0, #lumi
3.5, #jec
3.0, #jer
10.0, #btag
#3.0,#trig
10.0, #toptag
3.0
]: #pileup
sys_diff_ttbar[imtt - 1].append(
i / 100.0 * ttbar_histo.GetBinContent(imtt))
sys_diff_ttbar[imtt - 1].append(
-i / 100.0 * ttbar_histo.GetBinContent(imtt))
closureunc = 5.0
# if '1b' in histo:
# closureunc=5.0
# elif '2b' in histo:
# closureunc=10.0
for i in [
2.0, #modmass
closureunc
]: #closure
sys_diff_qcd[imtt - 1].append(i / 100.0 *
qcd_histo.GetBinContent(imtt))
sys_diff_qcd[imtt - 1].append(-i / 100.0 *
qcd_histo.GetBinContent(imtt))
# #3% trigger
# sys_diff_ttbar[imtt-1].append(0.03*ttbar_histo.GetBinContent(imtt))
# sys_diff_ttbar[imtt-1].append(-0.03*ttbar_histo.GetBinContent(imtt))
# #2.7% lumi
# sys_diff_ttbar[imtt-1].append(0.023*ttbar_histo.GetBinContent(imtt))
# sys_diff_ttbar[imtt-1].append(-0.023*ttbar_histo.GetBinContent(imtt))
# #15% ttbar
# #sys_diff_ttbar[imtt-1].append(0.15*ttbar_histo.GetBinContent(imtt))
# #sys_diff_ttbar[imtt-1].append(-0.15*ttbar_histo.GetBinContent(imtt))
# #2.8% QCD
# sys_diff_qcd[imtt-1].append(0.028*qcd_histo.GetBinContent(imtt))
# sys_diff_qcd[imtt-1].append(-0.028*qcd_histo.GetBinContent(imtt))
#combining uncertainties
sys_tot_ttbar = []
sys_tot_qcd = []
sys_tot = []
sys_global_ttbar = [0.0, 0.0]
sys_global_qcd = [0.0, 0.0]
nevt_global = [0.0, 0.0, 0.0]
for imtt in range(1, ttbar_histo.GetNbinsX() + 1):
uperr_qcd = 0
downerr_qcd = 0
uperr_ttbar = 0
downerr_ttbar = 0
for error in sys_diff_ttbar[imtt - 1]:
if error < 0:
downerr_ttbar = downerr_ttbar + error * error
else:
uperr_ttbar = uperr_ttbar + error * error
for error in sys_diff_qcd[imtt - 1]:
if error < 0:
downerr_qcd = downerr_qcd + error * error
else:
uperr_qcd = uperr_qcd + error * error
sys_tot_ttbar.append(
[math.sqrt(downerr_ttbar),
math.sqrt(uperr_ttbar)])
sys_tot_qcd.append([math.sqrt(downerr_qcd), math.sqrt(uperr_qcd)])
sys_tot.append([
math.sqrt(downerr_qcd + downerr_ttbar),
math.sqrt(uperr_qcd + uperr_ttbar)
])
sys_global_qcd[0] = sys_global_qcd[0] + downerr_qcd
sys_global_qcd[1] = sys_global_qcd[1] + uperr_qcd
sys_global_ttbar[0] = sys_global_ttbar[0] + downerr_ttbar
sys_global_ttbar[1] = sys_global_ttbar[1] + uperr_ttbar
# nevt_global[0]=nevt_global[0]+data_histo.GetBinContent(imtt)
nevt_global[1] = nevt_global[1] + qcd_histo.GetBinContent(imtt)
nevt_global[2] = nevt_global[2] + ttbar_histo.GetBinContent(imtt)
#print 'ttbar+qcd',math.sqrt(uperr_qcd+uperr_ttbar),math.sqrt(downerr_qcd+downerr_ttbar)
#print 'qcd',math.sqrt(uperr_qcd),math.sqrt(downerr_qcd)
#print 'ttbar',math.sqrt(uperr_ttbar),math.sqrt(downerr_ttbar)
err.SetPointEYhigh(imtt - 1, math.sqrt(uperr_qcd + uperr_ttbar))
err.SetPointEYlow(imtt - 1, math.sqrt(downerr_qcd + downerr_ttbar))
sys_global = [0.0, 0.0]
sys_global[0] = math.sqrt(sys_global_qcd[0] + sys_global_ttbar[0])
sys_global[1] = math.sqrt(sys_global_qcd[1] + sys_global_ttbar[1])
sys_global_qcd[0] = math.sqrt(sys_global_qcd[0])
sys_global_qcd[1] = math.sqrt(sys_global_qcd[1])
sys_global_ttbar[0] = math.sqrt(sys_global_ttbar[0])
sys_global_ttbar[1] = math.sqrt(sys_global_ttbar[1])
# print name
# print "\hline"
# print "Multijet QCD & $%.0f^{+%.0f}_{-%.0f}$ \\\\" % (nevt_global[1],sys_global_qcd[1],sys_global_qcd[0])
# print "SM ttbar & $%.0f^{+%.0f}_{-%.0f}$ \\\\" % (nevt_global[2],sys_global_ttbar[1],sys_global_ttbar[0])
# print "\hline"
# print "Total background & $%.0f^{+%.0f}_{-%.0f}$ \\\\" % (nevt_global[1]+nevt_global[2],sys_global[1],sys_global[0])
# print 'DATA & %.0f' %nevt_global[0]
err.SetFillStyle(3145)
err.SetFillColor(kGray + 1)
###drawing top
canvas.cd()
stack.Draw('hist')
stack.GetXaxis().SetTitle(ttbar_histo.GetXaxis().GetTitle())
stack.GetYaxis().SetTitle(ttbar_histo.GetYaxis().GetTitle())
stack.GetXaxis().SetLabelSize(charsize)
stack.GetXaxis().SetTitleSize(charsize)
stack.GetYaxis().SetLabelSize(charsize)
stack.GetYaxis().SetTitleSize(charsize)
stack.GetYaxis().SetTitleOffset(offset)
if minx != 0 or maxx != 0:
stack.GetXaxis().SetRangeUser(minx, maxx)
#else:
# stack.GetXaxis().SetRangeUser(0,4000)
if miny != 0 or maxy != 0:
stack.SetMaximum(maxy)
stack.SetMinimum(miny)
else:
if logy:
stack.SetMaximum(stack.GetMaximum() * 10)
stack.SetMinimum(0.2)
else:
stack.SetMaximum(stack.GetMaximum() * 2.0)
stack.SetMinimum(0.001)
err.Draw('2')
sum_mc.Draw('samehist')
if ttbar_file != 0:
ttbar_line.Draw('samehist')
for i in signal_histos:
i.Draw('samehist')
if logy:
canvas.SetLogy()
legend.Draw()
latex2text = ''
if 'ldy_0b' in name:
latex2text = '#Deltay < 1; 0 b tag'
elif 'ldy_1b' in name:
latex2text = '#Deltay < 1; 1 b tag'
elif 'ldy_2b' in name:
latex2text = '#Deltay < 1; 2 b tag'
elif 'hdy_0b' in name:
latex2text = '#Deltay > 1; 0 b tag'
elif 'hdy_1b' in name:
latex2text = '#Deltay > 1; 1 b tag'
elif 'hdy_2b' in name:
latex2text = '#Deltay > 1; 2 b tag'
latex2 = TLatex(0.19, 0.7, latex2text)
latex2.SetTextSize(0.03)
latex2.SetNDC(1)
latex2.SetTextFont(42)
latex2.Draw()
if docms:
if '3000' in name:
CMS_lumi.CMS_lumi(canvas, 3, 11)
elif '1000' in name:
CMS_lumi.CMS_lumi(canvas, 2, 11)
elif '300' in name:
CMS_lumi.CMS_lumi(canvas, 1, 11)
elif '36' in name:
CMS_lumi.CMS_lumi(canvas, 0, 11)
###saving
canvas.SaveAs('pdf/' + name + '.pdf')
if outfile != 0:
canvas.Write()
def limit2HDM():
global signals
signals = range(800, 2000 + 1, 50)
multF = HTOBB
THEORY = ['T1', 'T2']
mass, val = fillValues("./combine/AZh/AZh_M%d.txt")
Obs0s = TGraph()
Exp0s = TGraph()
Exp1s = TGraphAsymmErrors()
Exp2s = TGraphAsymmErrors()
massB, valB = fillValues("./combine/BBAZh/BBAZh_M%d.txt")
Obs0sB = TGraph()
Exp0sB = TGraph()
Exp1sB = TGraphAsymmErrors()
Exp2sB = TGraphAsymmErrors()
for i, m in enumerate(mass):
if not m in val:
print "Key Error:", m, "not in value map"
continue
n = Exp0s.GetN()
Obs0s.SetPoint(n, m, val[m][0] * multF)
Exp0s.SetPoint(n, m, val[m][3] * multF)
Exp1s.SetPoint(n, m, val[m][3] * multF)
Exp1s.SetPointError(n, 0., 0., val[m][3] * multF - val[m][2] * multF,
val[m][4] * multF - val[m][3] * multF)
Exp2s.SetPoint(n, m, val[m][3] * multF)
Exp2s.SetPointError(n, 0., 0., val[m][3] * multF - val[m][1] * multF,
val[m][5] * multF - val[m][3] * multF)
Obs0sB.SetPoint(n, m, valB[m][0] * multF)
Exp0sB.SetPoint(n, m, valB[m][3] * multF)
Exp1sB.SetPoint(n, m, valB[m][3] * multF)
Exp1sB.SetPointError(n, 0., 0.,
valB[m][3] * multF - valB[m][2] * multF,
valB[m][4] * multF - valB[m][3] * multF)
Exp2sB.SetPoint(n, m, valB[m][3] * multF)
Exp2sB.SetPointError(n, 0., 0.,
valB[m][3] * multF - valB[m][1] * multF,
valB[m][5] * multF - valB[m][3] * multF)
col = 629
Exp2s.SetLineWidth(2)
Exp2s.SetLineStyle(1)
Obs0s.SetLineWidth(3)
Obs0s.SetMarkerStyle(0)
Obs0s.SetLineColor(1)
Exp0s.SetLineStyle(2)
Exp0s.SetLineWidth(3)
Exp0s.SetLineColor(1)
# Exp1s.SetFillColorAlpha(col, 0.4) #kGreen+1
# Exp1s.SetLineColorAlpha(col, 0.4)
# Exp2s.SetFillColorAlpha(col, 0.2) #kOrange
# Exp2s.SetLineColorAlpha(col, 0.2)
Exp1s.SetFillColor(417)
Exp1s.SetLineColor(417)
Exp2s.SetFillColor(800)
Exp2s.SetLineColor(800)
colB = 922
Exp2sB.SetLineWidth(2)
Obs0sB.SetLineStyle(9)
Obs0sB.SetLineWidth(3)
Obs0sB.SetMarkerStyle(0)
Obs0sB.SetLineColor(colB)
Exp0sB.SetLineStyle(8)
Exp0sB.SetLineWidth(3)
Exp0sB.SetLineColor(colB)
Exp1sB.SetFillColorAlpha(colB, 0.4) #kGreen+1
Exp1sB.SetLineColorAlpha(colB, 0.4)
Exp2sB.SetFillColorAlpha(colB, 0.2) #kOrange
Exp2sB.SetLineColorAlpha(colB, 0.2)
Exp2s.GetXaxis().SetTitle("m_{A} (GeV)")
Exp2s.GetXaxis().SetTitleSize(Exp2s.GetXaxis().GetTitleSize() * 1.25)
Exp2s.GetXaxis().SetNoExponent(True)
Exp2s.GetXaxis().SetMoreLogLabels(True)
Exp2s.GetYaxis().SetTitle(
"#sigma(A) #bf{#it{#Beta}}(A #rightarrow Zh) #bf{#it{#Beta}}(h #rightarrow bb) (fb)"
)
Exp2s.GetYaxis().SetTitleOffset(1.5)
Exp2s.GetYaxis().SetNoExponent(True)
Exp2s.GetYaxis().SetMoreLogLabels()
Theory = {}
#for t in THEORY:
# Theory[t] = TGraphAsymmErrors()
# for m in sorted(THDM[t]['ggA'].keys()):
# if m < mass[0] or m > mass[-1]: continue
# Xs, Xs_Up, Xs_Down = 0., 0., 0.
# Xs = THDM[t]['ggA'][m]
# Xs_Up = Xs*(1.+math.sqrt((THDM['PDF']['ggA'][m][0]-1.)**2 + (THDM['QCD']['ggA'][m][0]-1.)**2))
# Xs_Down = Xs*(1.-math.sqrt((1.-THDM['PDF']['ggA'][m][1])**2 + (1.-THDM['QCD']['ggA'][m][1])**2))
# n = Theory[t].GetN()
# Theory[t].SetPoint(n, m, Xs)
# Theory[t].SetPointError(n, 0., 0., (Xs-Xs_Down), (Xs_Up-Xs))
# Theory[t].SetLineColor(theoryLineColor[t])
# Theory[t].SetFillColor(theoryFillColor[t])
# Theory[t].SetFillStyle(theoryFillStyle[t])
# Theory[t].SetLineWidth(2)
# #Theory[t].SetLineStyle(7)
c1 = TCanvas("c1", "Exclusion Limits", 800, 600)
c1.cd()
#SetPad(c1.GetPad(0))
c1.GetPad(0).SetTopMargin(0.06)
c1.GetPad(0).SetRightMargin(0.05)
c1.GetPad(0).SetLeftMargin(0.12)
c1.GetPad(0).SetTicks(1, 1)
c1.GetPad(0).SetLogy()
Exp2s.Draw("A3")
Exp1s.Draw("SAME, 3")
Exp0s.Draw("SAME, L")
# Exp2sB.Draw("SAME, 3")
# Exp1sB.Draw("SAME, 3")
Exp0sB.Draw("SAME, L")
if not options.blind:
Obs0s.Draw("SAME, L")
Obs0sB.Draw("SAME, L")
for t in THEORY:
Theory[t].Draw("SAME, L3")
Theory[t].Draw("SAME, L3X0Y0")
#setHistStyle(Exp2s)
# Exp2s.GetXaxis().SetTitleSize(0.045)
# Exp2s.GetYaxis().SetTitleSize(0.04)
# Exp2s.GetXaxis().SetLabelSize(0.04)
# Exp2s.GetYaxis().SetLabelSize(0.04)
# Exp2s.GetXaxis().SetTitleOffset(1)
# Exp2s.GetYaxis().SetTitleOffset(1.25)
Exp2s.GetXaxis().SetTitleSize(0.050)
Exp2s.GetYaxis().SetTitleSize(0.050)
Exp2s.GetXaxis().SetLabelSize(0.045)
Exp2s.GetYaxis().SetLabelSize(0.045)
Exp2s.GetXaxis().SetTitleOffset(0.90)
Exp2s.GetYaxis().SetTitleOffset(1.25)
Exp2s.GetYaxis().SetMoreLogLabels(True)
Exp2s.GetYaxis().SetNoExponent(True)
Exp2s.GetYaxis().SetRangeUser(0.5, 1.e3)
Exp2s.GetXaxis().SetRangeUser(mass[0], mass[-1])
drawAnalysis('AZh')
drawRegion('AZHsl', True)
drawCMS(LUMI, "") #Preliminary
#drawCMS(LUMI, "Work in Progress", suppressCMS=True)
# legend
leg = TLegend(0.6, 0.90, 0.99, 0.90)
leg.SetBorderSize(0)
leg.SetFillStyle(0) #1001
leg.SetFillColor(0)
leg.SetHeader("95% CL upper limits")
leg.AddEntry(None, "gg #rightarrow A #rightarrow Zh",
"") #"95% CL upper limits"
leg.AddEntry(Obs0s, "Observed", "l")
leg.AddEntry(Exp0s, "Expected", "l")
leg.AddEntry(Exp1s, "#pm 1 std. deviation", "f")
leg.AddEntry(Exp2s, "#pm 2 std. deviation", "f")
leg.AddEntry(None, "", "")
leg.AddEntry(None, "bbA #rightarrow Zh", "")
leg.AddEntry(Obs0sB, "Observed", "l")
leg.AddEntry(Exp0sB, "Expected", "l")
leg.SetY1(leg.GetY2() - leg.GetNRows() * 0.045)
leg.Draw()
# latex = TLatex()
# latex.SetNDC()
# latex.SetTextSize(0.040)
# latex.SetTextFont(42)
# latex.DrawLatex(0.65, leg.GetY1()-0.045, "cos(#beta-#alpha)=0.25, tan(#beta)=1")
# legB = TLegend(0.12, 0.4-4*0.3/5., 0.65, 0.4)
legB = TLegend(0.15, 0.27, 0.68, 0.27)
legB.SetBorderSize(0)
legB.SetFillStyle(0) #1001
legB.SetFillColor(0)
for t in THEORY:
legB.AddEntry(Theory[t], theoryLabel[t], "fl")
legB.AddEntry(None, "cos(#beta-#alpha)=0.25, tan(#beta)=1", "")
legB.SetY1(legB.GetY2() - legB.GetNRows() * 0.045)
legB.Draw()
c1.GetPad(0).RedrawAxis()
leg.Draw()
c1.Update()
if not gROOT.IsBatch(): raw_input("Press Enter to continue...")
c1.Print("plotsLimit/Exclusion/THDM.png")
c1.Print("plotsLimit/Exclusion/THDM.pdf")
def makeBiasPlot(output,
muFile,
chan,
interference,
printStats=False,
obs2="",
ratioLabel=""):
mu = open(muFile, 'r')
limits = {}
mux = []
muy = []
mu1SigLow = []
mu1SigHigh = []
mu2SigLow = []
mu2SigHigh = []
for entry in mu:
massPoint = float(entry.split()[0])
limitEntry = float(entry.split()[1])
if massPoint not in limits: limits[massPoint] = []
limits[massPoint].append(limitEntry)
if printStats: print "len limits:", len(limits)
for massPoint in sorted(limits):
limits[massPoint].sort()
numLimits = len(limits[massPoint])
nrExpts = len(limits[massPoint])
medianNr = int(nrExpts * 0.5)
#get indexes:
upper1Sig = int(nrExpts * (1 - (1 - 0.68) * 0.5))
lower1Sig = int(nrExpts * (1 - 0.68) * 0.5)
upper2Sig = int(nrExpts * (1 - (1 - 0.95) * 0.5))
lower2Sig = int(nrExpts * (1 - 0.95) * 0.5)
if printStats:
print massPoint, ":", limits[massPoint][lower2Sig], limits[
massPoint][lower1Sig], limits[massPoint][medianNr], limits[
massPoint][upper1Sig], limits[massPoint][upper2Sig]
#fill lists:
mux.append(massPoint)
print massPoint, limits[massPoint][medianNr]
muy.append(limits[massPoint][medianNr])
mu1SigLow.append(limits[massPoint][lower1Sig])
mu1SigHigh.append(limits[massPoint][upper1Sig])
mu2SigLow.append(limits[massPoint][lower2Sig])
mu2SigHigh.append(limits[massPoint][upper2Sig])
muX = numpy.array(mux)
muY = numpy.array(muy)
values2 = []
xPointsForValues2 = []
values = []
xPointsForValues = []
if printStats: print "length of mux: ", len(mux)
if printStats: print "length of mu1SigLow: ", len(mu1SigLow)
if printStats: print "length of mu1SigHigh: ", len(mu1SigHigh)
#Here is some Voodoo via Sam:
for x in range(0, len(mux)):
values2.append(mu2SigLow[x])
xPointsForValues2.append(mux[x])
for x in range(len(mux) - 1, 0 - 1, -1):
values2.append(mu2SigHigh[x])
xPointsForValues2.append(mux[x])
if printStats: print "length of values2: ", len(values2)
for x in range(0, len(mux)):
values.append(mu1SigLow[x])
xPointsForValues.append(mux[x])
for x in range(len(mux) - 1, 0 - 1, -1):
values.append(mu1SigHigh[x])
xPointsForValues.append(mux[x])
if printStats: print "length of values: ", len(values)
mu2Sig = numpy.array(values2)
xPoints2 = numpy.array(xPointsForValues2)
mu1Sig = numpy.array(values)
xPoints = numpy.array(xPointsForValues)
if printStats: print "xPoints2: ", xPoints2
if printStats: print "mu2Sig: ", mu2Sig
if printStats: print "xPoints: ", xPoints
if printStats: print "mu1Sig: ", mu1Sig
GraphErr2Sig = TGraphAsymmErrors(len(xPoints), xPoints2, mu2Sig)
GraphErr2Sig.SetFillColor(ROOT.kYellow + 1)
GraphErr1Sig = TGraphAsymmErrors(len(xPoints), xPoints, mu1Sig)
GraphErr1Sig.SetFillColor(ROOT.kGreen)
cCL = TCanvas("cCL", "cCL", 0, 0, 800, 500)
gStyle.SetOptStat(0)
plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0, 1, 1)
plotPad.Draw()
plotPad.cd()
muX = numpy.array(mux)
muY = numpy.array(muy)
GraphMU = TGraph(len(muX), muX, muY)
GraphMU.SetLineWidth(3)
GraphMU.SetLineStyle(2)
GraphMU.SetLineColor(ROOT.kBlue)
#Draw the graphs:
DummyGraph = TH1F("DummyGraph", "", 100, 10, 40)
DummyGraph.GetXaxis().SetTitle("#Lambda [TeV]")
DummyGraph.GetYaxis().SetTitle("#hat{#mu}")
gStyle.SetOptStat(0)
if "Des" in output:
DummyGraph.GetXaxis().SetRangeUser(10, 28)
else:
DummyGraph.GetXaxis().SetRangeUser(10, 40)
DummyGraph.SetMinimum(-2)
DummyGraph.SetMaximum(10)
DummyGraph.GetXaxis().SetLabelSize(0.04)
DummyGraph.GetXaxis().SetTitleSize(0.045)
DummyGraph.GetXaxis().SetTitleOffset(1.)
DummyGraph.GetYaxis().SetLabelSize(0.04)
DummyGraph.GetYaxis().SetTitleSize(0.045)
DummyGraph.GetYaxis().SetTitleOffset(1.)
DummyGraph.Draw()
DummyGraph.SetLineColor(ROOT.kWhite)
if (FULL):
GraphErr2Sig.Draw("F")
GraphErr1Sig.Draw("F")
GraphMU.Draw("lpsame")
else:
GraphMU.Draw("lp")
plCMS = TPaveLabel(.12, .81, .22, .88, "CMS", "NBNDC")
#plCMS.SetTextSize(0.8)
plCMS.SetTextAlign(12)
plCMS.SetTextFont(62)
plCMS.SetFillColor(0)
plCMS.SetFillStyle(0)
plCMS.SetBorderSize(0)
plCMS.Draw()
plPrelim = TPaveLabel(.12, .76, .25, .82, "Preliminary", "NBNDC")
plPrelim.SetTextSize(0.6)
plPrelim.SetTextAlign(12)
plPrelim.SetTextFont(52)
plPrelim.SetFillColor(0)
plPrelim.SetFillStyle(0)
plPrelim.SetBorderSize(0)
plPrelim.Draw()
cCL.SetTickx(1)
cCL.SetTicky(1)
cCL.RedrawAxis()
cCL.Update()
#leg=TLegend(0.65,0.65,0.87,0.87,"","brNDC")
leg = TLegend(0.540517, 0.623051, 0.834885, 0.878644, "", "brNDC")
# leg=TLegend(0.55,0.55,0.87,0.87,"","brNDC")
leg.SetTextSize(0.032)
leg.AddEntry(GraphMU, "median value", "l")
if (FULL):
leg.AddEntry(GraphErr1Sig, "1#sigma quantile", "f")
leg.AddEntry(GraphErr2Sig, "2#sigma quantile", "f")
leg.SetLineWidth(0)
leg.SetLineStyle(0)
leg.SetFillStyle(0)
leg.SetLineColor(0)
leg.Draw("hist")
if "Moriond" in output:
if (chan == "mumu"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"36.3 fb^{-1} (13 TeV, #mu#mu)", "NBNDC")
elif (chan == "elel"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"35.9 fb^{-1} (13 TeV, ee)", "NBNDC")
elif (chan == "elmu"):
plLumi = TPaveLabel(
.4, .905, .9, .99,
"35.9 fb^{-1} (13 TeV, ee) + 36.3 fb^{-1} (13 TeV, #mu#mu)",
"NBNDC")
else:
if (chan == "mumu"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"13.0 fb^{-1} (13 TeV, #mu#mu)", "NBNDC")
elif (chan == "elel"):
plLumi = TPaveLabel(.65, .905, .9, .99, "2.7 fb^{-1} (13 TeV, ee)",
"NBNDC")
elif (chan == "elmu"):
plLumi = TPaveLabel(
.4, .905, .9, .99,
"12.4 fb^{-1} (13 TeV, ee) + 13.0 fb^{-1} (13 TeV, #mu#mu)",
"NBNDC")
plLumi.SetTextSize(0.5)
plLumi.SetTextFont(42)
plLumi.SetFillColor(0)
plLumi.SetBorderSize(0)
plLumi.Draw()
maxX = 40
if "Des" in output:
maxX = 28
line = ROOT.TLine(10, 0, maxX, 0)
if "mu1" in output:
line = ROOT.TLine(10, 1, maxX, 1)
line.SetLineStyle(ROOT.kDashed)
line.Draw("same")
plotPad.RedrawAxis()
cCL.Update()
printPlots(cCL, output)
def pullsVertical(fileName):
content = filterPullFile(fileName)
nbins, off = len(content), 0.10
b_pulls = TH1F("b_pulls", ";;Pulls", nbins, 0. - off, nbins - off)
s_pulls = TH1F("s_pulls", ";;Pulls", nbins, 0. + off, nbins + off) #
for i, s in enumerate(content):
l = s.split()
b_pulls.GetXaxis().SetBinLabel(i + 1, l[0])
s_pulls.GetXaxis().SetBinLabel(i + 1, l[0])
b_pulls.SetBinContent(i + 1, float(l[1]))
b_pulls.SetBinError(i + 1, float(l[2]))
s_pulls.SetBinContent(i + 1, float(l[3]))
s_pulls.SetBinError(i + 1, float(l[4]))
b_pulls.SetFillStyle(3005)
b_pulls.SetFillColor(923)
b_pulls.SetLineColor(923)
b_pulls.SetLineWidth(1)
b_pulls.SetMarkerStyle(20)
b_pulls.SetMarkerSize(1.25)
s_pulls.SetLineColor(602)
s_pulls.SetMarkerColor(602)
s_pulls.SetMarkerStyle(24) #24
s_pulls.SetLineWidth(1)
b_pulls.GetYaxis().SetRangeUser(-2.5, 2.5)
# Graphs
h_pulls = TH2F("pulls", "", 6, -3., 3., nbins, 0, nbins)
B_pulls = TGraphAsymmErrors(nbins)
S_pulls = TGraphAsymmErrors(nbins)
boxes = []
canvas = TCanvas("canvas", "Pulls", 600, 150 + nbins * 10) #nbins*20)
canvas.cd()
canvas.SetGrid(0, 1)
canvas.GetPad(0).SetTopMargin(0.01)
canvas.GetPad(0).SetRightMargin(0.01)
canvas.GetPad(0).SetBottomMargin(0.05)
canvas.GetPad(0).SetLeftMargin(0.25) #(0.25)#(0.065)
canvas.GetPad(0).SetTicks(1, 1)
for i, s in enumerate(content):
l = s.split()
if "1034h" in l[0]: l[0] = "CMS_PDF_13TeV"
h_pulls.GetYaxis().SetBinLabel(i + 1, l[0].replace('CMS2016_', '')) #C
#y1 = gStyle.GetPadBottomMargin()
#y2 = 1. - gStyle.GetPadTopMargin()
#h = (y2 - y1) / float(nbins)
#y1 = y1 + float(i) * h
#y2 = y1 + h
#box = TPaveText(0, y1, 1, y2, 'NDC')
#box.SetFillColor(0)
#box.SetTextSize(0.02)
#box.SetBorderSize(0)
#box.SetTextAlign(12)
#box.SetMargin(0.005)
#if i % 2 == 0:
# box.SetFillColor(18)
#box.Draw()
#boxes.append(box)
B_pulls.SetPoint(i + 1, float(l[1]), float(i + 1) - 0.3) #C
B_pulls.SetPointError(i + 1, float(l[2]), float(l[2]), 0., 0.) #C
for i, s in enumerate(content):
l = s.split()
S_pulls.SetPoint(i + 1, float(l[3]), float(i + 1) - 0.7) #C
S_pulls.SetPointError(i + 1, float(l[4]), float(l[4]), 0., 0.) #C
h_pulls.GetXaxis().SetTitle("(#hat{#theta} - #theta_{0}) / #Delta#theta")
h_pulls.GetXaxis().SetLabelOffset(-0.01)
h_pulls.GetXaxis().SetTitleOffset(.6)
h_pulls.GetYaxis().SetNdivisions(nbins, 0, 0)
B_pulls.SetFillColor(1)
B_pulls.SetLineColor(1)
B_pulls.SetLineStyle(1)
B_pulls.SetLineWidth(2)
B_pulls.SetMarkerColor(1)
B_pulls.SetMarkerStyle(20)
B_pulls.SetMarkerSize(1) #(0.75)
S_pulls.SetFillColor(629)
S_pulls.SetLineColor(629)
S_pulls.SetMarkerColor(629)
S_pulls.SetLineWidth(2)
S_pulls.SetMarkerStyle(20)
S_pulls.SetMarkerSize(1)
box1 = TBox(-1., 0., 1., nbins)
box1.SetFillStyle(3001)
#box1.SetFillStyle(0)
box1.SetFillColor(417)
box1.SetLineWidth(2)
box1.SetLineStyle(2)
box1.SetLineColor(417)
box2 = TBox(-2., 0., 2., nbins)
box2.SetFillStyle(3001)
#box2.SetFillStyle(0)
box2.SetFillColor(800)
box2.SetLineWidth(2)
box2.SetLineStyle(2)
box2.SetLineColor(800)
leg = TLegend(0.1, -0.05, 0.7, 0.08)
leg.SetBorderSize(0)
leg.SetFillStyle(0)
leg.SetFillColor(0)
leg.SetNColumns(2)
leg.AddEntry(B_pulls, "B-only fit", "lp")
leg.AddEntry(S_pulls, "S+B fit", "lp")
if text: leg.AddEntry(0, text, "")
h_pulls.Draw("")
box2.Draw()
box1.Draw()
B_pulls.Draw("P6SAME")
S_pulls.Draw("P6SAME")
leg.Draw()
# drawCMS(35867, "Preliminary")
# drawAnalysis("VH")
# drawRegion(outName)
canvas.Print(outName + ".png")
canvas.Print(outName + ".pdf")
if not gROOT.IsBatch(): raw_input("Press Enter to continue...")
def makeLimitPlot(output,
obs,
exp,
chan,
interference,
printStats=False,
obs2="",
ratioLabel=""):
fileObs = open(obs, 'r')
fileExp = open(exp, 'r')
observedx = []
observedy = []
obsLimits = {}
xSecs = getFittedXSecCurve("CI_%s" % interference, 1.3)
for entry in fileObs:
massPoint = float(entry.split()[0])
limitEntry = float(entry.split()[1]) * xSecs.Eval(
int(float(entry.split()[0])))
if massPoint not in obsLimits: obsLimits[massPoint] = []
obsLimits[massPoint].append(limitEntry)
if printStats: print "len obsLimits:", len(obsLimits)
for massPoint in sorted(obsLimits):
observedx.append(massPoint)
observedy.append(numpy.mean(obsLimits[massPoint]))
if (numpy.std(obsLimits[massPoint]) / numpy.mean(obsLimits[massPoint])
> 0.05):
print massPoint, " mean: ", numpy.mean(
obsLimits[massPoint]), " std dev: ", numpy.std(
obsLimits[massPoint]), " from: ", obsLimits[massPoint]
if not obs2 == "":
fileObs2 = open(obs2, 'r')
observedx2 = []
observedy2 = []
obsLimits2 = {}
for entry in fileObs2:
massPoint = float(entry.split()[0])
limitEntry = float(entry.split()[1]) * xSecs.Eval(
int(float(entry.split()[0])))
if massPoint not in obsLimits2: obsLimits2[massPoint] = []
obsLimits2[massPoint].append(limitEntry)
if printStats: print "len obsLimits:", len(obsLimits2)
for massPoint in sorted(obsLimits2):
observedx2.append(massPoint)
observedy2.append(numpy.mean(obsLimits2[massPoint]))
if (numpy.std(obsLimits2[massPoint]) /
numpy.mean(obsLimits2[massPoint]) > 0.05):
print massPoint, " mean: ", numpy.mean(
obsLimits2[massPoint]), " std dev: ", numpy.std(
obsLimits2[massPoint]
), " from: ", obsLimits2[massPoint]
limits = {}
expectedx = []
expectedy = []
expected1SigLow = []
expected1SigHigh = []
expected2SigLow = []
expected2SigHigh = []
for entry in fileExp:
massPoint = float(entry.split()[0])
limitEntry = float(entry.split()[1]) * xSecs.Eval(
int(float(entry.split()[0])))
if massPoint not in limits: limits[massPoint] = []
limits[massPoint].append(limitEntry)
if printStats: print "len limits:", len(limits)
for massPoint in sorted(limits):
limits[massPoint].sort()
numLimits = len(limits[massPoint])
nrExpts = len(limits[massPoint])
medianNr = int(nrExpts * 0.5)
#get indexes:
upper1Sig = int(nrExpts * (1 - (1 - 0.68) * 0.5))
lower1Sig = int(nrExpts * (1 - 0.68) * 0.5)
upper2Sig = int(nrExpts * (1 - (1 - 0.95) * 0.5))
lower2Sig = int(nrExpts * (1 - 0.95) * 0.5)
if printStats:
print massPoint, ":", limits[massPoint][lower2Sig], limits[
massPoint][lower1Sig], limits[massPoint][medianNr], limits[
massPoint][upper1Sig], limits[massPoint][upper2Sig]
#fill lists:
expectedx.append(massPoint)
print massPoint, limits[massPoint][medianNr]
expectedy.append(limits[massPoint][medianNr])
expected1SigLow.append(limits[massPoint][lower1Sig])
expected1SigHigh.append(limits[massPoint][upper1Sig])
expected2SigLow.append(limits[massPoint][lower2Sig])
expected2SigHigh.append(limits[massPoint][upper2Sig])
expX = numpy.array(expectedx)
expY = numpy.array(expectedy)
values2 = []
xPointsForValues2 = []
values = []
xPointsForValues = []
if printStats: print "length of expectedx: ", len(expectedx)
if printStats: print "length of expected1SigLow: ", len(expected1SigLow)
if printStats: print "length of expected1SigHigh: ", len(expected1SigHigh)
#Here is some Voodoo via Sam:
for x in range(0, len(expectedx)):
values2.append(expected2SigLow[x])
xPointsForValues2.append(expectedx[x])
for x in range(len(expectedx) - 1, 0 - 1, -1):
values2.append(expected2SigHigh[x])
xPointsForValues2.append(expectedx[x])
if printStats: print "length of values2: ", len(values2)
for x in range(0, len(expectedx)):
values.append(expected1SigLow[x])
xPointsForValues.append(expectedx[x])
for x in range(len(expectedx) - 1, 0 - 1, -1):
values.append(expected1SigHigh[x])
xPointsForValues.append(expectedx[x])
if printStats: print "length of values: ", len(values)
exp2Sig = numpy.array(values2)
xPoints2 = numpy.array(xPointsForValues2)
exp1Sig = numpy.array(values)
xPoints = numpy.array(xPointsForValues)
if printStats: print "xPoints2: ", xPoints2
if printStats: print "exp2Sig: ", exp2Sig
if printStats: print "xPoints: ", xPoints
if printStats: print "exp1Sig: ", exp1Sig
GraphErr2Sig = TGraphAsymmErrors(len(xPoints), xPoints2, exp2Sig)
GraphErr2Sig.SetFillColor(ROOT.kOrange)
GraphErr1Sig = TGraphAsymmErrors(len(xPoints), xPoints, exp1Sig)
GraphErr1Sig.SetFillColor(ROOT.kGreen + 1)
cCL = TCanvas("cCL", "cCL", 0, 0, 800, 500)
gStyle.SetOptStat(0)
if not obs2 == "":
plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0.3, 1, 1)
ratioPad = ROOT.TPad("ratioPad", "ratioPad", 0, 0., 1, 0.3)
plotPad.Draw()
ratioPad.Draw()
plotPad.cd()
else:
plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0, 1, 1)
plotPad.Draw()
plotPad.cd()
expX = numpy.array(expectedx)
expY = numpy.array(expectedy)
GraphExp = TGraph(len(expX), expX, expY)
GraphExp.SetLineWidth(3)
GraphExp.SetLineStyle(2)
GraphExp.SetLineColor(ROOT.kBlue)
obsX = numpy.array(observedx)
obsY = numpy.array(observedy)
if printStats: print "obsX: ", obsX
if printStats: print "obsY: ", obsY
if SMOOTH:
smooth_obs = TGraphSmooth("normal")
GraphObs_nonSmooth = TGraph(len(obsX), obsX, obsY)
GraphObs = smooth_obs.SmoothSuper(GraphObs_nonSmooth, "linear", 0,
0.005)
else:
GraphObs = TGraph(len(obsX), obsX, obsY)
GraphObs.SetLineWidth(3)
if not obs2 == "":
ratio = []
ratiox = []
for index, val in enumerate(observedy):
mass = observedx[index]
foundIndex = -1
for index2, mass2 in enumerate(observedx2):
if mass == mass2:
foundIndex = index2
if foundIndex > 0:
ratio.append(observedy2[foundIndex] / val)
ratiox.append(mass)
ratioA = numpy.array(ratio)
ratioX = numpy.array(ratiox)
obsX2 = numpy.array(observedx2)
obsY2 = numpy.array(observedy2)
ratioGraph = TGraph(len(ratioX), ratioX, ratioA)
if printStats: print "obsX2: ", obsX2
if printStats: print "obsY2: ", obsY2
if SMOOTH:
smooth_obs2 = TGraphSmooth("normal")
GraphObs2_nonSmooth = TGraph(len(obsX2), obsX2, obsY2)
GraphObs2 = smooth_obs2.SmoothSuper(GraphObs2_nonSmooth, "linear",
0, 0.005)
else:
GraphObs2 = TGraph(len(obsX2), obsX2, obsY2)
GraphObs2.SetLineWidth(3)
xSecCurves = []
xSecCurves.append(getFittedXSecCurve("CI_%s" % interference, 1.3))
#Draw the graphs:
plotPad.SetLogy()
DummyGraph = TH1F("DummyGraph", "", 100, 10, 46)
DummyGraph.GetXaxis().SetTitle("#Lambda [TeV]")
if chan == "mumu":
DummyGraph.GetYaxis().SetTitle(
"95% CL limit on #sigma(pp#rightarrow CI+X#rightarrow#mu#mu +X) [pb]"
)
elif chan == "elel":
DummyGraph.GetYaxis().SetTitle(
"95% CL limit on #sigma(pp#rightarrow CI+X#rightarrowee +X) [pb]")
elif chan == "elmu":
DummyGraph.GetYaxis().SetTitle(
"95% CL limit on #sigma(pp#rightarrow CI+X#rightarrow#font[12]{ll}) [pb]"
)
gStyle.SetOptStat(0)
DummyGraph.GetXaxis().SetRangeUser(10, 46)
DummyGraph.SetMinimum(5e-4)
DummyGraph.SetMaximum(1)
DummyGraph.GetXaxis().SetLabelSize(0.04)
DummyGraph.GetXaxis().SetTitleSize(0.045)
DummyGraph.GetXaxis().SetTitleOffset(1.)
DummyGraph.GetYaxis().SetLabelSize(0.04)
DummyGraph.GetYaxis().SetTitleSize(0.045)
DummyGraph.GetYaxis().SetTitleOffset(1.)
DummyGraph.Draw()
if (FULL):
GraphErr2Sig.Draw("F")
GraphErr1Sig.Draw("F")
GraphExp.Draw("lpsame")
else:
if obs2 == "":
GraphExp.Draw("lp")
if not EXPONLY:
GraphObs.Draw("plsame")
if not obs2 == "":
GraphObs2.SetLineColor(ROOT.kRed)
GraphObs2.SetLineStyle(ROOT.kDashed)
GraphObs2.Draw("plsame")
for curve in xSecCurves:
print curve.Eval(28)
#curve.Draw()
curve.Draw("sameR")
plCMS = TPaveLabel(.15, .81, .25, .88, "CMS", "NBNDC")
#plCMS.SetTextSize(0.8)
plCMS.SetTextAlign(12)
plCMS.SetTextFont(62)
plCMS.SetFillColor(0)
plCMS.SetFillStyle(0)
plCMS.SetBorderSize(0)
plCMS.Draw()
plPrelim = TPaveLabel(.15, .76, .275, .82, "Supplementary", "NBNDC")
plPrelim.SetTextSize(0.6)
plPrelim.SetTextAlign(12)
plPrelim.SetTextFont(52)
plPrelim.SetFillColor(0)
plPrelim.SetFillStyle(0)
plPrelim.SetBorderSize(0)
#plPrelim.Draw()
cCL.SetTickx(1)
cCL.SetTicky(1)
cCL.RedrawAxis()
cCL.Update()
#leg=TLegend(0.65,0.65,0.87,0.87,"","brNDC")
leg = TLegend(0.440517, 0.523051, 0.834885, 0.878644, "", "brNDC")
# leg=TLegend(0.55,0.55,0.87,0.87,"","brNDC")
leg.SetTextSize(0.032)
if not obs2 == "":
if ratioLabel == "":
ratioLabel = "Variant/Default"
ratioLabels = ratioLabel.split("/")
print ratioLabels
leg.AddEntry(GraphObs, "%s Observed 95%% CL limit" % ratioLabels[1],
"l")
leg.AddEntry(GraphObs2, "%s Observed 95%% CL limit" % ratioLabels[0],
"l")
else:
if not EXPONLY:
leg.AddEntry(GraphObs, "Obs. 95% CL limit", "l")
leg.AddEntry(GraphExp, "Exp. 95% CL limit, median", "l")
if (FULL):
leg.AddEntry(GraphErr1Sig, "Exp. (68%)", "f")
leg.AddEntry(GraphErr2Sig, "Exp. (95%)", "f")
leg.AddEntry(xSecCurves[0], labels[interference], "l")
leg.SetLineWidth(0)
leg.SetLineStyle(0)
leg.SetFillStyle(0)
leg.SetLineColor(0)
leg.Draw("hist")
if "Moriond" in output:
if (chan == "mumu"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"36.3 fb^{-1} (13 TeV, #mu#mu)", "NBNDC")
elif (chan == "elel"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"35.9 fb^{-1} (13 TeV, ee)", "NBNDC")
elif (chan == "elmu"):
plLumi = TPaveLabel(
.4, .905, .9, .99,
"35.9 fb^{-1} (13 TeV, ee) + 36.3 fb^{-1} (13 TeV, #mu#mu)",
"NBNDC")
elif "2017" in output:
if (chan == "mumu"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"42.1 fb^{-1} (13 TeV, #mu#mu)", "NBNDC")
elif (chan == "elel"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"41.5 fb^{-1} (13 TeV, ee)", "NBNDC")
elif (chan == "elmu"):
plLumi = TPaveLabel(
.4, .905, .9, .99,
"41.5 fb^{-1} (13 TeV, ee) + 42.1 fb^{-1} (13 TeV, #mu#mu)",
"NBNDC")
else:
if (chan == "mumu"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"13.0 fb^{-1} (13 TeV, #mu#mu)", "NBNDC")
elif (chan == "elel"):
plLumi = TPaveLabel(.65, .905, .9, .99, "2.7 fb^{-1} (13 TeV, ee)",
"NBNDC")
elif (chan == "elmu"):
plLumi = TPaveLabel(
.4, .905, .9, .99,
"12.4 fb^{-1} (13 TeV, ee) + 13.0 fb^{-1} (13 TeV, #mu#mu)",
"NBNDC")
plLumi.SetTextSize(0.5)
plLumi.SetTextFont(42)
plLumi.SetFillColor(0)
plLumi.SetBorderSize(0)
plLumi.Draw()
plotPad.RedrawAxis()
if not obs2 == "":
ratioPad.cd()
line = ROOT.TLine(200, 1, 5500, 1)
line.SetLineStyle(ROOT.kDashed)
ROOT.gStyle.SetTitleSize(0.12, "Y")
ROOT.gStyle.SetTitleYOffset(0.35)
ROOT.gStyle.SetNdivisions(000, "Y")
ROOT.gStyle.SetNdivisions(408, "Y")
ratioPad.DrawFrame(200, 0.8, 5500, 1.2, "; ; %s" % ratioLabel)
line.Draw("same")
ratioGraph.Draw("sameP")
cCL.Update()
printPlots(cCL, output)
can_scan_SL1_L1 = TCanvas("can_scan_SL1_L1","can_scan_SL1_L1", 1000, 800)
can_scan_SL1_L1.SetGrid()
can_scan_SL1_L1.cd()
##Prepare summary TGraph
graph = TGraphAsymmErrors()
n=0
for a in sorted(threshold_scan):
#for a in sorted(run_parameters):
##Fill the TGraph with threshold (x-axis) and rate (y-axis)
#######graph.SetPoint(n,int(run_parameters[a]['VTHR']),float(run_parameters[a]['RATE_SL1_L1']))
graph.SetPoint(n,int(a),float(threshold_scan[a]))
n = n+1
graph.SetMarkerSize(1.)
graph.SetMarkerStyle(21)
graph.SetMarkerColor(862)
graph.SetFillColor(868)
graph.SetFillStyle(3844)
graph.SetLineColor(868)
graph.SetLineWidth(2)
graph.SetLineStyle(2)
graph.GetXaxis().SetTitle("threshold [mV]")
graph.GetYaxis().SetTitleOffset(1.2)
graph.GetYaxis().SetTitle("rate [kHz]")
graph.Draw("APL")
latex = TLatex()
latex.SetNDC()
latex.SetTextSize(0.04)
latex.SetTextColor(1)
latex.SetTextFont(42)
latex.SetTextAlign(33)
latex.SetTextSize(0.04)
def limit(channel, signal):
multF = 1. # in fb
filename = "./limitOutput_" + options.name + "/" + signal + "_MChi1_MPhi%d_scalar" + options.bjets + "_" + channel + "_AsymptoticLimits_grepOutput.txt"
if (options.mediator == 'SC'):
filename = "./limitOutput_" + options.name + "/" + signal + "_MChi1_MPhi%d_scalar" + options.bjets + "_" + channel + "_AsymptoticLimits_grepOutput.txt"
elif (options.mediator == 'PS'):
filename = "./limitOutput_" + options.name + "/" + signal + "_MChi1_MPhi%d_pseudo" + options.bjets + "_" + channel + "_AsymptoticLimits_grepOutput.txt"
else:
print 'WRONG mediator type'
mass, val = fillValues(filename)
Obs0s = TGraph()
Exp0s = TGraph()
Exp1s = TGraphAsymmErrors()
Exp2s = TGraphAsymmErrors()
Sign = TGraph()
pVal = TGraph()
Best = TGraphAsymmErrors()
for i, m in enumerate(mass):
if not m in val:
print "Key Error:", m, "not in value map"
continue
n = Exp0s.GetN()
Obs0s.SetPoint(n, m, val[m][0] * multF)
Exp0s.SetPoint(n, m, val[m][3] * multF)
Exp1s.SetPoint(n, m, val[m][3] * multF)
Exp1s.SetPointError(n, 0., 0., val[m][3] * multF - val[m][2] * multF,
val[m][4] * multF - val[m][3] * multF)
Exp2s.SetPoint(n, m, val[m][3] * multF)
Exp2s.SetPointError(n, 0., 0., val[m][3] * multF - val[m][1] * multF,
val[m][5] * multF - val[m][3] * multF)
#Sign.SetPoint(n, m, val[m][6])
#pVal.SetPoint(n, m, val[m][7])
#Best.SetPoint(n, m, val[m][8])
#Best.SetPointError(m, 0., 0., abs(val[m][9]), abs(val[m][10]))
Exp2s.SetLineWidth(2)
Exp2s.SetLineStyle(1)
Obs0s.SetLineWidth(3)
Obs0s.SetMarkerStyle(0)
Obs0s.SetLineColor(1)
Exp0s.SetLineStyle(2)
Exp0s.SetLineWidth(3)
Exp1s.SetFillColor(417) #kGreen+1
Exp1s.SetLineColor(417) #kGreen+1
Exp2s.SetFillColor(800) #kOrange
Exp2s.SetLineColor(800) #kOrange
Exp2s.GetXaxis().SetTitle("m_{#phi} (GeV)")
Exp2s.GetXaxis().SetTitleSize(Exp2s.GetXaxis().GetTitleSize() * 1.25)
Exp2s.GetXaxis().SetNoExponent(True)
Exp2s.GetXaxis().SetMoreLogLabels(True)
Exp2s.GetYaxis().SetTitle("#sigma/#sigma_{th}")
Exp2s.GetYaxis().SetTitleOffset(1.5)
Exp2s.GetYaxis().SetNoExponent(True)
Exp2s.GetYaxis().SetMoreLogLabels()
Sign.SetLineWidth(2)
Sign.SetLineColor(629)
Sign.GetXaxis().SetTitle("m_{#phi} (GeV)")
Sign.GetXaxis().SetTitleSize(Sign.GetXaxis().GetTitleSize() * 1.1)
Sign.GetYaxis().SetTitle("Significance")
pVal.SetLineWidth(2)
pVal.SetLineColor(629)
pVal.GetXaxis().SetTitle("m_{#phi} (GeV)")
pVal.GetXaxis().SetTitleSize(pVal.GetXaxis().GetTitleSize() * 1.1)
pVal.GetYaxis().SetTitle("local p-Value")
Best.SetLineWidth(2)
Best.SetLineColor(629)
Best.SetFillColor(629)
Best.SetFillStyle(3003)
Best.GetXaxis().SetTitle("m_{#phi} (GeV)")
Best.GetXaxis().SetTitleSize(Best.GetXaxis().GetTitleSize() * 1.1)
Best.GetYaxis().SetTitle("Best Fit (pb)")
c1 = TCanvas("c1", "Exclusion Limits", 800, 600)
c1.cd()
#SetPad(c1.GetPad(0))
c1.GetPad(0).SetTopMargin(0.06)
c1.GetPad(0).SetRightMargin(0.05)
c1.GetPad(0).SetTicks(1, 1)
#c1.GetPad(0).SetGridx()
#c1.GetPad(0).SetGridy()
c1.GetPad(0).SetLogx()
c1.GetPad(0).SetLogy()
Exp2s.Draw("A3")
Exp1s.Draw("SAME, 3")
Exp0s.Draw("SAME, L")
if not options.blind: Obs0s.Draw("SAME, L")
#Theory[0].Draw("SAME, L")
#Theory[1].Draw("SAME, L")
#setHistStyle(Exp2s)
Exp2s.GetXaxis().SetTitleSize(0.045)
Exp2s.GetXaxis().SetMoreLogLabels(True)
Exp2s.GetXaxis().SetNoExponent(True)
Exp2s.GetYaxis().SetTitleSize(0.04)
Exp2s.GetXaxis().SetLabelSize(0.04)
Exp2s.GetYaxis().SetLabelSize(0.04)
Exp2s.GetXaxis().SetTitleOffset(1)
Exp2s.GetYaxis().SetTitleOffset(1.25)
Exp2s.GetYaxis().SetMoreLogLabels(True)
Exp2s.GetYaxis().SetNoExponent(True)
Exp2s.GetYaxis().SetRangeUser(0.1, 1000.)
#else: Exp2s.GetYaxis().SetRangeUser(0.1, 1.e2)
Exp2s.GetXaxis().SetRangeUser(mass[0], mass[-1])
drawAnalysis("tDM")
drawRegion(channel, True)
drawCMS(LUMI, "Preliminary")
if True:
if (options.mediator == 'SC'):
massT, valT = fillValues("./limitOutput_" + options.name + "/" +
signal.replace('tttDM', 'tDM') +
"_MChi1_MPhi%d_scalar" + options.bjets +
"_" + channel +
"_AsymptoticLimits_grepOutput.txt")
elif (options.mediator == 'PS'):
massT, valT = fillValues("./limitOutput_" + options.name + "/" +
signal.replace('tttDM', 'tDM') +
"_MChi1_MPhi%d_pseudo" + options.bjets +
"_" + channel +
"_AsymptoticLimits_grepOutput.txt")
ExpT, ObsT = TGraphAsymmErrors(), TGraphAsymmErrors()
for i, m in enumerate(massT):
if not m in val: continue
ExpT.SetPoint(ExpT.GetN(), m, valT[m][3] * multF)
ObsT.SetPoint(ObsT.GetN(), m, valT[m][0] * multF)
ExpT.SetLineWidth(3)
ExpT.SetLineColor(602) #602
ExpT.SetLineStyle(5)
ObsT.SetLineWidth(3)
ObsT.SetLineColor(602)
ExpT.SetMarkerStyle(21)
ObsT.SetMarkerStyle(22)
ExpT.SetMarkerColor(602)
ObsT.SetMarkerColor(602)
ExpT.Draw("SAME, PC")
#if not options.blind: ObsT.Draw("SAME, P")
if (options.mediator == 'SC'):
massTTT, valTTT = fillValues("./limitOutput_" + options.name +
"/" +
signal.replace('tttDM', 'ttDM') +
"_MChi1_MPhi%d_scalar" +
options.bjets + "_" + channel +
"_AsymptoticLimits_grepOutput.txt")
elif (options.mediator == 'PS'):
massTTT, valTTT = fillValues("./limitOutput_" + options.name +
"/" +
signal.replace('tttDM', 'ttDM') +
"_MChi1_MPhi%d_pseudo" +
options.bjets + "_" + channel +
"_AsymptoticLimits_grepOutput.txt")
ExpTTT, ObsTTT = TGraphAsymmErrors(), TGraphAsymmErrors()
for i, m in enumerate(massTTT):
if not m in val: continue
ExpTTT.SetPoint(ExpTTT.GetN(), m, valTTT[m][3] * multF)
ObsTTT.SetPoint(ObsTTT.GetN(), m, valTTT[m][0] * multF)
ExpTTT.SetLineWidth(3)
ExpTTT.SetLineColor(634) #602
ExpTTT.SetLineStyle(5)
ObsTTT.SetLineWidth(3)
ObsTTT.SetLineColor(634)
ExpTTT.SetMarkerStyle(21)
ObsTTT.SetMarkerStyle(22)
ExpTTT.SetMarkerColor(634)
ObsTTT.SetMarkerColor(634)
ExpTTT.Draw("SAME, PC")
#if not options.blind: ObsTTT.Draw("SAME, P")
# legend
top = 0.9
nitems = 4 + 2
leg = TLegend(0.55, top - nitems * 0.3 / 5., 0.95, top)
leg.SetBorderSize(0)
leg.SetFillStyle(0) #1001
leg.SetFillColor(0)
leg.SetHeader("95% CL limits")
leg.AddEntry(Obs0s, "Observed", "l")
leg.AddEntry(Exp0s, "Expected (t+DM, tt+DM)", "l")
leg.AddEntry(Exp1s, "#pm 1 s. d.", "f")
leg.AddEntry(Exp2s, "#pm 2 s. d.", "f")
if True:
leg.AddEntry(ExpT, "Expected (t+DM)", "p")
leg.AddEntry(ExpTTT, "Expected (tt+DM)", "p")
leg.Draw()
c1.GetPad(0).RedrawAxis()
c1.GetPad(0).Update()
if gROOT.IsBatch():
c1.Print("plotsLimit_" + options.name + "/Exclusion_" + channel + "_" +
options.mediator + "_" + options.bjets + ".png")
c1.Print("plotsLimit_" + options.name + "/Exclusion_" + channel + "_" +
options.mediator + "_" + options.bjets + ".pdf")
if not gROOT.IsBatch(): raw_input("Press Enter to continue...")
# print "p1s[",
# for i in range(Exp0s.GetN()):
# print Exp0s.GetY()[i]+Exp1s.GetErrorYhigh(i), ",",
# print "],"
# print "m1s[",
# for i in range(Exp0s.GetN()):
# print Exp0s.GetY()[i]-Exp1s.GetErrorYlow(i), ",",
# print "],"
# print "[",
# for i in range(Exp0s.GetN()):
# print Exp0s.GetY()[i], ",",
# print "]"
return
# ---------- Significance ----------
c2 = TCanvas("c2", "Significance", 800, 600)
c2.cd()
c2.GetPad(0).SetTopMargin(0.06)
c2.GetPad(0).SetRightMargin(0.05)
c2.GetPad(0).SetTicks(1, 1)
c2.GetPad(0).SetGridx()
c2.GetPad(0).SetGridy()
Sign.GetYaxis().SetRangeUser(0., 5.)
Sign.Draw("AL3")
drawCMS(LUMI, "Preliminary")
drawAnalysis(channel[1:3])
if gROOT.IsBatch():
c2.Print("plotsLimit_" + options.name + "/Significance/" + channel +
"_" + options.mediator + "_" + options.bjets + ".png")
c2.Print("plotsLimit_" + options.name + "/Significance/" + channel +
"_" + options.mediator + "_" + options.bjets + ".pdf")
# c2.Print("plotsLimit/Significance/"+channel+suffix+".root")
# c2.Print("plotsLimit/Significance/"+channel+suffix+".C")
# ---------- p-Value ----------
c3 = TCanvas("c3", "p-Value", 800, 600)
c3.cd()
c3.GetPad(0).SetTopMargin(0.06)
c3.GetPad(0).SetRightMargin(0.05)
c3.GetPad(0).SetTicks(1, 1)
c3.GetPad(0).SetGridx()
c3.GetPad(0).SetGridy()
c3.GetPad(0).SetLogy()
pVal.Draw("AL3")
pVal.GetYaxis().SetRangeUser(2.e-7, 0.5)
ci = [
1., 0.317310508, 0.045500264, 0.002699796, 0.00006334, 0.000000573303,
0.000000001973
]
line = TLine()
line.SetLineColor(922)
line.SetLineStyle(7)
text = TLatex()
text.SetTextColor(922)
text.SetTextSize(0.025)
text.SetTextAlign(12)
for i in range(1, len(ci) - 1):
line.DrawLine(pVal.GetXaxis().GetXmin(), ci[i] / 2,
pVal.GetXaxis().GetXmax(), ci[i] / 2)
text.DrawLatex(pVal.GetXaxis().GetXmax() * 1.01, ci[i] / 2,
"%d #sigma" % i)
drawCMS(LUMI, "Preliminary")
drawAnalysis(channel[1:3])
if gROOT.IsBatch():
c3.Print("plotsLimit_" + options.name + "/pValue/" + channel + suffix +
"_" + options.mediator + "_" + options.bjets + ".png")
c3.Print("plotsLimit_" + options.name + "/pValue/" + channel + suffix +
"_" + options.mediator + "_" + options.bjets + ".pdf")
# c3.Print("plotsLimit/pValue/"+channel+suffix+".root")
# c3.Print("plotsLimit/pValue/"+channel+suffix+".C")
# --------- Best Fit ----------
c4 = TCanvas("c4", "Best Fit", 800, 600)
c4.cd()
c4.GetPad(0).SetTopMargin(0.06)
c4.GetPad(0).SetRightMargin(0.05)
c4.GetPad(0).SetTicks(1, 1)
c4.GetPad(0).SetGridx()
c4.GetPad(0).SetGridy()
Best.Draw("AL3")
drawCMS(LUMI, "Preliminary")
drawAnalysis(channel[1:3])
if gROOT.IsBatch():
c4.Print("plotsLimit_" + options.name + "/BestFit/" + channel +
suffix + "_" + options.mediator + "_" + options.bjets +
".png")
c4.Print("plotsLimit_" + options.name + "/BestFit/" + channel +
suffix + "_" + options.mediator + "_" + options.bjets +
".pdf")
# c4.Print("plotsLimit/BestFit/"+channel+suffix+".root")
# c4.Print("plotsLimit/BestFit/"+channel+suffix+".C")
if not gROOT.IsBatch(): raw_input("Press Enter to continue...")
def makeLimitPlot(output,
obs,
exp,
chan,
printStats=False,
obs2="",
ratioLabel=""):
fileObs = open(obs, 'r')
fileExp = open(exp, 'r')
observedx = []
observedy = []
obsLimits = {}
for entry in fileObs:
massPoint = float(entry.split()[0])
limitEntry = float(entry.split()[1])
if massPoint not in obsLimits: obsLimits[massPoint] = []
obsLimits[massPoint].append(limitEntry)
if printStats: print "len obsLimits:", len(obsLimits)
for massPoint in sorted(obsLimits):
observedx.append(massPoint)
observedy.append(numpy.mean(obsLimits[massPoint]))
if (numpy.std(obsLimits[massPoint]) / numpy.mean(obsLimits[massPoint])
> 0.05):
print massPoint, " mean: ", numpy.mean(
obsLimits[massPoint]), " std dev: ", numpy.std(
obsLimits[massPoint]), " from: ", obsLimits[massPoint]
if not obs2 == "":
fileObs2 = open(obs2, 'r')
observedx2 = []
observedy2 = []
obsLimits2 = {}
for entry in fileObs2:
massPoint = float(entry.split()[0])
limitEntry = float(entry.split()[1])
if massPoint not in obsLimits2: obsLimits2[massPoint] = []
obsLimits2[massPoint].append(limitEntry)
if printStats: print "len obsLimits:", len(obsLimits2)
for massPoint in sorted(obsLimits2):
observedx2.append(massPoint)
observedy2.append(numpy.mean(obsLimits2[massPoint]))
if (numpy.std(obsLimits2[massPoint]) /
numpy.mean(obsLimits2[massPoint]) > 0.05):
print massPoint, " mean: ", numpy.mean(
obsLimits2[massPoint]), " std dev: ", numpy.std(
obsLimits2[massPoint]
), " from: ", obsLimits2[massPoint]
limits = {}
expectedx = []
expectedy = []
expected1SigLow = []
expected1SigHigh = []
expected2SigLow = []
expected2SigHigh = []
for entry in fileExp:
massPoint = float(entry.split()[0])
limitEntry = float(entry.split()[1])
if massPoint not in limits: limits[massPoint] = []
limits[massPoint].append(limitEntry)
if printStats: print "len limits:", len(limits)
for massPoint in sorted(limits):
limits[massPoint].sort()
numLimits = len(limits[massPoint])
nrExpts = len(limits[massPoint])
medianNr = int(nrExpts * 0.5)
#get indexes:
upper1Sig = int(nrExpts * (1 - (1 - 0.68) * 0.5))
lower1Sig = int(nrExpts * (1 - 0.68) * 0.5)
upper2Sig = int(nrExpts * (1 - (1 - 0.95) * 0.5))
lower2Sig = int(nrExpts * (1 - 0.95) * 0.5)
if printStats:
print massPoint, ":", limits[massPoint][lower2Sig], limits[
massPoint][lower1Sig], limits[massPoint][medianNr], limits[
massPoint][upper1Sig], limits[massPoint][upper2Sig]
#fill lists:
expectedx.append(massPoint)
expectedy.append(limits[massPoint][medianNr])
expected1SigLow.append(limits[massPoint][lower1Sig])
expected1SigHigh.append(limits[massPoint][upper1Sig])
expected2SigLow.append(limits[massPoint][lower2Sig])
expected2SigHigh.append(limits[massPoint][upper2Sig])
expX = numpy.array(expectedx)
expY = numpy.array(expectedy)
values2 = []
xPointsForValues2 = []
values = []
xPointsForValues = []
if printStats: print "length of expectedx: ", len(expectedx)
if printStats: print "length of expected1SigLow: ", len(expected1SigLow)
if printStats: print "length of expected1SigHigh: ", len(expected1SigHigh)
#Here is some Voodoo via Sam:
for x in range(0, len(expectedx)):
values2.append(expected2SigLow[x])
xPointsForValues2.append(expectedx[x])
for x in range(len(expectedx) - 1, 0 - 1, -1):
values2.append(expected2SigHigh[x])
xPointsForValues2.append(expectedx[x])
if printStats: print "length of values2: ", len(values2)
for x in range(0, len(expectedx)):
values.append(expected1SigLow[x])
xPointsForValues.append(expectedx[x])
for x in range(len(expectedx) - 1, 0 - 1, -1):
values.append(expected1SigHigh[x])
xPointsForValues.append(expectedx[x])
if printStats: print "length of values: ", len(values)
exp2Sig = numpy.array(values2)
xPoints2 = numpy.array(xPointsForValues2)
exp1Sig = numpy.array(values)
xPoints = numpy.array(xPointsForValues)
if printStats: print "xPoints2: ", xPoints2
if printStats: print "exp2Sig: ", exp2Sig
if printStats: print "xPoints: ", xPoints
if printStats: print "exp1Sig: ", exp1Sig
GraphErr2Sig = TGraphAsymmErrors(len(xPoints), xPoints2, exp2Sig)
GraphErr2Sig.SetFillColor(ROOT.kYellow + 1)
GraphErr1Sig = TGraphAsymmErrors(len(xPoints), xPoints, exp1Sig)
GraphErr1Sig.SetFillColor(ROOT.kGreen)
cCL = TCanvas("cCL", "cCL", 0, 0, 800, 500)
gStyle.SetOptStat(0)
if not obs2 == "":
plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0.3, 1, 1)
ratioPad = ROOT.TPad("ratioPad", "ratioPad", 0, 0., 1, 0.3)
plotPad.Draw()
ratioPad.Draw()
plotPad.cd()
else:
plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0, 1, 1)
plotPad.Draw()
plotPad.cd()
expX = numpy.array(expectedx)
expY = numpy.array(expectedy)
GraphExp = TGraph(len(expX), expX, expY)
GraphExp.SetLineWidth(3)
GraphExp.SetLineStyle(2)
GraphExp.SetLineColor(ROOT.kBlue)
obsX = numpy.array(observedx)
obsY = numpy.array(observedy)
if printStats: print "obsX: ", obsX
if printStats: print "obsY: ", obsY
if SMOOTH:
smooth_obs = TGraphSmooth("normal")
GraphObs_nonSmooth = TGraph(len(obsX), obsX, obsY)
GraphObs = smooth_obs.SmoothSuper(GraphObs_nonSmooth, "linear", 0,
0.005)
else:
GraphObs = TGraph(len(obsX), obsX, obsY)
GraphObs.SetLineWidth(3)
if not obs2 == "":
ratio = []
ratiox = []
for index, val in enumerate(observedy):
mass = observedx[index]
foundIndex = -1
for index2, mass2 in enumerate(observedx2):
if mass == mass2:
foundIndex = index2
if foundIndex > 0:
ratio.append(observedy2[foundIndex] / val)
ratiox.append(mass)
ratioA = numpy.array(ratio)
ratioX = numpy.array(ratiox)
obsX2 = numpy.array(observedx2)
obsY2 = numpy.array(observedy2)
ratioGraph = TGraph(len(ratioX), ratioX, ratioA)
if printStats: print "obsX2: ", obsX2
if printStats: print "obsY2: ", obsY2
if SMOOTH:
smooth_obs2 = TGraphSmooth("normal")
GraphObs2_nonSmooth = TGraph(len(obsX2), obsX2, obsY2)
GraphObs2 = smooth_obs2.SmoothSuper(GraphObs2_nonSmooth, "linear",
0, 0.005)
else:
GraphObs2 = TGraph(len(obsX2), obsX2, obsY2)
GraphObs2.SetLineWidth(3)
smoother = TGraphSmooth("normal")
smoother2 = TGraphSmooth("normal")
zprimeX = []
zprimeY = []
fileZPrime = open('tools/xsec_SSM.txt', 'r')
for entries in fileZPrime:
entry = entries.split()
zprimeX.append(float(entry[0]))
zprimeY.append(float(entry[1]) * 1.3 / 1928)
zpX = numpy.array(zprimeX)
zpY = numpy.array(zprimeY)
GraphZPrime = TGraph(481, zpX, zpY)
GraphZPrimeSmooth = smoother2.SmoothSuper(GraphZPrime, "linear")
GraphZPrimeSmooth.SetLineWidth(3)
GraphZPrimeSmooth.SetLineColor(ROOT.kGreen + 3)
GraphZPrimeSmooth.SetLineStyle(2)
zprimePsiX = []
zprimePsiY = []
fileZPrimePsi = open('tools/xsec_PSI.txt', 'r')
for entries in fileZPrimePsi:
entry = entries.split()
zprimePsiX.append(float(entry[0]))
zprimePsiY.append(float(entry[1]) * 1.3 / 1928)
zpPsiX = numpy.array(zprimePsiX)
zpPsiY = numpy.array(zprimePsiY)
GraphZPrimePsi = TGraph(481, zpPsiX, zpPsiY)
GraphZPrimePsiSmooth = smoother.SmoothSuper(GraphZPrimePsi, "linear")
GraphZPrimePsiSmooth.SetLineWidth(3)
GraphZPrimePsiSmooth.SetLineColor(ROOT.kBlue)
#Draw the graphs:
plotPad.SetLogy()
if "Moriond" in output:
DummyGraph = TH1F("DummyGraph", "", 100, 120, 4500)
else:
DummyGraph = TH1F("DummyGraph", "", 100, 400, 4500)
DummyGraph.GetXaxis().SetTitle("M [GeV]")
if chan == "mumu":
DummyGraph.GetYaxis().SetTitle(
"#sigma(pp#rightarrowZ'+X#rightarrow#mu#mu+X) / #sigma(pp#rightarrowZ+X#rightarrow#mu#mu+X)"
)
elif chan == "elel":
DummyGraph.GetYaxis().SetTitle(
"#sigma(pp#rightarrowZ'+X#rightarrowee+X) / #sigma(pp#rightarrowZ+X#rightarrowee+X)"
)
elif chan == "elmu":
DummyGraph.GetYaxis().SetTitle(
"#sigma(pp#rightarrowZ'+X#rightarrow#font[12]{ll}+X) / #sigma(pp#rightarrowZ+X#rightarrow#font[12]{ll}+X)"
)
gStyle.SetOptStat(0)
if "Moriond" in output:
DummyGraph.GetXaxis().SetRangeUser(120, 4500)
else:
DummyGraph.GetXaxis().SetRangeUser(400, 4500)
DummyGraph.SetMinimum(1e-8)
DummyGraph.SetMaximum(4e-4)
DummyGraph.GetXaxis().SetLabelSize(0.04)
DummyGraph.GetXaxis().SetTitleSize(0.045)
DummyGraph.GetXaxis().SetTitleOffset(1.)
DummyGraph.GetYaxis().SetLabelSize(0.04)
DummyGraph.GetYaxis().SetTitleSize(0.045)
DummyGraph.GetYaxis().SetTitleOffset(1.)
DummyGraph.Draw()
if (FULL):
GraphErr2Sig.Draw("F")
GraphErr1Sig.Draw("F")
GraphExp.Draw("lpsame")
else:
if obs2 == "":
GraphExp.Draw("lp")
GraphObs.Draw("plsame")
if not obs2 == "":
GraphObs2.SetLineColor(ROOT.kRed)
GraphObs2.SetLineStyle(ROOT.kDashed)
GraphObs2.Draw("plsame")
if not SPIN2:
GraphZPrimeSmooth.Draw("lsame")
GraphZPrimePsiSmooth.Draw("lsame")
cCL.SetTickx(1)
cCL.SetTicky(1)
cCL.RedrawAxis()
cCL.Update()
#leg=TLegend(0.65,0.65,0.87,0.87,"","brNDC")
leg = TLegend(0.540517, 0.623051, 0.834885, 0.878644, "", "brNDC")
# leg=TLegend(0.55,0.55,0.87,0.87,"","brNDC")
leg.SetTextSize(0.032)
if not obs2 == "":
if ratioLabel == "":
ratioLabel = "Variant/Default"
ratioLabels = ratioLabel.split("/")
leg.AddEntry(GraphObs, "% Observed 95% CL limit" % ratioLabel[1], "l")
leg.AddEntry(GraphObs2, "%s Observed 95% CL limit" % ratioLabel[0],
"l")
else:
leg.AddEntry(GraphObs, "Observed 95% CL limit", "l")
leg.AddEntry(GraphExp, "Expected 95% CL limit, median", "l")
if (FULL):
leg.AddEntry(GraphErr1Sig, "Expected 95% CL limit, 1 s.d.", "f")
leg.AddEntry(GraphErr2Sig, "Expected 95% CL limit, 2 s.d.", "f")
leg1 = TLegend(0.665517, 0.483051, 0.834885, 0.623051, "", "brNDC")
leg1.SetTextSize(0.032)
if not SPIN2:
leg1.AddEntry(GraphZPrimePsiSmooth, "Z'_{#Psi} (LOx1.3)", "l")
leg1.AddEntry(GraphZPrimeSmooth, "Z'_{SSM} (LOx1.3)", "l")
leg.SetLineWidth(0)
leg.SetLineStyle(0)
leg.SetLineColor(0)
leg.Draw("hist")
leg1.SetLineWidth(0)
leg1.SetLineStyle(0)
leg1.SetLineColor(0)
leg1.Draw("hist")
if "Moriond" in output:
if (chan == "mumu"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"36.3 fb^{-1} (13 TeV, #mu#mu)", "NBNDC")
elif (chan == "elel"):
plLumi = TPaveLabel(.65, .905, .9, .99, "2.7 fb^{-1} (13 TeV, ee)",
"NBNDC")
elif (chan == "elmu"):
plLumi = TPaveLabel(
.4, .905, .9, .99,
"12.4 fb^{-1} (13 TeV, ee) + 13.0 fb^{-1} (13 TeV, #mu#mu)",
"NBNDC")
else:
if (chan == "mumu"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"13.0 fb^{-1} (13 TeV, #mu#mu)", "NBNDC")
elif (chan == "elel"):
plLumi = TPaveLabel(.65, .905, .9, .99, "2.7 fb^{-1} (13 TeV, ee)",
"NBNDC")
elif (chan == "elmu"):
plLumi = TPaveLabel(
.4, .905, .9, .99,
"12.4 fb^{-1} (13 TeV, ee) + 13.0 fb^{-1} (13 TeV, #mu#mu)",
"NBNDC")
plLumi.SetTextSize(0.5)
plLumi.SetTextFont(42)
plLumi.SetFillColor(0)
plLumi.SetBorderSize(0)
plLumi.Draw()
plCMS = TPaveLabel(.12, .81, .22, .88, "CMS", "NBNDC")
#plCMS.SetTextSize(0.8)
plCMS.SetTextAlign(12)
plCMS.SetTextFont(62)
plCMS.SetFillColor(0)
plCMS.SetBorderSize(0)
plCMS.Draw()
plPrelim = TPaveLabel(.12, .76, .25, .82, "Preliminary", "NBNDC")
plPrelim.SetTextSize(0.6)
plPrelim.SetTextAlign(12)
plPrelim.SetTextFont(52)
plPrelim.SetFillColor(0)
plPrelim.SetBorderSize(0)
plPrelim.Draw()
if not obs2 == "":
ratioPad.cd()
line = ROOT.TLine(400, 1, 4500, 1)
line.SetLineStyle(ROOT.kDashed)
ROOT.gStyle.SetTitleSize(0.12, "Y")
ROOT.gStyle.SetTitleYOffset(0.35)
ROOT.gStyle.SetNdivisions(000, "Y")
ROOT.gStyle.SetNdivisions(408, "Y")
ratioPad.DrawFrame(400, 0.9, 4500, 1.1, "; ; %s" % ratioLabel)
line.Draw("same")
ratioGraph.Draw("sameP")
cCL.Update()
printPlots(cCL, output)
theory.SetLineWidth(3)
observed_p = TGraphAsymmErrors(massv, obsv, masserrv, masserrv, obserrv,
obserrv)
observed_p.SetLineColor(ROOT.kBlack)
observed_p.SetLineWidth(2)
observed_p.SetMarkerStyle(20)
expected_p = TGraphAsymmErrors(massv, expv, masserrv, masserrv, experrv,
experrv)
expected_p.SetLineColor(ROOT.kBlack)
expected_p.SetLineWidth(2)
expected_p.SetLineStyle(2)
expected68 = TGraphAsymmErrors(massv, expv, masserrv, masserrv, exp68Lv,
exp68Hv)
expected68.SetFillColor(ROOT.kGreen)
expected95 = TGraphAsymmErrors(massv, expv, masserrv, masserrv, exp95Lv,
exp95Hv)
expected95.SetFillColor(ROOT.kYellow)
c4 = TCanvas("c4", "Diphoton c = 01 Limits", 1000, 800)
c4.SetBottomMargin(0.15)
c4.SetRightMargin(0.06)
#c4.SetLogy(1)
#expected95.SetMinimum(0.0001);
expected95.SetMaximum(0.0057)
expected95.Draw("a3")
expected95.GetXaxis().SetTitle("Diphoton Mass [GeV/c^{2}]")
def makeLimitPlot(output,
obs,
exp,
chan,
printStats=False,
obs2="",
ratioLabel=""):
#fileForHEPData = TFile("plots/"+output+"_forHEPData.root","RECREATE")
fileObs = open(obs, 'r')
fileExp = open(exp, 'r')
observedx = []
observedy = []
obsLimits = {}
for entry in fileObs:
massPoint = float(entry.split()[0])
limitEntry = float(entry.split()[1])
if massPoint not in obsLimits: obsLimits[massPoint] = []
obsLimits[massPoint].append(limitEntry)
if printStats: print "len obsLimits:", len(obsLimits)
for massPoint in sorted(obsLimits):
observedx.append(massPoint)
observedy.append(numpy.mean(obsLimits[massPoint]))
if (numpy.std(obsLimits[massPoint]) / numpy.mean(obsLimits[massPoint])
> 0.05):
print massPoint, " mean: ", numpy.mean(
obsLimits[massPoint]), " std dev: ", numpy.std(
obsLimits[massPoint]), " from: ", obsLimits[massPoint]
if not obs2 == "":
fileObs2 = open(obs2, 'r')
observedx2 = []
observedy2 = []
obsLimits2 = {}
for entry in fileObs2:
massPoint = float(entry.split()[0])
limitEntry = float(entry.split()[1])
if massPoint not in obsLimits2: obsLimits2[massPoint] = []
obsLimits2[massPoint].append(limitEntry)
if printStats: print "len obsLimits:", len(obsLimits2)
for massPoint in sorted(obsLimits2):
observedx2.append(massPoint)
observedy2.append(numpy.mean(obsLimits2[massPoint]))
if (numpy.std(obsLimits2[massPoint]) /
numpy.mean(obsLimits2[massPoint]) > 0.05):
print massPoint, " mean: ", numpy.mean(
obsLimits2[massPoint]), " std dev: ", numpy.std(
obsLimits2[massPoint]
), " from: ", obsLimits2[massPoint]
limits = {}
expectedx = []
expectedy = []
expected1SigLow = []
expected1SigHigh = []
expected2SigLow = []
expected2SigHigh = []
for entry in fileExp:
massPoint = float(entry.split()[0])
limitEntry = float(entry.split()[1])
if massPoint not in limits: limits[massPoint] = []
limits[massPoint].append(limitEntry)
if printStats: print "len limits:", len(limits)
for massPoint in sorted(limits):
limits[massPoint].sort()
numLimits = len(limits[massPoint])
nrExpts = len(limits[massPoint])
medianNr = int(nrExpts * 0.5)
#get indexes:
upper1Sig = int(nrExpts * (1 - (1 - 0.68) * 0.5))
lower1Sig = int(nrExpts * (1 - 0.68) * 0.5)
upper2Sig = int(nrExpts * (1 - (1 - 0.95) * 0.5))
lower2Sig = int(nrExpts * (1 - 0.95) * 0.5)
if printStats:
print massPoint, ":", limits[massPoint][lower2Sig], limits[
massPoint][lower1Sig], limits[massPoint][medianNr], limits[
massPoint][upper1Sig], limits[massPoint][upper2Sig]
#fill lists:
expectedx.append(massPoint)
print massPoint, limits[massPoint][medianNr]
expectedy.append(limits[massPoint][medianNr])
expected1SigLow.append(limits[massPoint][lower1Sig])
expected1SigHigh.append(limits[massPoint][upper1Sig])
expected2SigLow.append(limits[massPoint][lower2Sig])
expected2SigHigh.append(limits[massPoint][upper2Sig])
expX = numpy.array(expectedx)
expY = numpy.array(expectedy)
values2 = []
xPointsForValues2 = []
values = []
xPointsForValues = []
xPointsForErrors = []
if printStats: print "length of expectedx: ", len(expectedx)
if printStats: print "length of expected1SigLow: ", len(expected1SigLow)
if printStats: print "length of expected1SigHigh: ", len(expected1SigHigh)
#Here is some Voodoo via Sam:
for x in range(0, len(expectedx)):
values2.append(expected2SigLow[x])
xPointsForValues2.append(expectedx[x])
xPointsForErrors.append(0)
for x in range(len(expectedx) - 1, 0 - 1, -1):
values2.append(expected2SigHigh[x])
xPointsForValues2.append(expectedx[x])
if printStats: print "length of values2: ", len(values2)
for x in range(0, len(expectedx)):
values.append(expected1SigLow[x])
xPointsForValues.append(expectedx[x])
for x in range(len(expectedx) - 1, 0 - 1, -1):
values.append(expected1SigHigh[x])
xPointsForValues.append(expectedx[x])
if printStats: print "length of values: ", len(values)
exp2Sig = numpy.array(values2)
xPoints2 = numpy.array(xPointsForValues2)
exp1Sig = numpy.array(values)
xPoints = numpy.array(xPointsForValues)
xPointsErrors = numpy.array(xPointsForErrors)
if printStats: print "xPoints2: ", xPoints2
if printStats: print "exp2Sig: ", exp2Sig
if printStats: print "xPoints: ", xPoints
if printStats: print "exp1Sig: ", exp1Sig
GraphErr2SigForHEPData = TGraphAsymmErrors(len(expX), expX, expY,
numpy.array(xPointsErrors),
numpy.array(xPointsErrors),
numpy.array(expected2SigLow),
numpy.array(expected2SigHigh))
GraphErr1SigForHEPData = TGraphAsymmErrors(len(expX), expX, expY,
numpy.array(xPointsErrors),
numpy.array(xPointsErrors),
numpy.array(expected1SigLow),
numpy.array(expected1SigHigh))
GraphErr2Sig = TGraphAsymmErrors(len(xPoints), xPoints2, exp2Sig)
GraphErr2Sig.SetFillColor(ROOT.kOrange)
GraphErr1Sig = TGraphAsymmErrors(len(xPoints), xPoints, exp1Sig)
GraphErr1Sig.SetFillColor(ROOT.kGreen + 1)
#cCL=TCanvas("cCL", "cCL",0,0,567,384)
cCL = TCanvas("cCL", "cCL", 0, 0, 600, 450)
gStyle.SetOptStat(0)
gStyle.SetPadRightMargin(0.063)
gStyle.SetPadLeftMargin(0.14)
gStyle.SetPadBottomMargin(0.12)
if not obs2 == "":
plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0.3, 1, 1)
ratioPad = ROOT.TPad("ratioPad", "ratioPad", 0, 0., 1, 0.3)
plotPad.Draw()
ratioPad.Draw()
plotPad.cd()
else:
plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0, 1, 1)
plotPad.Draw()
plotPad.cd()
expX = numpy.array(expectedx)
expY = numpy.array(expectedy)
GraphExp = TGraph(len(expX), expX, expY)
GraphExp.SetLineWidth(3)
GraphExp.SetLineStyle(2)
GraphExp.SetLineColor(ROOT.kBlue)
obsX = numpy.array(observedx)
obsY = numpy.array(observedy)
if printStats: print "obsX: ", obsX
if printStats: print "obsY: ", obsY
if SMOOTH:
smooth_obs = TGraphSmooth("normal")
GraphObs_nonSmooth = TGraph(len(obsX), obsX, obsY)
GraphObs = smooth_obs.SmoothSuper(GraphObs_nonSmooth, "linear", 0,
0.005)
else:
GraphObs = TGraph(len(obsX), obsX, obsY)
GraphObs.SetLineWidth(3)
if not obs2 == "":
ratio = []
ratiox = []
for index, val in enumerate(observedy):
mass = observedx[index]
foundIndex = -1
for index2, mass2 in enumerate(observedx2):
if mass == mass2:
foundIndex = index2
if foundIndex > 0:
ratio.append(observedy2[foundIndex] / val)
ratiox.append(mass)
ratioA = numpy.array(ratio)
ratioX = numpy.array(ratiox)
obsX2 = numpy.array(observedx2)
obsY2 = numpy.array(observedy2)
ratioGraph = TGraph(len(ratioX), ratioX, ratioA)
if printStats: print "obsX2: ", obsX2
if printStats: print "obsY2: ", obsY2
if SMOOTH:
smooth_obs2 = TGraphSmooth("normal")
GraphObs2_nonSmooth = TGraph(len(obsX2), obsX2, obsY2)
GraphObs2 = smooth_obs2.SmoothSuper(GraphObs2_nonSmooth, "linear",
0, 0.005)
else:
GraphObs2 = TGraph(len(obsX2), obsX2, obsY2)
GraphObs2.SetLineWidth(3)
if SPIN2:
signals = ["RS_kMpl01", "RS_kMpl005", "RS_kMpl001"]
elif GUT:
signals = ["ssm", "psi", "kai", "eta", "I", "S", "N"]
else:
signals = ["ssm", "psi"]
xSecCurves = []
for signal in signals:
xSecCurves.append(getXSecCurve(signal, kFacs[signal]))
#xSecCurves.append(getXSecCurve(signal,kFacs[signal],massDependent=True))
#Draw the graphs:
plotPad.SetLogy()
DummyGraph = TH1F("DummyGraph", "", 100, 200, 5500)
DummyGraph.GetXaxis().SetTitle("M [GeV]")
if SPIN2:
DummyGraph.GetYaxis().SetTitle(
"[#sigma#upoint#font[12]{B}] G_{KK} / [#sigma#upoint#font[12]{B}] Z"
)
else:
DummyGraph.GetYaxis().SetTitle(
"[#sigma#upoint#font[12]{B}] Z' / [#sigma#upoint#font[12]{B}] Z")
# if SPIN2:
# if chan=="mumu":
# DummyGraph.GetYaxis().SetTitle("#sigma(pp#rightarrowG_{KK}+X#rightarrow#mu^{+}#mu^{-}+X) / #sigma(pp#rightarrowZ+X#rightarrow#mu^{+}#mu^{-}+X)")
# elif chan=="elel":
# DummyGraph.GetYaxis().SetTitle("#sigma(pp#rightarrowG_{KK}+X#rightarrowee+X) / #sigma(pp#rightarrowZ+X#rightarrowee+X)")
# elif chan=="elmu":
# DummyGraph.GetYaxis().SetTitle("#sigma(pp#rightarrowG_{KK}+X#rightarrow#font[12]{ll}+X) / #sigma(pp#rightarrowZ+X#rightarrow#font[12]{ll}+X)")
# else:
# if chan=="mumu":
# DummyGraph.GetYaxis().SetTitle("#sigma(pp#rightarrowZ'+X#rightarrow#mu^{+}#mu^{-}+X) / #sigma(pp#rightarrowZ+X#rightarrow#mu^{+}#mu^{-}+X)")
# elif chan=="elel":
# DummyGraph.GetYaxis().SetTitle("#sigma(pp#rightarrowZ'+X#rightarrowee+X) / #sigma(pp#rightarrowZ+X#rightarrowee+X)")
# elif chan=="elmu":
# DummyGraph.GetYaxis().SetTitle("#sigma(pp#rightarrowZ'+X#rightarrow#font[12]{ll}+X) / #sigma(pp#rightarrowZ+X#rightarrow#font[12]{ll}+X)")
gStyle.SetOptStat(0)
DummyGraph.GetXaxis().SetRangeUser(200, 5500)
DummyGraph.SetMinimum(1e-8)
DummyGraph.SetMaximum(1e-4)
DummyGraph.GetXaxis().SetLabelSize(0.055)
DummyGraph.GetXaxis().SetTitleSize(0.055)
DummyGraph.GetXaxis().SetTitleOffset(1.05)
DummyGraph.GetYaxis().SetLabelSize(0.055)
DummyGraph.GetYaxis().SetTitleSize(0.055)
DummyGraph.GetYaxis().SetTitleOffset(1.3)
DummyGraph.Draw()
if (FULL):
GraphErr2Sig.Draw("F")
GraphErr1Sig.Draw("F")
GraphExp.Draw("lpsame")
else:
if obs2 == "":
GraphExp.Draw("lp")
if not EXPONLY:
GraphObs.Draw("plsame")
if not obs2 == "":
GraphObs2.SetLineColor(ROOT.kRed)
GraphObs2.SetLineStyle(ROOT.kDashed)
GraphObs2.Draw("plsame")
for curve in xSecCurves:
curve.Draw("lsame")
plCMS = TPaveLabel(.16, .81, .27, .88, "CMS", "NBNDC")
#plCMS.SetTextSize(0.8)
plCMS.SetTextAlign(12)
plCMS.SetTextFont(62)
plCMS.SetFillColor(0)
plCMS.SetFillStyle(0)
plCMS.SetBorderSize(0)
plCMS.Draw()
plPrelim = TPaveLabel(.16, .76, .27, .82, "Preliminary", "NBNDC")
plPrelim.SetTextSize(0.6)
plPrelim.SetTextAlign(12)
plPrelim.SetTextFont(52)
plPrelim.SetFillColor(0)
plPrelim.SetFillStyle(0)
plPrelim.SetBorderSize(0)
if "2017" in output or "Combination" in output:
plPrelim.Draw()
cCL.SetTickx(1)
cCL.SetTicky(1)
cCL.RedrawAxis()
cCL.Update()
#leg=TLegend(0.65,0.65,0.87,0.87,"","brNDC")
#leg=TLegend(0.540517,0.623051,0.834885,0.878644,"","brNDC") Default
leg = TLegend(0.5, 0.58, 0.834885, 0.878644, "", "brNDC")
if SPIN2:
leg = TLegend(0.5, 0.58, 0.834885, 0.878644, "", "brNDC")
# leg=TLegend(0.55,0.55,0.87,0.87,"","brNDC")
leg.SetTextSize(0.0425)
if not obs2 == "":
if ratioLabel == "":
ratioLabel = "Variant/Default"
ratioLabels = ratioLabel.split("/")
print ratioLabels
leg.AddEntry(GraphObs, "%s Obs. 95%% CL limit" % ratioLabels[1], "l")
leg.AddEntry(GraphObs2, "%s Obs. 95%% CL limit" % ratioLabels[0], "l")
else:
if not EXPONLY:
leg.AddEntry(GraphObs, "Obs. 95% CL limit", "l")
leg.AddEntry(GraphExp, "Exp. 95% CL limit, median", "l")
if (FULL):
leg.AddEntry(GraphErr1Sig, "Exp. (68%)", "f")
leg.AddEntry(GraphErr2Sig, "Exp. (95%)", "f")
leg1 = TLegend(0.7, 0.4, 0.9, 0.55, "", "brNDC")
leg1.SetTextSize(0.05)
if GUT:
leg1 = TLegend(0.6, 0.35, 0.75, 0.623051, "", "brNDC")
if SPIN2:
leg1 = TLegend(0.7, 0.35, 0.9, 0.58, "G_{KK} (LO x 1.6)", "brNDC")
leg1.SetTextSize(0.045)
for index, signal in enumerate(signals):
xSecCurves[index].SetName(labels[signal])
xSecCurves[index].Write(labels[signal])
leg1.AddEntry(xSecCurves[index], labels[signal], "l")
leg1.SetBorderSize(0)
leg.SetLineWidth(0)
leg.SetLineStyle(0)
leg.SetFillStyle(0)
leg.SetLineColor(0)
leg.Draw("hist")
leg1.SetLineWidth(0)
leg1.SetLineStyle(0)
leg1.SetFillStyle(0)
leg1.SetLineColor(0)
leg1.Draw("hist")
if "Moriond" in output:
if (chan == "mumu"):
plLumi = TPaveLabel(.65, .885, .9, .99,
"36.3 fb^{-1} (13 TeV, #mu^{+}#mu^{-})",
"NBNDC")
elif (chan == "elel"):
plLumi = TPaveLabel(.65, .885, .9, .99,
"35.9 fb^{-1} (13 TeV, ee)", "NBNDC")
elif (chan == "elmu"):
plLumi = TPaveLabel(
.27, .885, .9, .99,
"35.9 fb^{-1} (13 TeV, ee) + 36.3 fb^{-1} (13 TeV, #mu^{+}#mu^{-})",
"NBNDC")
elif "2017" in output or "Combination" in output:
if (chan == "mumu"):
plLumi = TPaveLabel(.65, .885, .9, .99,
"42.4 fb^{-1} (13 TeV, #mu^{+}#mu^{-})",
"NBNDC")
elif (chan == "elel"):
plLumi = TPaveLabel(.65, .885, .9, .99,
"41.4 fb^{-1} (13 TeV, ee)", "NBNDC")
elif (chan == "elmu"):
plLumi = TPaveLabel(
.27, .885, .9, .99,
"77.3 fb^{-1} (13 TeV, ee) + 78.7 fb^{-1} (13 TeV, #mu^{+}#mu^{-})",
"NBNDC")
else:
if (chan == "mumu"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"13.0 fb^{-1} (13 TeV, #mu#mu)", "NBNDC")
elif (chan == "elel"):
plLumi = TPaveLabel(.65, .905, .9, .99, "2.7 fb^{-1} (13 TeV, ee)",
"NBNDC")
elif (chan == "elmu"):
plLumi = TPaveLabel(
.4, .905, .9, .99,
"12.4 fb^{-1} (13 TeV, ee) + 13.0 fb^{-1} (13 TeV, #mu#mu)",
"NBNDC")
plLumi.SetTextSize(0.5)
plLumi.SetTextFont(42)
plLumi.SetFillColor(0)
plLumi.SetBorderSize(0)
plLumi.Draw()
plotPad.SetTicks(1, 1)
plotPad.RedrawAxis()
if not obs2 == "":
ratioPad.cd()
line = ROOT.TLine(200, 1, 5500, 1)
line.SetLineStyle(ROOT.kDashed)
ROOT.gStyle.SetTitleSize(0.12, "Y")
ROOT.gStyle.SetTitleYOffset(0.35)
ROOT.gStyle.SetNdivisions(000, "Y")
ROOT.gStyle.SetNdivisions(408, "Y")
ratioPad.DrawFrame(200, 0.8, 5500, 1.2, "; ; %s" % ratioLabel)
line.Draw("same")
ratioGraph.Draw("sameP")
#GraphErr2SigForHEPData.SetName("graph2Sig")
#GraphErr2SigForHEPData.Write("graph2Sig")
#GraphErr1SigForHEPData.SetName("graph1Sig")
#GraphErr1SigForHEPData.Write("graph1Sig")
#GraphExp.SetName("graphExp")
#GraphExp.Write("graphExp")
#GraphObs.SetName("graphObs")
#GraphObs.Write("graphObs")
#fileForHEPData.Write()
#fileForHEPData.Close()
cCL.Update()
printPlots(cCL, output)
def getGraph(self,dset):
from array import array
from ROOT import TMultiGraph, TLegend, TGraphAsymmErrors
n = len(self.__x)
if n != len(self.__y) or n != len(self.__yErrLow) or n != len(self.__yErrHigh):
raise StandardError, "The length of the x(%s), y(%s) and y error(%s,%s) lists does not match"%(len(self.__x), len(self.__y), len(self.__yErrLow), len(self.__yErrHigh))
result = TMultiGraph()
legendPosition = [float(i) for i in self.__getStyleOption("legendPosition").split()]
legend = TLegend(*legendPosition)
legend.SetFillColor(0)
result.SetTitle("%s;%s;%s"%(self.__title,self.__xTitle,self.__yTitle))
#(refArrays, refLabel) = self.__getRefernceGraphArrays()
#refGraph = TGraphAsymmErrors(*refArrays)
#refGraph.SetLineWidth(2)
#refGraph.SetLineColor(int(self.__config.get("reference","lineColor")))
#refGraph.SetFillColor(int(self.__config.get("reference","fillColor")))
#result.Add(refGraph,"L3")
#legend.AddEntry(refGraph,self.__config.get("reference","name"))
xErr = array("d",[0 for i in range(n)])
print "__x = ", self.__x
print "__y = ", self.__y
lst = []
for inc in range (0,n):
d={}
d['run']=self.__runs[inc]
d['x']=self.__x[inc]
d['y']=self.__y[inc]
d['yErr']=self.__yErrLow[inc]
d['yTitle']=self.__yTitle
if self.__config.has_option(self.__section,"yMin") and self.__config.has_option(self.__section,"yMax") :
d['ymin']=float(self.__config.get(self.__section,"yMin"))
d['ymax']=float(self.__config.get(self.__section,"yMax"))
else:
d['ymin']=0
d['ymax']=0
lst.append(d)
obj ={}
obj[self.__title]=lst
#finalObj[self.__title]=lst
#finalList.append(finalObj)
# save_path = './JSON_A/'
#completeName = os.path.join(save_path, self.__title+".json")
if not os.path.exists("JSON_RECO"):
os.makedirs("JSON_RECO")
if not os.path.exists("JSON_RECO/"+dset):
os.makedirs("JSON_RECO/"+dset)
with open("./JSON_RECO/"+dset+"/"+self.__title+".json", 'w') as outfile:
json.dump(obj, outfile,indent=4)
print json.dumps(obj,indent=2)
graph = TGraphAsymmErrors(n, self.__x, self.__y, xErr, xErr, self.__yErrLow,self.__yErrHigh)
graph.SetLineWidth(2)
graph.SetFillColor(0)
graph.SetLineColor(int(self.__getStyleOption("lineColor")))
graph.SetMarkerColor(int(self.__getStyleOption("markerColor")))
graph.SetMarkerStyle(int(self.__getStyleOption("markerStyle")))
graph.SetMarkerSize(float(self.__getStyleOption("markerSize")))
sysGraph = TGraphAsymmErrors(n, self.__x, self.__y, xErr, xErr, self.__ySysErrLow,self.__ySysErrHigh)
sysGraph.SetLineWidth(1)
sysGraph.SetFillColor(0)
sysGraph.SetLineColor(int(self.__getStyleOption("lineColor")))
sysGraph.SetMarkerColor(int(self.__getStyleOption("markerColor")))
sysGraph.SetMarkerStyle(int(self.__getStyleOption("markerStyle")))
sysGraph.SetMarkerSize(float(self.__getStyleOption("markerSize")))
#TOMAS removed sys error from the plot
#result.Add(sysGraph,"[]")
result.Add(graph,"P")
# result.SetName("MultiPlots")
# result.SetTitle("%s;%s;%s"%(self.__title,self.__xTitle,self.__yTitle))
result.SetName("MG_%s"%(self.__title))
legend.AddEntry(graph, self.__getStyleOption("name"))
#for (x,y,yErr) in zip(self.__x, self.__y, zip(self.__yErrLow,self.__yErrHigh)):
# self.__addAnnotaion("hallo",x,y,yErr)
return (result, legend)
def makePlot1D(filepath, foutname, plottitle='', masstitle=''):
br = 1 if 'Resonant' in plottitle else 0.68
limits = parseLimitFiles2D(filepath, br)
xaxis = []
xseclist = []
xsecerr = []
cent = []
obs = []
up1 = []
up2 = []
down1 = []
down2 = []
maxval = 0
minval = 999
for m in sorted(limits):
l = limits[m]
xaxis.append(m)
xseclist.append(l.xsec)
xsecerr.append(l.xsec * .2)
cent.append(l.cent)
up1.append(l.up1 - l.cent)
up2.append(l.up2 - l.cent)
down1.append(l.cent - l.down1)
down2.append(l.cent - l.down2)
obs.append(l.obs)
maxval = max(maxval, l.up2)
minval = min(minval, l.down2)
N = len(xaxis)
up1Sigma = array('f', up1)
up2Sigma = array('f', up2)
down1Sigma = array('f', down1)
down2Sigma = array('f', down2)
cent = array('f', cent)
obs = array('f', obs)
xarray = array('f', xaxis)
xsecarray = array('f', xseclist)
xsecerrarray = array('f', xsecerr)
zeros = array('f', [0 for i in xrange(N)])
graphXsec = TGraphErrors(N, xarray, xsecarray, zeros, xsecerrarray)
graphCent = TGraph(N, xarray, cent)
graphObs = TGraph(N, xarray, obs)
graph1Sigma = TGraphAsymmErrors(N, xarray, cent, zeros, zeros, down1Sigma,
up1Sigma)
graph2Sigma = TGraphAsymmErrors(N, xarray, cent, zeros, zeros, down2Sigma,
up2Sigma)
c = TCanvas('c', 'c', 700, 600)
c.SetLogy()
c.SetLeftMargin(.15)
graph2Sigma.GetXaxis().SetTitle(masstitle + ' [GeV]')
graph2Sigma.GetYaxis().SetTitle(
'95% C.L. upper limit [#sigma/#sigma_{theory}]')
c2 = root.kOrange
c1 = root.kGreen + 1
graph2Sigma.SetLineColor(c2)
graph1Sigma.SetLineColor(c1)
graph2Sigma.SetFillColor(c2)
graph1Sigma.SetFillColor(c1)
graph2Sigma.SetMinimum(0.5 * minval)
graph2Sigma.SetMaximum(10 * maxval)
graphCent.SetLineWidth(2)
graphCent.SetLineStyle(2)
graphObs.SetLineColor(1)
graphObs.SetLineWidth(3)
graphObs.SetMarkerStyle(20)
graphObs.SetMarkerSize(1)
graphObs.SetMarkerColor(1)
graph1Sigma.SetLineStyle(0)
graph2Sigma.SetLineStyle(0)
leg = TLegend(0.55, 0.7, 0.9, 0.9)
leg.AddEntry(graphCent, 'Expected', 'L')
if not BLIND:
leg.AddEntry(graphObs, 'Observed', 'Lp')
leg.AddEntry(graph1Sigma, '1 std. dev.', 'F')
leg.AddEntry(graph2Sigma, '2 std. dev.', 'F')
leg.SetFillStyle(0)
leg.SetBorderSize(0)
graph2Sigma.Draw('A3')
graph1Sigma.Draw('3 same')
graphCent.Draw('same L')
if not BLIND:
graphObs.Draw('same Lp')
subscript = 'SR' if 'Resonant' in plottitle else 'FC'
coupling = '0.1' if 'Resonant' in plottitle else '0.25'
graphXsec.SetLineColor(2)
graphXsec.SetLineWidth(2)
graphXsec.SetLineStyle(2)
graphXsec.SetFillColor(2)
graphXsec.SetFillStyle(3005)
graphXsec.Draw('same L3')
'''
if not scale:
if 'Resonant' in plottitle:
leg.AddEntry(graphXsec,'Theory #splitline{a_{%s}=b_{%s}=%s}{m_{#chi}=100 GeV}'%(subscript,subscript,coupling),'l')
else:
leg.AddEntry(graphXsec,'Theory #splitline{a_{%s}=b_{%s}=%s}{m_{#chi}=10 GeV}'%(subscript,subscript,coupling),'l')
'''
if not BLIND:
findIntersect1D(graphObs, graphXsec, xaxis[0], xaxis[-1])
findIntersect1D(graphCent, graphXsec, xaxis[0], xaxis[-1])
leg.Draw()
label = TLatex()
label.SetNDC()
label.SetTextSize(0.8 * c.GetTopMargin())
label.SetTextFont(62)
label.SetTextAlign(11)
label.DrawLatex(0.15, 0.94, "CMS")
label.SetTextFont(52)
label.SetTextSize(0.6 * c.GetTopMargin())
# label.DrawLatex(0.25,0.94,"Preliminary")
label.SetTextFont(42)
label.SetTextSize(0.7 * c.GetTopMargin())
label.DrawLatex(0.19, 0.83, plottitle)
if 'Resonant' in plottitle:
label.DrawLatex(0.19, 0.75, "a_{SR} = b_{SR} = %s" % coupling)
label.DrawLatex(0.19, 0.68, "m_{#chi}=100 GeV")
else:
label.DrawLatex(0.19, 0.75, "g_{DM}^{V}=1,g_{q}^{V}=0.25")
label.DrawLatex(0.19, 0.68, "m_{#chi}=1 GeV")
label.SetTextSize(0.6 * c.GetTopMargin())
label.SetTextFont(42)
label.SetTextAlign(31) # align right
label.DrawLatex(0.95, 0.94, "%.1f fb^{-1} (13 TeV)" % (plotConfig.lumi))
c.SaveAs(foutname + '.pdf')
c.SaveAs(foutname + '.png')
exp1sigma = TGraphAsymmErrors(3, x, y_exp, zeros, zeros,
y_err1down, y_err1up)
exp2sigma = TGraphAsymmErrors(3, x, y_exp, zeros, zeros,
y_err2down, y_err2up)
explim = TGraph(3, x, y_exp)
obslim = TGraph(3, x, y_obs)
obslim.SetLineWidth(3)
explim.SetLineWidth(3)
explim.SetLineStyle(2)
explim.SetTitle('')
obslim.SetTitle('')
exp2sigma.SetTitle('')
exp1sigma.SetTitle('')
#obslim.SetMinimum(0.001);
#duesigma=TGraphAsymmErrors(3,)
exp1sigma.SetFillColor(kGreen + 1)
exp2sigma.SetFillColor(kOrange)
exp2sigma.SetMaximum(150)
exp2sigma.SetMinimum(0.07)
exp2sigma.Draw('a3lp')
exp2sigma.GetXaxis().SetTitle("Z' mass [TeV]")
exp2sigma.GetXaxis().SetRangeUser(1.4, 2.6)
exp2sigma.GetYaxis().SetTitle("Upper cross section limit [pb]")
sizefactor = 1.6
exp2sigma.GetXaxis().SetTitleSize(
sizefactor * exp2sigma.GetXaxis().GetTitleSize())
exp2sigma.GetYaxis().SetTitleSize(
sizefactor * exp2sigma.GetYaxis().GetTitleSize())
exp2sigma.GetXaxis().SetLabelSize(
sizefactor * exp2sigma.GetXaxis().GetLabelSize())
def pullsVertical_noBonly(fileName):
content = filterPullFile(fileName)
nbins, off = len(content), 0.10
# Graphs
h_pulls = TH2F("pulls", "", 6, -3., 3., nbins, 0, nbins)
S_pulls = TGraphAsymmErrors(nbins)
boxes = []
canvas = TCanvas("canvas", "Pulls", 720, 300 + nbins * 18) #nbins*20)
canvas.cd()
canvas.SetGrid(0, 1)
canvas.SetTopMargin(0.01)
canvas.SetRightMargin(0.01)
canvas.SetBottomMargin(0.10)
canvas.SetLeftMargin(0.40)
canvas.SetTicks(1, 1)
for i, s in enumerate(content):
l = s.split()
h_pulls.GetYaxis().SetBinLabel(i + 1, l[0])
S_pulls.SetPoint(i, float(l[3]), float(i + 1) - 0.5)
S_pulls.SetPointError(i, float(l[4]), float(l[4]), 0., 0.)
h_pulls.GetXaxis().SetTitle("(#hat{#theta} - #theta_{0}) / #Delta#theta")
h_pulls.GetXaxis().SetLabelOffset(0.0)
h_pulls.GetXaxis().SetTitleOffset(0.8)
h_pulls.GetXaxis().SetLabelSize(0.045)
h_pulls.GetXaxis().SetTitleSize(0.050)
h_pulls.GetYaxis().SetLabelSize(0.046)
h_pulls.GetYaxis().SetNdivisions(nbins, 0, 0)
S_pulls.SetFillColor(kBlack)
S_pulls.SetLineColor(kBlack)
S_pulls.SetMarkerColor(kBlack)
S_pulls.SetLineWidth(2)
S_pulls.SetMarkerStyle(20)
S_pulls.SetMarkerSize(1)
box1 = TBox(-1., 0., 1., nbins)
#box1.SetFillStyle(3001) # 3001 checkered
#box1.SetFillStyle(0)
box1.SetFillColor(kGreen + 1) # 417
box1.SetLineWidth(2)
box1.SetLineStyle(2)
box1.SetLineColor(kGreen + 1) # 417
box2 = TBox(-2., 0., 2., nbins)
#box2.SetFillStyle(3001) # 3001 checkered
#box2.SetFillStyle(0)
box2.SetFillColor(kOrange) # 800
box2.SetLineWidth(2)
box2.SetLineStyle(2)
box2.SetLineColor(kOrange) # 800
leg = TLegend(0.01, 0.01, 0.3, 0.15)
leg.SetTextSize(0.05)
leg.SetBorderSize(0)
leg.SetFillStyle(0)
leg.SetFillColor(0)
#leg.SetNColumns(2)
leg.AddEntry(S_pulls, "S+B fit", "lp")
if text: leg.AddEntry(0, text, "")
h_pulls.Draw("")
box2.Draw()
box1.Draw()
S_pulls.Draw("P6SAME")
leg.Draw()
canvas.RedrawAxis()
canvas.Print(outName + ".png")
canvas.Print(outName + ".pdf")
if not gROOT.IsBatch(): raw_input("Press Enter to continue...")
vexh = array('d',exh)
vey1l = array('d',ey1l)
vey1h = array('d',ey1h)
vey2l = array('d',ey2l)
vey2h = array('d',ey2h)
g1 = TGraphAsymmErrors(len(vx),vx,vy1,vexl,vexh,vey1l,vey1h)
g2 = TGraphAsymmErrors(len(vx),vx,vy2,vexl,vexh,vey2l,vey2h)
gObs = TGraph(len(vx),vx,vyObs)
gExp = TGraph(len(vx),vx,vyExp)
gxs = TGraph(len(vx),vx,vxs)
gExpDinko = TGraph(len(massesTeV_v),massesTeV_v,xs_exp_limits)
for i in range(0,len(massesTeV_v)):
print "exp limit Dinko: "+str(xs_exp_limits[i])
g2.SetFillColor(ROOT.kYellow)
g2.SetLineColor(ROOT.kYellow)
g1.SetFillColor(ROOT.kGreen)
g1.SetLineColor(ROOT.kGreen)
gExp.SetLineWidth(2)
gExp.SetLineStyle(9)
gExpDinko.SetLineWidth(2)
gExpDinko.SetLineStyle(2)
gObs.SetLineWidth(2)
gObs.SetLineStyle(1)
gObs.SetLineColor(ROOT.kBlue+1)
gObs.SetMarkerColor(ROOT.kBlue+1)
gObs.SetMarkerStyle(21)
gObs.SetMarkerSize(1.5)
gxs.SetLineStyle(5)
gxs.SetLineWidth(3)
