def nuisance_plot(input_file_, orien_, sticker_, oname_):
pars = get_parameters_from_file(input_file_)
#adjust_parameters(pars)
N = len(pars)
g68 = TGraph(2 * N + 7)
g95 = TGraph(2 * N + 7)
gPR = TGraphAsymmErrors(N)
for i in range(0, N):
x = pars[i].value
y = i + 1.5
xerr = pars[i].error
yerr = 0.
if orien_ == 'h':
x, y = y, x
xerr, yerr = yerr, xerr
gPR.SetPoint(i, x, y)
gPR.SetPointEXlow(i, xerr)
gPR.SetPointEYlow(i, yerr)
gPR.SetPointEXhigh(i, xerr)
gPR.SetPointEYhigh(i, yerr)
for a in range(0, N + 3):
if orien_ == 'h':
g68.SetPoint(a, a, -1)
g95.SetPoint(a, a, -2)
g68.SetPoint(a + 1 + N + 2, N + 2 - a, 1)
g95.SetPoint(a + 1 + N + 2, N + 2 - a, 2)
else:
g68.SetPoint(a, -1, a)
g95.SetPoint(a, -2, a)
g68.SetPoint(a + 1 + N + 2, 1, N + 2 - a)
g95.SetPoint(a + 1 + N + 2, 2, N + 2 - a)
gPR.SetLineStyle(1)
gPR.SetLineWidth(1)
gPR.SetLineColor(1)
gPR.SetMarkerStyle(21)
gPR.SetMarkerSize(1.25)
g68.SetFillColor(416)
g95.SetFillColor(400)
if orien_ == 'h':
text_TL = TPaveText(0.100, 0.925, 0.440, 0.995, 'NDC')
text_TR = TPaveText(0.587, 0.925, 0.999, 0.993, 'NDC')
else:
text_TL = TPaveText(0.370, 0.945, 0.590, 0.995, 'NDC')
text_TR = TPaveText(0.600, 0.945, 0.995, 0.993, 'NDC')
text_TL.AddText(label_TL)
text_TL.SetFillColor(0)
text_TL.SetTextAlign(12)
text_TL.SetTextSize(0.06)
text_TL.SetTextFont(42)
text_TR.AddText(sticker_)
text_TR.SetFillColor(0)
text_TR.SetTextAlign(32)
text_TR.SetTextSize(0.05)
text_TR.SetTextFont(42)
if orien_ == 'h':
c = TCanvas('c', 'c', 1000, 700)
c.SetTopMargin(0.08)
c.SetRightMargin(0.02)
c.SetBottomMargin(0.16)
c.SetLeftMargin(0.11)
else:
c = TCanvas('c', 'c', 700, 1000)
c.SetTopMargin(0.06)
c.SetRightMargin(0.02)
c.SetBottomMargin(0.12)
c.SetLeftMargin(0.35 * 700 / 650)
c.SetTickx()
c.SetTicky()
c.Update()
g95.Draw('AF')
g68.Draw('F')
gPR.Draw('P')
text_TL.Draw('same')
text_TR.Draw('same')
ax_1 = g95.GetHistogram().GetYaxis()
ax_2 = g95.GetHistogram().GetXaxis()
if orien_ == 'h': ax_1, ax_2 = ax_2, ax_1
ax_1.Set(N + 2, 0, N + 2)
ax_1.SetNdivisions(-414)
for i in range(0, N):
ax_1.SetBinLabel(i + 2, pars[i].name)
g95.SetTitle('')
ax_2.SetTitle('post-fit nuisance parameters values')
#ax_2.SetTitle('deviation in units of #sigma')
ax_1.SetTitleSize(0.050)
ax_2.SetTitleSize(0.050)
ax_1.SetTitleOffset(1.4)
ax_2.SetTitleOffset(1.0)
ax_1.SetLabelSize(0.05)
#ax_2.SetLabelSize(0.05)
ax_1.SetRangeUser(0, N + 2)
ax_2.SetRangeUser(-2.4, 2.4)
g95.GetHistogram().Draw('axis,same')
c.SaveAs(oname_ + '.pdf')
c.Close()
statBox.SetBorderSize(0)
# statBox.SetY2NDC(0.89)
# statBox.SetY1NDC(0.71)
# statBox.SetX2NDC(0.49)
# statBox.SetX1NDC(0.11)
statBox.SetX1NDC(0.11)
statBox.SetX2NDC(0.49)
statBox.SetY1NDC(0.69)
statBox.SetY2NDC(0.89)
# txt1 = TPaveText(x_0,gPad.GetUymin()+0.1,x_0+30,gPad.GetUymin()+1.50)
txt1 = TPaveText(0.65, 100, 0.75, 120)
txt1.AddText(str(lineFit.Eval(1 - (t_m / t_f))))
print(lineFit.Eval(1 - (t_m / t_f)))
txt1.SetFillColor(0)
txt1.SetTextFont(44)
txt1.SetTextSize(26)
# statBox.SetTextFont(44)
# statBox.SetTextSize(26)
statBox.Draw()
gPad.Update()
txt1.Draw()
gPad.Update()
DrawScatYLine(
tgr2, ";(t_{m+f} #minus t_{m})/t_{f} / event;Times FSQ is called / event",
"../images/mainFitEnhanced/fine/FvsFSQCalls", 1 - (t_m / t_f))
# Tested
#DrawScat(DefineScat(pValueCutLoFloat, tPerEvent), ";p-value low cut;CPU time / event [s]","../images/mainFitEnhanced/coarse/time")
# tracks_.append(tracks.GetEntries())
filler = 1
else:
filler = difference / all_value
h_acp.SetBinContent(bins + 1, math.fabs(1 - filler))
c1 = TCanvas()
tl = TLegend(.15, .785, .45, .9)
tl.SetBorderSize(0)
tl.SetFillColor(0)
tl.SetTextSize(16)
tl.SetTextFont(63)
tl.AddEntry(h_all, 'All events', 'l')
tl.AddEntry(h_hit, 'Coincidence', 'l')
tit = TPaveText(.5, .785, .7, .9, 'brNDC')
tit.SetTextSize(20)
tit.SetTextFont(63)
tit.SetBorderSize(0)
tit.SetFillColor(0)
tit.AddText('300 mm gap')
c1.SetTickx()
c1.SetTicky()
h_all.Draw()
h_hit.Draw('same')
tl.Draw('same')
tit.Draw('same')
h_acp.SetMarkerStyle(8)
c2 = TCanvas()
h_acp.Draw()
def DrawOverlap(fileVec,
histVec,
titleVec,
legendtext,
pngname,
logstatus=[0, 0],
xRange=[-99999, 99999, 1]):
gStyle.SetOptTitle(0)
gStyle.SetOptStat(0)
gStyle.SetTitleOffset(1.1, "Y")
gStyle.SetTitleOffset(0.9, "X")
gStyle.SetLineWidth(3)
gStyle.SetFrameLineWidth(3)
i = 0
histList_ = []
histList = []
histList1 = []
maximum = []
## Legend
leg = TLegend(0.4, 0.70, 0.939, 0.89) #,NULL,"brNDC");
legendtitle = legendtext[-1]
leg.SetHeader(legendtitle)
leg.SetBorderSize(0)
leg.SetNColumns(2)
leg.SetLineColor(1)
leg.SetLineStyle(1)
leg.SetLineWidth(1)
leg.SetFillColor(0)
leg.SetFillStyle(0)
leg.SetTextFont(22)
leg.SetTextSize(0.045)
c = TCanvas("c1", "c1", 0, 0, 500, 500)
#c.SetBottomMargin(0.15)
#c.SetLeftMargin(0.15)
#c.SetLogy(0)
#c.SetLogx(0)
c1_2 = TPad("c1_2", "newpad", 0.04, 0.05, 1, 0.994)
c1_2.Draw()
print("you have provided " + str(len(fileVec)) + " files and " +
str(len(histVec)) + " histograms to make a overlapping plot")
print "opening rootfiles"
c.cd()
#c1_2.SetBottomMargin(0.13)
c1_2.SetLogy(logstatus[1])
c1_2.SetLogx(logstatus[0])
c1_2.cd()
ii = 0
inputfile = {}
print str(fileVec[(len(fileVec) - 1)])
for ifile_ in range(len(fileVec)):
print("opening file " + fileVec[ifile_])
inputfile[ifile_] = TFile(fileVec[ifile_])
print "fetching histograms"
for ihisto_ in range(len(histVec)):
print("printing histo " + str(histVec[ihisto_]))
histo = inputfile[ifile_].Get(histVec[ihisto_])
#status_ = type(histo) is TGraphAsymmErrors
histList.append(histo)
# for ratio plot as they should nt be normalize
histList1.append(histo)
print histList[ii].Integral()
#histList[ii].Rebin(xRange[2])
type_obj = type(histList[ii])
if (type_obj is TH1D) or (type_obj is TH1F) or (
type_obj is TH1) or (type_obj is TH1I):
histList[ii].Rebin(1)
histList[ii].Scale(1.0 / histList[ii].Integral())
maximum.append(histList[ii].GetMaximum())
maximum.sort()
ii = ii + 1
print histList
for ih in range(len(histList)):
tt = type(histList[ih])
# print "graph_status =" ,(tt is TGraphAsymmErrors)
# print "hist status =", (tt is TH1D) or (tt is TH1F)
if ih == 0:
if (tt is TGraphAsymmErrors) | (tt is TGraph):
histList[ih].Draw("A3P")
if (tt is TH1D) or (tt is TH1F) or (tt is TH1) or (tt is TH1I):
histList[ih].Draw("HIST")
if ih > 0:
#histList[ih].SetLineWidth(2)
if (tt is TGraphAsymmErrors) | (tt is TGraph):
histList[ih].Draw("3P same")
if (tt is TH1D) or (tt is TH1F) or (tt is TH1) or (tt is TH1I):
histList[ih].Draw("HISTsame")
if (tt is TGraphAsymmErrors) | (tt is TGraph):
# histList[ih].SetMaximum(0.06)
# histList[ih].SetMinimum(0.02)
# histList[ih].SetMaximum(maximum+0.3)
histList[ih].SetMinimum(0.02)
histList[ih].SetMarkerColor(colors[ih])
histList[ih].SetLineColor(colors[ih])
histList[ih].SetLineWidth(3)
histList[ih].SetLineStyle(linestyle[ih])
histList[ih].SetMarkerStyle(markerStyle[ih])
histList[ih].SetMarkerSize(1)
leg.AddEntry(histList[ih], legendtext[ih], "P")
if (tt is TH1D) or (tt is TH1F) or (tt is TH1) or (tt is TH1I):
histList[ih].SetLineStyle(linestyle[ih])
histList[ih].SetLineColor(colors[ih])
histList[ih].SetLineWidth(3)
histList[ih].SetMaximum(maximum[0] + 0.3)
histList[ih].SetMinimum(0)
leg.AddEntry(histList[ih], legendtext[ih], "L")
histList[ih].GetYaxis().SetTitle(titleVec[1])
histList[ih].GetYaxis().SetTitleSize(0.045)
histList[ih].GetYaxis().SetTitleOffset(1.1000998)
histList[ih].GetYaxis().SetTitleFont(22)
histList[ih].GetYaxis().SetLabelFont(22)
histList[ih].GetYaxis().SetLabelSize(.045)
histList[ih].GetXaxis().SetRangeUser(xRange[0], xRange[1])
histList[ih].GetXaxis().SetLabelSize(0.0000)
histList[ih].GetXaxis().SetTitle(titleVec[0])
histList[ih].GetXaxis().SetLabelSize(0.052)
histList[ih].GetXaxis().SetTitleSize(0.052)
histList[ih].GetXaxis().SetTitleOffset(1.04)
histList[ih].GetXaxis().SetTitleFont(22)
histList[ih].GetXaxis().SetTickLength(0.07)
histList[ih].GetXaxis().SetLabelFont(22)
histList[ih].GetYaxis().SetLabelFont(22)
# histList[ih].GetXaxis().SetNdivisions(508)
#
i = i + 1
pt = TPaveText(0.0877181, 0.9, 0.9580537, 0.96, "brNDC")
pt.SetBorderSize(0)
pt.SetTextAlign(12)
pt.SetFillStyle(0)
pt.SetTextFont(22)
pt.SetTextSize(0.046)
text = pt.AddText(0.05, 0.5, "CMS Preliminary")
#text = pt.AddText(0.5,0.5,"12.9 fb^{-1} (13 TeV)")
# text = pt.AddText(0.8,0.5," (13 TeV)")
# text = pt.AddText(0.65,0.5," AK8")
pt.Draw()
# t2a = TPaveText(0.0877181,0.81,0.9580537,0.89,"brNDC")
# t2a.SetBorderSize(0)
# t2a.SetFillStyle(0)
# t2a.SetTextSize(0.040)
# t2a.SetTextAlign(12)
# t2a.SetTextFont(62)
# histolabel1= str(fileVec[(len(fileVec)-1)])
# text1 = t2a.AddText(0.06,0.5,"CMS Internal")
# t2a.Draw()
leg.Draw()
#
# c.cd()
outputdirname = 'HGCAL/'
histname = outputdirname + pngname
c.SaveAs(histname + '.png')
c.SaveAs(histname + '.pdf')
def make_histos(signal, com, cutflows, stage):
N2s = []
N1s = []
N2mN1s = []
nTots = []
nTotErrs = []
nEnds = []
nEndErrs = []
paveTitle = '?'
paveTitle2 = ''
for cutflow in glob(cutflows):
N2 = cutflow.split('_')[7]
N1 = cutflow.split('_')[8]
with open(cutflow, 'r') as f:
for line in f:
if line.split()[0] == 'entry' and line.split()[1] == 'point':
nTot = line.split()[2]
nTotErr = line.split()[3]
elif line.split()[0] == 'dR-Lep1-Lep2-smaller-2':
nEnd = line.split()[1]
nEndErr = line.split()[2]
N2s.append(float(N2))
N1s.append(float(N1))
N2mN1s.append(float(N2) - float(N1))
nTots.append(float(nTot))
nTotErrs.append(float(nTotErr))
nEnds.append(float(nEnd))
nEndErrs.append(float(nEndErr))
if signal == 'N2N1' and com == '13':
N2bins = [90., 110., 130., 150., 170., 190., 210., 230., 250.]
N2mN1bins = [6.5, 8.5, 12.5, 17.5, 25., 35., 45.]
elif signal == 'N2C1' and com == '13':
N2bins = [
87.5, 112.5, 137.5, 162.5, 187.5, 212.5, 237.5, 262.5, 287.5, 312.5
]
N2mN1bins = [6.5, 8.5, 12.5, 17.5, 25., 35., 45.]
elif signal == 'N2C1' and com == '14':
N2bins = [75., 125., 175., 225., 275., 325., 375., 425.]
N2mN1bins = [2.5, 7.5, 12.5, 17.5, 22.5, 27.5, 32.5, 37.5, 42.5]
N2bina = array('d', sorted(set(N2bins)))
N2mN1bina = array('d', sorted(set(N2mN1bins)))
# Histogram
h = TH2D('', '', len(N2bina) - 1, N2bina, len(N2mN1bina) - 1, N2mN1bina)
for idx in range(0, len(N2s)):
N2 = N2s[idx]
N1 = N1s[idx]
N2mN1 = N2mN1s[idx]
nTot = nTots[idx]
nTotErr = nTotErrs[idx]
nEnd = nEnds[idx]
nEndErr = nEndErrs[idx]
#print 'Foo01', N2, N2mN1, nEnd
if stage == 'nTot':
paveTitle = 'Total events'
h.Fill(N2, N2mN1, nTot)
elif stage == 'nEnd':
paveTitle = 'Events in SR'
h.Fill(N2, N2mN1, nEnd)
elif stage == 'Acc':
paveTitle = 'Acceptance'
paveTitle2 = '(*1000)'
try:
h.Fill(N2, N2mN1, 1000. * nEnd / nTot)
except ZeroDivisionError:
pass
# Style
gStyle.SetOptStat(0)
gStyle.SetPaintTextFormat('.2f')
h.GetXaxis().SetTitle('N2')
h.GetYaxis().SetTitle('dM')
set_palette()
# Pave Text
t1 = TPaveText(.1, .906, .2, 1., 'NDC')
t1.SetTextSize(.039)
t1.SetFillColor(0)
t1.SetFillStyle(0)
t1.SetLineWidth(0)
t1.SetTextAlign(12)
t1.AddText('CMS')
t2 = TPaveText(.13, .9, .9, 1., 'NDC')
t2.SetTextSize(.033)
t2.SetFillColor(0)
t2.SetFillStyle(0)
t2.SetLineWidth(0)
t2.SetTextAlign(12)
t2.SetTextFont(42)
t2.AddText('Phase-2 Simulation Preliminary {} {} at {}TeV {}'.format(
signal, paveTitle, com, paveTitle2))
# Plot
c = TCanvas()
#c.SetLogy()
h.Draw('colz|text')
t1.Draw('same')
t2.Draw('same')
c.Print('{}_{}_{}TeV.pdf'.format(stage, signal, com))
c.Print('{}_{}_{}TeV.png'.format(stage, signal, com))
def draw_fit(self, save_name, flag_plot_message=None, shade_regions=False):
#Draw
self.histo_to_fit.GetXaxis().SetTitle("Invariant Mass L_{c}^{+}(GeV/c^{2})")
self.histo_to_fit.SetStats(0)
c1 = TCanvas('c1', 'The Fit Canvas', 700, 700)
c1.cd()
gStyle.SetOptStat(0)
gStyle.SetCanvasColor(0)
gStyle.SetFrameFillColor(0)
c1.cd()
self.histo_to_fit.GetXaxis().SetRangeUser(self.fit_range_low, self.fit_range_up)
# Adjust y-range for good readability
histo_min = self.histo_to_fit.GetMinimum() * 0.9
histo_max = self.histo_to_fit.GetMaximum() + (self.histo_to_fit.GetMaximum() - histo_min)
self.histo_to_fit.GetYaxis().SetRangeUser(histo_min, histo_max)
self.histo_to_fit.SetMarkerStyle(20)
self.histo_to_fit.SetMarkerSize(1)
#histo.SetMinimum(0.)
self.histo_to_fit.Draw("PE")
self.bkg_tot_fit_func.Draw("same")
self.tot_fit_func.Draw("same")
c1.Update()
# Shading sideband area
sideband_fill_left = None
sideband_fill_right = None
sig_fill = None
bkg_fill = None
if shade_regions:
sideband_fill_left = self.bkg_tot_fit_func.Clone("bkg_fit_fill_left")
sideband_fill_left.SetRange(self.mean_fit - 9 * self.sigma_fit,
self.mean_fit - self.nsigma_sideband * self.sigma_fit)
sideband_fill_left.SetLineWidth(0)
sideband_fill_left.SetFillColor(self.bkg_tot_fit_func.GetLineColor())
sideband_fill_left.SetFillStyle(3001)
sideband_fill_left.Draw("same fc")
sideband_fill_right = self.bkg_tot_fit_func.Clone("bkg_fit_fill_right")
sideband_fill_right.SetRange(self.mean_fit + self.nsigma_sideband * self.sigma_fit,
self.mean_fit + 9 * self.sigma_fit)
sideband_fill_right.SetLineWidth(0)
sideband_fill_right.SetFillColor(self.bkg_tot_fit_func.GetLineColor())
sideband_fill_right.SetFillStyle(3001)
sideband_fill_right.Draw("same fc")
# Shading bakground in signal region
bkg_fill = self.bkg_tot_fit_func.Clone("bkg_fit_under_sig_fill")
bkg_fill.SetRange(self.mean_fit - self.nsigma_sig * self.sigma_fit,
self.mean_fit + self.nsigma_sig * self.sigma_fit)
bkg_fill.SetLineWidth(0)
bkg_fill.SetFillColor(kRed + 2)
bkg_fill.SetFillStyle(3001)
bkg_fill.Draw("same fc")
# Shading signal above background
n_points = 100
dx = (2 * self.nsigma_sig * self.sigma_fit) / n_points
sig_fill = TGraph(2 * n_points)
sig_fill.SetFillColor(kGreen + 2)
sig_fill.SetFillStyle(3001)
range_low = self.mean_fit - self.nsigma_sig * self.sigma_fit
range_up = self.mean_fit + self.nsigma_sig * self.sigma_fit
for ip in range(n_points):
sig_fill.SetPoint(ip, range_low + ip * dx,
self.tot_fit_func.Eval(range_low + ip * dx))
sig_fill.SetPoint(n_points + ip, range_up - ip * dx,
self.bkg_tot_fit_func.Eval(range_up - ip * dx))
sig_fill.Draw("f")
#write info.
pinfos = TPaveText(0.12, 0.7, 0.47, 0.89, "NDC")
pinfos.SetBorderSize(0)
pinfos.SetFillStyle(0)
pinfos.SetTextAlign(11)
pinfos.SetTextSize(0.03)
pinfom = TPaveText(0.5, 0.7, 1., .89, "NDC")
pinfom.SetTextAlign(11)
pinfom.SetBorderSize(0)
pinfom.SetFillStyle(0)
pinfom.SetTextColor(kBlue)
pinfom.SetTextSize(0.03)
chisquare_ndf = self.tot_fit_func.GetNDF()
chisquare_ndf = self.tot_fit_func.GetChisquare() / chisquare_ndf if chisquare_ndf > 0. \
else 0.
pinfom.AddText("#chi^{2}/NDF = %f" % (chisquare_ndf))
pinfom.AddText("%s = %.3f #pm %.3f" % (self.sig_fit_func.GetParName(1),\
self.sig_fit_func.GetParameter(1), self.sig_fit_func.GetParError(1)))
pinfom.AddText("%s = %.3f #pm %.3f" % (self.sig_fit_func.GetParName(2),\
self.sig_fit_func.GetParameter(2), self.sig_fit_func.GetParError(2)))
pinfom.Draw()
flag_info = None
if flag_plot_message is not None:
flag_info = TPaveText(0.5, 0.5, 1., 0.68, "NDC")
flag_info.SetBorderSize(0)
flag_info.SetFillStyle(0)
flag_info.SetTextAlign(11)
flag_info.SetTextSize(0.03)
for t in flag_plot_message:
text = flag_info.AddText(t)
text.SetTextColor(kRed + 2)
flag_info.Draw()
sig_text = pinfos.AddText("S = %.0f #pm %.0f " % (self.yield_sig, self.yield_sig_err))
sig_text.SetTextColor(kGreen + 2)
bkg_text = pinfos.AddText("B (%.0f#sigma) = %.0f #pm %.0f" % \
(self.nsigma_sig, self.yield_bkg, self.yield_bkg_err))
bkg_text.SetTextColor(kRed + 2)
sig_over_back = self.yield_sig / self.yield_bkg if self.yield_bkg > 0. else 0.
pinfos.AddText("S/B (%.0f#sigma) = %.4f " % (self.nsigma_sig, sig_over_back))
pinfos.AddText("Signif (%.0f#sigma) = %.1f #pm %.1f " %\
(self.nsigma_sig, self.significance, self.errsignificance))
pinfos.Draw()
c1.Update()
c1.SaveAs(save_name)
c1.Close()
def DrawOverlap(fileVec,
histVec,
titleVec,
legendtext,
pngname,
logstatus=[0, 0],
xRange=[-99999, 99999, 1]):
gStyle.SetOptTitle(0)
gStyle.SetOptStat(0)
gStyle.SetTitleOffset(1.1, "Y")
#gStyle.SetTitleOffset(1.9,"X");
gStyle.SetLineWidth(3)
gStyle.SetFrameLineWidth(3)
i = 0
histList_ = []
histList = []
histList1 = []
maximum = []
## Legend
leg = TLegend(0.1, 0.70, 0.89, 0.89) #,NULL,"brNDC");
leg.SetBorderSize(0)
leg.SetNColumns(2)
leg.SetLineColor(1)
leg.SetLineStyle(1)
leg.SetLineWidth(1)
leg.SetFillColor(0)
leg.SetFillStyle(0)
leg.SetTextFont(42)
leg.SetTextSize(0.04)
c = TCanvas("c1", "c1", 0, 0, 500, 500)
c.SetBottomMargin(0.15)
c.SetLogy(logstatus[1])
c.SetLogx(logstatus[0])
print("you have provided " + str(len(fileVec)) + " files and " +
str(len(histVec)) + " histograms to make a overlapping plot")
print "opening rootfiles"
c.cd()
ii = 0
inputfile = {}
print str(fileVec[(len(fileVec) - 1)])
for ifile_ in range(len(fileVec)):
print("opening file " + fileVec[ifile_])
inputfile[ifile_] = TFile(fileVec[ifile_])
print "fetching histograms"
for ihisto_ in range(len(histVec)):
print("printing histo " + str(histVec[ihisto_]))
histo = inputfile[ifile_].Get(histVec[ihisto_])
#status_ = type(histo) is TGraphAsymmErrors
histList.append(histo)
# for ratio plot as they should nt be normalize
histList1.append(histo)
#print histList[ii].Integral()
#histList[ii].Rebin(xRange[2])
#histList[ii].Scale(1.0/histList[ii].Integral())
maximum.append(histList[ii].GetMaximum())
maximum.sort()
ii = ii + 1
print histList
for ih in range(len(histList)):
tt = type(histList[ih])
if logstatus[1] is 1:
#histList[ih].SetMaximum(100) #1.4 for log
#histList[ih].SetMinimum(0.1) #1.4 for log
histList[ih].SetMaximum(10)
histList[ih].SetMinimum(0.001)
if logstatus[1] is 0:
histList[ih].SetMaximum(1.4) #1.4 for log
histList[ih].SetMinimum(0.001) #1.4 for log
# print "graph_status =" ,(tt is TGraphAsymmErrors)
# print "hist status =", (tt is TH1D) or (tt is TH1F)
if ih == 0:
if tt is TGraphAsymmErrors:
histList[ih].Draw("APL")
if (tt is TH1D) or (tt is TH1F) or (tt is TH1) or (tt is TH1I):
histList[ih].Draw() ## removed hist
if ih > 0:
#histList[ih].SetLineWidth(2)
if tt is TGraphAsymmErrors:
histList[ih].Draw("PL same")
if (tt is TH1D) or (tt is TH1F) or (tt is TH1) or (tt is TH1I):
histList[ih].Draw("same") ## removed hist
if tt is TGraphAsymmErrors:
histList[ih].SetMaximum(100)
histList[ih].SetMarkerColor(colors[ih])
histList[ih].SetLineColor(colors[ih])
histList[ih].SetLineWidth(2)
histList[ih].SetMarkerStyle(markerStyle[ih])
histList[ih].SetMarkerSize(1)
leg.AddEntry(histList[ih], legendtext[ih], "PL")
if (tt is TH1D) or (tt is TH1F) or (tt is TH1) or (tt is TH1I):
histList[ih].SetLineStyle(linestyle[ih])
histList[ih].SetLineColor(colors[ih])
histList[ih].SetLineWidth(3)
leg.AddEntry(histList[ih], legendtext[ih], "L")
histList[ih].GetYaxis().SetTitle(titleVec[1])
histList[ih].GetYaxis().SetTitleSize(0.052)
histList[ih].GetYaxis().SetTitleOffset(0.98)
histList[ih].GetYaxis().SetTitleFont(42)
histList[ih].GetYaxis().SetLabelFont(42)
histList[ih].GetYaxis().SetLabelSize(.052)
histList[ih].GetXaxis().SetRangeUser(xRange[0], xRange[1])
# histList[ih].GetXaxis().SetLabelSize(0.0000);
histList[ih].GetXaxis().SetTitle(titleVec[0])
histList[ih].GetXaxis().SetLabelSize(0.052)
histList[ih].GetXaxis().SetTitleSize(0.052)
#histList[ih].GetXaxis().SetTitleOffset(1.14)
histList[ih].GetXaxis().SetTitleFont(42)
histList[ih].GetXaxis().SetLabelFont(42)
histList[ih].GetYaxis().SetLabelFont(42)
histList[ih].GetXaxis().SetNdivisions(507)
#histList[ih].GetXaxis().SetMoreLogLabels();
#histList[ih].GetXaxis().SetNoExponent();
#histList[ih].GetTGaxis().SetMaxDigits(3);
i = i + 1
pt = TPaveText(0.01, 0.92, 0.95, 0.96, "brNDC")
pt.SetBorderSize(0)
pt.SetTextAlign(12)
pt.SetFillStyle(0)
pt.SetTextFont(42)
pt.SetTextSize(0.046)
#text = pt.AddText(0.12,0.35,"CMS Internal 36 fb^{-1} (2016) ")
text = pt.AddText(0.12, 0.35,
"CMS Internal 41.5 fb^{-1} (2017) ")
#text = pt.AddText(0.12,0.35,"CMS Internal 59.6 fb^{-1} (2018) ")
#text = pt.AddText(0.6,0.5,"41.5 fb^{-1} (2017) ")
pt.Draw()
leg.Draw()
outputdirname = 'plots_limit/limitcomp//'
histname = outputdirname + pngname
c.SaveAs(histname + '.png')
c.SaveAs(histname + '.pdf')
outputname = 'cp -r ' + outputdirname + '/*' + ' /afs/cern.ch/work/k/khurana/public/AnalysisStuff/monoH/LimitModelPlots/plots_limit/limitcomp/'
def plotMet(self):
if hasattr(self, "TagPt35") or hasattr(self, "TagPt35ForNctrl"):
if self._fout and self._canvas:
sample = self.TagPt35ForNctrl["sample"] if hasattr(
self, "TagPt35ForNctrl") else self.TagPt35["sample"]
condorDir = self.TagPt35ForNctrl["condorDir"] if hasattr(
self, "TagPt35ForNctrl") else self.TagPt35["condorDir"]
name = self.TagPt35ForNctrl["name"] if hasattr(
self, "TagPt35ForNctrl") else self.TagPt35["name"]
hist = self._Flavor + " Plots/" + self._flavor + "MetNoMuMinusOnePt"
metMinusOne = getHist(sample, condorDir, name + "Plotter",
hist)
hist = self._Flavor + " Plots/" + self._flavor + "MetNoMuMinusOneUpPt"
metMinusOneUp = getHist(sample, condorDir, name + "Plotter",
hist)
metMinusOne.Rebin(self._rebinFactor)
metMinusOneUp.Rebin(self._rebinFactor)
pt = TPaveText(0.398496, 0.839147, 0.798246, 0.886951, "brNDC")
pt.SetBorderSize(0)
pt.SetFillStyle(0)
pt.SetTextFont(42)
pt.SetTextSize(0.0387597)
pt.AddText(str(self._plotLabel))
cmsLabel = TPaveText(0.134085, 0.937984, 0.418546, 0.984496,
"brNDC")
cmsLabel.SetBorderSize(0)
cmsLabel.SetFillStyle(0)
cmsLabel.SetTextFont(62)
cmsLabel.SetTextSize(0.0387597)
cmsLabel.AddText("CMS Preliminary")
lumiLabel = TPaveText(0.66416, 0.937339, 0.962406, 0.992894,
"brNDC")
lumiLabel.SetBorderSize(0)
lumiLabel.SetFillStyle(0)
lumiLabel.SetTextFont(42)
lumiLabel.SetTextSize(0.0387597)
lumiLabel.AddText(str(self._luminosityLabel))
leg = TLegend(0.414787, 0.726098, 0.606516, 0.829457)
leg.SetBorderSize(0)
leg.SetTextSize(0.0388601)
leg.SetTextFont(42)
leg.SetLineColor(1)
leg.SetLineStyle(1)
leg.SetLineWidth(1)
leg.SetFillColor(0)
leg.SetFillStyle(0)
leg.AddEntry(
metMinusOne,
"nominal (#mu = " + str(round(metMinusOne.GetMean(), 1)) +
" #pm " + str(round(metMinusOne.GetMeanError(), 1)) + ")",
"p")
leg.AddEntry(
metMinusOneUp, "scaled down (#mu = " +
str(round(metMinusOneUp.GetMean(), 1)) + " #pm " +
str(round(metMinusOneUp.GetMeanError(), 1)) + ")", "p")
setStyle(metMinusOne, 600)
setAxisStyle(
metMinusOne, "E_{T}^{miss, no #mu} " +
("excluding selected " +
self._flavor if self._flavor != "muon" else "") +
" [GeV]")
setStyle(metMinusOneUp, 632)
setAxisStyle(
metMinusOneUp, "E_{T}^{miss, no #mu} " +
("excluding selected " +
self._flavor if self._flavor != "muon" else "") +
" [GeV]")
self._canvas.cd()
metMinusOneUp.Draw()
metMinusOne.Draw("same")
pt.Draw("same")
cmsLabel.Draw("same")
lumiLabel.Draw("same")
leg.Draw("same")
self._fout.cd()
self._canvas.Write("metMinusOneComparison")
else:
print("A TFile and TCanvas must be added. Not making plots...")
else:
print(
"Neither TagPt35 nor TagPt35ForNctrl defined. Not plotting MET..."
)
def main():
from optparse import OptionParser
parser = OptionParser()
parser.add_option("-i", "--inputfile", dest="inputfile")
(options, args) = parser.parse_args()
from ROOT import TFile, TCanvas, TPaveText, TLegend
import configurations as config
from Styles import formatCL
infile = TFile(options.inputfile, "READ")
oldfile = TFile(config.MI_old_file, "READ")
store = []
alphabet = "abcdefghijklmnopqrstuvwxyz"
for iNmin, Nmin in enumerate(config.inclusive_multiplicities):
c = TCanvas("UpperLimits_Inclusive_Mul%d" % Nmin,
"N >= %d" % Nmin, 500, 500)
store.append(c)
gCL95 = infile.Get("CL95_N%dup" % Nmin)
formatCL(gCL95, "CL95")
gCL95.SetTitle("")
gCL95.Draw("AL")
gCLA = infile.Get("CLA_N%dup" % Nmin)
formatCL(gCLA, "CLA")
gCLA.SetTitle("")
gCLA.Draw("L")
label_11 = TPaveText(0.7116935,0.2076271,0.9193548,0.2605932,"brNDC")
label_11.AddText(config.MI_new_label)
label_11.SetTextSize(0.03813559);
label_11.SetTextFont(42)
label_11.SetFillColor(0)
label_11.Draw("plain")
store.append(label_11)
if Nmin <= config.MI_old_Nmin:
gCL95_ = oldfile.Get("CL95_N%dup" % Nmin)
formatCL(gCL95_, "CL95", 2)
gCL95_.SetLineStyle(9)
gCL95_.SetTitle("")
gCL95_.Draw("L")
gCLA_ = oldfile.Get("CLA_N%dup" % Nmin)
formatCL(gCLA_, "CLA", 2)
gCLA_.SetTitle("")
gCLA_.Draw("L")
label_10 = TPaveText(0.6995968,0.4364407,0.9314516,0.4809322,"brNDC")
label_10.AddText(config.MI_old_label)
label_10.SetTextSize(0.03813559);
label_10.SetTextFont(42)
label_10.SetFillColor(0)
label_10.Draw("plain")
gCLA_.SetLineStyle(10)
store.append(label_10)
gCL95.GetXaxis().SetRangeUser(config.low_bin[0], config.MI_maxST + 100)
gCL95.GetYaxis().SetRangeUser(1e-3, 15.0)
cmslabel = TPaveText(0.3991935,0.7775424,0.8306452,0.9237288,"brNDC")
cmslabel.AddText(config.cmsTitle)
cmslabel.AddText(config.cmsSubtitle)
cmslabel.SetFillColor(0)
cmslabel.Draw("plain")
store.append(cmslabel)
legend = TLegend(0.4274194,0.5614407,0.7983871,0.7605932)
legend.SetTextSize(0.04237288)
legend.SetTextFont(42)
legend.SetHeader("N #geq %d" % Nmin)
legend.AddEntry(gCL95, "Observed #sigma^{95}", "l")
legend.AddEntry(gCLA, "Expected #sigma^{95}_{exp.}", "l")
legend.SetFillColor(0)
legend.SetLineColor(0)
legend.Draw("plain")
store.append(legend)
label = TPaveText(0.8891129,0.8644068,0.9435484,0.9258475,"brNDC")
label.SetFillColor(0)
label.SetTextSize(0.0529661);
label.AddText("%s)" % alphabet[iNmin])
label.Draw("plain")
store.append(label)
c.SetLogy(1)
c.Print("UpperLimits_Inclusive_Mul%d.pdf" % Nmin)
c.Update()
raw_input("Press Enter to continue...")
def limit_canvas(limits_, signal_, oname_):
m = [mp.mass for mp in limits_]
exp = [mp.exp for mp in limits_]
exp68up = [mp.exp68up for mp in limits_]
exp68dn = [mp.exp68dn for mp in limits_]
exp95up = [mp.exp95up for mp in limits_]
exp95dn = [mp.exp95dn for mp in limits_]
obs = [mp.obs for mp in limits_]
N = len(limits_)
gExp = TGraph()
g68 = TGraph(2*N)
g95 = TGraph(2*N)
gObs = TGraph()
gTH = get_theory_XsecBR_graph(signal_)
for a in range(0,N):
gExp.SetPoint(a,m[a],exp[a])
gObs.SetPoint(a,m[a],obs[a])
g68.SetPoint(a,m[a],exp68dn[a])
g95.SetPoint(a,m[a],exp95dn[a])
g68.SetPoint(N+a,m[N-a-1],exp68up[N-a-1])
g95.SetPoint(N+a,m[N-a-1],exp95up[N-a-1])
trans = 0
up = 0
if signal_ == 'n':
trans = 0.770776
up = 3
if signal_ == 'w':
trans = 0.836432
up = 10
if signal_ == 'r':
trans = 0.899902
up = 4
gExp.SetLineStyle(2)
gExp.SetLineWidth(4)
gExp.SetLineColor(TColor.GetColor('#112288'))
#gExp.Print()
g68.SetLineStyle(1)
g68.SetLineWidth(0)
g68.SetLineColor(kBlack)
g68.SetFillColor(TColor.GetColor('#4488dd'))
g95.SetLineStyle(1)
g95.SetLineWidth(0)
g95.SetLineColor(kBlack)
g95.SetFillColor(TColor.GetColor('#99bbff'))
gObs.SetLineStyle(1)
gObs.SetLineWidth(4)
gObs.SetLineColor(kBlack)
gObs.SetMarkerStyle(21)
gObs.SetMarkerSize(0.8)
gTH.SetLineStyle(7)
gTH.SetLineWidth(4)
gTH.SetMarkerSize(0)
gTH.SetMarkerColor(kRed+1)
gTH.SetLineColor(kRed+1)
leg = TLegend(0.58,0.633,0.969,0.908)
leg.SetFillColor(0)
leg.SetBorderSize(0)
leg.AddEntry(gExp,'Expected (95% CL)','l')
leg.AddEntry(gObs,'Observed (95% CL)','l')
leg.AddEntry(gTH,signal_dict[signal_][1],'l')
leg.AddEntry(g68,'#pm1#sigma Expected','f')
leg.AddEntry(g95,'#pm2#sigma Expected','f')
text_TL = TPaveText(0.18,0.830,0.44,0.900,'NDC')
text_TL.AddText(label_TL)
text_TL.SetFillColor(0)
text_TL.SetTextAlign(12)
text_TL.SetTextSize(0.06)
text_TL.SetTextFont(42)
text_TR = TPaveText(0.586,0.923,0.999,0.997,'NDC')
text_TR.AddText(label_TR)
text_TR.SetFillColor(0)
text_TR.SetTextAlign(32)
text_TR.SetTextSize(0.055)
text_TR.SetTextFont(42)
c = TCanvas('c','c',950,750)
c.SetTopMargin(0.08)
c.SetRightMargin(0.02)
c.SetBottomMargin(0.135)
c.SetLeftMargin(0.11)
#c.SetGrid()
c.SetLogy()
#hr = c.DrawFrame(0.401,0.001,3.999,1000)
#hr = c.DrawFrame(0.401,0.001,4.199,1000)
hr = c.DrawFrame(0.401,0.001,5.199,1000)
gExp.Sort()
gTH.Print()
g95.Draw('f')
g95.Print()
g68.Draw('f')
gTH.Draw('L')
gExp.Draw('L')
#Don't draw observed for blind analysis
# gObs.Sort()
# gObs.Draw('L')
hr.GetXaxis().SetTitle('M_{'+signal_dict[signal_][0]+'} [TeV]')
hr.GetYaxis().SetTitle('Upper limit on #sigma_{'+signal_dict[signal_][0]+'} #times B('+signal_dict[signal_][0]+' #rightarrow t#bar{t}) [pb]')
#hr.GetYaxis().SetTitle('\\mathrm{Upper~limit~on~}\\sigma_{'+signal_dict[signal_][0]+'}\\times\\mathscr{B}('+signal_dict[signal_][0]+' \\rightarrow t\\bar{t}) [pb]')
hr.GetXaxis().SetTitleSize(0.055)
hr.GetYaxis().SetTitleSize(0.055)
hr.GetXaxis().SetTitleFont(42)
hr.GetYaxis().SetTitleFont(42)
hr.GetXaxis().SetTitleOffset(1.00)
hr.GetYaxis().SetTitleOffset(0.98)
hr.GetXaxis().SetLabelSize(0.045)
hr.GetYaxis().SetLabelSize(0.045)
name = TString(oname_)
if name.Contains("com"):
tl = TLine(trans, 1e-3, trans, up)
tl.SetLineStyle(ROOT.kDashed)
tl.SetLineColor(kGray+1)
tl.SetLineWidth(3)
tl.Draw()
c.Update()
text_TL.Draw('same')
text_TR.Draw('same')
leg.Draw()
c.SaveAs(oname_+'.pdf')
c.Close()
def printSystematic(self):
fakeRate3, fakeRate3Error, ratio3, ratio3Error = self.printFakeRateRatio(
3)
fakeRate4, fakeRate4Error, ratio4, ratio4Error = self.printFakeRateRatio(
4)
fakeRate5, fakeRate5Error, ratio5, ratio5Error = self.printFakeRateRatio(
5)
fakeRate6, fakeRate6Error, ratio6, ratio6Error = self.printFakeRateRatio(
6)
print("systematic uncertainty: " +
str((abs(ratio5 - 1.0) + ratio5Error) * 100.0) + "%")
basicFakeRate = TH1D("basicFakeRate", ";number of hits", 400, 2.5, 6.5)
zToMuMuFakeRate = TH1D("zToMuMuFakeRate", ";number of hits", 400, 2.5,
6.5)
ratio = TH1D("ratio", ";number of hits", 400, 2.5, 6.5)
basicFakeRate.SetBinContent(basicFakeRate.FindBin(3.0), fakeRate3[0])
basicFakeRate.SetBinError(basicFakeRate.FindBin(3.0),
fakeRate3Error[0])
basicFakeRate.SetBinContent(basicFakeRate.FindBin(4.0), fakeRate4[0])
basicFakeRate.SetBinError(basicFakeRate.FindBin(4.0),
fakeRate4Error[0])
basicFakeRate.SetBinContent(basicFakeRate.FindBin(5.0), fakeRate5[0])
basicFakeRate.SetBinError(basicFakeRate.FindBin(5.0),
fakeRate5Error[0])
basicFakeRate.SetBinContent(basicFakeRate.FindBin(6.0), fakeRate6[0])
basicFakeRate.SetBinError(basicFakeRate.FindBin(6.0),
fakeRate6Error[0])
zToMuMuFakeRate.SetBinContent(zToMuMuFakeRate.FindBin(3.0),
fakeRate3[1])
zToMuMuFakeRate.SetBinError(zToMuMuFakeRate.FindBin(3.0),
fakeRate3Error[1])
zToMuMuFakeRate.SetBinContent(zToMuMuFakeRate.FindBin(4.0),
fakeRate4[1])
zToMuMuFakeRate.SetBinError(zToMuMuFakeRate.FindBin(4.0),
fakeRate4Error[1])
zToMuMuFakeRate.SetBinContent(zToMuMuFakeRate.FindBin(5.0),
fakeRate5[1])
zToMuMuFakeRate.SetBinError(zToMuMuFakeRate.FindBin(5.0),
fakeRate5Error[1])
zToMuMuFakeRate.SetBinContent(zToMuMuFakeRate.FindBin(6.0),
fakeRate6[1])
zToMuMuFakeRate.SetBinError(zToMuMuFakeRate.FindBin(6.0),
fakeRate6Error[1])
ratio.SetBinContent(ratio.FindBin(3.0), ratio3)
ratio.SetBinError(ratio.FindBin(3.0), ratio3Error)
ratio.SetBinContent(ratio.FindBin(4.0), ratio4)
ratio.SetBinError(ratio.FindBin(4.0), ratio4Error)
ratio.SetBinContent(ratio.FindBin(5.0), ratio5)
ratio.SetBinError(ratio.FindBin(5.0), ratio5Error)
ratio.SetBinContent(ratio.FindBin(6.0), ratio6)
ratio.SetBinError(ratio.FindBin(6.0), ratio6Error)
cmsLabel = TPaveText(0.134085, 0.937984, 0.418546, 0.984496, "brNDC")
cmsLabel.SetBorderSize(0)
cmsLabel.SetFillStyle(0)
cmsLabel.SetTextFont(62)
cmsLabel.SetTextSize(0.0387597)
cmsLabel.AddText("CMS Preliminary")
lumiLabel = TPaveText(0.66416, 0.937339, 0.962406, 0.992894, "brNDC")
lumiLabel.SetBorderSize(0)
lumiLabel.SetFillStyle(0)
lumiLabel.SetTextFont(42)
lumiLabel.SetTextSize(0.0387597)
lumiLabel.AddText(str(self._luminosityLabel))
leg = TLegend(0.7550251, 0.7759067, 0.9459799, 0.8795337)
leg.SetBorderSize(0)
leg.SetTextSize(0.0388601)
leg.SetTextFont(42)
leg.SetLineColor(1)
leg.SetLineStyle(1)
leg.SetLineWidth(1)
leg.SetFillColor(0)
leg.SetFillStyle(0)
leg.AddEntry(zToMuMuFakeRate, "Z#rightarrow#mu#mu", "p")
leg.AddEntry(basicFakeRate, "basic", "p")
setStyle(basicFakeRate, 632)
setStyle(zToMuMuFakeRate, 600)
setAxisStyle(basicFakeRate, yTitle="P_{fake}")
setAxisStyle(zToMuMuFakeRate, yTitle="P_{fake}")
self._canvas.cd()
self._canvas.SetLogy()
zToMuMuFakeRate.Draw()
basicFakeRate.Draw("same")
leg.Draw("same")
cmsLabel.Draw("same")
lumiLabel.Draw("same")
self._fout.cd()
self._canvas.Write("fakeRate")
line = TLine(2.5, 1.0, 6.5, 1.0)
line.SetLineStyle(2)
line.SetLineWidth(2)
line.SetLineColor(1)
setStyle(ratio)
setAxisStyle(
ratio,
yTitle=("P_{fake}^{Z#rightarrow#mu#mu} / P_{fake}^{basic}"
if not self._plotDiff else
"P_{fake}^{Z#rightarrow#mu#mu} - P_{fake}^{basic}"))
self._canvas.cd()
self._canvas.SetLogy(False)
ratio.Draw()
line.Draw("same")
cmsLabel.Draw("same")
lumiLabel.Draw("same")
self._fout.cd()
self._canvas.Write("fakeRateRatio")
def Measure_Integral(AllRuns, Title, RootName):
FNumber=len(AllRuns)
xIntegral=array("d",xrange(0,FNumber))
yIntegral=array("d",xrange(0,FNumber))
yIntegralErrUp=array("d",xrange(0,FNumber))
yIntegralErrDown=array("d",xrange(0,FNumber))
xIntegral_RMS=array("d",xrange(0,FNumber))
yIntegral_RMS=array("d",xrange(0,FNumber))
yIntegral_RMSErrUp=array("d",xrange(0,FNumber))
yIntegral_RMSErrDown=array("d",xrange(0,FNumber))
xRatio=array("d",xrange(0,FNumber))
yRatio=array("d",xrange(0,FNumber))
xSingleEv=array("d",xrange(0,40))
ySingleEv=array("d",xrange(0,40))
OutFile=TFile(RootName,"RECREATE")
num=-1
iAmp=0
for Fname in AllRuns:
num+=1
iAmp+=1
f = open(Fname)
data = getData(f)
M=TH1F(Fname,Fname,600,0,120000)
x = array("d", xrange(0,1001))
y = array("d", xrange(0,1001))
for event in xrange(0,995):
pedSum=0
sigSum=0
Signal=0
Pedestal=0
for BX in xrange(0, 40):
adcValue=data[event][link][BX][linkChannel]
if BX < 15 : pedSum += adcValue
if BX > 19 and BX < 25: sigSum += adcValue
xSingleEv[BX]=BX
ySingleEv[BX]=adcValue
scanvas = MakeCanvas("mm","nn",800,800)
GrSingleEv=TGraph(len(xSingleEv),xSingleEv,ySingleEv)
OutFile.WriteObject(GrSingleEv,"singleEv_"+str(iAmp)+"_"+str(event))
SFit=TF1("fit", "gaus", 19,23)
SFit.SetParameter(0, 4000)
SFit.SetParameter(1, 20.9)
SFit.SetParLimits(1, 20, 22)
SFit.SetParameter(2, 1.5)
GrSingleEv.Draw("AC*")
GrSingleEv.Fit("fit","R0")
SFit.Draw("same")
FitParam=SFit.GetParameters()
print "Gaus fit param 1, 2, 3= " , round(FitParam[0],4), round(FitParam[1],4), round(FitParam[2],4)
scanvas.SaveAs("PLOT/singleEv_"+str(iAmp)+"_"+str(event)+".pdf")
Pedestal=pedSum/15.
y[event]= sigSum- Pedestal*5
M.Fill(y[event])
histMean= M.GetMean()
histRMS= M.GetStdDev()
highVal = histMean + 4 * histRMS
lowVal = histMean - 4 * histRMS
highValAx = histMean + 6 * histRMS
lowValAx = histMean - 6 * histRMS
canvas = MakeCanvas("asdf","asdf",800,800)
canvas.Update()
MyGr= TGraph(len(x), x,y)
mfit=TF1("fit", "gaus", lowVal,highVal)
M.Fit(mfit, "R0","")
FitParam=mfit.GetParameters()
# FitParErr=mfit.GetParError()
integral= round(FitParam[1],4)
integral_RMS= round(FitParam[2],4)
integralErr= round(mfit.GetParError(1),4)
integral_RMSErr= round(mfit.GetParError(2),4)
print "iAmp=", iAmp, " integral= ", integral, " integral_RMS=", integral_RMS
M.SetMarkerStyle(22)
M.GetXaxis().SetRangeUser(lowValAx,highValAx)
M.SetTitle(Title+" = "+str(iAmp))
M.Draw("pe")
mfit.Draw("same")
fitInfo =TPaveText(.20,0.7,.60,0.9, "NDC");
fitInfo.SetBorderSize( 0 );
fitInfo.SetFillStyle( 0 );
fitInfo.SetTextAlign( 12 );
fitInfo.SetTextSize ( 0.03 );
fitInfo.SetTextColor( 1 );
fitInfo.SetTextFont ( 62 );
fitInfo.AddText("Mean of Fit=" + str(round(FitParam[1],1)))
fitInfo.AddText("RMS of Fit =" + str(round(FitParam[2],1)))
fitInfo.Draw()
canvas.SaveAs("HistoSingleRun_"+str(iAmp)+"_"+Title+RootName+".pdf")
xIntegral[num]=iAmp
yIntegral[num]=integral
yIntegralErrUp[num]=integral+integralErr
yIntegralErrDown[num]=integral-integralErr
xIntegral_RMS[num]=iAmp
yIntegral_RMS[num]=integral_RMS
yIntegral_RMSErrUp[num]=integral_RMS+integral_RMSErr
yIntegral_RMSErrDown[num]=integral_RMS-integral_RMSErr
xRatio[num]=iAmp
yRatio[num]=integral_RMS/integral
# xIntegral.append(iAmp)
# yIntegral.append(integral)
# xIntegral_RMS.append(iAmp)
# yIntegral_RMS.append(integral_RMS)
Graph_Integral= TGraph(len(xIntegral), xIntegral,yIntegral)
Graph_IntegralErUp= TGraph(len(xIntegral), xIntegral,yIntegralErrUp)
Graph_IntegralErDown= TGraph(len(xIntegral), xIntegral,yIntegralErrDown)
canvas_Integral = MakeCanvas("can1","can1",800,800)
# canvas_Integral.SetLogy()
Graph_Integral.SetTitle("Pulse Integral Stability")
Graph_Integral.SetMarkerStyle(22)
Graph_Integral.SetMarkerColor(3)
Graph_Integral.SetMarkerSize(2)
Graph_Integral.GetXaxis().SetTitle("Day")
Graph_Integral.GetYaxis().SetRangeUser(80000,85000)
Graph_Integral.Draw()
# Graph_IntegralErUp.Draw("same")
# Graph_IntegralErDown.Draw("same")
canvas_Integral.SaveAs("Integral_"+Title+RootName+".pdf")
Graph_Integral_RMS= TGraph(len(xIntegral_RMS), xIntegral_RMS,yIntegral_RMS)
Graph_Integral_RMSErUp= TGraph(len(xIntegral_RMS), xIntegral_RMS,yIntegral_RMSErrUp)
Graph_Integral_RMSErDown= TGraph(len(xIntegral_RMS), xIntegral_RMS,yIntegral_RMSErrDown)
canvas_Integral_RMS = MakeCanvas("can2","can2",800,800)
Graph_Integral_RMS.SetTitle("Pulse Integral RMS vs. Pulse "+Title)
Graph_Integral_RMS.SetMarkerStyle(23)
Graph_Integral_RMS.SetMarkerColor(2)
Graph_Integral_RMS.SetMarkerSize(2)
Graph_Integral.GetXaxis().SetTitle("Day")
Graph_Integral_RMS.Draw()
# Graph_Integral_RMSErUp.Draw("same")
# Graph_Integral_RMSErDown.Draw("same")
canvas_Integral_RMS.SaveAs("Integral_RMS_"+Title+RootName+".pdf")
Graph_Ratio= TGraph(len(xRatio), xRatio,yRatio)
canvas_Ratio = MakeCanvas("can2","can2",800,800)
Graph_Ratio.SetTitle("Ratio of Pulse Integral RMS and Pulse Integral "+Title)
Graph_Ratio.SetMarkerStyle(21)
Graph_Ratio.SetMarkerColor(8)
Graph_Ratio.SetMarkerSize(2)
Graph_Integral.GetXaxis().SetTitle("Day")
Graph_Ratio.Draw()
canvas_Ratio.SaveAs("Ratio_"+Title+RootName+".pdf")
# OutFile=TFile(RootName,"RECREATE")
OutFile.WriteObject(Graph_Integral,"Graph_Integral")
OutFile.WriteObject(Graph_Integral_RMS,"Graph_Integral_RMS")
OutFile.WriteObject(Graph_Ratio,"Graph_Ratio")
OutFile.Close()
def main():
import configurations as config
import csv
from ModelParser import ModelKey, GroupXsecLimit
from ROOT import gStyle
from Styles import marker
gStyle.SetPadTopMargin(0.05)
gStyle.SetPadRightMargin(0.05)
from optparse import OptionParser
parser = OptionParser()
parser.add_option("-i", "--inputfile", dest="inputfile")
(options, args) = parser.parse_args()
models = []
with open(config.bh_list, 'rb') as f:
reader = csv.reader(f)
for r in reader:
models.append(ModelKey(r[0]))
from ROOT import TFile, TMultiGraph, TGraph, TLegend, TCanvas
infile_xsec = TFile(config.bh_xsec, "READ")
infile_CL = TFile(options.inputfile, "READ")
from OptimizationTools import Bisection
from Styles import formatXsecCL, formatExcludedMass
store = []
mg = TMultiGraph()
legend1 = TLegend(0.3241611,0.49,0.746644,0.69)
legend1.SetHeader("Observed Cross Section Limits")
legend1.SetTextSize(0.037)
legend1.SetTextFont(42)
legend1.SetFillColor(0)
legend1.SetLineColor(0)
legend2 = TLegend(0.3241611,0.68,0.746644,0.88)
legend2.SetHeader("Theoretical Cross Section")
legend2.SetTextSize(0.037)
legend2.SetTextFont(42)
legend2.SetFillColor(0)
legend2.SetLineColor(0)
legend3 = TLegend(0.3241611,0.8806993,0.886644,0.9273427)
legend3.SetHeader("String Ball (BlackMax)")
legend3.SetTextSize(0.037)
legend3.SetTextFont(42)
legend3.SetFillColor(0)
legend3.SetLineColor(0)
iColor = 0
iStyle = 2
#for key, group in ModelLimitGroup(models).items():
for key, group in GroupXsecLimit(models).items():
if not "SB" in key:
continue
name = ModelKey(key).name
gXsec = infile_xsec.Get(key)
formatXsecCL(gXsec, iColor, iStyle)
mg.Add(gXsec, "c")
legend2.AddEntry(gXsec, config.model_description[name], "l")
gCL95 = infile_CL.Get("%s-CL95" % key)
formatXsecCL(gCL95, iColor, 1)
mg.Add(gCL95, "pl")
legend1.AddEntry(gCL95, config.model_description[name], "pl")
iColor += 1
iStyle += 2
c = TCanvas("SB_BM", "SB_BM", 500, 500)
c.SetLogy()
mg.Draw("A")
mg.GetXaxis().SetTitle("M^{ min} (TeV)")
mg.GetXaxis().SetRangeUser(3.9,7.1)
mg.GetYaxis().SetRangeUser(1e-4,50)
mg.GetYaxis().SetTitle("#sigma (pb)")
mg.GetYaxis().SetTitleOffset(1.05)
mg.GetYaxis().SetTitleSize(0.045)
mg.GetYaxis().SetLabelSize(0.045)
mg.GetXaxis().SetTitleSize(0.045)
mg.GetXaxis().SetLabelSize(0.045)
legend1.Draw("plain")
legend2.Draw("plain")
legend3.Draw("plain")
c.Update()
from ROOT import TPaveText
cmslabel = TPaveText(0.45,0.96,0.60,0.99,"brNDC")
cmslabel.AddText(config.cmsTitle)
cmslabel.SetTextSize(0.041)
#cmslabel.AddText(config.cmsSubtitle)
cmslabel.SetFillColor(0)
cmslabel.Draw("plain")
raw_input("Press Enter to continue...")
def Measure_Integral(Fname1, Fname2, Title, XaxisT, low, high, freq, RootName):
FNumber = int((high - low) / freq)
print "************* -> initiating The ", Fname1, " and number of files exist= ", FNumber
# xIntegral=[]
# yIntegral=[]
# xIntegral_RMS=[]
# yIntegral_RMS=[]
# LINK=[15]
LINK = [15, 16, 17, 18, 19.20]
# LINKkChannel=[0,1,2,3,4,5]
LINKkChannel = [4]
for linkChannel in LINKkChannel:
for link in LINK:
xIntegral = array("d", xrange(0, FNumber))
yIntegral = array("d", xrange(0, FNumber))
yIntegralErrUp = array("d", xrange(0, FNumber))
yIntegralErrDown = array("d", xrange(0, FNumber))
xIntegral_RMS = array("d", xrange(0, FNumber))
yIntegral_RMS = array("d", xrange(0, FNumber))
yIntegral_RMSErrUp = array("d", xrange(0, FNumber))
yIntegral_RMSErrDown = array("d", xrange(0, FNumber))
xRatio = array("d", xrange(0, FNumber))
yRatio = array("d", xrange(0, FNumber))
num = -1
for iAmp in range(low, high, freq):
num += 1
Fname = Fname1 + str(iAmp) + Fname2
print "************* -> initiating The ", Fname, " and number of files exist= ", FNumber
print "--------------------> Now is doing .... ", low, " ____ ", Fname
f = open(Fname)
# data = getData(f)
tdc = getTDCValues(f)
M = TH1F(Fname, Fname, 200, 0, 100)
x = array("d", xrange(0, 1001))
y = array("d", xrange(0, 1001))
for event in xrange(0, 995):
tdcValue = 0
for BX in xrange(0, 40):
if (iAmp <= 10 and BX == 20
and tdc[event][link][BX][linkChannel] != 31.5):
tdcValue = tdc[event][link][BX][linkChannel]
if (iAmp > 10 and BX == 21
and tdc[event][link][BX][linkChannel] != 31.5):
tdcValue = tdc[event][link][BX][linkChannel]
y[event] = tdcValue
M.Fill(y[event])
histMean = M.GetMean()
histRMS = M.GetStdDev()
highVal = histMean + 4 * histRMS
lowVal = histMean - 4 * histRMS
highValAx = histMean + 6 * histRMS
lowValAx = histMean - 6 * histRMS
canvas = MakeCanvas("can", "can", 800, 800)
canvas.Update()
MyGr = TGraph(len(x), x, y)
mfit = TF1("fit", "gaus", lowVal, highVal)
M.Fit(mfit, "R0", "")
FitParam = mfit.GetParameters()
# FitParErr=mfit.GetParError()
integral = histMean
if FitParam[1] < 1.5 * histMean:
integral = round(FitParam[1], 4)
integral_RMS = histRMS
if round(FitParam[2], 4) < 2 * histRMS:
integral_RMS = round(FitParam[2], 4)
integralErr = round(mfit.GetParError(1), 4)
integral_RMSErr = round(mfit.GetParError(2), 4)
print "iAmp=", iAmp, " integral= ", integral, " integral_RMS=", integral_RMS
M.SetMarkerStyle(22)
M.GetXaxis().SetRangeUser(0, 30)
M.SetTitle("TDC v.s. Delay Setting (ns)")
M.Draw("pe")
mfit.Draw("same")
fitInfo = TPaveText(.20, 0.7, .60, 0.9, "NDC")
fitInfo.SetBorderSize(0)
fitInfo.SetFillStyle(0)
fitInfo.SetTextAlign(12)
fitInfo.SetTextSize(0.03)
fitInfo.SetTextColor(1)
fitInfo.SetTextFont(62)
fitInfo.AddText("Mean of Fit=" + str(round(FitParam[1], 1)))
fitInfo.AddText("RMS of Fit =" + str(round(FitParam[2], 1)))
fitInfo.AddText("Delay Setting =" + str(iAmp))
fitInfo.AddText("link =" + str(link) + " channel=" +
str(linkChannel))
fitInfo.Draw()
canvas.SaveAs("outHistoSingleRun_" + RootName + str(iAmp) +
"_link" + str(link) + "_ch_" + str(linkChannel) +
".pdf")
XVAL = low + num * freq
xIntegral[num] = XVAL
yIntegral[num] = integral
yIntegralErrUp[num] = integral + integralErr
yIntegralErrDown[num] = integral - integralErr
xIntegral_RMS[num] = XVAL
yIntegral_RMS[num] = integral_RMS
yIntegral_RMSErrUp[num] = integral_RMS + integral_RMSErr
yIntegral_RMSErrDown[num] = integral_RMS - integral_RMSErr
print "iAmp, integral= ", iAmp, " ", integral, " XVAL= ", XVAL
# xRatio[num]=XVAL
# yRatio[num]=integral_RMS/integral
# xIntegral.append(iAmp)
# yIntegral.append(integral)
# xIntegral_RMS.append(iAmp)
# yIntegral_RMS.append(integral_RMS)
Graph_TDC = TGraph(len(xIntegral), xIntegral, yIntegral)
Graph_TDCErUp = TGraph(len(xIntegral), xIntegral, yIntegralErrUp)
Graph_TDCErDown = TGraph(len(xIntegral), xIntegral,
yIntegralErrDown)
canvas_TDC = MakeCanvas("can1", "can1", 800, 800)
Graph_TDC.SetTitle("")
Graph_TDC.SetMarkerStyle(22)
Graph_TDC.SetMarkerColor(3)
Graph_TDC.SetMarkerSize(2)
Graph_TDC.GetXaxis().SetTitle(XaxisT)
Graph_TDC.GetYaxis().SetRangeUser(0, 30)
Graph_TDC.GetYaxis().SetTitle("TDC [ns]")
Graph_TDC.Draw()
Graph_TDCErUp.Draw("same")
Graph_TDCErDown.Draw("same")
canvas_TDC.SaveAs("outHisto_" + RootName + "_link" + str(link) +
"_ch_" + str(linkChannel) + ".pdf")
Graph_TDC_RMS = TGraph(len(xIntegral_RMS), xIntegral_RMS,
yIntegral_RMS)
Graph_TDC_RMSErUp = TGraph(len(xIntegral_RMS), xIntegral_RMS,
yIntegral_RMSErrUp)
Graph_TDC_RMSErDown = TGraph(len(xIntegral_RMS), xIntegral_RMS,
yIntegral_RMSErrDown)
canvas_TDC_RMS = MakeCanvas("can2", "can2", 800, 800)
Graph_TDC_RMS.SetTitle("TDC RMS vs. Pulse " + Title)
Graph_TDC_RMS.SetMarkerStyle(23)
Graph_TDC_RMS.SetMarkerColor(2)
Graph_TDC_RMS.SetMarkerSize(2)
Graph_TDC_RMS.GetXaxis().SetTitle(XaxisT)
Graph_TDC_RMS.GetYaxis().SetRangeUser(0, 2)
Graph_TDC_RMS.Draw()
Graph_TDC_RMSErUp.Draw("same")
Graph_TDC_RMSErDown.Draw("same")
canvas_TDC_RMS.SaveAs("outHistoRMS_" + RootName + "_link" +
str(link) + "_ch_" + str(linkChannel) +
".pdf")
OutFile = TFile(
"outFile_" + RootName + "_link" + str(link) + "_ch_" +
str(linkChannel) + ".root", "RECREATE")
OutFile.WriteObject(Graph_TDC, "Graph_TDC")
OutFile.WriteObject(Graph_TDC_RMS, "Graph_TDC_RMS")
OutFile.Close()
def Measure_Integral(Fname1, Fname2, Title, XaxisT, low, high, freq, RootName):
FNumber = int((high - low) / freq)
LINK = [3]
# LINK=[15,16,17,18,19]
LINKkChannel = [0, 1, 2, 3, 4, 5]
# LINKkChannel=[0]
for linkChannel in LINKkChannel:
for link in LINK:
xIntegral = array("d", xrange(0, FNumber))
yIntegral = array("d", xrange(0, FNumber))
yIntegralErrUp = array("d", xrange(0, FNumber))
yIntegralErrDown = array("d", xrange(0, FNumber))
xIntegral_RMS = array("d", xrange(0, FNumber))
yIntegral_RMS = array("d", xrange(0, FNumber))
yIntegral_RMSErrUp = array("d", xrange(0, FNumber))
yIntegral_RMSErrDown = array("d", xrange(0, FNumber))
xRatio = array("d", xrange(0, FNumber))
yRatio = array("d", xrange(0, FNumber))
xSingleEv = array("d", xrange(0, 40))
ySingleEv = array("d", xrange(0, 40))
num = -1
for iAmp in range(low, high, freq):
num += 1
Fname = Fname1 + str(iAmp) + Fname2
f = open(Fname)
data = getData(f)
M = TH1F(Fname, Fname, 200, 0.4, 1.4)
HistoSergey = TH1F(Fname, Fname, 200, -10, 200)
M.SetDefaultSumw2()
x = array("d", xrange(0, 1001))
y = array("d", xrange(0, 1001))
for event in xrange(0, 9):
for BX in xrange(0, 40):
xSingleEv[BX] = BX
ySingleEv[BX] = data[event][link][BX][linkChannel]
if BX < 16: HistoSergey.Fill(ySingleEv[BX])
if ySingleEv[BX] <= 0: ySingleEv[BX] = 0.1
if ySingleEv[BX] < 0.1: print "--->", ySingleEv[BX]
scanvas = MakeCanvas("mm", "nn", 800, 800)
scanvas.SetLogy()
GrSingleEv = TGraph(len(xSingleEv), xSingleEv, ySingleEv)
# SFit=TF1("fit", "gaus", 19,23)
# SFit.SetParameter(0, 250)
# SFit.SetParameter(1, 20.9)
# SFit.SetParLimits(1, 20, 22)
# SFit.SetParameter(2, 1)
GrSingleEv.GetXaxis().SetRangeUser(0, 40)
GrSingleEv.GetYaxis().SetRangeUser(0.05, 100000)
GrSingleEv.Draw("AC*")
# GrSingleEv.Fit("fit","R0")
# SFit.Draw("same")
# FitParam=SFit.GetParameters()
# print "Gaus fit param 1, 2, 3= " , round(FitParam[0],4), round(FitParam[1],4), round(FitParam[2],4)
fitInfo = TPaveText(.20, 0.7, .60, 0.9, "NDC")
fitInfo.SetBorderSize(0)
fitInfo.SetFillStyle(0)
fitInfo.SetTextAlign(12)
fitInfo.SetTextSize(0.03)
fitInfo.SetTextColor(1)
fitInfo.SetTextFont(62)
fitInfo.AddText("eventNumber_" + str(event) + "_link" +
str(link) + "_ch_" + str(linkChannel))
fitInfo.Draw()
scanvas.SaveAs("PLOT/singleEv_" + str(iAmp) + "_" +
str(event) + RootName + "_link" +
str(link) + "_ch_" + str(linkChannel) +
".pdf")
sergeycanvas = MakeCanvas("mm", "nn", 800, 800)
HistoSergey.Draw()
sergeycanvas.SaveAs("SergeyHisto" + RootName + "_link" +
str(link) + "_ch_" + str(linkChannel) +
".pdf")
def main():
from optparse import OptionParser
parser = OptionParser()
parser.add_option("-i", "--inputfile", dest="inputfile")
parser.add_option("-N", "--multiplicity", dest="N", type="int", default=3)
parser.add_option("-x", "--exclusive", action="store_true",\
dest="isExclusive", default=False)
parser.add_option("-l", "--label", dest="label", type="string", default="")
(options, args) = parser.parse_args()
N = options.N
isExclusive = options.isExclusive
label_text = options.label
if isExclusive and not (N == 2 or N == 3):
parser.error("Exclusive plot only for N =2 or 3")
import configurations as config
from ROOT import TFile, TCanvas, THStack, TLegend, TPaveText, TH1F, gStyle
from ModelParser import ModelKey
gStyle.SetPadTopMargin(0.05)
gStyle.SetPadRightMargin(0.05)
gStyle.SetOptStat(0000000)
suffix = ""
if not isExclusive:
suffix = "up"
sm_files = []
for model in config.sm_models:
f = TFile("%s/%s.root" % (config.sm_dir, model), "READ")
sm_files.append(f)
bh_weights = []
bh_files = []
from BHXsec import BHXsec
xsec = BHXsec()
for model in config.bh_showcase:
f = TFile("%s/%s.root" % (config.bh_dir, model), "READ")
bh_files.append(f)
h = f.Get("plotsNoCut/ST")
nEvents = h.GetEntries()
bh_weights.append(
xsec.get(model) / nEvents * config.integrated_luminosity)
c = TCanvas("ST_Mul%d%s" % (N, suffix), "ST_Mul%d%s" % (N, suffix), 500,
500)
hs = THStack()
hs1 = THStack()
infile = TFile(options.inputfile, "READ")
hBkg = infile.Get("Background_N%d%s" % (N, suffix))
gBkg = infile.Get("BackgroundGraph_N%d%s" % (N, suffix))
hData = infile.Get("Data_N%d%s" % (N, suffix))
hBkg = infile.Get("Background_N%d%s" % (N, suffix))
hBkg.SetMarkerSize(0)
hBkg_ = hBkg.Clone("BkgLine")
hBkg.SetFillColor(33)
hBkg.SetLineColor(33)
hBkg_.SetLineWidth(3)
hBkg_.SetLineColor(862)
hs.Add(hBkg, "e3")
hData_N2 = infile.Get("Data_N2")
hBkg_N2 = infile.Get("Background_N2")
ratio_data = infile.Get("Data_N%d%s" % (N, suffix))
ratio_data.Sumw2()
ratio_data.Divide(hData_N2, hBkg_N2)
ref_N2 = infile.Get("ReferenceTemplateN2_0")
ref_N3 = infile.Get("ReferenceTemplateN3_0")
ratio_fits = infile.Get("ReferenceTemplateN2_0")
ratio_fits.Sumw2()
ratio_fits.Divide(ref_N2, ref_N3)
legend = TLegend(0.3026613, 0.6919492, 0.6094355, 0.8816102)
legend.SetTextSize(0.041)
#was 0.02966102
legend.SetTextFont(42)
legend.SetFillColor(0)
legend.SetLineColor(0)
if isExclusive:
legend.SetHeader("Multiplicity, N = %d" % N)
else:
legend.SetHeader("Multiplicity, N #geq %d" % N)
legend.AddEntry(ratio_data, "Data/Background", "p")
legend.AddEntry(ratio_fits, "Fit-0 (N=2)/Fit-0 (N=3)", "l")
legend_sm = TLegend(0.6271774, 0.6769492, 0.8308065, 0.8171186)
legend_sm.SetTextSize(0.041)
legend_sm.SetTextFont(42)
legend_sm.SetFillColor(0)
legend_sm.SetLineColor(0)
for i, f in enumerate(bh_files):
h = f.Get("plotsN%d%s/ST" % (N, suffix))
h.Rebin(config.rebin)
h.Scale(bh_weights[i])
# Add background
for ibin in range(h.GetNbinsX()):
h.SetBinContent(ibin+1,\
h.GetBinContent(ibin+1)\
+ hBkg.GetBinContent(ibin+1))
h.SetLineWidth(2)
h.SetLineStyle(i + 2)
hs.Add(h, "hist")
model = ModelKey(config.bh_showcase[i])
bh_legend = "M_{D} = %.1f TeV, M_{BH}^{ min} = %.1f TeV, n = %d" % (\
model.parameter["MD"],
model.parameter["M"],
model.parameter["n"])
#legend.AddEntry(h, bh_legend, "l")
if isExclusive:
for i, f in enumerate(sm_files):
h = f.Get("plotsN%d%s/ST" % (N, suffix))
h.Rebin(config.rebin)
h.Scale(config.integrated_luminosity)
h.SetFillColor(config.sm_colors[i])
h.SetLineColor(config.sm_colors[i])
hs1.Add(h, "hist")
#legend_sm.AddEntry(h, config.sm_models[i], "f")
#hs.Add(hData, "e")
#TH1F *ratio_data
ratio_fits.SetLineColor(4)
ratio_fits.SetMarkerStyle(0)
ratio_fits.SetLineWidth(2)
#hs1.SetMinimum(1e-1)
ratio_fits.Draw("linee1")
ratio_data.Draw("same")
#hs.Draw("samenostack")
#c.SetLogy(1)
ratio_fits.GetXaxis().SetTitle("S_{T} (GeV)")
ratio_fits.GetYaxis().SetTitle("Arbitrary Units")
ratio_fits.GetYaxis().SetTitleOffset(1.1)
ratio_fits.GetYaxis().SetTitleSize(0.045)
ratio_fits.GetYaxis().SetLabelSize(0.045)
ratio_fits.GetXaxis().SetTitleSize(0.045)
ratio_fits.GetXaxis().SetLabelSize(0.045)
ratio_fits.GetXaxis().Draw()
ibin = 0
if isExclusive:
ratio_fits.GetXaxis().SetRangeUser(config.fit_range[0],
config.fit_range[1] + 330)
ibin = hData.FindBin(config.fit_range[0])
else:
ratio_fits.GetXaxis().SetRangeUser(config.norm_range[0],
config.norm_range[1] + 330)
ibin = hData.FindBin(config.norm_range[0])
from Styles import formatUncertainty
formatUncertainty(gBkg)
#gBkg.Draw("LX")
#hData.GetXaxis().SetNdivisions(510)
#hData.Draw("esame")
ratio_fits.SetTitle("")
ratio_fits.SetMinimum(0)
ratio_fits.SetMaximum(3)
legend.Draw("plain")
#if isExclusive:
# legend_sm.Draw("plain")
if isExclusive:
cmslabel = TPaveText(0.45, 0.90, 0.60, 0.93, "brNDC")
else:
cmslabel = TPaveText(0.45, 0.90, 0.60, 0.93, "brNDC")
cmslabel.AddText(config.cmsTitle)
#cmslabel.AddText(config.cmsSubtitle)
cmslabel.SetFillColor(0)
cmslabel.SetTextSize(0.041)
cmslabel.Draw("plain")
label = TPaveText(0.8891129, 0.8644068, 0.9435484, 0.9258475, "brNDC")
label.SetFillColor(0)
label.SetTextSize(0.0529661)
label.AddText(label_text)
label.Draw("plain")
if isExclusive:
c.Print("ST_Residuals_Mul%d.pdf" % N)
c.Print("ST_Residuals_Mul%d.png" % N)
else:
c.Print("ST_Mul%dup.pdf" % N)
c.Print("ST_Mul%dup.png" % N)
c.Update()
raw_input("Press Enter to continue...")
from ROOT import gROOT
c1 = TCanvas('c1', 'ROOT FilDir description', 700, 900)
c1.Range(1, 1, 19, 24.5)
title = TPaveLabel(4, 23, 16, 24.2, 'ROOT File/Directory/Key description')
title.SetFillColor(16)
title.Draw()
keycolor = 42
dircolor = 21
objcolor = 46
file = TPaveText(2, 19, 6, 22)
file.SetFillColor(39)
file.Draw()
file.SetTextSize(0.04)
file.AddText('TFile')
file.AddText('Header')
arrow = TArrow(6, 20.5, 17, 20.5, 0.02, '|>')
arrow.SetFillStyle(1001)
arrow.SetLineWidth(2)
arrow.Draw()
free = TPaveText(8, 20, 11, 21)
free.SetFillColor(18)
free.Draw()
free.AddText('First:Last')
free2 = TPaveText(12, 20, 15, 21)
free2.SetFillColor(18)
free2.Draw()
free2.AddText('First:Last')
tfree = TText(6.2, 21.2, 'fFree = TList of free blocks')
def main():
from optparse import OptionParser
parser = OptionParser()
parser.add_option("-i", "--inputfile", dest="inputfile")
parser.add_option("-N", "--multiplicity", dest="N", type="int", default=3)
parser.add_option("-x", "--exclusive", action="store_true",\
dest="isExclusive", default=False)
parser.add_option("-l", "--label", dest="label", type="string", default="")
(options, args) = parser.parse_args()
N = options.N
isExclusive = options.isExclusive
label_text = options.label
if isExclusive and not (N == 2 or N == 3):
parser.error("Exclusive plot only for N =2 or 3")
import configurations as config
from ROOT import TFile, TCanvas, THStack, TLegend, TPaveText, gStyle
from ModelParser import ModelKey
gStyle.SetPadTopMargin(0.05)
gStyle.SetPadRightMargin(0.05)
suffix = ""
if not isExclusive:
suffix = "up"
sm_files = []
for model in config.sm_models:
f = TFile("%s/%s.root" % (config.sm_dir, model), "READ")
sm_files.append(f)
bh_weights = []
bh_files = []
from BHXsec import BHXsec
xsec = BHXsec()
for model in config.bh_showcase:
f = TFile("%s/%s.root" % (config.bh_dir, model), "READ")
bh_files.append(f)
h = f.Get("plotsNoCut/ST")
nEvents = h.GetEntries()
bh_weights.append(
xsec.get(model) / nEvents * config.integrated_luminosity)
c = TCanvas("ST_Mul%d%s" % (N, suffix), "ST_Mul%d%s" % (N, suffix), 500,
500)
hs = THStack()
infile = TFile(options.inputfile, "READ")
hBkg = infile.Get("Background_N%d%s" % (N, suffix))
gBkg = infile.Get("BackgroundGraph_N%d%s" % (N, suffix))
hData = infile.Get("Data_N%d%s" % (N, suffix))
hBkg = infile.Get("Background_N%d%s" % (N, suffix))
hBkg.SetMarkerSize(0)
hBkg_ = hBkg.Clone("BkgLine")
hBkg.SetFillColor(33)
hBkg.SetLineColor(33)
hBkg_.SetLineWidth(3)
hBkg_.SetLineColor(862)
hs.Add(hBkg, "e3")
legend = TLegend(0.3326613, 0.6419492, 0.9294355, 0.9216102)
legend.SetTextSize(0.02966102)
legend.SetTextFont(42)
legend.SetFillColor(0)
legend.SetLineColor(0)
if isExclusive:
legend.SetHeader("N = %d" % N)
else:
legend.SetHeader("N #geq %d" % N)
legend.AddEntry(hData, "Data", "p")
legend.AddEntry(hBkg_, "Background", "l")
legend.AddEntry(hBkg, "Uncertainty", "f")
legend_sm = TLegend(0.6471774, 0.7669492, 0.8508065, 0.8771186)
legend_sm.SetTextSize(0.02966102)
legend_sm.SetTextFont(42)
legend_sm.SetFillColor(0)
legend_sm.SetLineColor(0)
for i, f in enumerate(bh_files):
h = f.Get("plotsN%d%s/ST" % (N, suffix))
h.Rebin(config.rebin)
h.Scale(bh_weights[i])
# Add background
for ibin in range(h.GetNbinsX()):
h.SetBinContent(ibin+1,\
h.GetBinContent(ibin+1)\
+ hBkg.GetBinContent(ibin+1))
h.SetLineWidth(2)
h.SetLineStyle(i + 2)
hs.Add(h, "hist")
model = ModelKey(config.bh_showcase[i])
bh_legend = "M_{D} = %.1f TeV, M_{BH}^{ min} = %.1f TeV, n = %d" % (\
model.parameter["MD"],
model.parameter["M"],
model.parameter["n"])
legend.AddEntry(h, bh_legend, "l")
# if isExclusive:
for i, f in enumerate(sm_files):
h = f.Get("plotsN%d%s/ST" % (N, suffix))
h.Rebin(config.rebin)
h.Scale(config.integrated_luminosity)
h.SetFillColor(config.sm_colors[i])
h.SetLineColor(config.sm_colors[i])
hs.Add(h, "hist")
legend_sm.AddEntry(h, config.sm_models[i], "f")
#hs.Add(hData, "e")
hs.Draw("nostack")
c.SetLogy(1)
hs.GetXaxis().SetTitle("S_{T} (GeV)")
hs.GetYaxis().SetTitle(hData.GetYaxis().GetTitle())
hs.GetYaxis().SetTitleOffset(1.2)
ibin = 0
if isExclusive:
hs.GetXaxis().SetRangeUser(config.fit_range[0], config.maxST)
ibin = hData.FindBin(config.fit_range[0])
else:
hs.GetXaxis().SetRangeUser(config.norm_range[0], config.maxST)
ibin = hData.FindBin(config.norm_range[0])
from Styles import formatUncertainty
formatUncertainty(gBkg)
gBkg.Draw("LX")
hData.Draw("esame")
hs.SetMinimum(5e-2)
if isExclusive:
hs.SetMaximum(hData.GetBinContent(ibin) * 20)
else:
#hs.SetMaximum(4e4)
hs.SetMaximum(hData.GetBinContent(ibin) * 20)
legend.Draw("plain")
if isExclusive:
legend_sm.Draw("plain")
if isExclusive:
cmslabel = TPaveText(0.5544355, 0.5127119, 0.8991935, 0.6292373,
"brNDC")
else:
cmslabel = TPaveText(0.1955645, 0.1631356, 0.5403226, 0.279661,
"brNDC")
cmslabel.AddText(config.cmsTitle)
cmslabel.AddText(config.cmsSubtitle)
cmslabel.SetFillColor(0)
cmslabel.Draw("plain")
label = TPaveText(0.8891129, 0.8644068, 0.9435484, 0.9258475, "brNDC")
label.SetFillColor(0)
label.SetTextSize(0.0529661)
label.AddText(label_text)
label.Draw("plain")
c.Update()
raw_input("Press Enter to continue...")
tbig.SetTextAlign( 22 ) tbig.SetTextSize( 0.03 ) tbig.Draw() tbig.DrawText( 2.6, 7, 'fBEGIN' ) tbig.DrawText( 20., 7, 'fEND' ) arrow.DrawArrow( 2.6, 7, 2.6, 8.4, 0.01, '|>' ) arrow.DrawArrow( 20, 7, 20, 8.4, 0.01, '|>' ) #file header header = TPaveText( 0.5, .2, 9.4, 6.5 ) header.SetFillColor( 44 ) header.Draw() fh = header.AddText( 'File Header' ) fh.SetTextAlign( 22 ) fh.SetTextSize( 0.04 ) header.SetTextSize( 0.027 ) header.SetTextAlign( 12 ) header.AddText( ' ' ) header.AddLine( 0, 0, 0, 0 ) header.AddText( '"root": Root File Identifier' ) header.AddText( 'fVersion: File version identifier' ) header.AddText( 'fBEGIN: Pointer to first data record' ) header.AddText( 'fEND: Pointer to first free word at EOF' ) header.AddText( 'fSeekFree: Pointer to FREE data record' ) header.AddText( 'fNbytesFree: Number of bytes in FREE' ) header.AddText( 'fNfree: Number of free data records' ) header.AddText( 'fNbytesName: Number of bytes in name/title' ) header.AddText( 'fUnits: Number of bytes for pointers' ) header.AddText( 'fCompress: Compression level' ) #logical record header
def compareDatasets(trigger, leg, datasets, lineColors, legendLabels, axisTitle, canvas, dataLumi, metHLTFilters, outputSuffix = None):
inputFiles = [TFile.Open("triggerEfficiency_" + x + ".root") for x in datasets]
efficiencies = [x.Get(trigger + "_" + leg) for x in inputFiles]
for iEff in range(len(efficiencies)):
SetStyle(efficiencies[iEff])
efficiencies[iEff].SetLineColor(lineColors[iEff])
efficiencies[iEff].SetMarkerColor(lineColors[iEff])
oneLine = TLine(xlo, 1.0, xhi, 1.0)
oneLine.SetLineWidth(3)
oneLine.SetLineStyle(2)
backgroundHist = TH1D("backgroundHist", "backgroundHist", 1, xlo, xhi)
backgroundHist.GetYaxis().SetTitle("Trigger Efficiency")
backgroundHist.GetYaxis().SetRangeUser(ylo, yhi)
backgroundHist.GetXaxis().SetTitle(axisTitle)
SetStyle(backgroundHist)
canvas.cd()
backgroundHist.Draw()
for eff in efficiencies:
eff.Draw("CP same")
#oneLine.Draw("same")
pt_cmsPrelim = TPaveText(0.132832, 0.859453, 0.486216, 0.906716, "brNDC")
pt_cmsPrelim.SetBorderSize(0)
pt_cmsPrelim.SetFillStyle(0)
pt_cmsPrelim.SetTextFont(62)
pt_cmsPrelim.SetTextSize(0.0374065)
if dataLumi > 0:
pt_cmsPrelim.AddText("CMS Preliminary")
else:
pt_cmsPrelim.AddText("CMS Simulation")
pt_cmsPrelim.Draw("same")
if dataLumi > 0:
pt_lumi = TPaveText(0.744361, 0.92928, 0.860902, 0.977667, "brNDC")
pt_lumi.SetBorderSize(0)
pt_lumi.SetFillStyle(0)
pt_lumi.SetTextFont(42)
pt_lumi.SetTextSize(0.0374065)
pt_lumi.AddText("{:.2f}".format(dataLumi / 1000.0) + " fb^{-1}, 13 TeV")
pt_lumi.Draw("same")
pt_leg = TPaveText(0.160401, 0.768657, 0.342105, 0.863184, "brNDC")
pt_leg.SetBorderSize(0)
pt_leg.SetFillStyle(0)
pt_leg.SetTextFont(42)
pt_leg.SetTextSize(0.025)
pt_leg.SetTextAlign(12)
if leg == "METLeg":
legLabel = ""
for filt in metHLTFilters[:-1]:
legLabel = legLabel + filt + ", "
legLabel = legLabel + metHLTFilters[-1]
pt_leg.AddText(legLabel)
if leg == "TrackLeg":
pt_leg.AddText(trigger + "*")
legLabel = ""
for filt in metHLTFilters[:-1]:
legLabel = legLabel + filt + ", "
legLabel = legLabel + metHLTFilters[-1] + " applied"
pt_leg.AddText(legLabel)
if leg == "METPath":
if trigger == "GrandOr":
pt_leg.AddText("OR of Signal Paths")
else:
if len(trigger) > 25 and len(trigger.split("_")) > 2:
firstLine = trigger.split("_")[0] + "_" + trigger.split("_")[1] + "_"
pt_leg.AddText(firstLine)
secondLine = ""
for line in trigger.split("_")[2:-1]:
secondLine += line + "_"
secondLine += trigger.split("_")[-1] + "*"
pt_leg.AddText(secondLine)
else:
pt_leg.AddText(trigger + "*")
pt_leg.Draw("same")
legendLabel = trigger
legend = TLegend(0.65, 0.75, 0.93, 0.88)
legend.SetBorderSize(0)
legend.SetFillColor(0)
legend.SetFillStyle(0)
legend.SetTextFont(42)
if leg == 'METLeg':
legend.SetHeader('MET Leg')
elif leg == 'TrackLeg':
legend.SetHeader('Track Leg')
for iEff in range(len(efficiencies)):
legend.AddEntry(efficiencies[iEff], legendLabels[iEff], 'P')
legend.Draw("same")
if outputSuffix is not None:
canvas.SaveAs('compareDatasets_' + trigger + '_' + leg + '_' + outputSuffix + '.pdf')
else:
canvas.SaveAs('compareDatasets_' + trigger + '_' + leg + '_.pdf')
for inputFile in inputFiles:
inputFile.Close()
return
ratioHistogram = currentHistogram.Clone()
ratioHistogram.Divide(baselineHistogram)
ratios.append(ratioHistogram)
for histogram in histograms:
legend.AddEntry(histogram, histogram.GetName(), "LEFP")
histogram.Draw("E0 same")
baselineHistogram.Draw("E0 same")
pt1 = TPaveText(0.1174497, 0.8621291, 0.5469799, 0.9075044,
"brNDC")
pt1.SetBorderSize(0)
pt1.SetFillStyle(0)
pt1.SetTextFont(62)
pt1.SetTextSize(0.0374065)
pt1.SetTextAlign(32)
pt1.AddText("CMS Phase II Simulation")
pt1.Draw("same")
pt2 = TPaveText(0.639087, 0.8572587, 0.9286733, 0.9042985, "brNDC")
pt2.SetBorderSize(0)
pt2.SetFillStyle(0)
pt2.SetTextFont(42)
pt2.SetTextSize(0.0374065)
pt2.SetTextAlign(32)
pt2.AddText("14 TeV, PU = 140")
pt2.Draw("same")
pt3 = TPaveText(0.5035663, 0.7875101, 0.9400856, 0.8572587,
"brNDC")
def compare(trigger, leg, data, mc, axisTitle, canvas, dataLumi, metHLTFilters):
dataFile = TFile.Open("triggerEfficiency_" + data + ".root", "read")
mcFile = TFile.Open("triggerEfficiency_" + mc + ".root", "read")
dataEff = dataFile.Get(trigger + "_" + leg)
mcEff = mcFile.Get(trigger + "_" + leg)
SetStyle(dataEff)
SetStyle(mcEff)
mcEff.SetLineColor(600)
mcEff.SetMarkerColor(600)
oneLine = TLine(xlo, 1.0, xhi, 1.0)
oneLine.SetLineWidth(3)
oneLine.SetLineStyle(2)
backgroundHist = TH1D("backgroundHist", "backgroundHist", 1, xlo, xhi)
backgroundHist.GetYaxis().SetTitle("Trigger Efficiency")
backgroundHist.GetYaxis().SetRangeUser(ylo, yhi)
backgroundHist.GetXaxis().SetTitle(axisTitle)
SetStyle(backgroundHist)
canvas.cd()
backgroundHist.Draw()
dataEff.Draw("CP same")
mcEff.Draw("CP same")
#oneLine.Draw("same")
pt_cmsPrelim = TPaveText(0.132832, 0.859453, 0.486216, 0.906716, "brNDC")
pt_cmsPrelim.SetBorderSize(0)
pt_cmsPrelim.SetFillStyle(0)
pt_cmsPrelim.SetTextFont(62)
pt_cmsPrelim.SetTextSize(0.0374065)
pt_cmsPrelim.AddText("CMS Preliminary")
pt_cmsPrelim.Draw("same")
pt_lumi = TPaveText(0.744361, 0.92928, 0.860902, 0.977667, "brNDC")
pt_lumi.SetBorderSize(0)
pt_lumi.SetFillStyle(0)
pt_lumi.SetTextFont(42)
pt_lumi.SetTextSize(0.0374065)
pt_lumi.AddText("{:.2f}".format(dataLumi / 1000.0) + " fb^{-1}, 13 TeV")
pt_lumi.Draw("same")
pt_leg = TPaveText(0.160401, 0.768657, 0.342105, 0.863184, "brNDC")
pt_leg.SetBorderSize(0)
pt_leg.SetFillStyle(0)
pt_leg.SetTextFont(42)
pt_leg.SetTextSize(0.025)
pt_leg.SetTextAlign(12)
if leg == "METLeg":
legLabel = ""
for filt in metHLTFilters[:-1]:
legLabel = legLabel + filt + ", "
legLabel = legLabel + metHLTFilters[-1]
pt_leg.AddText(legLabel)
if leg == "TrackLeg":
pt_leg.AddText(trigger + "*")
legLabel = ""
for filt in metHLTFilters[:-1]:
legLabel = legLabel + filt + ", "
legLabel = legLabel + metHLTFilters[-1] + " applied"
pt_leg.AddText(legLabel)
if leg == "METPath":
if trigger == "GrandOr":
pt_leg.AddText("OR of Signal Paths")
else:
if len(trigger) > 25 and len(trigger.split("_")) > 2:
firstLine = trigger.split("_")[0] + "_" + trigger.split("_")[1] + "_"
pt_leg.AddText(firstLine)
secondLine = ""
for line in trigger.split("_")[2:-1]:
secondLine += line + "_"
secondLine += trigger.split("_")[-1] + "*"
pt_leg.AddText(secondLine)
else:
pt_leg.AddText(trigger + "*")
pt_leg.Draw("same")
dataLabel = '2015 data'
if '2016BC' in data:
dataLabel = '2016 B+C data'
if '2016DEFGH' in data:
dataLabel = '2016 D-H data'
if '2017' in data:
dataLabel = '2017 data'
if '2018' in data:
dataLabel = '2018 data'
legendLabel = trigger
legend = TLegend(0.65, 0.75, 0.93, 0.88)
legend.SetBorderSize(0)
legend.SetFillColor(0)
legend.SetFillStyle(0)
legend.SetTextFont(42)
if leg == 'METLeg':
legend.SetHeader('MET Leg')
elif leg == 'TrackLeg':
legend.SetHeader('Track Leg')
legend.AddEntry(dataEff, dataLabel, 'P')
legend.AddEntry(mcEff, 'W #rightarrow l#nu MC', 'P')
legend.Draw("same")
outputDirectory = 'plots_compare'
if 'BC' in data:
outputDirectory = 'plots_compareBC'
if 'DEFGH' in data:
outputDirectory = 'plots_compareDEFGH'
if not os.path.exists(outputDirectory):
os.mkdir(outputDirectory)
canvas.SaveAs(outputDirectory + '/' + trigger + '_' + leg + '.pdf')
mcFile.Close()
dataFile.Close()
return
h.Fill(200., 10., 1.72)
h.Fill(200., 15., 1.77)
h.Fill(200., 20., 1.63)
h.Fill(200., 30., 1.71)
h.Fill(200., 40., 1.82)
# Style
gStyle.SetOptStat(0)
gStyle.SetPaintTextFormat('.2f')
h.GetXaxis().SetTitle('N2')
h.GetYaxis().SetTitle('dM')
set_palette()
# Pave Text
t1 = TPaveText(.1, .906, .2, 1., 'NDC')
t1.SetTextSize(.039)
t1.SetFillColor(0)
t1.SetFillStyle(0)
t1.SetLineWidth(0)
t1.SetTextAlign(12)
t1.AddText('CMS')
t2 = TPaveText(.13, .9, .9, 1., 'NDC')
t2.SetTextSize(.033)
t2.SetFillColor(0)
t2.SetFillStyle(0)
t2.SetLineWidth(0)
t2.SetTextAlign(12)
t2.SetTextFont(42)
t2.AddText('Phase-2 Simulation Preliminary (N2C1+N2N1)/N2C1 Events in SR')
# Plot
def plotEfficiency(self, doFit = False):
if hasattr(self, "Denominator") and hasattr(self, "Numerator"):
if self._rebinFactor != 1:
self.Denominator["hist"].Rebin(self._rebinFactor)
self.Numerator["hist"].Rebin(self._rebinFactor)
for ibin in range(-1, self.Numerator["hist"].GetNbinsX()+1):
if self.Numerator["hist"].GetBinContent(ibin+1) > self.Denominator["hist"].GetBinContent(ibin+1):
print('Fixing bad bin:', (ibin+1))
self.Numerator["hist"].SetBinContent(ibin+1, self.Denominator["hist"].GetBinContent(ibin+1))
self.Numerator["hist"].SetBinError(ibin+1, self.Denominator["hist"].GetBinError(ibin+1))
efficiencyGraph = TGraphAsymmErrors(self.Numerator["hist"], self.Denominator["hist"], "cp")
pt_cmsPrelim = TPaveText(0.132832, 0.859453, 0.486216, 0.906716, "brNDC")
pt_cmsPrelim.SetBorderSize(0)
pt_cmsPrelim.SetFillStyle(0)
pt_cmsPrelim.SetTextFont(62)
pt_cmsPrelim.SetTextSize(0.0374065)
pt_cmsPrelim.AddText("CMS Preliminary")
pt_lumi = TPaveText(0.744361, 0.92928, 0.860902, 0.977667, "brNDC")
pt_lumi.SetBorderSize(0)
pt_lumi.SetFillStyle(0)
pt_lumi.SetTextFont(42)
pt_lumi.SetTextSize(0.0374065)
pt_lumi.AddText(self._luminosityLabel)
pt_leg = TPaveText(0.160401, 0.768657, 0.342105, 0.863184, "brNDC")
pt_leg.SetBorderSize(0)
pt_leg.SetFillStyle(0)
pt_leg.SetTextFont(42)
pt_leg.SetTextSize(0.0349127)
pt_leg.SetTextAlign(12)
if self._leg == "METLeg":
legLabel = ""
for filt in self._metHLTFilters[:-1]:
legLabel = legLabel + filt + ", "
legLabel = legLabel + self._metHLTFilters[-1]
pt_leg.AddText(legLabel)
pt_leg.AddText(self._datasetLabel)
if self._leg == "TrackLeg":
pt_leg.AddText(self._path + "*")
pt_leg.AddText(self._datasetLabel)
legLabel = ""
for filt in self._metHLTFilters[:-1]:
legLabel = legLabel + filt + ", "
legLabel = legLabel + self._metHLTFilters[-1] + " applied"
pt_leg.AddText(legLabel)
if self._leg == "METPath":
if self._path == "GrandOr":
pt_leg.AddText("OR of Signal Paths")
else:
pt_leg.AddText(self._path + "*")
pt_leg.AddText(self._datasetLabel)
lumiLabel = TPaveText(0.66416, 0.937339, 0.962406, 0.992894, "brNDC")
lumiLabel.SetBorderSize(0)
lumiLabel.SetFillStyle(0)
lumiLabel.SetTextFont(42)
lumiLabel.SetTextSize(0.0387597)
lumiLabel.AddText(str (self._luminosityLabel))
oneLine = TLine(xlo, 1.0, xhi, 1.0)
oneLine.SetLineWidth(3)
oneLine.SetLineStyle(2)
backgroundHist = TH1D("backgroundHist", "backgroundHist", 1, xlo, xhi)
backgroundHist.GetYaxis().SetTitle("Trigger Efficiency")
backgroundHist.GetYaxis().SetRangeUser(ylo, yhi)
if self._leg == "METLeg" or self._leg == "METPath":
backgroundHist.GetXaxis().SetTitle(self._metLegAxisTitle)
elif self._leg == "TrackLeg":
backgroundHist.GetXaxis().SetTitle(self._trackLegAxisTitle)
SetStyle(backgroundHist)
SetStyle(efficiencyGraph)
self._canvas.cd()
backgroundHist.Draw()
efficiencyGraph.Draw("P")
pt_cmsPrelim.Draw("same")
pt_lumi.Draw("same")
pt_leg.Draw("same")
oneLine.Draw("same")
if doFit:
(fitFunc, fitText) = self.PlotFit(efficiencyGraph)
fitFunc.Draw("same")
fitText.Draw("same")
if not os.path.exists('plots_' + self.Denominator["sample"]):
os.mkdir('plots_' + self.Denominator["sample"])
if self._leg == "METPath":
self._canvas.SaveAs('plots_' + self.Denominator["sample"] + '/' + self._path + "_Efficiency.pdf")
else:
self._canvas.SaveAs('plots_' + self.Denominator["sample"] + '/' + self._path + "_" + self._leg + ".pdf")
self._fout.cd()
if self._tgraphSuffix is not None:
efficiencyGraph.Write(self._path + "_" + self._leg + "_" + self._tgraphSuffix)
if doFit:
fitFunc.Write(self._path + "_" + self._leg + "_" + self._tgraphSuffix + "_fitResult")
else:
efficiencyGraph.Write(self._path + "_" + self._leg)
if doFit:
fitFunc.Write(self._path + "_" + self._leg + "_fitResult")
else:
print("Denominator and Numerator must be defined for path ", self._path, ", leg ", self._leg)
return 0.0
def Measure_Integral(AllRuns, Title, RootName, WID):
FNumber = len(AllRuns)
xIntegral = array("d", xrange(0, FNumber))
yIntegral = array("d", xrange(0, FNumber))
yIntegralErrUp = array("d", xrange(0, FNumber))
yIntegralErrDown = array("d", xrange(0, FNumber))
xIntegral_RMS = array("d", xrange(0, FNumber))
yIntegral_RMS = array("d", xrange(0, FNumber))
yIntegral_RMSErrUp = array("d", xrange(0, FNumber))
yIntegral_RMSErrDown = array("d", xrange(0, FNumber))
xRatio = array("d", xrange(0, FNumber))
yRatio = array("d", xrange(0, FNumber))
xSingleEv = array("d", xrange(0, 40))
ySingleEv = array("d", xrange(0, 40))
OutFile = TFile(RootName, "RECREATE")
num = -1
iAmp = 0
for Fname in AllRuns:
num += 1
iAmp += 1
f = open(Fname)
# data = getData(f)
tdc = getTDCValues(f)
M = TH1F(Fname, Fname, 200, 0, 100)
x = array("d", xrange(0, 1001))
y = array("d", xrange(0, 1001))
for event in xrange(0, 995):
pedSum = 0
sigSum = 0
Signal = 0
Pedestal = 0
for BX in xrange(0, 40):
# print "[event][link][BX][linkChannel] = ", event," " ,link," " , BX ," " ,linkChannel, "---->data[event][link][BX][linkChannel]", tdc[event][link][BX][linkChannel]
# print BX
# print event
# print "data=", data[event][link][BX][linkChannel]
# print "TDC=", tdc[event][link][BX][linkChannel]
# print "\n"
# print "@@@@@@@@-------> [event] ", event
tdcValue = tdc[event][link][BX][linkChannel]
# print "@@@@@@@@-------> [event] ", event
if (WID[num] < 10 and BX == 20
and tdc[event][link][BX][linkChannel] != 31.5):
sigSum += tdcValue
if (WID[num] > 10 and BX == 21
and tdc[event][link][BX][linkChannel] != 31.5):
sigSum += tdcValue
# print "[event][link][BX][linkChannel] = ", event," " ,link," " , BX ," " ,linkChannel, "---->data[event][link][BX][linkChannel]", tdc[event][link][BX][linkChannel]
# if BX > 19 and BX < 25: sigSum += adcValue
# if BX > 18 and BX < 26: print "[event][link][BX][linkChannel] = ", event," " ,link," " , BX ," " ,linkChannel, "---->data[event][link][BX][linkChannel]", data[event][link][BX][linkChannel]
# print "---------------------> sigSum= ",sigSum
y[event] = sigSum
M.Fill(y[event])
histMean = M.GetMean()
histRMS = M.GetStdDev()
highVal = histMean + 4 * histRMS
lowVal = histMean - 4 * histRMS
highValAx = histMean + 6 * histRMS
lowValAx = histMean - 6 * histRMS
canvas = MakeCanvas("asdf", "asdf", 800, 800)
canvas.Update()
MyGr = TGraph(len(x), x, y)
mfit = TF1("fit", "gaus", lowVal, highVal)
M.Fit(mfit, "R0", "")
FitParam = mfit.GetParameters()
# FitParErr=mfit.GetParError()
integral = histMean
if FitParam[1] < 1.5 * histMean: integral = round(FitParam[1], 4)
integral_RMS = histRMS
if round(FitParam[2], 4) < 2 * histRMS:
integral_RMS = round(FitParam[2], 4)
integralErr = round(mfit.GetParError(1), 4)
integral_RMSErr = round(mfit.GetParError(2), 4)
print "iAmp=", iAmp, " integral= ", integral, " integral_RMS=", integral_RMS
M.SetMarkerStyle(22)
M.GetXaxis().SetRangeUser(lowValAx, highValAx)
# M.GetXaxis().SetRangeUser(lowValAx,highValAx)
M.SetTitle(Title + " = " + str(iAmp))
M.Draw("pe")
mfit.Draw("same")
fitInfo = TPaveText(.20, 0.7, .60, 0.9, "NDC")
fitInfo.SetBorderSize(0)
fitInfo.SetFillStyle(0)
fitInfo.SetTextAlign(12)
fitInfo.SetTextSize(0.03)
fitInfo.SetTextColor(1)
fitInfo.SetTextFont(62)
fitInfo.AddText("Mean of Fit=" + str(round(FitParam[1], 1)))
fitInfo.AddText("RMS of Fit =" + str(round(FitParam[2], 1)))
fitInfo.Draw()
canvas.SaveAs("HistoSingleRun_" + str(iAmp) + "_" + Title + "_TDC.pdf")
XVAL = iAmp
xIntegral[num] = XVAL
yIntegral[num] = integral
yIntegralErrUp[num] = integral + integralErr
yIntegralErrDown[num] = integral - integralErr
xIntegral_RMS[num] = XVAL
yIntegral_RMS[num] = integral_RMS
yIntegral_RMSErrUp[num] = integral_RMS + integral_RMSErr
yIntegral_RMSErrDown[num] = integral_RMS - integral_RMSErr
print "iAmp, integral= ", iAmp, " ", integral, " XVAL= ", XVAL
xRatio[num] = XVAL
yRatio[num] = integral_RMS / integral
# xIntegral.append(iAmp)
# yIntegral.append(integral)
# xIntegral_RMS.append(iAmp)
# yIntegral_RMS.append(integral_RMS)
Graph_Integral = TGraph(len(xIntegral), xIntegral, yIntegral)
Graph_IntegralErUp = TGraph(len(xIntegral), xIntegral, yIntegralErrUp)
Graph_IntegralErDown = TGraph(len(xIntegral), xIntegral, yIntegralErrDown)
canvas_Integral = MakeCanvas("can1", "can1", 800, 800)
# canvas_Integral.SetLogy()
Graph_Integral.SetTitle("TDC Stability")
Graph_Integral.SetMarkerStyle(22)
Graph_Integral.SetMarkerColor(3)
Graph_Integral.SetMarkerSize(2)
Graph_Integral.GetXaxis().SetTitle("Day")
Graph_Integral.GetYaxis().SetRangeUser(0, 40)
print "%%%%%%%% Graph_Integral.GetMaximum()= ", TMath.MaxElement(
len(xIntegral_RMS), Graph_Integral.GetY())
# Graph_Integral.SetMaximum(1.5)
Graph_Integral.Draw()
# Graph_IntegralErUp.Draw("same")
# Graph_IntegralErDown.Draw("same")
canvas_Integral.SaveAs("Integral_" + Title + "_TDC.pdf")
Graph_Integral_RMS = TGraph(len(xIntegral_RMS), xIntegral_RMS,
yIntegral_RMS)
Graph_Integral_RMSErUp = TGraph(len(xIntegral_RMS), xIntegral_RMS,
yIntegral_RMSErrUp)
Graph_Integral_RMSErDown = TGraph(len(xIntegral_RMS), xIntegral_RMS,
yIntegral_RMSErrDown)
canvas_Integral_RMS = MakeCanvas("can2", "can2", 800, 800)
Graph_Integral_RMS.SetTitle("TDC RMS vs. Pulse " + Title)
Graph_Integral_RMS.SetMarkerStyle(23)
Graph_Integral_RMS.SetMarkerColor(2)
Graph_Integral_RMS.SetMarkerSize(2)
Graph_Integral_RMS.GetXaxis().SetTitle("Day")
Graph_Integral_RMS.GetYaxis().SetRangeUser(
TMath.MinElement(len(xIntegral_RMS), Graph_Integral_RMS.GetY()) / 2,
TMath.MaxElement(len(xIntegral_RMS), Graph_Integral_RMS.GetY()) * 1.5)
Graph_Integral_RMS.Draw()
# Graph_Integral_RMSErUp.Draw("same")
# Graph_Integral_RMSErDown.Draw("same")
canvas_Integral_RMS.SaveAs("Integral_RMS_" + Title + "_TDC.pdf")
Graph_Ratio = TGraph(len(xRatio), xRatio, yRatio)
canvas_Ratio = MakeCanvas("can2", "can2", 800, 800)
Graph_Ratio.SetTitle("Ratio of TDC RMS and TDC " + Title)
Graph_Ratio.SetMarkerStyle(21)
Graph_Ratio.SetMarkerColor(4)
Graph_Ratio.SetMarkerSize(2)
Graph_Ratio.GetXaxis().SetTitle("Day")
Graph_Ratio.GetYaxis().SetRangeUser(
TMath.MinElement(len(xIntegral_RMS), Graph_Ratio.GetY()) / 2,
TMath.MaxElement(len(xIntegral_RMS), Graph_Ratio.GetY()) * 1.5)
Graph_Ratio.Draw()
canvas_Ratio.SaveAs("Ratio_" + Title + "_TDC.pdf")
OutFile = TFile(RootName, "RECREATE")
OutFile.WriteObject(Graph_Integral, "Graph_Integral")
OutFile.WriteObject(Graph_Integral_RMS, "Graph_Integral_RMS")
OutFile.WriteObject(Graph_Ratio, "Graph_Ratio")
OutFile.Close()
def makePlots():
# gROOT.SetStyle('Plain') # white background
# gStyle.SetOptStat(222211)
ROOT.gROOT.ProcessLine('.L ../tdrstyle.C')
ROOT.gROOT.Reset()
ROOT.gROOT.ProcessLine('setTDRStyle()') #Set CMS TDR style
inputFile = TFile(output_name + '.root', 'READ')
histos_SR1 = dict()
histos_SR2 = dict()
histos_LSB = dict()
histos_RSB = dict()
histos_MC = dict()
keys = [
'photon_pt', 'photon_eta', 'dimuon_pt', 'dimuon_rapidity', 'chib_pt'
]
for key in keys:
histos_SR1[key] = inputFile.Get(key + '_SR1')
histos_SR2[key] = inputFile.Get(key + '_SR2')
histos_LSB[key] = inputFile.Get(key + '_LSB')
histos_RSB[key] = inputFile.Get(key + '_RSB')
histos_MC[key] = inputFile.Get(key + '_MC')
titles = dict(
photon_pt='photon E_{T};E_{T}(#gamma) [GeV];Entries / 100 MeV',
photon_eta='photon_eta;#eta(#gamma);Entries / 0.05',
dimuon_pt='#Upsilon p_{T};p_{T}(#Upsilon) [GeV];Entries / GeV',
dimuon_rapidity='#Upsilon rapidity(#Upsilon);y(#Upsilon);Entries / 0.1',
chib_pt='#chi_{b} p_{T};p_{T}(#chi_{b}) [GeV];Entries / GeV',
)
titles_chib = dict(
photon_pt='photon E_{T};E_{T}(#gamma) [GeV];A.U.',
photon_eta='photon_eta;#eta(#gamma);A.U.',
dimuon_pt='#Upsilon p_{T};p_{T}(#Upsilon) [GeV];A.U.',
dimuon_rapidity='#Upsilon rapidity(#Upsilon);y(#Upsilon);A.U.',
chib_pt='#chi_{b} p_{T};p_{T}(#chi_{b}) [GeV];A.U.',
)
logY = dict(
photon_pt=0,
photon_eta=0,
dimuon_pt=0,
dimuon_rapidity=0,
chib_pt=0,
)
maxY = dict(
photon_pt=750,
photon_eta=350,
dimuon_pt=800,
dimuon_rapidity=400,
chib_pt=800,
)
integralData1 = histos_SR1[keys[0]].Integral()
integralData2 = histos_SR2[keys[0]].Integral()
integralData = integralData1 + integralData2
for histo in histos_LSB.values() + histos_RSB.values() + histos_MC.values(
):
if (histo.Integral() != 0):
histo.Scale(1. / histo.Integral())
histo.Rebin(3)
for histo in histos_SR1.values() + histos_SR2.values():
histo.Rebin(3)
fBG = 0.48 #0.28
fLSB = 0.5
histos_BG = dict()
for key in keys:
histos_BG[key] = histos_RSB[key].Clone()
histos_BG[key].SetNameTitle(key + '_BG', 'bgd from side-bands')
histos_BG[key].Scale(1 - fLSB)
histos_BG[key].Add(histos_LSB[key], fLSB)
histos_Signal1 = dict()
histos_Signal2 = dict()
histos_Signal = dict()
histos_SR = dict()
for key in keys:
histos_Signal1[key] = histos_SR1[key].Clone()
histos_Signal1[key].SetNameTitle(key + '_signal1', 'Signal1')
histos_Signal1[key].Add(histos_BG[key], -1 * integralData1 * fBG)
histos_Signal2[key] = histos_SR2[key].Clone()
histos_Signal2[key].SetNameTitle(key + '_signal2', 'Signal2')
histos_Signal2[key].Add(histos_BG[key], -1 * integralData2 * fBG)
histos_Signal[key] = histos_Signal1[key].Clone()
histos_Signal[key].Add(histos_Signal2[key])
histos_Signal[key].SetNameTitle(key + '_signal', 'data bkg-subtracted')
histos_SR[key] = histos_SR1[key].Clone()
histos_SR[key].Add(histos_SR2[key])
histos_SR[key].SetNameTitle(key + '_SR', 'data')
for histo in histos_Signal.values() + histos_BG.values():
if (histo.Integral() != 0):
histo.Scale(1. / histo.Integral())
# Normalize SR to their original value, MC to be comparable with signal background-subtracted and background such that Signal+background = SR
for histo in histos_MC.values():
histo.Scale(integralData * (1 - fBG))
for histo in histos_BG.values():
histo.Scale(integralData * fBG)
for histo in histos_LSB.values():
histo.Scale(integralData * fBG * fLSB)
for histo in histos_RSB.values():
histo.Scale(integralData * fBG * (1 - fLSB))
chi2Prob = dict()
kolmogorovProb = dict()
h_ratio = dict()
for key in histos_Signal.keys():
h_ratio[key] = histos_SR[key].Clone()
histo_sum_MC_BG = histos_MC[key].Clone()
histo_sum_MC_BG.Add(histos_BG[key])
h_ratio[key].Divide(histo_sum_MC_BG)
h_ratio[key].SetNameTitle(key + '_ratio', titles[key])
h_ratio[key].SetMarkerStyle(20)
h_ratio[key].SetMarkerSize(1)
h_ratio[key].GetYaxis().SetLabelSize(0.18)
h_ratio[key].GetYaxis().SetTitle('DATA/MC')
h_ratio[key].GetYaxis().SetTitleSize(0.22)
h_ratio[key].GetYaxis().SetTitleOffset(0.2)
h_ratio[key].GetYaxis().SetNdivisions(005)
h_ratio[key].GetXaxis().SetLabelSize(0.16)
h_ratio[key].GetXaxis().SetTitleSize(0.16)
h_ratio[key].SetMaximum(1.5)
h_ratio[key].SetMinimum(0.667)
chi2Prob[key] = histos_SR[key].Chi2Test(
histo_sum_MC_BG) #, 'UW')#, 'NORM')
kolmogorovProb[key] = histos_SR[key].KolmogorovTest(histo_sum_MC_BG)
for histo in histos_SR.values():
histo.SetLineColor(ROOT.kBlack)
histo.SetLineWidth(2)
histo.SetMarkerColor(ROOT.kBlack)
histo.SetMarkerStyle(20)
for histo in histos_SR1.values() + histos_Signal1.values():
histo.SetLineColor(ROOT.kBlue)
histo.SetLineWidth(2)
histo.SetMarkerColor(ROOT.kBlue)
histo.SetMarkerStyle(22)
for histo in histos_SR2.values() + histos_Signal2.values():
histo.SetLineColor(ROOT.kRed)
histo.SetLineWidth(2)
histo.SetMarkerColor(ROOT.kRed)
histo.SetMarkerStyle(23)
for histo in histos_Signal.values():
histo.SetLineColor(ROOT.kBlack)
histo.SetLineWidth(2)
# histo.SetMarkerColor(ROOT.kBlack)
# histo.SetMarkerStyle(21)
for histo in histos_BG.values():
histo.SetLineColor(ROOT.kRed)
histo.SetLineWidth(2)
histo.SetFillColor(ROOT.kRed)
# histo.SetMarkerColor(ROOT.kRed)
# histo.SetMarkerStyle(22)
# for histo in histos_RSB.values():
# histo.SetLineColor(ROOT.kViolet)
# histo.SetLineWidth(2)
for histo in histos_MC.values():
histo.SetLineColor(ROOT.kBlue)
histo.SetLineWidth(2)
histo.SetFillColor(ROOT.kBlue)
# histo.SetMarkerColor(ROOT.kBlue)
# histo.SetMarkerStyle(20)
outputFile = TFile(output_name + '_plots.root', 'RECREATE')
for histo in histos_Signal.values() + histos_MC.values(
) + histos_BG.values() + histos_SR.values():
histo.Write()
outputFile.Close()
canvas = TCanvas("canvas", "canvas")
canvas.Print(outputFile_name + "[") #apre file .ps
for key in keys:
pad1 = TPad("pad1", "The pad 80% of the height", 0.0, 0.2, 1.0, 1.0)
pad1.cd()
pad1.SetLogy(logY[key])
hs = THStack('hs', titles[key])
#hs.Add(histos_SR[key])
#hs.Add(histos_Signal[key])
hs.Add(histos_BG[key])
hs.Add(histos_MC[key])
#hs.Add(histos_LSB[key])
#hs.Add(histos_RSB[key])
#maxHisto = max(hs.GetMaximum(), histos_SR[key].GetMaximum())
hs.SetMaximum(maxY[key]) #maxHisto)
hs.Draw('HIST')
histos_SR[key].Draw('same')
leg = pad1.BuildLegend(.65, .93, .95, .7)
leg.SetFillStyle(0)
leg.SetBorderSize(0)
leg.Draw("SAME")
pad2 = TPad("pad2", "The pad 20% of the height", 0.0, 0.01, 1.0, 0.2)
pad2.cd()
h_ratio[key].Draw()
xmin = h_ratio[key].GetBinLowEdge(1)
xmax = h_ratio[key].GetBinLowEdge(
h_ratio[key].GetNbinsX()) + h_ratio[key].GetBinWidth(
h_ratio[key].GetNbinsX())
line0 = TLine(xmin, 1, xmax, 1)
line0.SetLineColor(ROOT.kBlue)
line0.SetLineWidth(2)
line0.Draw('same')
canvas.cd()
pad1.Draw()
pad2.Draw()
canvas.Update()
canvas.Print(outputFile_name)
canvas.Print('plots/' + key + '_' + mc_ptSpectrum + '.png')
canvas.Print('plots/' + key + '_' + mc_ptSpectrum + '.pdf')
canvas.Print('plots/' + key + '_' + mc_ptSpectrum + '.root')
# Make comparisison between chib1 and chib2
histos_SR1[key].Scale(1. / histos_SR1[key].Integral())
histos_SR2[key].Scale(1. / histos_SR2[key].Integral())
histos_Signal1[key].Scale(1. / histos_Signal1[key].Integral())
histos_Signal2[key].Scale(1. / histos_Signal2[key].Integral())
# histos_SR1[key].Rebin(3)
# histos_SR2[key].Rebin(3)
# histos_Signal1[key].Rebin(3)
# histos_Signal2[key].Rebin(3)
hsc = THStack('hsc', titles_chib[key])
hsc.Add(histos_Signal1[key])
hsc.Add(histos_Signal2[key])
#hsc.SetMaximum(maxY[key])
hsc.Draw('nostack')
legc = canvas.BuildLegend(.65, .93, .95, .7)
legc.SetFillStyle(0)
legc.SetBorderSize(0)
legc.Draw("SAME")
print 'kolmogorov prob SR ' + key + ' ' + str(
histos_SR1[key].KolmogorovTest(histos_SR2[key]))
print 'kolmogorov prob Signal ' + key + ' ' + str(
histos_Signal1[key].KolmogorovTest(histos_Signal2[key]))
cfr = 2 if key not in ['dimuon_pt', 'chib_pt'] else 5
kolmogorovProb_chi = round(
histos_Signal1[key].KolmogorovTest(histos_Signal2[key]), cfr)
pvtxt = TPaveText(.2, .0, 0.5, 0.1, "NDC")
pvtxt.SetFillStyle(0)
pvtxt.SetBorderSize(0)
pvtxt.SetTextSize(0.04)
pvtxt.AddText('Kolmogorov prob = ' + str(kolmogorovProb_chi))
pvtxt.Draw()
canvas.Update()
canvas.Print(outputFile_name)
canvas.Print('plots/' + key + '_' + mc_ptSpectrum + '_comparison' +
'.png')
canvas.Print('plots/' + key + '_' + mc_ptSpectrum + '_comparison' +
'.pdf')
canvas.Print('plots/' + key + '_' + mc_ptSpectrum + '_comparison' +
'.root')
canvas.Clear()
canvas.Print(outputFile_name + "]") #chiude file .ps
for key in keys:
print '\n'
print key + ' Kolmogorov probability: ' + str(chi2Prob[key])
print key + ' chiSqure probability: ' + str(kolmogorovProb[key])
#print 'Kolmogorov probability with sidebands: '+str(histos_MC['dimuon_pt'].KolmogorovTest(histos_LSB['dimuon_pt'])) #
inputFile.Close()
def main():
cc.cd()
cc.SetBorderMode(0)
cc.SetFixedAspectRatio(1)
cc.FeedbackMode(1)
gStyle.SetOptStat(0)
gStyle.SetGridStyle(0)
gStyle.SetGridColor(18)
nbinsX = 0
for ix in range(len(SECTORSPERREGION)):
nbinsX += SECTORSPERREGION[ix]
hh = TH2D('hh', ';Strip;Sector', STRIPSPERSECTOR, 0, STRIPSPERSECTOR,
nbinsX, 0, nbinsX)
setupHists([hh])
hh.Draw('COLZ')
gPad.SetLogz()
gPad.SetLeftMargin(0.09)
gPad.SetRightMargin(0.11)
tt2 = TPaveText(240, 43, 500, 45)
ttime = TPaveText(100, -5.5, 412, -3)
setupPaveTexts([tt2, ttime])
tt2.SetTextSize(0.03)
lll = TLine()
lll.SetLineColor(15)
y1 = SECTORSPERREGION[0]
y2 = SECTORSPERREGION[0] + SECTORSPERREGION[1]
lll.DrawLine(0, y1, STRIPSPERSECTOR, y1)
lll.DrawLine(0, y2, STRIPSPERSECTOR, y2)
tt = TText()
tt.SetTextColor(1)
tt.SetTextAngle(90)
tt.SetTextSize(0.04)
tt.DrawText(532, 22, 'Hz')
tt.SetTextSize(0.06)
tt.SetTextAngle(0)
tt.SetTextColor(1)
tt.DrawTextNDC(0.1, 0.93, 'SVT Scalers')
tt.SetTextSize(0.03)
tt.DrawText(-42, 4, 'R1')
tt.DrawText(-42, 16, 'R2')
tt.DrawText(-42, 32, 'R3')
cc.cd()
for xx in [ttime, tt2]:
xx.Draw()
cc.cd()
gPad.SetEditable(0)
while True:
iy = 0
for ch in SVT.chans:
loadPV(ch)
ch = ch.vals
data = ch['PVVAL']
time2 = ch['PVTIMEVAL']
if time2 > 10:
print 'More than 10 seconds since message: ' + ch['PVNAME']
for ii in range(512):
data[ii] = 0
if iy < SECTORSPERREGION[0]:
region = 1
sector = iy
elif iy < SECTORSPERREGION[0] + SECTORSPERREGION[1]:
region = 2
sector = iy - SECTORSPERREGION[0]
else:
region = 3
sector = iy - SECTORSPERREGION[0] - SECTORSPERREGION[1]
if data == None or len(data) != STRIPSPERSECTOR:
print 'Error Reading ' + ch['PVNAME']
continue
for ix in range(STRIPSPERSECTOR):
hh.SetBinContent(ix, iy + 1, data[ix])
iy += 1
for xx in [ttime, tt2]:
xx.Clear()
[r1, r2, r3] = calcRates(SVT.chans)
tt2.AddText('Sums: R1 / R2 / R3 = %.2E / %.2E / %.2E Hz' %
(r1, r2, r3))
ttime.AddText(makeTime())
if not gPad: sys.exit()
cc.Modified()
cc.Update()
time.sleep(POLLPERIOD)
ldot.DrawLine(.9, .775, .99, .775)
ldot.DrawLine(.9, .275, .99, .275)
ldot.DrawLine(.55, .05, .55, 0)
ldot.DrawLine(.9, .05, .75, 0)
pname = TText(.46, .21, 'fEventOffset')
pname.SetTextFont(72)
pname.SetTextSize(0.018)
pname.Draw()
pname.DrawText(.44, .11, 'fBuffer')
pname.DrawText(.42, .01, 'fZipBuffer')
pname.DrawText(.26, .81, 'fLeaves = TObjArray of TLeaf')
pname.DrawText(.24, .40, 'fBasketEvent')
pname.DrawText(.22, .31, 'fBaskets = TObjArray of TBasket')
pname.DrawText(.20, 1.0, 'fBranches = TObjArray of TBranch')
ntleaf = TPaveText(0.30, .42, .62, .7)
ntleaf.SetTextSize(0.014)
ntleaf.SetFillColor(leafcolor)
ntleaf.SetTextAlign(12)
ntleaf.AddText('fLen: number of fixed elements')
ntleaf.AddText('fLenType: number of bytes of data type')
ntleaf.AddText('fOffset: relative to Leaf0-fAddress')
ntleaf.AddText('fNbytesIO: number of bytes used for I/O')
ntleaf.AddText('fIsPointer: True if pointer')
ntleaf.AddText('fIsRange: True if leaf has a range')
ntleaf.AddText('fIsUnsigned: True if unsigned')
ntleaf.AddText('*fLeafCount: points to Leaf counter')
ntleaf.AddText(' ')
ntleaf.AddLine(0, 0, 0, 0)
ntleaf.AddText('fName = Leaf name')
ntleaf.AddText('fTitle = Leaf type (see Type codes)')
ntleaf.Draw()
def main():
from optparse import OptionParser
parser = OptionParser()
parser.add_option("-i", "--inputfile", dest="inputfile")
parser.add_option("-N", "--multiplicity", dest="N", type="int", default=3)
parser.add_option("-x", "--exclusive", action="store_true",\
dest="isExclusive", default=False)
parser.add_option("-l", "--label", dest="label", type="string", default="")
(options, args) = parser.parse_args()
N = options.N
isExclusive = options.isExclusive
label_text = options.label
if isExclusive and not (N == 2 or N == 3):
parser.error("Exclusive plot only for N =2 or 3")
import configurations as config
from ROOT import TFile, TCanvas, THStack, TLegend, TPaveText, gStyle
from ModelParser import ModelKey
gStyle.SetPadTopMargin(0.05)
gStyle.SetPadRightMargin(0.05)
gStyle.SetErrorX(0.)
suffix = ""
if not isExclusive:
suffix = "up"
sm_files = []
for model in config.sm_models:
f = TFile("%s/%s.root" % (config.sm_dir, model), "READ")
sm_files.append(f)
bh_weights = []
bh_files = []
from BHXsec import BHXsec
xsec = BHXsec()
for model in config.bh_showcase:
f = TFile("%s/%s.root" % (config.bh_dir, model), "READ")
bh_files.append(f)
h = f.Get("plotsNoCut/ST")
nEvents= h.GetEntries()
bh_weights.append(xsec.get(model) / nEvents * config.integrated_luminosity)
c = TCanvas("ST_Mul%d%s" % (N, suffix),
"ST_Mul%d%s" % (N, suffix), 500, 500)
hs = THStack()
hs1 = THStack()
infile = TFile(options.inputfile, "READ")
hBkg = infile.Get("Background_N%d%s" % (N, suffix))
gBkg = infile.Get("BackgroundGraph_N%d%s" % (N, suffix))
hData = infile.Get("Data_N%d%s" % (N, suffix))
hBkg = infile.Get("Background_N%d%s" % (N, suffix))
hBkg.SetMarkerSize(0)
hBkg_ = hBkg.Clone("BkgLine")
hBkg.SetFillColor(33)
hBkg.SetLineColor(33)
hBkg_.SetLineWidth(3)
hBkg_.SetLineColor(862)
hs.Add(hBkg, "e3")
#legend = TLegend(0.2826613,0.4819492,0.6094355,0.9416102) # - only for N >= 2 and 3
legend = TLegend(0.3026613,0.5519492,0.6094355,0.9416102) # was 0.4919...
legend.SetTextSize(0.041); #was 0.02966102
legend.SetTextFont(42);
legend.SetFillColor(0)
legend.SetLineColor(0)
if isExclusive:
legend.SetHeader("Multiplicity N = %d" % N)
else:
legend.SetHeader("Multiplicity N #geq %d" % N)
legend.AddEntry(hData, "Data", "lep")
legend.AddEntry(hBkg_, "Background", "l")
legend.AddEntry(hBkg, "Uncertainty", "f")
legend_sm = TLegend(0.6271774,0.7369492,0.8308065,0.8771186)
legend_sm.SetTextSize(0.041);
legend_sm.SetTextFont(42);
legend_sm.SetFillColor(0)
legend_sm.SetLineColor(0)
for i, f in enumerate(bh_files):
h = f.Get("plotsN%d%s/ST" % (N, suffix))
h.Rebin(config.rebin)
h.Scale(bh_weights[i])
# Add background
for ibin in range(h.GetNbinsX()):
h.SetBinContent(ibin+1,\
h.GetBinContent(ibin+1)\
+ hBkg.GetBinContent(ibin+1))
h.SetLineWidth(3)
#h.SetLineColor(i+2)
h.SetLineStyle(i+2)
if i == 0:
h.SetLineColor(814)
if i == 1:
h.SetLineStyle(5)
h.SetLineColor(899)
if i == 2:
h.SetLineStyle(9)
h.SetLineColor(4)
if i == 3:
h.SetLineStyle(3)
h.SetLineColor(614)
hs.Add(h, "hist")
model = ModelKey(config.bh_showcase[i])
bh_legend = "M_{D} = %.1f TeV, M_{BH}^{ min} = %.1f TeV, n = %d" % (\
model.parameter["MD"],
model.parameter["M"],
model.parameter["n"])
if i == 3:
bh_legend = "M_{D} = 3.0 TeV, M_{QBH}^{ min} = 4.0 TeV, n = 4"
legend.AddEntry(h, bh_legend, "l")
# qbh_legend = "M_{D} = 4.0 TeV, M_{QBH}^{ min} = 5.0 TeV, n = 5"
# legend.AddEntry(h, qbh_legend, "l")
if isExclusive:
for i, f in enumerate(sm_files):
h = f.Get("plotsN%d%s/ST" % (N, suffix))
h.Rebin(config.rebin)
h.Scale(config.integrated_luminosity)
h.SetFillColor(config.sm_colors[i])
h.SetLineColor(config.sm_colors[i])
hs1.Add(h, "hist")
legend_sm.AddEntry(h, config.sm_models[i], "f")
#hs.Add(hData, "e")
hs.Draw("nostack")
hs1.Draw("same")
c.SetLogy(1)
hs.GetXaxis().SetTitle("S_{T} (GeV)")
hs.GetYaxis().SetTitle(hData.GetYaxis().GetTitle())
hs.GetYaxis().SetTitleOffset(1.25)
hs.GetYaxis().SetTitleSize(0.04)
hs.GetYaxis().SetLabelSize(0.04)
hs.GetXaxis().SetTitleSize(0.04)
hs.GetXaxis().SetLabelSize(0.04)
ibin = 0
#if isExclusive:
# hs.GetXaxis().SetRangeUser(config.fit_range[0], config.maxST)
# ibin = hData.FindBin(config.fit_range[0])
#else:
# hs.GetXaxis().SetRangeUser(config.norm_range[0], config.maxST)
# ibin = hData.FindBin(config.norm_range[0])
if isExclusive:
hs.GetXaxis().SetRangeUser(1800, config.maxST)
ibin = hData.FindBin(1800)
else:
hs.GetXaxis().SetRangeUser(config.norm_range[0], config.maxST)
ibin = hData.FindBin(config.norm_range[0])
from Styles import formatUncertainty
formatUncertainty(gBkg)
gBkg.Draw("LX")
hData.Draw("sameex0")
hs.SetMinimum(5e-1)
if isExclusive:
hs.SetMaximum(hData.GetBinContent(ibin) * 40)
else:
#hs.SetMaximum(4e4)
hs.SetMaximum(hData.GetBinContent(ibin) * 20) # or 1e7 for N>=3 and use 4 models
legend.Draw("plain")
if isExclusive:
legend_sm.Draw("plain")
if isExclusive:
cmslabel =TPaveText(0.45,0.96,0.60,0.99,"brNDC");
else:
cmslabel = TPaveText(0.45,0.96,0.60,0.99,"brNDC")
cmslabel.AddText(config.cmsTitle)
#cmslabel.AddText(config.cmsSubtitle)
cmslabel.SetFillColor(0)
cmslabel.SetTextSize(0.041)
cmslabel.Draw("plain")
label = TPaveText(0.8891129,0.8644068,0.9435484,0.9258475,"brNDC")
label.SetFillColor(0)
label.SetTextSize(0.0529661);
label.AddText(label_text);
label.Draw("plain")
#block1 =TPaveText(0.333,0.84,0.354,0.86,"brNDC"); # for N>=2 and >=3 only
block1 =TPaveText(0.351,0.85,0.37,0.87,"brNDC");
block1.SetFillColor(0)
block1.Draw("plain")
#block2 =TPaveText(0.295,0.84,0.315,0.86,"brNDC"); # for N>=2 and >=3 only
block2 =TPaveText(0.314,0.85,0.332,0.87,"brNDC");
block2.SetFillColor(0)
block2.Draw("plain")
if isExclusive:
c.Print("ST_Mul%d.pdf" % N)
c.Print("ST_Mul%d.png" % N)
else:
c.Print("ST_Mul%dup.pdf" % N)
c.Print("ST_Mul%dup.png" % N)
c.Update()
raw_input("Press Enter to continue...")
def DrawOverlap(histList,
titleVec,
legendtext,
pngname,
logstatus=[0, 0],
xRange=[-99999, 99999, 1],
cat='2b'):
gStyle.SetOptTitle(0)
gStyle.SetOptStat(0)
gStyle.SetTitleOffset(1.1, "Y")
#gStyle.SetTitleOffset(1.9,"X");
gStyle.SetLineWidth(3)
gStyle.SetFrameLineWidth(3)
gStyle.SetTickLength(0.0, "x")
i = 0
# histList_=[]
# histList=[]
# histList1=[]
# maximum=[]
## Legend
leg = TLegend(0.2, 0.80, 0.89, 0.89) #,NULL,"brNDC");
leg.SetBorderSize(0)
leg.SetNColumns(3)
# leg.SetLineColor(1)
leg.SetLineStyle(1)
leg.SetLineWidth(1)
# leg.SetFillColor(0)
leg.SetFillStyle(0)
leg.SetTextFont(42)
leg.SetTextSize(0.05)
c = TCanvas("c1", "c1", 0, 0, 500, 500)
c.SetBottomMargin(0.15)
c.SetLeftMargin(0.15)
c.SetLogy(logstatus[1])
c.SetLogx(logstatus[0])
# print ("you have provided "+str(len(fileVec))+" files and "+str(len(histVec))+" histograms to make a overlapping plot" )
# print "opening rootfiles"
c.cd()
print "provided hists", histList
for ih in range(len(histList)):
tt = type(histList[ih])
if logstatus[1] is 1:
histList[ih].SetMaximum(1.5) #1.4 for log
histList[ih].SetMinimum(0.1) #1.4 for log
if logstatus[1] is 0:
maxi = histList[ih].GetMaximum()
histList[ih].SetMaximum(maxi * 2) #1.4 for log
histList[ih].SetMinimum(0) #1.4 for log
# print "graph_status =" ,(tt is TGraphAsymmErrors)
# print "hist status =", (tt is TH1D) or (tt is TH1F)
if ih == 0:
if tt is TGraphAsymmErrors:
histList[ih].Draw("APL")
if (tt is TH1D) or (tt is TH1F) or (tt is TH1) or (tt is TH1I):
histList[ih].Draw("PE2 ")
if ih > 0:
#histList[ih].SetLineWidth(2)
if tt is TGraphAsymmErrors:
histList[ih].Draw("PL same")
if (tt is TH1D) or (tt is TH1F) or (tt is TH1) or (tt is TH1I):
histList[ih].Draw("PE0 same")
if tt is TGraphAsymmErrors:
histList[ih].SetMaximum(100)
histList[ih].SetMarkerColor(colors[ih])
histList[ih].SetLineColor(colors[ih])
histList[ih].SetLineWidth(0)
histList[ih].SetMarkerStyle(markerStyle[ih])
histList[ih].SetMarkerSize(1)
leg.AddEntry(histList[ih], legendtext[ih], "PL")
if (tt is TH1D) or (tt is TH1F) or (tt is TH1) or (tt is TH1I):
print "setting style for hist"
print "color code", colors[ih]
# histList[ih].SetLineStyle(linestyle[ih])
histList[ih].SetLineColor(colors[ih])
histList[ih].SetMarkerColor(colors[ih])
histList[ih].SetFillColor(colors[ih])
histList[ih].SetMarkerStyle(20)
histList[ih].SetMarkerSize(1.0)
histList[ih].SetLineWidth(1)
#invert legend between first and second
if ih == 0:
leg.AddEntry(histList[ih + 1], legendtext[ih + 1],
"PEL") #"f")
if ih == 1:
leg.AddEntry(histList[ih - 1], legendtext[ih - 1],
'f') #"PEL")
histList[ih].GetYaxis().SetTitle(titleVec[1])
histList[ih].GetYaxis().SetTitleSize(0.052)
histList[ih].GetYaxis().SetTitleOffset(1.4)
histList[ih].GetYaxis().SetTitleFont(42)
histList[ih].GetYaxis().SetLabelFont(42)
histList[ih].GetYaxis().SetLabelSize(.052)
histList[ih].GetXaxis().SetRangeUser(xRange[0], xRange[1])
# histList[ih].GetXaxis().SetLabelSize(0.0000);
histList[ih].GetXaxis().SetTitle(titleVec[0])
histList[ih].GetXaxis().SetLabelSize(0.052)
histList[ih].GetXaxis().SetTitleSize(0.052)
#histList[ih].GetXaxis().SetTitleOffset(1.14)
histList[ih].GetXaxis().SetTitleFont(42)
histList[ih].GetXaxis().SetLabelFont(42)
histList[ih].GetYaxis().SetLabelFont(42)
histList[ih].GetXaxis().SetNdivisions(507)
#histList[ih].GetXaxis().SetMoreLogLabels();
#histList[ih].GetXaxis().SetNoExponent();
#histList[ih].GetTGaxis().SetMaxDigits(3);
# histList[ih].GetXaxis().SetTickSize(0.00)
i = i + 1
pt = TPaveText(0.01, 0.92, 0.95, 0.96, "brNDC")
pt.SetBorderSize(0)
pt.SetTextAlign(12)
pt.SetFillStyle(0)
pt.SetTextFont(42)
pt.SetTextSize(0.046)
#text = pt.AddText(0.12,0.35,"CMS Internal 36 fb^{-1} (2016) ")
text = pt.AddText(0.12, 0.35,
"CMS Internal 41.5 fb^{-1} (2017) ")
#text = pt.AddText(0.12,0.35,"CMS Internal 59.6 fb^{-1} (2018) ")
#text = pt.AddText(0.6,0.5,"41.5 fb^{-1} (2017) ")
cattxt = TLatex(0.20, 0.75, cat + ' ' + "category")
cattxt.SetTextSize(0.06)
cattxt.SetTextAlign(12)
cattxt.SetNDC(1)
cattxt.SetTextFont(42)
pt.Draw()
cattxt.Draw()
leg.Draw()
outputdirname = 'TFplots/'
histname = outputdirname + pngname
c.SaveAs(histname + '.png')
c.SaveAs(histname + '.pdf')
