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check_bias.py
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check_bias.py
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#! /usr/bin/env python
###
### Macro for creating the exclusion limits plots from the combine outputs.
###
import os, sys, getopt
import copy
import time
import math
from array import array
from ROOT import gROOT, gRandom
from ROOT import TFile, TTree, TCut, TH1F, TH2F, TGraph, TGraph2D, TGraphErrors, TGraphAsymmErrors
from ROOT import TStyle, TCanvas, TPad
from ROOT import TLegend, TLatex, TText, TColor
#from DMPD.Heppy.tools.samples import *
from utils import *
from theoryXs import HVT, SSM
#from thdmXs import THDM
# Combine output
# 0 - Observed Limit
# 1 - Expected 2.5%
# 2 - Expected 16.0%
# 3 - Expected 50.0%
# 4 - Expected 84.0%
# 5 - Expected 97.5%
# 6 - Significance
# 7 - p-value
# 8 - Best fit r
# 9 - Best fit r down
#10 - Best fit r up
import optparse
usage = "usage: %prog [options]"
parser = optparse.OptionParser(usage)
parser.add_option("-y", "--year", action="store", type="string", dest="year",default="run2c")
parser.add_option("-M", "--isMC", action="store_true", default=False, dest="isMC")
parser.add_option("-c", "--category", action="store", type="string", dest="category", default="")
parser.add_option("-B", "--blind", action="store_true", default=False, dest="blind")
parser.add_option("-b", "--btagging", action="store", type="string", dest="btagging", default="medium")
parser.add_option("-A", "--Acceptance", action="store_true", default=False, dest="Acceptance")
(options, args) = parser.parse_args()
gStyle.SetOptStat(0)
gROOT.SetBatch(True)
luminosities = {'2016':35920., '2017':41530., '2018':59740., 'run2':137190.}
#HTOBB = 0.5824#0.577
ZPTOBB = 1.
LUMI = 35867
MAXIMUM = {'XVHsl' : 4500., 'XWHsl' : 4500., 'XZHsl' : 3500., 'bb':100}
BTAGGING = options.btagging
YEAR = options.year
ISMC = options.isMC
CATEGORY = options.category
INCLUDEACC = options.Acceptance
CAT_LABELS = {'bb': "2 b tag", 'bq': "1 b tag", 'mumu': "1 #mu"}
if YEAR not in ['2016', '2017', '2018', 'run2', 'run2c']:
print "unknown year:", YEAR
sys.exit()
if BTAGGING not in ['tight', 'medium', 'loose', 'semimedium']:
print "unknown btagging requirement:", BTAGGING
sys.exit()
if CATEGORY not in ['', 'bb', 'bq', 'mumu']:
print "unknown btagging category"
sys.exit()
if YEAR=='run2c':
YEAR='run2'
SY=True
print "Plotting the result from combine on separate years for run2..."
else:
SY=False
LUMI = luminosities[YEAR]
SIGNALS = range(1600, 8000+1, 100)
ACCEPTANCE = {}
for s in range(500,9000+1,100): ACCEPTANCE[s] = 0.405 ##FIXME could include mass dependent exact value FIXME
theoryLabel = {'B3' : "HVT model B (g_{V}=3)", 'A1' : "HVT model A (g_{V}=1)", "SSM" : "SSM Z'"}
theoryLineColor = {'B3' : 629, 'A1' : 616-3, "SSM" : 602}
theoryFillColor = {'B3' : 625, 'A1' : 616-7, 'SSM' : 856}
theoryFillStyle = {'B3' : 3002, 'A1' : 3013, 'SSM' : 3013}
pull0 = {1600: 20.,
1700: 15.,
1800: 10.,
1900: 15.,
2000: 15.,
2100: 3.,
2200: 15.,
2300: 8.,
2400: 8.,
2500: 3.,
2600: 8.,
2700: 10.,
2800: 10.,
2900: 5.,
3000: 8.,
3100: 10.,
3200: 15.,
3300: 3.,
3400: 10.,
3500: 5.,
3600: 15.,
3700: 5.,
3800: 3.,
3900: 1.,
4000: 1.,
4100: 1.,
4200: 10.,
4300: 8.,
4400: 8.,
4500: 15.,
4600: 8.,
4700: 3.,
4800: 3.,
4900: 3.,
5000: 3.,
5100: 1.,
5200: 3.,
5300: 5.,
5400: 5.,
5500: 10.,
5600: 1.,
5700: 5.,
5800: 1.,
5900: 1.,
6000: 15.,
6100: 1.,
6200: 5.,
6300: 1.,
6400: 3.,
6500: 3.,
6600: 5.,
6700: 10.,
6800: 3.,
6900: 10.,
7000: 5.,
7100: 10.,
7200: 8.,
7300: 8.,
7400: 3.,
7500: 10.,
7600: 3.,
7700: 1.,
7800: 3.,
7900: 15.,
8000: 8.}
def fillValues(filename):
val = {}
mass = []
for i, s in enumerate(SIGNALS):
try:
file = open(filename % s, 'r')
if file==None:
print "Signal", filename % s, "does not exist"
continue
val[s] = file.read().splitlines()
if len(val[s]) <= 1:
#signals.remove(s)
print "Signal", filename % s, "has no values"
continue
for i, f in enumerate(val[s]): val[s][i] = float(val[s][i])
if 'fullCls' in filename: val[1:5]=sorted(val[1:5])
if not s in mass: mass.append(s)
except:
print "File", filename % s, "does not exist"
pass
return mass, val
def limit():
method = ''
channel = "bb"
if INCLUDEACC:
particleP = "X"
else:
particleP = "Z'"
particle = 'b#bar{b}'
multF = ZPTOBB
THEORY = ['A1', 'B3']
if INCLUDEACC: THEORY.append('SSM')
suffix = "_"+BTAGGING
if ISMC: suffix += "_MC"
if SY: suffix += "_comb"
#if method=="cls": suffix="_CLs"
if INCLUDEACC: suffix+="_acc"
if SY:
filename = "./combine/limits/" + BTAGGING + "/combined_run2/"+ YEAR + "_M%d.txt"
else:
filename = "./combine/limits/" + BTAGGING + "/"+ YEAR + "_M%d.txt"
if CATEGORY!="":
if SY:
filename = filename.replace(BTAGGING + "/combined_run2/", BTAGGING + "/single_category/combined_run2/"+CATEGORY+"_")
else:
filename = filename.replace(BTAGGING + "/", BTAGGING + "/single_category/"+CATEGORY+"_")
suffix += "_"+CATEGORY
if ISMC: filename = filename.replace(".txt", "_MC.txt")
mass, val = fillValues(filename)
#print "mass =",mass
#print "val =", val
Obs0s = TGraph()
Exp0s = TGraph()
Exp1s = TGraphAsymmErrors()
Exp2s = TGraphAsymmErrors()
Sign = TGraph()
pVal = TGraph()
Best = TGraphAsymmErrors()
Theory = {}
for i, m in enumerate(mass):
if not m in val:
print "Key Error:", m, "not in value map"
continue
if INCLUDEACC:
acc_factor = ACCEPTANCE[m]
else:
acc_factor = 1.
n = Exp0s.GetN()
#print "m =", m, " --> fitted r / injected r = {:<7} / {:<7} = {:<5}".format(val[m][3], pull0[m], val[m][3]/pull0[m])
#print "m =", m, " --> central r = {:<5}".format(val[m][3])
print "m =", m, " --> 2.5 x central r = {:<5}".format(2.5*val[m][3])
#for t in THEORY:
# Theory[t] = TGraphAsymmErrors()
# Xs_dict = HVT[t]['Z']['XS'] if t!='SSM' else SSM['Z']
# for m in sorted(Xs_dict.keys()):
# if INCLUDEACC and t!='SSM':
# acc_factor = ACCEPTANCE[m]
# else:
# acc_factor = 1.
# if m < SIGNALS[0] or m > SIGNALS[-1]: continue
# #if m < mass[0] or m > mass[-1]: continue
# #if t!= 'SSM' and m>4500: continue ## I don't have the higher mass xs
# if m>4500: continue
# XsZ, XsZ_Up, XsZ_Down = 0., 0., 0.
# if t!='SSM':
# XsZ = 1000.*HVT[t]['Z']['XS'][m]*SSM["BrZ"][m] #assuming the same BR as the SSM Z' one
# XsZ_Up = XsZ*(1.+math.hypot(HVT[t]['Z']['QCD'][m][0]-1., HVT[t]['Z']['PDF'][m][0]-1.))
# XsZ_Down = XsZ*(1.-math.hypot(1.-HVT[t]['Z']['QCD'][m][0], 1.-HVT[t]['Z']['PDF'][m][0]))
# else:
# XsZ = 1000.*SSM['Z'][m]*SSM["BrZ"][m]
# XsZ_Up = XsZ*(1.+math.hypot(HVT['A1']['Z']['QCD'][m][0]-1., HVT['A1']['Z']['PDF'][m][0]-1.))
# XsZ_Down = XsZ*(1.-math.hypot(1.-HVT['A1']['Z']['QCD'][m][0], 1.-HVT['A1']['Z']['PDF'][m][0]))
#
# n = Theory[t].GetN()
# Theory[t].SetPoint(n, m, XsZ*acc_factor)
# Theory[t].SetPointError(n, 0., 0., (XsZ-XsZ_Down)*acc_factor, (XsZ_Up-XsZ)*acc_factor)
# Theory[t].SetLineColor(theoryLineColor[t])
# Theory[t].SetFillColor(theoryFillColor[t])
# Theory[t].SetFillStyle(theoryFillStyle[t])
# Theory[t].SetLineWidth(2)
# #Theory[t].SetLineStyle(7)
#Exp2s.SetLineWidth(2)
#Exp2s.SetLineStyle(1)
#Obs0s.SetLineWidth(3)
#Obs0s.SetMarkerStyle(0)
#Obs0s.SetLineColor(1)
#Exp0s.SetLineStyle(2)
#Exp0s.SetLineWidth(3)
#Exp1s.SetFillColor(417) #kGreen+1
#Exp1s.SetLineColor(417) #kGreen+1
#Exp2s.SetFillColor(800) #kOrange
#Exp2s.SetLineColor(800) #kOrange
#Exp2s.GetXaxis().SetTitle("m_{"+particleP+"} (GeV)")
#Exp2s.GetXaxis().SetTitleSize(Exp2s.GetXaxis().GetTitleSize()*1.25)
#Exp2s.GetXaxis().SetNoExponent(True)
#Exp2s.GetXaxis().SetMoreLogLabels(True)
#Exp2s.GetYaxis().SetTitle("#sigma("+particleP+") #bf{#it{#Beta}}("+particleP+" #rightarrow "+particle+"){} (fb)".format(" #times #Alpha" if INCLUDEACC else ""))
#Exp2s.GetYaxis().SetTitleOffset(1.5)
#Exp2s.GetYaxis().SetNoExponent(True)
#Exp2s.GetYaxis().SetMoreLogLabels()
#Sign.SetLineWidth(2)
#Sign.SetLineColor(629)
#Sign.GetXaxis().SetTitle("m_{"+particleP+"} (GeV)")
#Sign.GetXaxis().SetTitleSize(Sign.GetXaxis().GetTitleSize()*1.1)
#Sign.GetYaxis().SetTitle("Significance")
#pVal.SetLineWidth(2)
#pVal.SetLineColor(629)
#pVal.GetXaxis().SetTitle("m_{"+particleP+"} (GeV)")
#pVal.GetXaxis().SetTitleSize(pVal.GetXaxis().GetTitleSize()*1.1)
#pVal.GetYaxis().SetTitle("local p-Value")
#Best.SetLineWidth(2)
#Best.SetLineColor(629)
#Best.SetFillColor(629)
#Best.SetFillStyle(3003)
#Best.GetXaxis().SetTitle("m_{"+particleP+"} (GeV)")
#Best.GetXaxis().SetTitleSize(Best.GetXaxis().GetTitleSize()*1.1)
#Best.GetYaxis().SetTitle("Best Fit (pb)")
#c1 = TCanvas("c1", "Exclusion Limits", 800, 600)
#c1.cd()
##SetPad(c1.GetPad(0))
#c1.GetPad(0).SetTopMargin(0.06)
#c1.GetPad(0).SetRightMargin(0.05)
#c1.GetPad(0).SetLeftMargin(0.12)
#c1.GetPad(0).SetTicks(1, 1)
##c1.GetPad(0).SetGridx()
##c1.GetPad(0).SetGridy()
#c1.GetPad(0).SetLogy()
#Exp2s.Draw("A3")
#Exp1s.Draw("SAME, 3")
#for t in THEORY:
# Theory[t].Draw("SAME, L3")
# Theory[t].Draw("SAME, L3X0Y0")
#Exp0s.Draw("SAME, L")
#if not options.blind: Obs0s.Draw("SAME, L")
##setHistStyle(Exp2s)
#Exp2s.GetXaxis().SetTitleSize(0.050)
#Exp2s.GetYaxis().SetTitleSize(0.050)
#Exp2s.GetXaxis().SetLabelSize(0.045)
#Exp2s.GetYaxis().SetLabelSize(0.045)
#Exp2s.GetXaxis().SetTitleOffset(0.90)
#Exp2s.GetYaxis().SetTitleOffset(1.25)
#Exp2s.GetYaxis().SetMoreLogLabels(True)
#Exp2s.GetYaxis().SetNoExponent(True)
#if INCLUDEACC:
# Exp2s.GetYaxis().SetRangeUser(0.05, 5.e3)
#else:
# Exp2s.GetYaxis().SetRangeUser(0.1, 5.e3)
##else: Exp2s.GetYaxis().SetRangeUser(0.1, 1.e2)
##Exp2s.GetXaxis().SetRangeUser(mass[0], min(mass[-1], MAXIMUM[channel] if channel in MAXIMUM else 1.e6))
#Exp2s.GetXaxis().SetRangeUser(SIGNALS[0], SIGNALS[-1])
##drawAnalysis(channel)
#drawAnalysis("")
##drawRegion(channel, True)
#drawRegion("", True)
##drawCMS(LUMI, "Simulation Preliminary") #Preliminary
#if CATEGORY=="":
# #drawCMS(LUMI, "Work in Progress", suppressCMS=True)
# drawCMS(LUMI, "Preliminary")
# #drawCMS(LUMI, "", suppressCMS=True)
#else:
# #drawCMS(LUMI, "Work in Progress, "+CAT_LABELS[CATEGORY], suppressCMS=True)
# drawCMS(LUMI, "Preliminary "+CAT_LABELS[CATEGORY])
# #drawCMS(LUMI, CAT_LABELS[CATEGORY], suppressCMS=True)
## legend
#top = 0.9
#nitems = 4 + len(THEORY)
#leg = TLegend(0.55, top-nitems*0.3/5., 0.98, top)
##leg = TLegend(0.45, top-nitems*0.3/5., 0.98, top)
#leg.SetBorderSize(0)
#leg.SetFillStyle(0) #1001
#leg.SetFillColor(0)
#leg.SetHeader("95% CL upper limits")
#leg.AddEntry(Obs0s, "Observed", "l")
#leg.AddEntry(Exp0s, "Expected", "l")
#leg.AddEntry(Exp1s, "#pm 1 std. deviation", "f")
#leg.AddEntry(Exp2s, "#pm 2 std. deviation", "f")
#for t in THEORY: leg.AddEntry(Theory[t], theoryLabel[t], "fl")
#leg.Draw()
#latex = TLatex()
#latex.SetNDC()
#latex.SetTextSize(0.045)
#latex.SetTextFont(42)
##latex.DrawLatex(0.66, leg.GetY1()-0.045, particleP+" #rightarrow "+particle+"h")
#leg2 = TLegend(0.12, 0.225-2*0.25/5., 0.65, 0.225)
#leg2.SetBorderSize(0)
#leg2.SetFillStyle(0) #1001
#leg2.SetFillColor(0)
#c1.GetPad(0).RedrawAxis()
#leg2.Draw()
#if not options.blind: Obs0s.Draw("SAME, L")
#c1.GetPad(0).Update()
#if not gROOT.IsBatch(): raw_input("Press Enter to continue...")
#c1.Print("combine/plotsLimit/ExclusionLimits/"+YEAR+suffix+".png")
#c1.Print("combine/plotsLimit/ExclusionLimits/"+YEAR+suffix+".pdf")
#if 'ah' in channel or 'sl' in channel:
# c1.Print("combine/plotsLimit/ExclusionLimits/"+YEAR+suffix+".C")
# c1.Print("combine/plotsLimit/ExclusionLimits/"+YEAR+suffix+".root")
#for t in THEORY:
# print "Model", t, ":",
# for m in range(mass[0], mass[-1], 1):
# if not (Theory[t].Eval(m) > Obs0s.Eval(m)) == (Theory[t].Eval(m+1) > Obs0s.Eval(m+1)): print m,
# print ""
return ##FIXME
# ---------- Significance ----------
c2 = TCanvas("c2", "Significance", 800, 600)
c2.cd()
c2.GetPad(0).SetTopMargin(0.06)
c2.GetPad(0).SetRightMargin(0.05)
c2.GetPad(0).SetTicks(1, 1)
c2.GetPad(0).SetGridx()
c2.GetPad(0).SetGridy()
Sign.GetYaxis().SetRangeUser(0., 5.)
Sign.Draw("AL3")
drawCMS(LUMI, "Preliminary")
#drawCMS(LUMI, "Work in Progress", suppressCMS=True)
drawAnalysis(channel[1:3])
c2.Print("combine/plotsLimit/Significance/"+YEAR+suffix+".png")
c2.Print("combine/plotsLimit/Significance/"+YEAR+suffix+".pdf")
# c2.Print("plotsLimit/Significance/"+YEAR+suffix+".root")
# c2.Print("plotsLimit/Significance/"+YEAR+suffix+".C")
# ---------- p-Value ----------
c3 = TCanvas("c3", "p-Value", 800, 600)
c3.cd()
c3.GetPad(0).SetTopMargin(0.06)
c3.GetPad(0).SetRightMargin(0.05)
c3.GetPad(0).SetTicks(1, 1)
c3.GetPad(0).SetGridx()
c3.GetPad(0).SetGridy()
c3.GetPad(0).SetLogy()
pVal.Draw("AL3")
pVal.GetYaxis().SetRangeUser(2.e-7, 0.5)
ci = [1., 0.317310508, 0.045500264, 0.002699796, 0.00006334, 0.000000573303, 0.000000001973]
line = TLine()
line.SetLineColor(922)
line.SetLineStyle(7)
text = TLatex()
text.SetTextColor(922)
text.SetTextSize(0.025)
text.SetTextAlign(12)
for i in range(1, len(ci)-1):
line.DrawLine(pVal.GetXaxis().GetXmin(), ci[i]/2, pVal.GetXaxis().GetXmax(), ci[i]/2);
text.DrawLatex(pVal.GetXaxis().GetXmax()*1.01, ci[i]/2, "%d #sigma" % i);
drawCMS(LUMI, "Preliminary")
#drawCMS(LUMI, "Work in Progress", suppressCMS=True)
drawAnalysis(channel[1:3])
c3.Print("combine/plotsLimit/pValue/"+YEAR+suffix+".png")
c3.Print("combine/plotsLimit/pValue/"+YEAR+suffix+".pdf")
# c3.Print("plotsLimit/pValue/"+YEAR+suffix+".root")
# c3.Print("plotsLimit/pValue/"+YEAR+suffix+".C")
# --------- Best Fit ----------
c4 = TCanvas("c4", "Best Fit", 800, 600)
c4.cd()
c4.GetPad(0).SetTopMargin(0.06)
c4.GetPad(0).SetRightMargin(0.05)
c4.GetPad(0).SetTicks(1, 1)
c4.GetPad(0).SetGridx()
c4.GetPad(0).SetGridy()
Best.Draw("AL3")
drawCMS(LUMI, "Preliminary")
#drawCMS(LUMI, "Work in Progress", suppressCMS=True)
drawAnalysis(channel[1:3])
c4.Print("combine/plotsLimit/BestFit/"+YEAR+suffix+".png")
c4.Print("combine/plotsLimit/BestFit/"+YEAR+suffix+".pdf")
# c4.Print("plotsLimit/BestFit/"+YEAR+suffix+".root")
# c4.Print("plotsLimit/BestFit/"+YEAR+suffix+".C")
if not gROOT.IsBatch(): raw_input("Press Enter to continue...")
if 'ah' in channel:
outFile = TFile("bands.root", "RECREATE")
outFile.cd()
pVal.Write("graph")
Best.Write("best")
outFile.Close()
def limit2HDM():
global signals
signals = range(800, 2000+1, 50)
multF = HTOBB
THEORY = ['T1', 'T2']
mass, val = fillValues("./combine/AZh/AZh_M%d.txt")
Obs0s = TGraph()
Exp0s = TGraph()
Exp1s = TGraphAsymmErrors()
Exp2s = TGraphAsymmErrors()
massB, valB = fillValues("./combine/BBAZh/BBAZh_M%d.txt")
Obs0sB = TGraph()
Exp0sB = TGraph()
Exp1sB = TGraphAsymmErrors()
Exp2sB = TGraphAsymmErrors()
for i, m in enumerate(mass):
if not m in val:
print "Key Error:", m, "not in value map"
continue
n = Exp0s.GetN()
Obs0s.SetPoint(n, m, val[m][0]*multF)
Exp0s.SetPoint(n, m, val[m][3]*multF)
Exp1s.SetPoint(n, m, val[m][3]*multF)
Exp1s.SetPointError(n, 0., 0., val[m][3]*multF-val[m][2]*multF, val[m][4]*multF-val[m][3]*multF)
Exp2s.SetPoint(n, m, val[m][3]*multF)
Exp2s.SetPointError(n, 0., 0., val[m][3]*multF-val[m][1]*multF, val[m][5]*multF-val[m][3]*multF)
Obs0sB.SetPoint(n, m, valB[m][0]*multF)
Exp0sB.SetPoint(n, m, valB[m][3]*multF)
Exp1sB.SetPoint(n, m, valB[m][3]*multF)
Exp1sB.SetPointError(n, 0., 0., valB[m][3]*multF-valB[m][2]*multF, valB[m][4]*multF-valB[m][3]*multF)
Exp2sB.SetPoint(n, m, valB[m][3]*multF)
Exp2sB.SetPointError(n, 0., 0., valB[m][3]*multF-valB[m][1]*multF, valB[m][5]*multF-valB[m][3]*multF)
col = 629
Exp2s.SetLineWidth(2)
Exp2s.SetLineStyle(1)
Obs0s.SetLineWidth(3)
Obs0s.SetMarkerStyle(0)
Obs0s.SetLineColor(1)
Exp0s.SetLineStyle(2)
Exp0s.SetLineWidth(3)
Exp0s.SetLineColor(1)
# Exp1s.SetFillColorAlpha(col, 0.4) #kGreen+1
# Exp1s.SetLineColorAlpha(col, 0.4)
# Exp2s.SetFillColorAlpha(col, 0.2) #kOrange
# Exp2s.SetLineColorAlpha(col, 0.2)
Exp1s.SetFillColor(417)
Exp1s.SetLineColor(417)
Exp2s.SetFillColor(800)
Exp2s.SetLineColor(800)
colB = 922
Exp2sB.SetLineWidth(2)
Obs0sB.SetLineStyle(9)
Obs0sB.SetLineWidth(3)
Obs0sB.SetMarkerStyle(0)
Obs0sB.SetLineColor(colB)
Exp0sB.SetLineStyle(8)
Exp0sB.SetLineWidth(3)
Exp0sB.SetLineColor(colB)
Exp1sB.SetFillColorAlpha(colB, 0.4) #kGreen+1
Exp1sB.SetLineColorAlpha(colB, 0.4)
Exp2sB.SetFillColorAlpha(colB, 0.2) #kOrange
Exp2sB.SetLineColorAlpha(colB, 0.2)
Exp2s.GetXaxis().SetTitle("m_{A} (GeV)")
Exp2s.GetXaxis().SetTitleSize(Exp2s.GetXaxis().GetTitleSize()*1.25)
Exp2s.GetXaxis().SetNoExponent(True)
Exp2s.GetXaxis().SetMoreLogLabels(True)
Exp2s.GetYaxis().SetTitle("#sigma(A) #bf{#it{#Beta}}(A #rightarrow Zh) #bf{#it{#Beta}}(h #rightarrow bb) (fb)")
Exp2s.GetYaxis().SetTitleOffset(1.5)
Exp2s.GetYaxis().SetNoExponent(True)
Exp2s.GetYaxis().SetMoreLogLabels()
Theory = {}
#for t in THEORY:
# Theory[t] = TGraphAsymmErrors()
# for m in sorted(THDM[t]['ggA'].keys()):
# if m < mass[0] or m > mass[-1]: continue
# Xs, Xs_Up, Xs_Down = 0., 0., 0.
# Xs = THDM[t]['ggA'][m]
# Xs_Up = Xs*(1.+math.sqrt((THDM['PDF']['ggA'][m][0]-1.)**2 + (THDM['QCD']['ggA'][m][0]-1.)**2))
# Xs_Down = Xs*(1.-math.sqrt((1.-THDM['PDF']['ggA'][m][1])**2 + (1.-THDM['QCD']['ggA'][m][1])**2))
# n = Theory[t].GetN()
# Theory[t].SetPoint(n, m, Xs)
# Theory[t].SetPointError(n, 0., 0., (Xs-Xs_Down), (Xs_Up-Xs))
# Theory[t].SetLineColor(theoryLineColor[t])
# Theory[t].SetFillColor(theoryFillColor[t])
# Theory[t].SetFillStyle(theoryFillStyle[t])
# Theory[t].SetLineWidth(2)
# #Theory[t].SetLineStyle(7)
c1 = TCanvas("c1", "Exclusion Limits", 800, 600)
c1.cd()
#SetPad(c1.GetPad(0))
c1.GetPad(0).SetTopMargin(0.06)
c1.GetPad(0).SetRightMargin(0.05)
c1.GetPad(0).SetLeftMargin(0.12)
c1.GetPad(0).SetTicks(1, 1)
c1.GetPad(0).SetLogy()
Exp2s.Draw("A3")
Exp1s.Draw("SAME, 3")
Exp0s.Draw("SAME, L")
# Exp2sB.Draw("SAME, 3")
# Exp1sB.Draw("SAME, 3")
Exp0sB.Draw("SAME, L")
if not options.blind:
Obs0s.Draw("SAME, L")
Obs0sB.Draw("SAME, L")
for t in THEORY:
Theory[t].Draw("SAME, L3")
Theory[t].Draw("SAME, L3X0Y0")
#setHistStyle(Exp2s)
# Exp2s.GetXaxis().SetTitleSize(0.045)
# Exp2s.GetYaxis().SetTitleSize(0.04)
# Exp2s.GetXaxis().SetLabelSize(0.04)
# Exp2s.GetYaxis().SetLabelSize(0.04)
# Exp2s.GetXaxis().SetTitleOffset(1)
# Exp2s.GetYaxis().SetTitleOffset(1.25)
Exp2s.GetXaxis().SetTitleSize(0.050)
Exp2s.GetYaxis().SetTitleSize(0.050)
Exp2s.GetXaxis().SetLabelSize(0.045)
Exp2s.GetYaxis().SetLabelSize(0.045)
Exp2s.GetXaxis().SetTitleOffset(0.90)
Exp2s.GetYaxis().SetTitleOffset(1.25)
Exp2s.GetYaxis().SetMoreLogLabels(True)
Exp2s.GetYaxis().SetNoExponent(True)
Exp2s.GetYaxis().SetRangeUser(0.5, 1.e3)
Exp2s.GetXaxis().SetRangeUser(mass[0], mass[-1])
drawAnalysis('AZh')
drawRegion('AZHsl', True)
drawCMS(LUMI, "") #Preliminary
#drawCMS(LUMI, "Work in Progress", suppressCMS=True)
# legend
leg = TLegend(0.6, 0.90, 0.99, 0.90)
leg.SetBorderSize(0)
leg.SetFillStyle(0) #1001
leg.SetFillColor(0)
leg.SetHeader("95% CL upper limits")
leg.AddEntry(None, "gg #rightarrow A #rightarrow Zh", "") #"95% CL upper limits"
leg.AddEntry(Obs0s, "Observed", "l")
leg.AddEntry(Exp0s, "Expected", "l")
leg.AddEntry(Exp1s, "#pm 1 std. deviation", "f")
leg.AddEntry(Exp2s, "#pm 2 std. deviation", "f")
leg.AddEntry(None, "", "")
leg.AddEntry(None, "bbA #rightarrow Zh", "")
leg.AddEntry(Obs0sB, "Observed", "l")
leg.AddEntry(Exp0sB, "Expected", "l")
leg.SetY1(leg.GetY2()-leg.GetNRows()*0.045)
leg.Draw()
# latex = TLatex()
# latex.SetNDC()
# latex.SetTextSize(0.040)
# latex.SetTextFont(42)
# latex.DrawLatex(0.65, leg.GetY1()-0.045, "cos(#beta-#alpha)=0.25, tan(#beta)=1")
# legB = TLegend(0.12, 0.4-4*0.3/5., 0.65, 0.4)
legB = TLegend(0.15, 0.27, 0.68, 0.27)
legB.SetBorderSize(0)
legB.SetFillStyle(0) #1001
legB.SetFillColor(0)
for t in THEORY: legB.AddEntry(Theory[t], theoryLabel[t], "fl")
legB.AddEntry(None, "cos(#beta-#alpha)=0.25, tan(#beta)=1", "")
legB.SetY1(legB.GetY2()-legB.GetNRows()*0.045)
legB.Draw()
c1.GetPad(0).RedrawAxis()
leg.Draw()
c1.Update()
if not gROOT.IsBatch(): raw_input("Press Enter to continue...")
c1.Print("plotsLimit/Exclusion/THDM.png")
c1.Print("plotsLimit/Exclusion/THDM.pdf")
def limitCompare(method):
signal, particle, particleP = "XVH", "V", "V'"
channels = ["ah", "wrhpbb", "wrhpb", "wrlpbb", "wrlpb", "zrhpbb", "zrhpb", "zrlpbb", "zrlpb"]
colors = [1, 610+4, 632, 800+7, 800, 416+1, 860+10, 600, 616, 921, 922]
masses, vals, graphs = {}, {}, {}
for j, c in enumerate(channels):
masses[c], vals[c] = fillValues("./combine/" + method + "/"+signal+c+"_M%d.txt")
graphs[c] = TGraph()
n = 0
#print vals[c]
for i, m in enumerate(masses[c]):
#if not signals[i] >= 1000: continue
graphs[c].SetPoint(n, m, vals[c][m][3])
n = n + 1
graphs[c].SetLineColor(colors[j])
graphs[c].SetLineWidth(3)
graphs[c].Draw("SAME, L")
c1 = TCanvas("c1", "Exclusion Limits", 800, 600)
c1.cd()
#SetPad(c1.GetPad(0))
c1.GetPad(0).SetTopMargin(0.06)
c1.GetPad(0).SetRightMargin(0.05)
c1.GetPad(0).SetTicks(1, 1)
c1.GetPad(0).SetLogy()
for c in channels:
graphs[c].Draw("AL" if 'ah' in c else "SAME, L")
graphs[channels[0]].GetXaxis().SetRangeUser(SIGNALS[0], SIGNALS[-1])
graphs[channels[0]].GetYaxis().SetRangeUser(0.25, 2.5e4)
graphs[channels[0]].GetXaxis().SetTitle("m_{"+particleP+"} (GeV)")
graphs[channels[0]].GetYaxis().SetTitle("#sigma("+particleP+") #bf{#it{#Beta}}("+particleP+" #rightarrow "+particle+"H) #bf{#it{#Beta}}(H #rightarrow bb) (fb)")
drawAnalysis(signal)
#drawRegion(signal, True)
drawCMS(LUMI, "Preliminary")
#drawCMS(LUMI, "Work in Progress", suppressCMS=True)
# legend
top = 0.9
leg = TLegend(0.4, top-len(channels)*0.2/5., 0.99, top)
leg.SetBorderSize(0)
leg.SetFillStyle(0) #1001
leg.SetFillColor(0)
leg.SetHeader("95% CL expected limits")
for c in channels:
leg.AddEntry(graphs[c], getChannel(c), "l")
leg.Draw()
c1.Update()
c1.Print("plotsLimit/Multi.png")
c1.Print("plotsLimit/Multi.pdf")
if __name__ == "__main__":
limit()