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(0.6891129, 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...")
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...")
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 main():
from optparse import OptionParser
parser = OptionParser()
parser.add_option("-i", "--inputfile", dest="inputfile")
parser.add_option("-o", "--ouputfile", dest="outputfile")
parser.add_option("-b", "--batch", action="store_true",\
dest="isBatch", default=False)
parser.add_option("--normalization", nargs=2,\
type="float", dest="norm_range")
parser.add_option("--fit", nargs=2,\
type="float", dest="fit_range")
(options, args) = parser.parse_args()
isSaveOutput = options.outputfile is not None
if not (options.inputfile):
parser.error("Please specify inputfiles.")
import configurations as config
integrated_luminosity = config.integrated_luminosity
if options.fit_range:
fit_range = options.fit_range
norm_range = (fit_range[1] - 200., fit_range[1])
else:
fit_range = config.fit_range
norm_range = config.norm_range
# Override normalization range from input
if options.norm_range:
norm_range = options.norm_range
from Styles import formatST, formatTemplate, formatUncertainty
from ROOT import TFile, TF1, TH1D, TMath, TCanvas, TLegend,\
TGraphAsymmErrors, TVectorD, gStyle
gStyle.SetPadTopMargin(0.05)
gStyle.SetPadRightMargin(0.05)
#gStyle.SetOptFit(2222222)
#gStyle.SetStatX(0.95)
#gStyle.SetStatY(0.95)
gStyle.SetOptStat(0000000)
gStyle.SetOptFit(0000000)
from ROOT import TFile, TCanvas, TMultiGraph, TLegend, TPaveText
#input file name
infile = TFile(options.inputfile, "READ")
from HistoStore import HistoStore
store = HistoStore()
canvas = HistoStore()
print "Fit range: %d - %d GeV" % fit_range
print "Normalization range: %d - %d GeV" % norm_range
print "Integrated luminosity: %d inv. pb" % integrated_luminosity
# Fit
for N in config.exclusive_multiplicities:
hST = infile.Get("plots%dJets/ST" % N)
hST.GetXaxis().SetNdivisions(510)
if not options.isBatch:
c = TCanvas("TemplateN%d" % N,
"TemplateN%d" % N, 500, 500)
canvas.book(c)
formatST(hST)
hST.SetTitle("")
hST.Draw("e")
hST.GetXaxis().SetRangeUser(fit_range[0], config.maxST)
hST.GetYaxis().SetRangeUser(1e-2, 2e4)
hST.GetYaxis().SetTitleOffset(1.25)
hST.GetYaxis().SetTitleSize(0.04)
hST.GetYaxis().SetLabelSize(0.04)
hST.GetXaxis().SetTitleSize(0.04)
hST.GetXaxis().SetLabelSize(0.04)
c.SetLogy(1)
for i,formula in enumerate(config.templates):
print "formula %d" % (i)
if N == 2:
f = TF1("templateN%d_%d" % (N, i), formula, 0, 10000)
elif N == 3:
f = store.get("templateN2_%d" % i).Clone("templateN%d_%d" % (N, i))
if i < 3:
hST.Fit(f, "QN0", "", 1800, 2800)
hST.Fit(f, "QN0", "", 1800, 2800)
hST.Fit(f, "QN0", "", 1800, 2800)
hST.Fit(f, "QN0", "", 1800, 2800)
hST.Fit(f, "QN0", "", 1800, 2800)
hST.Fit(f, "QN0", "", 1800, 2800)
hST.Fit(f, "QN0", "", 1800, 2800)
hST.Fit(f, "QN0", "", 1800, 2800)
hST.Fit(f, "QN0", "", 1800, 2800)
hST.Fit(f, "QN0", "", 1800, 2800)
hST.Fit(f, "QN0", "", 1800, 2800)
hST.Fit(f, "QN0", "", 1800, 2800)
hST.Fit(f, "QN0", "", 1800, 2800)
hST.Fit(f, "QN0", "", 1800, 2800)
hST.Fit(f, "QN0", "", 1800, 2800)
hST.Fit(f, "QN0", "", 1800, 2800)
hST.Fit(f, "QN0", "", 1800, 2800)
hST.Fit(f, "QN0", "", 1800, 2800)
hST.Fit(f, "QN0", "", 1800, 2800)
hST.Fit(f, "QN0", "", 1800, 2800)
hST.Fit(f, "QN0", "", 1800, 2800)
hST.Fit(f, "QN0", "", 1800, 2800)
hST.Fit(f, "QN0", "", 1800, 2800)
hST.Fit(f, "QN0", "", 1800, 2800)
hST.Fit(f, "N0", "", 1800, 2800)
elif i == 0:
hST.Fit(f, "Q0", "", fit_range[0], fit_range[1])
elif i > 2:
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
formatTemplate(f, N, i)
store.book(f)
if not options.isBatch:
f.Draw("same")
hTemplate = hST.Clone("histoTemplateN%d_%d" % (N,i))
hTemplate.Reset()
hTemplate.Eval(f)
formatTemplate(hTemplate, N, i)
store.book(hTemplate)
if i == 0:
hRef = hTemplate.Clone("ReferenceTemplateN%d_0" % N)
store.book(hRef)
# Print Chi-squre/Ndof
print "N = %d, Chi^2/Ndof = %0.2f/%d" %\
(N, f.GetChisquare(), f.GetNDF())
if not options.isBatch:
c.Update()
c.Print("TemplateN%d.pdf" % N)
c.Print("TemplateN%d.png" % N)
# Calculate scale/error
from OptimizationTools import OptimizeScale
for histoN, templateN in [[2,3]]:
hST = store.get("ReferenceTemplateN%d_0" % histoN)
hTemplate = store.get("ReferenceTemplateN%d_0" % templateN)
hlnL, scale, err = OptimizeScale(hST, hTemplate, norm_range)
hlnL.SetName("LogLikelihood_%dto%d" % (templateN, histoN))
store.book(hlnL)
for i in range(len(config.templates)):
hTemplate = store.get("histoTemplateN%d_%d" % (templateN, i))
hTemplate_ = hTemplate.Clone("histoTemplateN%d_%d__RescaledToN%d"
% (templateN, i, histoN))
hTemplate_.Scale(scale)
store.book(hTemplate_)
# Shape Uncertainty
hBkgTemplate = store.get("histoTemplateN2_0")
hBkgTemplate.Rebin(config.rebin)
nbins = hBkgTemplate.GetNbinsX()
vST = TVectorD(nbins)
vBkg = TVectorD(nbins)
vexl = TVectorD(nbins)
vexh = TVectorD(nbins)
shape_el = TVectorD(nbins)
shape_eh = TVectorD(nbins)
rel_shape_el = TVectorD(nbins)
rel_shape_eh = TVectorD(nbins)
for i in range(nbins):
vST[i] = hBkgTemplate.GetBinCenter(i+1)
if (vST[i] < config.com):
vBkg[i] = hBkgTemplate.GetBinContent(i+1)
else:
vBkg[i] = 0.0
vexl[i] = 0.0
vexh[i] = 0.0
shape_el[i] = 0.0
shape_eh[i] = 0.0
rel_shape_el[i] = 0.0
rel_shape_eh[i] = 0.0
for i in range(len(config.templates)):
for label in ["histoTemplateN2_%d", "histoTemplateN3_%d__RescaledToN2"]:
if label % i == "histoTemplateN2_0":
continue
h = store.get(label % i)
h.Rebin(config.rebin)
for ibin in range(nbins):
diff = h.GetBinContent(ibin+1) - vBkg[ibin]
if diff > 0 and diff > shape_eh[ibin]:
shape_eh[ibin] = diff
elif diff < 0 and abs(diff) > shape_el[ibin]:
shape_el[ibin] = abs(diff)
# Relative Shape Uncertaincy
for i in range(nbins):
if vBkg[i] > 0:
#rel_shape_el[i] = rel_shape_el[i] / vBkg[i]
#hape_eh[i] = rel_shape_eh[i] / vBkg[i]
max_err = max(shape_el[i], shape_eh[i])
shape_el[i] = max_err
shape_eh[i] = max_err
rel_shape_el[i] = max_err /vBkg[i]
rel_shape_eh[i] = max_err /vBkg[i]
else:
rel_shape_el[i] = 0.0
rel_shape_eh[i] = 0.0
#print vST[i], vBkg[i], rel_shape_el[i], rel_shape_eh[i]
gShapeUncertainty = TGraphAsymmErrors(vST, vBkg,
vexl, vexh, shape_el, shape_eh)
gShapeUncertainty.SetName("Shape_Uncertainty")
formatUncertainty(gShapeUncertainty)
store.book(gShapeUncertainty)
gRelShapeUncertainty = TGraphAsymmErrors(vST, vexl,
vexl, vexh, rel_shape_el, rel_shape_eh)
gRelShapeUncertainty.SetName("Relative_Shape_Uncertainty")
formatUncertainty(gRelShapeUncertainty)
store.book(gRelShapeUncertainty)
# Generate Backgrouds
for N in config.label_for_data:
hST = infile.Get("plotsN%s/ST" % N)
rel_scale_err2 = 0.0
scale_factor = 1.0
for Nref in config.label_for_ref:
if N == Nref:
continue
template = store.get("ReferenceTemplateN%s_0" % Nref)
hlnL, scale, err = OptimizeScale(hST, template, norm_range)
hlnL.SetName("LogLikelihood_%sto%s" % (Nref, N))
store.book(hlnL)
if Nref == "2":
scale_factor = scale
rel_scale_err2 += err/scale * err/scale
print "%s/%s %.3f $\pm$ %.3f" % (N, Nref, scale, err)
vy = TVectorD(nbins)
veyh = TVectorD(nbins)
veyl = TVectorD(nbins)
for i in range(nbins):
vy[i] = vBkg[i] * scale_factor
veyh[i] = vy[i] * TMath.Sqrt(rel_scale_err2
+ rel_shape_eh[i]*rel_shape_eh[i])
veyl[i] = vy[i] * TMath.Sqrt(rel_scale_err2
+ rel_shape_el[i]*rel_shape_el[i])
print "Scaling uncertainty (%s): %.2f" %\
(N, TMath.sqrt(rel_scale_err2) * 100.0)
gBkg = TGraphAsymmErrors(vST, vy, vexl, vexh, veyl, veyh)
gBkg.SetName("BackgroundGraph_N%s" % N)
formatUncertainty(gBkg)
store.book(gBkg)
hST.Rebin(config.rebin)
hST.SetName("Data_N%s" % N)
formatST(hST)
store.book(hST)
hBkg = hST.Clone("Background_N%s" % N)
hBkg.Reset()
store.book(hBkg)
for i in range(nbins):
ibin = hBkg.FindBin(vST[i])
hBkg.SetBinContent(ibin, vy[i])
hBkg.SetBinError(ibin, max(veyh[i], vexl[i]))
from OptimizationTools import Integral
hIntBkg = hBkg.Clone("IntegralBackground_N%s" % N)
Integral(hIntBkg)
store.book(hIntBkg)
hIntData = hST.Clone("IntegralData_N%s" % N)
Integral(hIntData)
store.book(hIntData)
# Plot Shape Uncertainty
if not options.isBatch:
legend_shape = TLegend(0.4244355,0.4241525,0.9395968,0.8652542)
legend_shape.SetTextFont(42)
legend_shape.SetFillColor(0)
legend_shape.SetLineColor(0)
legend_shape.SetTextSize(0.036)
c = TCanvas("ShapeUncertaintyN2", "ShapeUncertaintyN2", 500, 500)
canvas.book(c)
gShapeUncertainty.Draw("AC3")
gShapeUncertainty.GetXaxis().SetNdivisions(510)
gShapeUncertainty.GetXaxis().SetRangeUser(fit_range[0], config.maxST)
gShapeUncertainty.GetYaxis().SetRangeUser(5e-2, 5e6)
legend_shape.AddEntry(store.get("Data_N2"), "Data (N = 2)", "p")
legend_shape.AddEntry(gShapeUncertainty, "Shape Uncertainty", "f")
for i in range(len(config.templates)):
for label in ["histoTemplateN2_%d", "histoTemplateN3_%d__RescaledToN2"]:
h = store.get(label % i)
h.GetXaxis().SetRangeUser(fit_range[0], config.maxST)
h.Draw("histcsame")
h.GetXaxis().SetNdivisions(510)
if label == "histoTemplateN2_%d":
N = 2
else:
N = 3
legend_shape.AddEntry(h, "Parameterization %d (N = %d)" % (i, N), "l")
store.get("Data_N2").Draw("esame")
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")
c.SetLogy(1)
legend_shape.Draw("plain")
c.Update()
c.Print("ShapeUncertaintyN2.pdf")
c.Print("ShapeUncertaintyN2.png")
if isSaveOutput:
store.saveAs(options.outputfile)
if not options.isBatch:
raw_input("Press Enter to continue...")
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(0.6891129,0.8644068,0.9435484,0.9258475,"brNDC")
label.SetFillColor(0)
label.SetTextSize(0.0529661);
label.AddText(label_text);
label.Draw("plain")
c.Update()
raw_input("Press Enter to continue...")
def main():
from optparse import OptionParser
parser = OptionParser()
parser.add_option("-i", "--inputfile", dest="inputfile")
parser.add_option("-o", "--ouputfile", dest="outputfile")
parser.add_option("-b", "--batch", action="store_true",\
dest="isBatch", default=False)
parser.add_option("--normalization", nargs=2,\
type="float", dest="norm_range")
parser.add_option("--fit", nargs=2,\
type="float", dest="fit_range")
(options, args) = parser.parse_args()
isSaveOutput = options.outputfile is not None
if not (options.inputfile):
parser.error("Please specify inputfiles.")
import configurations as config
if options.fit_range:
fit_range = options.fit_range
norm_range = (fit_range[1] - 200., fit_range[1])
else:
fit_range = config.fit_range
norm_range = config.norm_range
# Override normalization range from input
if options.norm_range:
norm_range = options.norm_range
from Styles import formatST, formatTemplate, formatUncertainty
from ROOT import TFile, TF1, TH1D, TMath, TCanvas, TLegend,\
TGraphAsymmErrors, TVectorD, gStyle
gStyle.SetPadTopMargin(0.05)
gStyle.SetPadRightMargin(0.05)
#gStyle.SetOptFit(1111111)
#input file name
infile = TFile(options.inputfile, "READ")
from HistoStore import HistoStore
store = HistoStore()
canvas = HistoStore()
print "Fit range: %d - %d GeV" % fit_range
print "Normalization range: %d - %d GeV" % norm_range
# Fit
for N in config.exclusive_multiplicities:
hST = infile.Get("plots%dJets/ST" % N)
if not options.isBatch:
c = TCanvas("TemplateN%d" % N, "TemplateN%d" % N, 500, 500)
canvas.book(c)
formatST(hST)
hST.Draw("e")
hST.GetXaxis().SetRangeUser(fit_range[0], config.maxST)
hST.GetYaxis().SetRangeUser(1e-2, 2e4)
hST.GetYaxis().SetTitleOffset(1.2)
c.SetLogy(1)
for i, formula in enumerate(config.templates):
if N == 2:
f = TF1("templateN%d_%d" % (N, i), formula, 0, 10000)
elif N == 3:
f = store.get("templateN2_%d" % i).Clone("templateN%d_%d" %
(N, i))
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
hST.Fit(f, "QN0", "", fit_range[0], fit_range[1])
if i == 0:
hST.Fit(f, "Q0", "", fit_range[0], fit_range[1])
formatTemplate(f, N, i)
store.book(f)
if not options.isBatch:
f.Draw("same")
hTemplate = hST.Clone("histoTemplateN%d_%d" % (N, i))
hTemplate.Reset()
hTemplate.Eval(f)
formatTemplate(hTemplate, N, i)
store.book(hTemplate)
if i == 0:
hRef = hTemplate.Clone("ReferenceTemplateN%d_0" % N)
store.book(hRef)
# Print Chi-squre/Ndof
print "N = %d, Chi^2/Ndof = %0.2f/%d" %\
(N, f.GetChisquare(), f.GetNDF())
if not options.isBatch:
c.Update()
# Calculate scale/error
from OptimizationTools import OptimizeScale
for histoN, templateN in [[2, 3]]:
hST = store.get("ReferenceTemplateN%d_0" % histoN)
hTemplate = store.get("ReferenceTemplateN%d_0" % templateN)
hlnL, scale, err = OptimizeScale(hST, hTemplate, norm_range)
hlnL.SetName("LogLikelihood_%dto%d" % (templateN, histoN))
store.book(hlnL)
for i in range(len(config.templates)):
hTemplate = store.get("histoTemplateN%d_%d" % (templateN, i))
hTemplate_ = hTemplate.Clone("histoTemplateN%d_%d__RescaledToN%d" %
(templateN, i, histoN))
hTemplate_.Scale(scale)
store.book(hTemplate_)
# Shape Uncertainty
hBkgTemplate = store.get("histoTemplateN2_0")
hBkgTemplate.Rebin(config.rebin)
nbins = hBkgTemplate.GetNbinsX()
vST = TVectorD(nbins)
vBkg = TVectorD(nbins)
vexl = TVectorD(nbins)
vexh = TVectorD(nbins)
shape_el = TVectorD(nbins)
shape_eh = TVectorD(nbins)
rel_shape_el = TVectorD(nbins)
rel_shape_eh = TVectorD(nbins)
for i in range(nbins):
vST[i] = hBkgTemplate.GetBinCenter(i + 1)
if (vST[i] < config.com):
vBkg[i] = hBkgTemplate.GetBinContent(i + 1)
else:
vBkg[i] = 0.0
vexl[i] = 0.0
vexh[i] = 0.0
shape_el[i] = 0.0
shape_eh[i] = 0.0
rel_shape_el[i] = 0.0
rel_shape_eh[i] = 0.0
for i in range(len(config.templates)):
for label in [
"histoTemplateN2_%d", "histoTemplateN3_%d__RescaledToN2"
]:
if label % i == "histoTemplateN2_0":
continue
h = store.get(label % i)
h.Rebin(config.rebin)
for ibin in range(nbins):
diff = h.GetBinContent(ibin + 1) - vBkg[ibin]
if diff > 0 and diff > shape_eh[ibin]:
shape_eh[ibin] = diff
elif diff < 0 and abs(diff) > shape_el[ibin]:
shape_el[ibin] = abs(diff)
# Relative Shape Uncertaincy
for i in range(nbins):
if vBkg[i] > 0:
#rel_shape_el[i] = rel_shape_el[i] / vBkg[i]
#hape_eh[i] = rel_shape_eh[i] / vBkg[i]
max_err = max(shape_el[i], shape_eh[i])
shape_el[i] = max_err
shape_eh[i] = max_err
rel_shape_el[i] = max_err / vBkg[i]
rel_shape_eh[i] = max_err / vBkg[i]
else:
rel_shape_el[i] = 0.0
rel_shape_eh[i] = 0.0
#print vST[i], vBkg[i], rel_shape_el[i], rel_shape_eh[i]
gShapeUncertainty = TGraphAsymmErrors(vST, vBkg, vexl, vexh, shape_el,
shape_eh)
gShapeUncertainty.SetName("Shape_Uncertainty")
formatUncertainty(gShapeUncertainty)
store.book(gShapeUncertainty)
gRelShapeUncertainty = TGraphAsymmErrors(vST, vexl, vexl, vexh,
rel_shape_el, rel_shape_eh)
gRelShapeUncertainty.SetName("Relative_Shape_Uncertainty")
formatUncertainty(gRelShapeUncertainty)
store.book(gRelShapeUncertainty)
# Generate Backgrouds
for N in config.label_for_data:
hST = infile.Get("plotsN%s/ST" % N)
rel_scale_err2 = 0.0
scale_factor = 1.0
for Nref in config.label_for_ref:
if N == Nref:
continue
template = store.get("ReferenceTemplateN%s_0" % Nref)
hlnL, scale, err = OptimizeScale(hST, template, norm_range)
hlnL.SetName("LogLikelihood_%sto%s" % (Nref, N))
store.book(hlnL)
if Nref == "2":
scale_factor = scale
rel_scale_err2 += err / scale * err / scale
print "%s/%s %.3f +/- %.3f" % (N, Nref, scale, err)
vy = TVectorD(nbins)
veyh = TVectorD(nbins)
veyl = TVectorD(nbins)
for i in range(nbins):
vy[i] = vBkg[i] * scale_factor
veyh[i] = vy[i] * TMath.Sqrt(rel_scale_err2 +
rel_shape_eh[i] * rel_shape_eh[i])
veyl[i] = vy[i] * TMath.Sqrt(rel_scale_err2 +
rel_shape_el[i] * rel_shape_el[i])
print "Scaling uncertainty (%s): %.2f" %\
(N, TMath.sqrt(rel_scale_err2) * 100.0)
gBkg = TGraphAsymmErrors(vST, vy, vexl, vexh, veyl, veyh)
gBkg.SetName("BackgroundGraph_N%s" % N)
formatUncertainty(gBkg)
store.book(gBkg)
hST.Rebin(config.rebin)
hST.SetName("Data_N%s" % N)
formatST(hST)
store.book(hST)
hBkg = hST.Clone("Background_N%s" % N)
hBkg.Reset()
store.book(hBkg)
for i in range(nbins):
ibin = hBkg.FindBin(vST[i])
hBkg.SetBinContent(ibin, vy[i])
hBkg.SetBinError(ibin, max(veyh[i], vexl[i]))
from OptimizationTools import Integral
hIntBkg = hBkg.Clone("IntegralBackground_N%s" % N)
Integral(hIntBkg)
store.book(hIntBkg)
hIntData = hST.Clone("IntegralData_N%s" % N)
Integral(hIntData)
store.book(hIntData)
# Plot Shape Uncertainty
if not options.isBatch:
legend_shape = TLegend(0.5544355, 0.5741525, 0.9395968, 0.9152542)
legend_shape.SetTextFont(42)
legend_shape.SetFillColor(0)
legend_shape.SetLineColor(0)
c = TCanvas("ShapeUncertaintyN2", "ShapeUncertaintyN2", 500, 500)
canvas.book(c)
gShapeUncertainty.Draw("AC3")
gShapeUncertainty.GetXaxis().SetRangeUser(fit_range[0], config.maxST)
gShapeUncertainty.GetYaxis().SetRangeUser(5e-2, 1.2e6)
legend_shape.AddEntry(store.get("Data_N2"), "Data (N = 2)", "p")
legend_shape.AddEntry(gShapeUncertainty, "Shape Uncertainty", "f")
for i in range(len(config.templates)):
for label in [
"histoTemplateN2_%d", "histoTemplateN3_%d__RescaledToN2"
]:
h = store.get(label % i)
h.GetXaxis().SetRangeUser(fit_range[0], config.maxST)
h.Draw("histcsame")
if label == "histoTemplateN2_%d":
N = 2
else:
N = 3
legend_shape.AddEntry(h,
"Parametrization %d (N = %d)" % (i, N),
"l")
store.get("Data_N2").Draw("esame")
c.SetLogy(1)
legend_shape.Draw("plain")
c.Update()
if isSaveOutput:
store.saveAs(options.outputfile)
if not options.isBatch:
raw_input("Press Enter to continue...")
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...")
def main():
from optparse import OptionParser
parser = OptionParser()
parser.add_option("-i", "--inputfile", dest="inputfile")
parser.add_option("-N", "--multiplicity", dest="N", type="int", default=3)
parser.add_option("-x", "--exclusive", action="store_true",\
dest="isExclusive", default=False)
parser.add_option("-l", "--label", dest="label", type="string", default="")
parser.add_option("-z", "--zeyneplabel",action="store_true",dest="zeynep",default=True)
(options, args) = parser.parse_args()
N = options.N
isExclusive = options.isExclusive
label_text = options.label
zeynep = options.zeynep
if isExclusive and not (N == 2 or N == 3):
parser.error("Exclusive plot only for N =2 or 3")
import configurations as config
from ROOT import TFile, TCanvas, THStack, TLegend, TPaveText, gStyle, TPad, TH1F, TGraphAsymmErrors, TMath
from ModelParser import ModelKey
gStyle.SetPadTopMargin(0.05)
gStyle.SetPadRightMargin(0.05)
gStyle.SetPadBottomMargin(0.20)
gStyle.SetErrorX(0.)
suffix = ""
if not isExclusive:
suffix = "up"
sm_files = []
for model in config.sm_models:
f = TFile("%s/%s.root" % (config.sm_dir, model), "READ")
sm_files.append(f)
bh_weights = []
bh_files = []
from BHXsec import BHXsec
xsec = BHXsec()
for model in config.bh_showcase:
f = TFile("%s/%s.root" % (config.bh_dir, model), "READ")
bh_files.append(f)
h = f.Get("plotsNoCut/ST")
nEvents= h.GetEntries()
bh_weights.append(xsec.get(model) / nEvents * config.integrated_luminosity)
c = TCanvas("ST_Mul%d%s" % (N, suffix),
"ST_Mul%d%s" % (N, suffix), 500, 600)
hs = THStack()
hs1 = THStack()
infile = TFile(options.inputfile, "READ")
hBkg = infile.Get("Background_N%d%s" % (N, suffix))
#hnewBkg = infile.Get("histoTemplateN3_0")
hnewBkg = infile.Get("ReferenceTemplateN3_0")
gBkg = infile.Get("BackgroundGraph_N%d%s" % (N, suffix))
hData = infile.Get("Data_N%d%s" % (N, suffix))
hBkg = infile.Get("Background_N%d%s" % (N, suffix))
hBkg.SetMarkerSize(0)
hBkg_ = hBkg.Clone("BkgLine")
hBkg.SetFillColor(33)
hBkg.SetLineColor(33)
hBkg_.SetLineWidth(3)
hBkg_.SetLineColor(862)
hs.Add(hBkg, "e3")
hnewBkg.SetLineWidth(3)
hnewBkg.Scale(10*3.407)
hs.Add(hnewBkg,"l")
legend = TLegend(0.2826613,0.4819492,0.6094355,0.9416102) # - only for N >= 2 and 3
#legend = TLegend(0.3026613,0.5519492,0.6094355,0.9416102) # was 0.4919...zeynep
#legend = TLegend(0.3526613,0.5519492,0.6094355,0.9416102) # was 0.4919...
#legend.SetTextSize(0.041); #was 0.02966102
legend.SetTextSize(0.037);
legend.SetTextFont(42);
legend.SetFillColor(0)
legend.SetLineColor(0)
if isExclusive:
legend.SetHeader("Multiplicity N = %d" % N)
else:
legend.SetHeader("Multiplicity N #geq %d" % N)
legend.AddEntry(hData, "Data", "lep")
#legend.AddEntry(hnewBkg, "N=3 Fit Rescaled","l")
legend.AddEntry(hBkg_, "Background", "l")
legend.AddEntry(hBkg, "Uncertainty", "f")
legend_sm = TLegend(0.6471774,0.7069492,0.8508065,0.8471186)
# legend_sm = TLegend(0.6271774,0.7369492,0.8308065,0.8771186)
# legend_sm.SetTextSize(0.037);
legend_sm.SetTextSize(0.037);
legend_sm.SetTextFont(42);
legend_sm.SetFillColor(0)
legend_sm.SetLineColor(0)
for i, f in enumerate(bh_files):
h = f.Get("plotsN%d%s/ST" % (N, suffix))
h.Rebin(config.rebin)
h.Scale(bh_weights[i])
# Add background
for ibin in range(h.GetNbinsX()):
h.SetBinContent(ibin+1,\
h.GetBinContent(ibin+1)\
+ hBkg.GetBinContent(ibin+1))
h.SetLineWidth(3)
#h.SetLineColor(i+2)
h.SetLineStyle(i+2)
#if i == 0:
#h.SetLineColor(814)
if i == 0:
h.SetLineStyle(5)
h.SetLineColor(899)
if i == 1:
h.SetLineStyle(9)
h.SetLineColor(4)
if i == 2:
h.SetLineStyle(3)
h.SetLineColor(614)
hs.Add(h, "hist")
model = ModelKey(config.bh_showcase[i])
bh_legend = "M_{D} = %.1f TeV, M_{BH}^{ min} = %.1f TeV, n = %d" % (\
model.parameter["MD"],
model.parameter["M"],
model.parameter["n"])
if i == 3:
bh_legend = "M_{D} = 3.0 TeV, M_{QBH}^{ min} = 4.0 TeV, n = 4"
legend.AddEntry(h, bh_legend, "l")
# qbh_legend = "M_{D} = 4.0 TeV, M_{QBH}^{ min} = 5.0 TeV, n = 5"
# legend.AddEntry(h, qbh_legend, "l")
#if isExclusive:
zeynep = True
if zeynep:
for i, f in enumerate(sm_files):
h = f.Get("plotsN%d%s/ST" % (N, suffix))
h.Rebin(config.rebin)
h.Scale(config.integrated_luminosity)
h.SetFillColor(config.sm_colors[i])
h.SetLineColor(config.sm_colors[i])
hs1.Add(h, "hist")
legend_sm.AddEntry(h, config.sm_models[i], "f")
#hs.Add(hData, "e")
hs.Draw("nostack")
hs1.Draw("same")
c.SetLogy(1)
hs.GetXaxis().SetTitle("S_{T} (GeV)")
hs.GetYaxis().SetTitle(hData.GetYaxis().GetTitle())
hs.GetYaxis().SetTitleOffset(1.25)
hs.GetYaxis().SetTitleSize(0.04)
hs.GetYaxis().SetLabelSize(0.04)
hs.GetXaxis().SetTitleSize(0.01)
hs.GetXaxis().SetLabelSize(0.01)
ibin = 0
#if isExclusive:
# hs.GetXaxis().SetRangeUser(config.fit_range[0], config.maxST)
# ibin = hData.FindBin(config.fit_range[0])
#else:
# hs.GetXaxis().SetRangeUser(config.norm_range[0], config.maxST)
# ibin = hData.FindBin(config.norm_range[0])
if isExclusive:
hs.GetXaxis().SetRangeUser(1800, config.maxST)
ibin = hData.FindBin(1800)
else:
hs.GetXaxis().SetRangeUser(config.norm_range[0], config.maxST)
ibin = hData.FindBin(config.norm_range[0])
from Styles import formatUncertainty
formatUncertainty(gBkg)
gBkg.Draw("LX")
hData.Draw("sameex0")
hs.SetMinimum(5e-1)
if isExclusive:
hs.SetMaximum(1e7)
# hs.SetMaximum(hData.GetBinContent(ibin) * 40)
else:
#hs.SetMaximum(1e8)
hs.SetMaximum(hData.GetBinContent(ibin) * 20) # or 1e7 for N>=3 and use 4 models
legend.Draw("plain")
#if isExclusive:
if zeynep:
legend_sm.Draw("plain")
if isExclusive:
cmslabel =TPaveText(0.45,0.96,0.60,0.99,"brNDC");
else:
cmslabel = TPaveText(0.45,0.96,0.60,0.99,"brNDC")
cmslabel.AddText(config.cmsTitle)
#cmslabel.AddText(config.cmsSubtitle)
cmslabel.SetFillColor(0)
cmslabel.SetTextSize(0.041)
cmslabel.Draw("plain")
label = TPaveText(0.8891129,0.8644068,0.9435484,0.9258475,"brNDC")
label.SetFillColor(0)
#label.SetTextSize(0.0529661);
label.SetTextSize(0.0529661);
label.AddText(label_text);
label.Draw("plain")
c.RedrawAxis()
#Divide
ibin = hData.FindBin(config.norm_range[0])
#print ibin
fbin = hData.FindBin(config.maxST)
#print fbin
hData.Sumw2()
hBkg_.Sumw2()
Pull = TH1F("","",fbin-ibin+1,(ibin-1)*100,fbin*100)
Pull2 = TH1F("","",fbin-ibin+1,(ibin-1)*100,fbin*100)
Ratio = hData.Clone()
Ratio.Add(hBkg_,-1)
#Ratio.Divide(hBkg_)
Band = TGraphAsymmErrors(fbin-ibin+1)
for i in range(ibin-1,fbin+1):
i += 1
if hData.GetBinContent(i) != 0:
value = hData.GetBinContent(i) + (hBkg_.GetBinError(i)*hBkg_.GetBinError(i))
#print Ratio.GetBinError(i), value**(0.5)
#print i-19,i,(i)*100, hData.GetBinContent(i) , hBkg_.GetBinContent(i),hData.GetBinContent(i) - hBkg_.GetBinContent(i)
Pull.SetBinContent(i-19,(hData.GetBinContent(i) - hBkg_.GetBinContent(i))/ Ratio.GetBinError(i))
#print Ratio.GetBinError(i), abs(Ratio.GetBinContent(i))*0.05
#Pull.SetBinContent(i-19,(hData.GetBinContent(i) - hBkg_.GetBinContent(i))/ Ratio.GetBinError(i))
#Pull.SetBinContent(i-19,(hData.GetBinContent(i) / hBkg_.GetBinContent(i)))
Pull.SetBinError(i-19,Ratio.GetBinError(i))
#Pull.SetBinError(i-19,hData.GetBinError(i)/gBkg.GetErrorY(i))
if (hBkg_.GetBinContent(i)*0.05 > hBkg_.GetBinError(i)):
#print "bin error too small changing the error to: ", hBkg_.GetBinContent(i)*0.05
Pull2.SetBinContent(i-19,(hnewBkg.GetBinContent(i) - hBkg_.GetBinContent(i))/ (hBkg_.GetBinContent(i)*0.05))
else:
Pull2.SetBinContent(i-19,(hnewBkg.GetBinContent(i) - hBkg_.GetBinContent(i))/ hBkg_.GetBinError(i))
#print hBkg_.GetBinError(i), hBkg_.GetBinContent(i)*0.05
#print i, " Pull2: ", Pull2.GetBinContent(i-19), "hnewBkg.GetBinContent(i-1): " , hnewBkg.GetBinContent(i-1), "hBkg_.GetBinContent(i): ", hBkg_.GetBinContent(i)
else:
Pull.SetBinContent(i-19,0)
Pull2.SetBinContent(i-19,(hnewBkg.GetBinContent(i-1) - hBkg_.GetBinContent(i))/ hBkg_.GetBinError(i))
Band.SetPoint(i,hBkg_.GetBinCenter(i),1.0)
#print hBkg_.GetBinContent(i), hBkg_.GetBinError(i)
up = abs ( 1.- ((hBkg_.GetBinContent(i) + hBkg_.GetBinError(i)) / hBkg_.GetBinContent(i)))
down = abs ( 1.- ((hBkg_.GetBinContent(i) - hBkg_.GetBinError(i)) / hBkg_.GetBinContent(i)))
Band.SetPointError(i,0.,0.,down,up)
#Band.Print()
pad = TPad("pad", "pad", 0.0, 0.0, 1.0, 1.0)
pad.SetTopMargin(0.799999)
pad.SetRightMargin(0.05)
pad.SetBottomMargin(0.09)
pad.SetFillColor(0)
#pad.SetGridy(1)
pad.SetFillStyle(0)
pad.Draw("same")
pad.cd(0)
Ratio.SetMarkerStyle(20)
Pull.SetMarkerStyle(20)
Pull.SetLineColor(1)
Pull.SetMarkerSize(0.9)
#Pull.SetMaximum(3)
#Pull.SetMinimum(-1)
Pull.SetMaximum(2.5)
Pull.SetMinimum(-2.5)
Pull.GetYaxis().SetNdivisions(5,1);
Pull.GetXaxis().SetTitle('S_{T} (GeV)')
Pull.GetXaxis().SetLabelSize(0.04)
Pull.GetYaxis().SetTitleOffset(1.05)
Pull.GetYaxis().SetLabelSize(0.02)
Pull.GetYaxis().SetTitleSize(0.025)
Pull.GetYaxis().CenterTitle(1)
Pull.GetYaxis().SetTitle('#sigma(Data-Bkg)')
Pull.SetFillColor(2)
Pull.Draw("HIST")
Pull2.SetLineColor(862)
Pull2.SetLineWidth(3)
Pull2.SetLineStyle(2)
#Pull2.Draw("SAME")
formatUncertainty(Band)
Band.SetFillStyle(3001)
# Band.Draw("le3")
# Pull.Draw("ex0same")
pad.RedrawAxis()
gStyle.SetOptStat(0)
#block1 =TPaveText(0.370,0.84,0.351,0.86,"brNDC"); # for N>=2 and >=3 only
#block1 =TPaveText(0.361,0.85,0.377,0.87,"brNDC");
#block1 =TPaveText(0.333,0.88,0.354,0.85,"brNDC") #for n = 2 only
block1 =TPaveText(0.331,0.82,0.357,0.85,"brNDC"); #FOR n=3 only
block1.SetFillColor(0)
block1.Draw("plain")
#block2 =TPaveText(0.305,0.84,0.333,0.86,"brNDC"); # for N>=2 and >=3 only
#block2 =TPaveText(0.395,0.85,0.41,0.87,"brNDC");
#block2 =TPaveText(0.296,0.88,0.316,0.85,"brNDC"); for n =2 only
block2 =TPaveText(0.295,0.82,0.317,0.85,"brNDC"); #FOR n=3 only
block2.SetFillColor(0)
block2.Draw("plain")
if isExclusive:
c.Print("ST_Mul%d.pdf" % N)
c.Print("ST_Mul%d.png" % N)
else:
c.Print("ST_Mul%dup.pdf" % N)
c.Print("ST_Mul%dup.png" % N)
c.Update()
raw_input("Press Enter to continue...")
def main():
from optparse import OptionParser
parser = OptionParser()
parser.add_option("-i", "--inputfile", dest="inputfile")
parser.add_option("-N", "--multiplicity", dest="N", type="int", default=3)
parser.add_option("-x", "--exclusive", action="store_true",\
dest="isExclusive", default=False)
parser.add_option("-l", "--label", dest="label", type="string", default="")
parser.add_option("-z",
"--zeyneplabel",
action="store_true",
dest="zeynep",
default=True)
(options, args) = parser.parse_args()
N = options.N
isExclusive = options.isExclusive
label_text = options.label
zeynep = options.zeynep
if isExclusive and not (N == 2 or N == 3):
parser.error("Exclusive plot only for N =2 or 3")
import configurations as config
from ROOT import TFile, TCanvas, THStack, TLegend, TPaveText, gStyle, TPad, TH1F, TGraphAsymmErrors, TMath
from ModelParser import ModelKey
gStyle.SetPadTopMargin(0.05)
gStyle.SetPadRightMargin(0.05)
gStyle.SetPadBottomMargin(0.20)
gStyle.SetErrorX(0.)
suffix = ""
if not isExclusive:
suffix = "up"
sm_files = []
for model in config.sm_models:
f = TFile("%s/%s.root" % (config.sm_dir, model), "READ")
sm_files.append(f)
bh_weights = []
bh_files = []
from BHXsec import BHXsec
xsec = BHXsec()
for model in config.bh_showcase:
f = TFile("%s/%s.root" % (config.bh_dir, model), "READ")
bh_files.append(f)
h = f.Get("plotsNoCut/ST")
nEvents = h.GetEntries()
bh_weights.append(
xsec.get(model) / nEvents * config.integrated_luminosity)
c = TCanvas("ST_Mul%d%s" % (N, suffix), "ST_Mul%d%s" % (N, suffix), 500,
600)
hs = THStack()
hs1 = THStack()
infile = TFile(options.inputfile, "READ")
hBkg = infile.Get("Background_N%d%s" % (N, suffix))
#hnewBkg = infile.Get("histoTemplateN3_0")
hnewBkg = infile.Get("ReferenceTemplateN3_0")
gBkg = infile.Get("BackgroundGraph_N%d%s" % (N, suffix))
hData = infile.Get("Data_N%d%s" % (N, suffix))
hBkg = infile.Get("Background_N%d%s" % (N, suffix))
hBkg.SetMarkerSize(0)
hBkg_ = hBkg.Clone("BkgLine")
hBkg.SetFillColor(33)
hBkg.SetLineColor(33)
hBkg_.SetLineWidth(3)
hBkg_.SetLineColor(862)
hs.Add(hBkg, "e3")
hnewBkg.SetLineWidth(3)
hnewBkg.Scale(10 * 3.407)
hs.Add(hnewBkg, "l")
legend = TLegend(0.2826613, 0.4819492, 0.6094355,
0.9416102) # - only for N >= 2 and 3
#legend = TLegend(0.3026613,0.5519492,0.6094355,0.9416102) # was 0.4919...zeynep
#legend = TLegend(0.3526613,0.5519492,0.6094355,0.9416102) # was 0.4919...
#legend.SetTextSize(0.041); #was 0.02966102
legend.SetTextSize(0.037)
legend.SetTextFont(42)
legend.SetFillColor(0)
legend.SetLineColor(0)
if isExclusive:
legend.SetHeader("Multiplicity N = %d" % N)
else:
legend.SetHeader("Multiplicity N #geq %d" % N)
legend.AddEntry(hData, "Data", "lep")
#legend.AddEntry(hnewBkg, "N=3 Fit Rescaled","l")
legend.AddEntry(hBkg_, "Background", "l")
legend.AddEntry(hBkg, "Uncertainty", "f")
legend_sm = TLegend(0.6471774, 0.7069492, 0.8508065, 0.8471186)
# legend_sm = TLegend(0.6271774,0.7369492,0.8308065,0.8771186)
# legend_sm.SetTextSize(0.037);
legend_sm.SetTextSize(0.037)
legend_sm.SetTextFont(42)
legend_sm.SetFillColor(0)
legend_sm.SetLineColor(0)
for i, f in enumerate(bh_files):
h = f.Get("plotsN%d%s/ST" % (N, suffix))
h.Rebin(config.rebin)
h.Scale(bh_weights[i])
# Add background
for ibin in range(h.GetNbinsX()):
h.SetBinContent(ibin+1,\
h.GetBinContent(ibin+1)\
+ hBkg.GetBinContent(ibin+1))
h.SetLineWidth(3)
#h.SetLineColor(i+2)
h.SetLineStyle(i + 2)
#if i == 0:
#h.SetLineColor(814)
if i == 0:
h.SetLineStyle(5)
h.SetLineColor(899)
if i == 1:
h.SetLineStyle(9)
h.SetLineColor(4)
if i == 2:
h.SetLineStyle(3)
h.SetLineColor(614)
hs.Add(h, "hist")
model = ModelKey(config.bh_showcase[i])
bh_legend = "M_{D} = %.1f TeV, M_{BH}^{ min} = %.1f TeV, n = %d" % (\
model.parameter["MD"],
model.parameter["M"],
model.parameter["n"])
if i == 3:
bh_legend = "M_{D} = 3.0 TeV, M_{QBH}^{ min} = 4.0 TeV, n = 4"
legend.AddEntry(h, bh_legend, "l")
# qbh_legend = "M_{D} = 4.0 TeV, M_{QBH}^{ min} = 5.0 TeV, n = 5"
# legend.AddEntry(h, qbh_legend, "l")
#if isExclusive:
zeynep = True
if zeynep:
for i, f in enumerate(sm_files):
h = f.Get("plotsN%d%s/ST" % (N, suffix))
h.Rebin(config.rebin)
h.Scale(config.integrated_luminosity)
h.SetFillColor(config.sm_colors[i])
h.SetLineColor(config.sm_colors[i])
hs1.Add(h, "hist")
legend_sm.AddEntry(h, config.sm_models[i], "f")
#hs.Add(hData, "e")
hs.Draw("nostack")
hs1.Draw("same")
c.SetLogy(1)
hs.GetXaxis().SetTitle("S_{T} (GeV)")
hs.GetYaxis().SetTitle(hData.GetYaxis().GetTitle())
hs.GetYaxis().SetTitleOffset(1.25)
hs.GetYaxis().SetTitleSize(0.04)
hs.GetYaxis().SetLabelSize(0.04)
hs.GetXaxis().SetTitleSize(0.01)
hs.GetXaxis().SetLabelSize(0.01)
ibin = 0
#if isExclusive:
# hs.GetXaxis().SetRangeUser(config.fit_range[0], config.maxST)
# ibin = hData.FindBin(config.fit_range[0])
#else:
# hs.GetXaxis().SetRangeUser(config.norm_range[0], config.maxST)
# ibin = hData.FindBin(config.norm_range[0])
if isExclusive:
hs.GetXaxis().SetRangeUser(1800, config.maxST)
ibin = hData.FindBin(1800)
else:
hs.GetXaxis().SetRangeUser(config.norm_range[0], config.maxST)
ibin = hData.FindBin(config.norm_range[0])
from Styles import formatUncertainty
formatUncertainty(gBkg)
gBkg.Draw("LX")
hData.Draw("sameex0")
hs.SetMinimum(5e-1)
if isExclusive:
hs.SetMaximum(1e7)
# hs.SetMaximum(hData.GetBinContent(ibin) * 40)
else:
#hs.SetMaximum(1e8)
hs.SetMaximum(hData.GetBinContent(ibin) *
20) # or 1e7 for N>=3 and use 4 models
legend.Draw("plain")
#if isExclusive:
if zeynep:
legend_sm.Draw("plain")
if isExclusive:
cmslabel = TPaveText(0.45, 0.96, 0.60, 0.99, "brNDC")
else:
cmslabel = TPaveText(0.45, 0.96, 0.60, 0.99, "brNDC")
cmslabel.AddText(config.cmsTitle)
#cmslabel.AddText(config.cmsSubtitle)
cmslabel.SetFillColor(0)
cmslabel.SetTextSize(0.041)
cmslabel.Draw("plain")
label = TPaveText(0.8891129, 0.8644068, 0.9435484, 0.9258475, "brNDC")
label.SetFillColor(0)
#label.SetTextSize(0.0529661);
label.SetTextSize(0.0529661)
label.AddText(label_text)
label.Draw("plain")
c.RedrawAxis()
#Divide
ibin = hData.FindBin(config.norm_range[0])
#print ibin
fbin = hData.FindBin(config.maxST)
#print fbin
hData.Sumw2()
hBkg_.Sumw2()
Pull = TH1F("", "", fbin - ibin + 1, (ibin - 1) * 100, fbin * 100)
Pull2 = TH1F("", "", fbin - ibin + 1, (ibin - 1) * 100, fbin * 100)
Ratio = hData.Clone()
Ratio.Add(hBkg_, -1)
#Ratio.Divide(hBkg_)
Band = TGraphAsymmErrors(fbin - ibin + 1)
for i in range(ibin - 1, fbin + 1):
i += 1
if hData.GetBinContent(i) != 0:
value = hData.GetBinContent(i) + (hBkg_.GetBinError(i) *
hBkg_.GetBinError(i))
#print Ratio.GetBinError(i), value**(0.5)
#print i-19,i,(i)*100, hData.GetBinContent(i) , hBkg_.GetBinContent(i),hData.GetBinContent(i) - hBkg_.GetBinContent(i)
Pull.SetBinContent(
i - 19, (hData.GetBinContent(i) - hBkg_.GetBinContent(i)) /
Ratio.GetBinError(i))
#print Ratio.GetBinError(i), abs(Ratio.GetBinContent(i))*0.05
#Pull.SetBinContent(i-19,(hData.GetBinContent(i) - hBkg_.GetBinContent(i))/ Ratio.GetBinError(i))
#Pull.SetBinContent(i-19,(hData.GetBinContent(i) / hBkg_.GetBinContent(i)))
Pull.SetBinError(i - 19, Ratio.GetBinError(i))
#Pull.SetBinError(i-19,hData.GetBinError(i)/gBkg.GetErrorY(i))
if (hBkg_.GetBinContent(i) * 0.05 > hBkg_.GetBinError(i)):
#print "bin error too small changing the error to: ", hBkg_.GetBinContent(i)*0.05
Pull2.SetBinContent(
i - 19,
(hnewBkg.GetBinContent(i) - hBkg_.GetBinContent(i)) /
(hBkg_.GetBinContent(i) * 0.05))
else:
Pull2.SetBinContent(
i - 19,
(hnewBkg.GetBinContent(i) - hBkg_.GetBinContent(i)) /
hBkg_.GetBinError(i))
#print hBkg_.GetBinError(i), hBkg_.GetBinContent(i)*0.05
#print i, " Pull2: ", Pull2.GetBinContent(i-19), "hnewBkg.GetBinContent(i-1): " , hnewBkg.GetBinContent(i-1), "hBkg_.GetBinContent(i): ", hBkg_.GetBinContent(i)
else:
Pull.SetBinContent(i - 19, 0)
Pull2.SetBinContent(
i - 19,
(hnewBkg.GetBinContent(i - 1) - hBkg_.GetBinContent(i)) /
hBkg_.GetBinError(i))
Band.SetPoint(i, hBkg_.GetBinCenter(i), 1.0)
#print hBkg_.GetBinContent(i), hBkg_.GetBinError(i)
up = abs(1. - ((hBkg_.GetBinContent(i) + hBkg_.GetBinError(i)) /
hBkg_.GetBinContent(i)))
down = abs(1. - ((hBkg_.GetBinContent(i) - hBkg_.GetBinError(i)) /
hBkg_.GetBinContent(i)))
Band.SetPointError(i, 0., 0., down, up)
#Band.Print()
pad = TPad("pad", "pad", 0.0, 0.0, 1.0, 1.0)
pad.SetTopMargin(0.799999)
pad.SetRightMargin(0.05)
pad.SetBottomMargin(0.09)
pad.SetFillColor(0)
#pad.SetGridy(1)
pad.SetFillStyle(0)
pad.Draw("same")
pad.cd(0)
Ratio.SetMarkerStyle(20)
Pull.SetMarkerStyle(20)
Pull.SetLineColor(1)
Pull.SetMarkerSize(0.9)
#Pull.SetMaximum(3)
#Pull.SetMinimum(-1)
Pull.SetMaximum(2.5)
Pull.SetMinimum(-2.5)
Pull.GetYaxis().SetNdivisions(5, 1)
Pull.GetXaxis().SetTitle('S_{T} (GeV)')
Pull.GetXaxis().SetLabelSize(0.04)
Pull.GetYaxis().SetTitleOffset(1.05)
Pull.GetYaxis().SetLabelSize(0.02)
Pull.GetYaxis().SetTitleSize(0.025)
Pull.GetYaxis().CenterTitle(1)
Pull.GetYaxis().SetTitle('#sigma(Data-Bkg)')
Pull.SetFillColor(2)
Pull.Draw("HIST")
Pull2.SetLineColor(862)
Pull2.SetLineWidth(3)
Pull2.SetLineStyle(2)
#Pull2.Draw("SAME")
formatUncertainty(Band)
Band.SetFillStyle(3001)
# Band.Draw("le3")
# Pull.Draw("ex0same")
pad.RedrawAxis()
gStyle.SetOptStat(0)
#block1 =TPaveText(0.370,0.84,0.351,0.86,"brNDC"); # for N>=2 and >=3 only
#block1 =TPaveText(0.361,0.85,0.377,0.87,"brNDC");
#block1 =TPaveText(0.333,0.88,0.354,0.85,"brNDC") #for n = 2 only
block1 = TPaveText(0.331, 0.82, 0.357, 0.85, "brNDC")
#FOR n=3 only
block1.SetFillColor(0)
block1.Draw("plain")
#block2 =TPaveText(0.305,0.84,0.333,0.86,"brNDC"); # for N>=2 and >=3 only
#block2 =TPaveText(0.395,0.85,0.41,0.87,"brNDC");
#block2 =TPaveText(0.296,0.88,0.316,0.85,"brNDC"); for n =2 only
block2 = TPaveText(0.295, 0.82, 0.317, 0.85, "brNDC")
#FOR n=3 only
block2.SetFillColor(0)
block2.Draw("plain")
if isExclusive:
c.Print("ST_Mul%d.pdf" % N)
c.Print("ST_Mul%d.png" % N)
else:
c.Print("ST_Mul%dup.pdf" % N)
c.Print("ST_Mul%dup.png" % N)
c.Update()
raw_input("Press Enter to continue...")