def main():
#if 1 > 0 :
# declare the 2D ===> should be global variable
model = NonResonantModel()
# obtaining BSM/SM coeficients
#dumb = model.ReadCoefficients("../data/coefficientsByBin_A1A3A7.txt")
dumb = model.ReadCoefficients("../data/coefficientsByBin_extended_3M_costHHSim_19-4.txt")
#dumb = model.ReadCoefficients("../data/coefficientsByBin_extended_3M.txt")
counteventSM=0
sumWeight=0
# now loop over events, calculate weights using the coeffitients and plot histograms
# We sum SM + box + the benchmarks from 2-13
# read the 2D histo referent to the sum of events
#fileHH=ROOT.TFile("../../../Analysis/Support/NonResonant/Hist2DSum_V0_SM_box.root")
#sumHAnalyticalBin = fileHH.Get("SumV0_AnalyticalBin")
histfilename="../../../Analysis/Support/NonResonant/HistSum2D_4b_rebin_SimCostHH_19-4.root"
#histtitle= "SumV0_AnalyticalBinExt" #
histtitle= "SumV0_AnalyticalBinExtSimCostHH" #
fileHH=ROOT.TFile(histfilename)
sumHAnalyticalBin = fileHH.Get(histtitle)
calcSumOfWeights = model.getNormalization(kl, kt,c2,cg,c2g,histfilename,histtitle) # this input is flexible, tatabb may have only the SM
# print "sum of weights calculated" , calcSumOfWeights
# read the events
pathBenchEvents="/eos/user/a/acarvalh/asciiHH_tofit/GF_HH_BSM/" #"/eos/user/a/acarvalh/asciiHH_tofit/GF_HH_BSM/" # events to reweight
file=ROOT.TFile(pathBenchEvents+"events_SumV0.root")
tree=file.Get("treeout")
nev = tree.GetEntries()
# declare the histograms
CalcMhh = np.zeros((nev))
CalcCost = np.zeros((nev))
CalcPtH = np.zeros((nev))
CalcPtHH = np.zeros((nev))
CalcWeight = np.zeros((nev))
CalcPtHgg = np.zeros((nev))
CalcMhhReco = np.zeros((nev))
CalcMXReco = np.zeros((nev))
countevent = 0
#for kll in range(-5,5) : model.getNormalization(kll, kt,sumHBenchBin)
for iev in range(0,nev) :
tree.GetEntry(iev)
mhh = tree.Genmhh
cost = tree.GenHHCost
mhhcost= [mhh,cost,0,0] # to store [mhh , cost] of that event
# find the Nevents from the sum of events on that bin
bmhh = sumHAnalyticalBin.GetXaxis().FindBin(mhh)
bcost = sumHAnalyticalBin.GetYaxis().FindBin(abs(cost))
#print (tree.GenHHCost,cost,bcost)
effSumV0 = sumHAnalyticalBin.GetBinContent(bmhh,abs(bcost)) # quantity of simulated events in that bin (without cuts)
weight = model.getScaleFactor(mhh , cost,kl, kt,c2,cg,c2g, effSumV0 , calcSumOfWeights) # model.effSM,model.MHH,model.COSTS,model.A1,model.A3,model.A7, effSumV0)
#############################################
# fill histograms to test
#############################################
if weight > 0:
#print countevent
CalcMhh[countevent] = float(mhhcost[0])
CalcCost[countevent] = float(abs(mhhcost[1]))
CalcPtH[countevent] = float(mhhcost[2])
CalcPtHH[countevent] = float(mhhcost[3])
CalcWeight[countevent] = weight
countevent+=1
sumWeight+=weight
print "plotted histogram reweighted from ",countevent," events, ", float(100*(nev-countevent)/nev)," % of the events was lost in empty bins in SM simulation"
print "sum of weights",sumWeight
############################################################################################################################
# Draw test histos
###############################################
drawtest =0
nevtest=50000
if kl == 1 and kt == 1 and c2 ==0 and cg == 0 and c2g ==0 :
filne = "/eos/user/a/acarvalh/asciiHH_tofit/GF_HH_BSM/GF_HH_0.lhe.decayed" # 0 is SM
nevtest = 100000
drawtest = 1
# BSM events
pathBSMtest="/afs/cern.ch/work/a/acarvalh/generateHH/asciiHH_tofit/GF_HH_toRecursive/" # events of file to superimpose a test
# see the translation of coefficients for this last on: If you make this script smarter (to only read files we ask to test) you can implement more
# https://github.com/acarvalh/generateHH/blob/master/fit_GF_HH_lhe/tableToFitA3andA7.txt
if kl == -10 and kt == 0.5 and c2 ==0 and cg == 0 and c2g ==0 :
drawtest =1
filne = pathBSMtest+"GF_HH_42.lhe.decayed"
if kl == 0.0001 and kt == 2.25 and c2 ==0 and cg == 0 and c2g ==0 :
drawtest =1
filne = pathBSMtest+"GF_HH_9.lhe.decayed"
if kl == 2.5 and kt == 1.0 and c2 ==0 and cg == 0 and c2g ==0 :
drawtest =1
filne = pathBSMtest+"GF_HH_60.lhe.decayed"
klJHEP=[1.0, 7.5, 1.0, 1.0, -3.5, 1.0, 2.4, 5.0, 15.0, 1.0, 10.0, 2.4, 15.0]
ktJHEP=[1.0, 1.0, 1.0, 1.0, 1.5, 1.0, 1.0, 1.0, 1.0, 1.0, 1.5, 1.0, 1.0]
c2JHEP=[0.0, -1.0, 0.5, -1.5, -3.0, 0.0, 0.0, 0.0, 0.0, 1.0, -1.0, 0.0, 1.0]
cgJHEP=[0.0, 0.0, 0.6, 0.0, 0.0, 0.8, 0.2, 0.2, -1.0, -0.6, 0.0, 1.0, 0.0]
c2gJHEP=[0.0, 0.0, 1.0, -0.8, 0.0, -1.0, -0.2,-0.2, 1.0, 0.6, 0.0, -1.0, 0.0]
# python recastHH.py --kl 7.5 --kt 1 --c2 -1
# python recastHH.py --kl 1.0 --kt 1.0 --c2 0.5 --cg -0.8 --c2g 0.6
# python recastHH.py --kl 1.0 --kt 1.0 --c2 -1.5 --cg 0.0 --c2g -0.8
# python recastHH.py --kl 1.0 --kt 1.0 --c2 0.0 --cg 0.8 --c2g -1.0
# python recastHH.py --kl 1.0 --kt 1.0 --c2 1.0 --cg -0.6 --c2g 0.6
for sam in range(0,13):
#print (sam, ktJHEP[sam] , kt , klJHEP[sam] , c2 ,c2JHEP[sam] , cg , cgJHEP[sam] , c2g , c2gJHEP[sam])
if kl == klJHEP[sam] and kt == ktJHEP[sam] and c2 ==c2JHEP[sam] and cg == cgJHEP[sam] and c2g ==c2gJHEP[sam] :
print sam
filne="/eos/user/a/acarvalh/asciiHH_tofit/GF_HH_BSM/GF_HH_"+str(sam)+".lhe.decayed"
nevtest=100000
drawtest = sam
############################################################################################################################
CalcMhhTest = np.zeros((nevtest))
CalcCostTest = np.zeros((nevtest))
CalcPtHTest = np.zeros((nevtest))
CalcPtHHTest = np.zeros((nevtest))
CalcPtHggTest = np.zeros((nevtest))
CalcMhhRecoTest = np.zeros((nevtest))
CalcMXRecoTest = np.zeros((nevtest))
if options.doPlot :
print "draw plain histogram to test"
model.LoadTestEvents(CalcMhhTest,CalcCostTest,CalcPtHTest,CalcPtHHTest,filne)
model.plotting(kl,kt,c2,cg,c2g,CalcMhh,CalcCost,CalcPtHgg,CalcPtHH,CalcMhhReco,CalcMXReco,CalcWeight,CalcMhhTest,CalcCostTest,CalcPtHggTest,CalcPtHHTest,CalcMhhRecoTest,CalcMXRecoTest,drawtest)
def main():
model = NonResonantModel()
# obtaining BSM/SM coeficients
#dumb = model.ReadCoefficients("../data/coefficientsByBin_A1A3A7.txt")
#dumb = model.ReadCoefficients("../data/coefficientsByBin_extended_3M.txt")
dumb = model.ReadCoefficients(
"../data/coefficientsByBin_extended_3M_costHHSim_19-4.txt")
# We sum SM + box + the benchmarks from 2-13
# read the 2D histo referent to the sum of events
"""
fileHH=ROOT.TFile("../../../Support/NonResonant/Distros_5p_SM3M_sumBenchJHEP_13TeV.root")
sumJHEPAnalyticalBin = fileHH.Get("H1bin2")
SMAnalyticalBin = fileHH.Get("H0bin2")
"""
fileHH = ROOT.TFile(
"../../../Analysis/Support/NonResonant/Distros_5p_SM3M_sumBenchJHEP_13TeV_19-4.root"
) #Distros_5p_SM3M_sumBenchJHEP_13TeV.root") #Distros_5p_SM3M_rebin_sumBenchJHEP_5D_13TeV.root") #
#fileHH=ROOT.TFile("../../../Analysis/Support/NonResonant/Distros_5p_SM3M_rebin_sumBenchJHEP_5D_13TeV.root")
#sumJHEPAnalyticalBin = fileHH.Get("H1bin3")
histfile = "../../../Analysis/Support/NonResonant/Distros_5p_SM3M_sumBenchJHEP_13TeV_19-4.root" #Distros_5p_SM3M_sumBenchJHEP_13TeV.root" # #Distros_5p_SM3M_rebin_sumBenchJHEP_5D_13TeV.root"
#histfile = "../../../Analysis/Support/NonResonant/Distros_5p_SM3M_rebin_sumBenchJHEP_5D_13TeV.root"
histtitle = "H1bin4"
sumJHEPAnalyticalBin = fileHH.Get(histtitle)
SMAnalyticalBin = fileHH.Get("H0bin4")
#fileHHname = "../../../Analysis/Support/NonResonant/Distros_5p_SM3M_rebin_sumBenchJHEP_5D_13TeV.root"
calcSumOfWeights = model.getNormalization(
kl, kt, c2, cg, c2g, histfile,
histtitle) # this input is flexible, tatabb may have only the SM
#print ("normalization is: ",calcSumOfWeights)
#xaxis = sumJHEPAnalyticalBin.GetXaxis()
#yaxis = sumJHEPAnalyticalBin.GetYaxis()
#print "Sum hist ",sumJHEPAnalyticalBin.GetNbinsX(),sumJHEPAnalyticalBin.GetNbinsY(),sumJHEPAnalyticalBin.Integral(),sumJHEPAnalyticalBin.GetXaxis().GetBinLowEdge(1),sumJHEPAnalyticalBin.GetXaxis().GetBinUpEdge(xaxis.GetNbins())
#print SMAnalyticalBin.GetBinContent(4,4)
# now loop over events, calculate weights using the coeffitients and plot histograms
# events to reweights, in text format (for testing only)
pathBenchEvents = "/eos/user/a/acarvalh/asciiHH_tofit/GF_HH_BSM/" # events to reweight
# declare the histograms
CalcMhh = np.zeros((1200000))
CalcCost = np.zeros((1200000))
CalcPtH = np.zeros((1200000))
CalcPtHgg = np.zeros((1200000))
CalcPtHH = np.zeros((1200000))
CalcWeight = np.zeros((1200000))
CalcMhhReco = np.zeros((1200000))
CalcMXReco = np.zeros((1200000))
##########################################
# initialize tables of coefficients by bins
# calculate mhh and cost* and find the bin
# initialize events reading
countline = 0
countevent = 0
counteventSM = 0
# read events as text files for events to test
# particuliarity of the text file with events = each 2 lines are one event there
# save the information of the two Higgses
Px = np.zeros((2))
Py = np.zeros((2))
Pz = np.zeros((2))
En = np.zeros((2))
for sam in range(1, 13): # read events from the list of 12 benchmarks
filne = pathBenchEvents + "GF_HH_" + str(
sam
) + ".lhe.decayed" # 0 is SM = here it does not enter in the events to be reweighted in this version
f = open(filne, 'r+')
lines = f.readlines() # get all lines as a list (array)
countline = 0 # particuliarity of the text file with events = each 2 lines are one event there
for line in lines:
model.ReadLine(line, countline, Px, Py, Pz, En)
#print countline
countline += 1
mhhcost = [0, 0, 0,
0] # to store [mhh , cost,ptH , ptHH] of that event
if countline == 2: # if read 2 lines
model.CalculateMhhCost(mhhcost, countline, Px, Py, Pz,
En) # ==> adapt to your input
bmhh = sumJHEPAnalyticalBin.GetXaxis().FindBin(mhhcost[0])
bcost = sumJHEPAnalyticalBin.GetYaxis().FindBin(abs(
mhhcost[1]))
#print (mhhcost[1],bcost)
effSumV0 = sumJHEPAnalyticalBin.GetBinContent(
bmhh, bcost
) # quantity of simulated events in that bin (without cuts)
#weight = model.getScaleFactor(mhhcost,kl, kt,0,model.effSM,model.effSum,model.MHH,model.COSTS,model.A1,model.A3,model.A7,0)
#print mhhcost[1],bcost
#print effSumV0
weight = model.getScaleFactor(mhhcost[0], mhhcost[1], kl, kt,
c2, cg, c2g, effSumV0,
calcSumOfWeights)
countline = 0
#############################################
# fill histograms
#############################################
if weight > 0:
#print countevent
CalcMhh[countevent] = float(mhhcost[0])
CalcCost[countevent] = float(mhhcost[1])
CalcPtH[countevent] = float(mhhcost[2])
CalcPtHH[countevent] = float(mhhcost[3])
CalcWeight[countevent] = weight
countevent += 1
#else : print ("neg weight ",weight,mhhcost[0],mhhcost[1],bmhh,bcost,kl, kt,c2,cg,c2g,effSumV0,calcSumOfWeights)
f.close()
print "plotted hostogram reweighted from ", countevent, " events, ", float(
100 * (1200000 - countevent) /
1200000), " % of the events was lost in empty bins in SM simulation"
print kl, kt, c2, cg, c2g, "Sum of weights:", CalcWeight.sum(
), " correction ", calcSumOfWeights
############################################################################################################################
# Draw test histos
###############################################
drawtest = -1
nevtest = 50000
#if kl == 1 and kt == 1 and c2 ==0 and cg == 0 and c2g ==0 :
# filne = pathBenchEvents+"GF_HH_0.lhe.decayed" # 0 is SM
# nevtest = 100000
# drawtest = 1
# BSM events
pathBSMtest = "/afs/cern.ch/work/a/acarvalh/generateHH/asciiHH_tofit/GF_HH_toRecursive/" # events of file to superimpose a test
# see the translation of coefficients for this last on: If you make this script smarter (to only read files we ask to test) you can implement more
# https://github.com/acarvalh/generateHH/blob/master/fit_GF_HH_lhe/tableToFitA3andA7.txt
if kl == -10 and kt == 0.5 and c2 == 0 and cg == 0 and c2g == 0:
drawtest = 1
filne = pathBSMtest + "GF_HH_42.lhe.decayed"
if kl == 0.0001 and kt == 2.25 and c2 == 0 and cg == 0 and c2g == 0:
drawtest = 1
filne = pathBSMtest + "GF_HH_9.lhe.decayed"
if kl == 0.0001 and kt == 1.0 and c2 == 0 and cg == 0 and c2g == 0:
drawtest = 1
filne = pathBSMtest + "GF_HH_4.lhe.decayed"
if kl == 2.5 and kt == 1.0 and c2 == 0 and cg == 0 and c2g == 0:
drawtest = 1
filne = pathBSMtest + "GF_HH_60.lhe.decayed"
if kl == -15 and kt == 0.5 and c2 == 0 and cg == 0 and c2g == 0:
drawtest = 1
filne = pathBSMtest + "GF_HH_40.lhe.decayed"
if kl == 5 and kt == 1.5 and c2 == 0 and cg == 0 and c2g == 0:
drawtest = 1
filne = pathBSMtest + "GF_HH_74.lhe.decayed"
if kl == 7.5 and kt == 2.0 and c2 == 0 and cg == 0 and c2g == 0:
drawtest = 1
filne = pathBSMtest + "GF_HH_88.lhe.decayed"
if kl == 0.0001 and kt == 0.0001 and c2 == -3.0 and cg == 0.0 and c2g == -1.5:
drawtest = 1
filne = pathBSMtest + "GF_HH_281.lhe.decayed"
if kl == -10 and kt == 0.0 and c2 == 1.0 and cg == 1.0 and c2g == 1.0:
drawtest = 1
filne = pathBSMtest + "GF_HH_280.lhe.decayed"
#########################################################
klJHEP = [
1.0, 7.5, 1.0, 1.0, -3.5, 1.0, 2.4, 5.0, 15.0, 1.0, 10.0, 2.4, 15.0
]
ktJHEP = [1.0, 1.0, 1.0, 1.0, 1.5, 1.0, 1.0, 1.0, 1.0, 1.0, 1.5, 1.0, 1.0]
c2JHEP = [
0.0, -1.0, 0.5, -1.5, -3.0, 0.0, 0.0, 0.0, 0.0, 1.0, -1.0, 0.0, 1.0
]
cgJHEP = [
0.0, 0.0, 0.6, 0.0, 0.0, 0.8, 0.2, 0.2, -1.0, -0.6, 0.0, 1.0, 0.0
]
c2gJHEP = [
0.0, 0.0, 1.0, -0.8, 0.0, -1.0, -0.2, -0.2, 1.0, 0.6, 0.0, -1.0, 0.0
]
# python recastHH.py --kl 7.5 --kt 1 --c2 -1
# python recastHH.py --kl 1.0 --kt 1.0 --c2 0.5 --cg -0.8 --c2g 0.6
# python recastHH.py --kl 1.0 --kt 1.0 --c2 -1.5 --cg 0.0 --c2g -0.8
# python recastHH.py --kl 1.0 --kt 1.0 --c2 0.0 --cg 0.8 --c2g -1.0
# python recastHH.py --kl 1.0 --kt 1.0 --c2 1.0 --cg -0.6 --c2g 0.6
for sam in range(0, 13):
#print (sam, ktJHEP[sam] , kt , klJHEP[sam] , c2 ,c2JHEP[sam] , cg , cgJHEP[sam] , c2g , c2gJHEP[sam])
if kl == klJHEP[sam] and kt == ktJHEP[sam] and c2 == c2JHEP[
sam] and cg == cgJHEP[sam] and c2g == c2gJHEP[sam]:
print sam
filne = "/eos/user/a/acarvalh/asciiHH_tofit/GF_HH_BSM/GF_HH_" + str(
sam) + ".lhe.decayed"
nevtest = 100000
drawtest = sam
############################################################################################################################
CalcMhhTest = np.zeros((nevtest))
CalcCostTest = np.zeros((nevtest))
CalcPtHTest = np.zeros((nevtest))
CalcPtHHTest = np.zeros((nevtest))
CalcPtHggTest = np.zeros((nevtest))
CalcMhhRecoTest = np.zeros((nevtest))
CalcMXRecoTest = np.zeros((nevtest))
if options.doPlot and drawtest > 0:
print "draw plain histogram to test"
model.LoadTestEvents(CalcMhhTest, CalcCostTest, CalcPtHTest,
CalcPtHHTest, filne)
model.plotting(kl, kt, c2, cg, c2g, CalcMhh, CalcCost, CalcPtHgg, CalcPtHH,
CalcMhhReco, CalcMXReco, CalcWeight, CalcMhhTest,
CalcCostTest, CalcPtHggTest, CalcPtHHTest, CalcMhhRecoTest,
CalcMXRecoTest, drawtest)
def main():
#if 1 > 0 :
# declare the 2D ===> should be global variable
model = NonResonantModel()
# obtaining BSM/SM coeficients
#dumb = model.ReadCoefficients("../data/coefficientsByBin_A1A3A7.txt")
dumb = model.ReadCoefficients(
"../data/coefficientsByBin_extended_3M_costHHSim_19-4.txt")
#dumb = model.ReadCoefficients("../data/coefficientsByBin_extended_3M.txt")
counteventSM = 0
sumWeight = 0
# now loop over events, calculate weights using the coeffitients and plot histograms
# We sum SM + box + the benchmarks from 2-13
# read the 2D histo referent to the sum of events
#fileHH=ROOT.TFile("../../../Analysis/Support/NonResonant/Hist2DSum_V0_SM_box.root")
#sumHAnalyticalBin = fileHH.Get("SumV0_AnalyticalBin")
histfilename = "../../../Analysis/Support/NonResonant/HistSum2D_4b_rebin_SimCostHH_19-4.root"
#histtitle= "SumV0_AnalyticalBinExt" #
histtitle = "SumV0_AnalyticalBinExtSimCostHH" #
fileHH = ROOT.TFile(histfilename)
sumHAnalyticalBin = fileHH.Get(histtitle)
calcSumOfWeights = model.getNormalization(
kl, kt, c2, cg, c2g, histfilename,
histtitle) # this input is flexible, tatabb may have only the SM
# print "sum of weights calculated" , calcSumOfWeights
# read the events
pathBenchEvents = "/eos/user/a/acarvalh/asciiHH_tofit/GF_HH_BSM/" #"/eos/user/a/acarvalh/asciiHH_tofit/GF_HH_BSM/" # events to reweight
file = ROOT.TFile(pathBenchEvents + "events_SumV0.root")
tree = file.Get("treeout")
nev = tree.GetEntries()
# declare the histograms
CalcMhh = np.zeros((nev))
CalcCost = np.zeros((nev))
CalcPtH = np.zeros((nev))
CalcPtHH = np.zeros((nev))
CalcWeight = np.zeros((nev))
CalcPtHgg = np.zeros((nev))
CalcMhhReco = np.zeros((nev))
CalcMXReco = np.zeros((nev))
countevent = 0
#for kll in range(-5,5) : model.getNormalization(kll, kt,sumHBenchBin)
for iev in range(0, nev):
tree.GetEntry(iev)
mhh = tree.Genmhh
cost = tree.GenHHCost
mhhcost = [mhh, cost, 0, 0] # to store [mhh , cost] of that event
# find the Nevents from the sum of events on that bin
bmhh = sumHAnalyticalBin.GetXaxis().FindBin(mhh)
bcost = sumHAnalyticalBin.GetYaxis().FindBin(abs(cost))
#print (tree.GenHHCost,cost,bcost)
effSumV0 = sumHAnalyticalBin.GetBinContent(bmhh, abs(
bcost)) # quantity of simulated events in that bin (without cuts)
weight = model.getScaleFactor(
mhh, cost, kl, kt, c2, cg, c2g, effSumV0, calcSumOfWeights
) # model.effSM,model.MHH,model.COSTS,model.A1,model.A3,model.A7, effSumV0)
#############################################
# fill histograms to test
#############################################
if weight > 0:
#print countevent
CalcMhh[countevent] = float(mhhcost[0])
CalcCost[countevent] = float(abs(mhhcost[1]))
CalcPtH[countevent] = float(mhhcost[2])
CalcPtHH[countevent] = float(mhhcost[3])
CalcWeight[countevent] = weight
countevent += 1
sumWeight += weight
print "plotted histogram reweighted from ", countevent, " events, ", float(
100 * (nev - countevent) /
nev), " % of the events was lost in empty bins in SM simulation"
print "sum of weights", sumWeight
############################################################################################################################
# Draw test histos
###############################################
drawtest = 0
nevtest = 50000
if kl == 1 and kt == 1 and c2 == 0 and cg == 0 and c2g == 0:
filne = "/eos/user/a/acarvalh/asciiHH_tofit/GF_HH_BSM/GF_HH_0.lhe.decayed" # 0 is SM
nevtest = 100000
drawtest = 1
# BSM events
pathBSMtest = "/afs/cern.ch/work/a/acarvalh/generateHH/asciiHH_tofit/GF_HH_toRecursive/" # events of file to superimpose a test
# see the translation of coefficients for this last on: If you make this script smarter (to only read files we ask to test) you can implement more
# https://github.com/acarvalh/generateHH/blob/master/fit_GF_HH_lhe/tableToFitA3andA7.txt
if kl == -10 and kt == 0.5 and c2 == 0 and cg == 0 and c2g == 0:
drawtest = 1
filne = pathBSMtest + "GF_HH_42.lhe.decayed"
if kl == 0.0001 and kt == 2.25 and c2 == 0 and cg == 0 and c2g == 0:
drawtest = 1
filne = pathBSMtest + "GF_HH_9.lhe.decayed"
if kl == 2.5 and kt == 1.0 and c2 == 0 and cg == 0 and c2g == 0:
drawtest = 1
filne = pathBSMtest + "GF_HH_60.lhe.decayed"
klJHEP = [
1.0, 7.5, 1.0, 1.0, -3.5, 1.0, 2.4, 5.0, 15.0, 1.0, 10.0, 2.4, 15.0
]
ktJHEP = [1.0, 1.0, 1.0, 1.0, 1.5, 1.0, 1.0, 1.0, 1.0, 1.0, 1.5, 1.0, 1.0]
c2JHEP = [
0.0, -1.0, 0.5, -1.5, -3.0, 0.0, 0.0, 0.0, 0.0, 1.0, -1.0, 0.0, 1.0
]
cgJHEP = [
0.0, 0.0, 0.6, 0.0, 0.0, 0.8, 0.2, 0.2, -1.0, -0.6, 0.0, 1.0, 0.0
]
c2gJHEP = [
0.0, 0.0, 1.0, -0.8, 0.0, -1.0, -0.2, -0.2, 1.0, 0.6, 0.0, -1.0, 0.0
]
# python recastHH.py --kl 7.5 --kt 1 --c2 -1
# python recastHH.py --kl 1.0 --kt 1.0 --c2 0.5 --cg -0.8 --c2g 0.6
# python recastHH.py --kl 1.0 --kt 1.0 --c2 -1.5 --cg 0.0 --c2g -0.8
# python recastHH.py --kl 1.0 --kt 1.0 --c2 0.0 --cg 0.8 --c2g -1.0
# python recastHH.py --kl 1.0 --kt 1.0 --c2 1.0 --cg -0.6 --c2g 0.6
for sam in range(0, 13):
#print (sam, ktJHEP[sam] , kt , klJHEP[sam] , c2 ,c2JHEP[sam] , cg , cgJHEP[sam] , c2g , c2gJHEP[sam])
if kl == klJHEP[sam] and kt == ktJHEP[sam] and c2 == c2JHEP[
sam] and cg == cgJHEP[sam] and c2g == c2gJHEP[sam]:
print sam
filne = "/eos/user/a/acarvalh/asciiHH_tofit/GF_HH_BSM/GF_HH_" + str(
sam) + ".lhe.decayed"
nevtest = 100000
drawtest = sam
############################################################################################################################
CalcMhhTest = np.zeros((nevtest))
CalcCostTest = np.zeros((nevtest))
CalcPtHTest = np.zeros((nevtest))
CalcPtHHTest = np.zeros((nevtest))
CalcPtHggTest = np.zeros((nevtest))
CalcMhhRecoTest = np.zeros((nevtest))
CalcMXRecoTest = np.zeros((nevtest))
if options.doPlot:
print "draw plain histogram to test"
model.LoadTestEvents(CalcMhhTest, CalcCostTest, CalcPtHTest,
CalcPtHHTest, filne)
model.plotting(kl, kt, c2, cg, c2g, CalcMhh, CalcCost, CalcPtHgg,
CalcPtHH, CalcMhhReco, CalcMXReco, CalcWeight,
CalcMhhTest, CalcCostTest, CalcPtHggTest, CalcPtHHTest,
CalcMhhRecoTest, CalcMXRecoTest, drawtest)
def main():
model = NonResonantModel()
# obtaining BSM/SM coeficients
#dumb = model.ReadCoefficients("../data/coefficientsByBin_A1A3A7.txt")
#dumb = model.ReadCoefficients("../data/coefficientsByBin_extended_3M.txt")
dumb = model.ReadCoefficients("../data/coefficientsByBin_extended_3M_costHHSim_19-4.txt")
# We sum SM + box + the benchmarks from 2-13
# read the 2D histo referent to the sum of events
"""
fileHH=ROOT.TFile("../../../Support/NonResonant/Distros_5p_SM3M_sumBenchJHEP_13TeV.root")
sumJHEPAnalyticalBin = fileHH.Get("H1bin2")
SMAnalyticalBin = fileHH.Get("H0bin2")
"""
fileHH=ROOT.TFile("../../../Analysis/Support/NonResonant/Distros_5p_SM3M_sumBenchJHEP_13TeV_19-4.root") #Distros_5p_SM3M_sumBenchJHEP_13TeV.root") #Distros_5p_SM3M_rebin_sumBenchJHEP_5D_13TeV.root") #
#fileHH=ROOT.TFile("../../../Analysis/Support/NonResonant/Distros_5p_SM3M_rebin_sumBenchJHEP_5D_13TeV.root")
#sumJHEPAnalyticalBin = fileHH.Get("H1bin3")
histfile = "../../../Analysis/Support/NonResonant/Distros_5p_SM3M_sumBenchJHEP_13TeV_19-4.root" #Distros_5p_SM3M_sumBenchJHEP_13TeV.root" # #Distros_5p_SM3M_rebin_sumBenchJHEP_5D_13TeV.root"
#histfile = "../../../Analysis/Support/NonResonant/Distros_5p_SM3M_rebin_sumBenchJHEP_5D_13TeV.root"
histtitle = "H1bin4"
sumJHEPAnalyticalBin = fileHH.Get(histtitle)
SMAnalyticalBin = fileHH.Get("H0bin4")
#fileHHname = "../../../Analysis/Support/NonResonant/Distros_5p_SM3M_rebin_sumBenchJHEP_5D_13TeV.root"
calcSumOfWeights = model.getNormalization(kl, kt,c2,cg,c2g,histfile,histtitle) # this input is flexible, tatabb may have only the SM
#print ("normalization is: ",calcSumOfWeights)
#xaxis = sumJHEPAnalyticalBin.GetXaxis()
#yaxis = sumJHEPAnalyticalBin.GetYaxis()
#print "Sum hist ",sumJHEPAnalyticalBin.GetNbinsX(),sumJHEPAnalyticalBin.GetNbinsY(),sumJHEPAnalyticalBin.Integral(),sumJHEPAnalyticalBin.GetXaxis().GetBinLowEdge(1),sumJHEPAnalyticalBin.GetXaxis().GetBinUpEdge(xaxis.GetNbins())
#print SMAnalyticalBin.GetBinContent(4,4)
# now loop over events, calculate weights using the coeffitients and plot histograms
# events to reweights, in text format (for testing only)
pathBenchEvents="/eos/user/a/acarvalh/asciiHH_tofit/GF_HH_BSM/" # events to reweight
# declare the histograms
CalcMhh = np.zeros((1200000))
CalcCost = np.zeros((1200000))
CalcPtH = np.zeros((1200000))
CalcPtHgg = np.zeros((1200000))
CalcPtHH = np.zeros((1200000))
CalcWeight = np.zeros((1200000))
CalcMhhReco = np.zeros((1200000))
CalcMXReco = np.zeros((1200000))
##########################################
# initialize tables of coefficients by bins
# calculate mhh and cost* and find the bin
# initialize events reading
countline=0
countevent=0
counteventSM=0
# read events as text files for events to test
# particuliarity of the text file with events = each 2 lines are one event there
# save the information of the two Higgses
Px = np.zeros((2))
Py = np.zeros((2))
Pz = np.zeros((2))
En = np.zeros((2))
for sam in range(1,13): # read events from the list of 12 benchmarks
filne = pathBenchEvents+"GF_HH_"+str(sam)+".lhe.decayed" # 0 is SM = here it does not enter in the events to be reweighted in this version
f = open(filne, 'r+')
lines = f.readlines() # get all lines as a list (array)
countline = 0 # particuliarity of the text file with events = each 2 lines are one event there
for line in lines:
model.ReadLine(line, countline,Px,Py,Pz,En)
#print countline
countline+=1
mhhcost= [0,0,0,0] # to store [mhh , cost,ptH , ptHH] of that event
if countline==2 : # if read 2 lines
model.CalculateMhhCost(mhhcost,countline,Px,Py,Pz,En) # ==> adapt to your input
bmhh = sumJHEPAnalyticalBin.GetXaxis().FindBin(mhhcost[0])
bcost = sumJHEPAnalyticalBin.GetYaxis().FindBin(abs(mhhcost[1]))
#print (mhhcost[1],bcost)
effSumV0 = sumJHEPAnalyticalBin.GetBinContent(bmhh,bcost) # quantity of simulated events in that bin (without cuts)
#weight = model.getScaleFactor(mhhcost,kl, kt,0,model.effSM,model.effSum,model.MHH,model.COSTS,model.A1,model.A3,model.A7,0)
#print mhhcost[1],bcost
#print effSumV0
weight = model.getScaleFactor(mhhcost[0],mhhcost[1],kl, kt,c2,cg,c2g, effSumV0,calcSumOfWeights)
countline=0
#############################################
# fill histograms
#############################################
if weight > 0:
#print countevent
CalcMhh[countevent] = float(mhhcost[0])
CalcCost[countevent] = float(mhhcost[1])
CalcPtH[countevent] = float(mhhcost[2])
CalcPtHH[countevent] = float(mhhcost[3])
CalcWeight[countevent] = weight
countevent+=1
#else : print ("neg weight ",weight,mhhcost[0],mhhcost[1],bmhh,bcost,kl, kt,c2,cg,c2g,effSumV0,calcSumOfWeights)
f.close()
print "plotted hostogram reweighted from ",countevent," events, ", float(100*(1200000-countevent)/1200000)," % of the events was lost in empty bins in SM simulation"
print kl, kt,c2,cg,c2g, "Sum of weights:", CalcWeight.sum()," correction ",calcSumOfWeights
############################################################################################################################
# Draw test histos
###############################################
drawtest =-1
nevtest=50000
#if kl == 1 and kt == 1 and c2 ==0 and cg == 0 and c2g ==0 :
# filne = pathBenchEvents+"GF_HH_0.lhe.decayed" # 0 is SM
# nevtest = 100000
# drawtest = 1
# BSM events
pathBSMtest="/afs/cern.ch/work/a/acarvalh/generateHH/asciiHH_tofit/GF_HH_toRecursive/" # events of file to superimpose a test
# see the translation of coefficients for this last on: If you make this script smarter (to only read files we ask to test) you can implement more
# https://github.com/acarvalh/generateHH/blob/master/fit_GF_HH_lhe/tableToFitA3andA7.txt
if kl == -10 and kt == 0.5 and c2 ==0 and cg == 0 and c2g ==0 :
drawtest =1
filne = pathBSMtest+"GF_HH_42.lhe.decayed"
if kl == 0.0001 and kt == 2.25 and c2 ==0 and cg == 0 and c2g ==0 :
drawtest =1
filne = pathBSMtest+"GF_HH_9.lhe.decayed"
if kl == 0.0001 and kt == 1.0 and c2 ==0 and cg == 0 and c2g ==0 :
drawtest =1
filne = pathBSMtest+"GF_HH_4.lhe.decayed"
if kl == 2.5 and kt == 1.0 and c2 ==0 and cg == 0 and c2g ==0 :
drawtest =1
filne = pathBSMtest+"GF_HH_60.lhe.decayed"
if kl == -15 and kt == 0.5 and c2 ==0 and cg == 0 and c2g ==0 :
drawtest =1
filne = pathBSMtest+"GF_HH_40.lhe.decayed"
if kl == 5 and kt == 1.5 and c2 ==0 and cg == 0 and c2g ==0 :
drawtest =1
filne = pathBSMtest+"GF_HH_74.lhe.decayed"
if kl == 7.5 and kt == 2.0 and c2 ==0 and cg == 0 and c2g ==0 :
drawtest =1
filne = pathBSMtest+"GF_HH_88.lhe.decayed"
if kl == 0.0001 and kt == 0.0001 and c2 ==-3.0 and cg == 0.0 and c2g ==-1.5 :
drawtest =1
filne = pathBSMtest+"GF_HH_281.lhe.decayed"
if kl == -10 and kt == 0.0 and c2 ==1.0 and cg == 1.0 and c2g ==1.0 :
drawtest =1
filne = pathBSMtest+"GF_HH_280.lhe.decayed"
#########################################################
klJHEP=[1.0, 7.5, 1.0, 1.0, -3.5, 1.0, 2.4, 5.0, 15.0, 1.0, 10.0, 2.4, 15.0]
ktJHEP=[1.0, 1.0, 1.0, 1.0, 1.5, 1.0, 1.0, 1.0, 1.0, 1.0, 1.5, 1.0, 1.0]
c2JHEP=[0.0, -1.0, 0.5, -1.5, -3.0, 0.0, 0.0, 0.0, 0.0, 1.0, -1.0, 0.0, 1.0]
cgJHEP=[0.0, 0.0, 0.6, 0.0, 0.0, 0.8, 0.2, 0.2, -1.0, -0.6, 0.0, 1.0, 0.0]
c2gJHEP=[0.0, 0.0, 1.0, -0.8, 0.0, -1.0, -0.2,-0.2, 1.0, 0.6, 0.0, -1.0, 0.0]
# python recastHH.py --kl 7.5 --kt 1 --c2 -1
# python recastHH.py --kl 1.0 --kt 1.0 --c2 0.5 --cg -0.8 --c2g 0.6
# python recastHH.py --kl 1.0 --kt 1.0 --c2 -1.5 --cg 0.0 --c2g -0.8
# python recastHH.py --kl 1.0 --kt 1.0 --c2 0.0 --cg 0.8 --c2g -1.0
# python recastHH.py --kl 1.0 --kt 1.0 --c2 1.0 --cg -0.6 --c2g 0.6
for sam in range(0,13):
#print (sam, ktJHEP[sam] , kt , klJHEP[sam] , c2 ,c2JHEP[sam] , cg , cgJHEP[sam] , c2g , c2gJHEP[sam])
if kl == klJHEP[sam] and kt == ktJHEP[sam] and c2 ==c2JHEP[sam] and cg == cgJHEP[sam] and c2g ==c2gJHEP[sam] :
print sam
filne="/eos/user/a/acarvalh/asciiHH_tofit/GF_HH_BSM/GF_HH_"+str(sam)+".lhe.decayed"
nevtest=100000
drawtest = sam
############################################################################################################################
CalcMhhTest = np.zeros((nevtest))
CalcCostTest = np.zeros((nevtest))
CalcPtHTest = np.zeros((nevtest))
CalcPtHHTest = np.zeros((nevtest))
CalcPtHggTest = np.zeros((nevtest))
CalcMhhRecoTest = np.zeros((nevtest))
CalcMXRecoTest = np.zeros((nevtest))
if options.doPlot and drawtest >0 :
print "draw plain histogram to test"
model.LoadTestEvents(CalcMhhTest,CalcCostTest,CalcPtHTest,CalcPtHHTest,filne)
model.plotting(kl,kt,c2,cg,c2g,CalcMhh,CalcCost,CalcPtHgg,CalcPtHH,CalcMhhReco,CalcMXReco,CalcWeight,CalcMhhTest,CalcCostTest,CalcPtHggTest,CalcPtHHTest,CalcMhhRecoTest,CalcMXRecoTest,drawtest)
def main():
model = NonResonantModel()
# obtaining BSM/SM coeficients
dumb = model.ReadCoefficients("../data/coefficientsByBin_klkt.txt",model.effSM,model.effSum,model.MHH,model.COSTS,model.A1,model.A3,model.A7)
# We sum SM + box + the benchmarks from 2-13
# read the 2D histo referent to the sum of events
fileHH=ROOT.TFile("../../Support/NonResonant/Distros_5p_SM3M_sumBenchJHEP_13TeV.root")
sumJHEPAnalyticalBin = fileHH.Get("H1bin2")
SMAnalyticalBin = fileHH.Get("H0bin2")
xaxis = sumJHEPAnalyticalBin.GetXaxis()
yaxis = sumJHEPAnalyticalBin.GetYaxis()
print "Sum hist ",sumJHEPAnalyticalBin.GetNbinsX(),sumJHEPAnalyticalBin.GetNbinsY(),sumJHEPAnalyticalBin.Integral(),sumJHEPAnalyticalBin.GetXaxis().GetBinLowEdge(1),sumJHEPAnalyticalBin.GetXaxis().GetBinUpEdge(xaxis.GetNbins())
#print SMAnalyticalBin.GetBinContent(4,4)
# now loop over events, calculate weights using the coeffitients and plot histograms
# events to reweights, in text format (for testing only)
pathBenchEvents="/afs/cern.ch/work/a/acarvalh/public/toAnamika/GF_HH_BSM/" # events to reweight
# declare the histograms
CalcMhh = np.zeros((1200000))
CalcCost = np.zeros((1200000))
CalcWeight = np.zeros((1200000))
##########################################
# initialize tables of coefficients by bins
# calculate mhh and cost* and find the bin
# initialize events reading
countline=0
countevent=0
counteventSM=0
# read events as text files for events to test
# particuliarity of the text file with events = each 2 lines are one event there
# save the information of the two Higgses
Px = np.zeros((2))
Py = np.zeros((2))
Pz = np.zeros((2))
En = np.zeros((2))
for sam in range(1,13): # read events from the list of 12 benchmarks
filne = pathBenchEvents+"GF_HH_"+str(sam)+".lhe.decayed" # 0 is SM = here it does not enter in the events to be reweighted in this version
f = open(filne, 'r+')
lines = f.readlines() # get all lines as a list (array)
countline = 0 # particuliarity of the text file with events = each 2 lines are one event there
for line in lines:
model.ReadLine(line, countline,Px,Py,Pz,En)
#print countline
countline+=1
mhhcost= [0,0] # to store [mhh , cost] of that event
if countline==2 : # if read 2 lines
model.CalculateMhhCost(mhhcost,countline,Px,Py,Pz,En) # ==> adapt to your input
bmhh = sumJHEPAnalyticalBin.GetXaxis().FindBin(mhhcost[0])
bcost = sumJHEPAnalyticalBin.GetYaxis().FindBin(mhhcost[1])
effSumV0 = sumJHEPAnalyticalBin.GetBinContent(bmhh,bcost) # quantity of simulated events in that bin (without cuts)
#weight = model.getScaleFactor(mhhcost,kl, kt,0,model.effSM,model.effSum,model.MHH,model.COSTS,model.A1,model.A3,model.A7,0)
#print mhhcost[1],bcost
#print effSumV0
weight = model.getScaleFactor(mhhcost,kl, kt,model.effSM,model.MHH,model.COSTS,model.A1,model.A3,model.A7,effSumV0)
countline=0
#############################################
# fill histograms
#############################################
if weight > 0:
#print countevent
CalcMhh[countevent] = float(mhhcost[0])
CalcCost[countevent] = float(mhhcost[1])
CalcWeight[countevent] = weight
countevent+=1
f.close()
print "plotted hostogram reweighted from ",countevent," events, ", float(100*(1200000-countevent)/1200000)," % of the events was lost in empty bins in SM simulation"
############################################################################################################################
# Draw test histos
###############################################
drawtest =0
nevtest=50000
if kl == 1 and kt == 1 and c2 ==0 and cg == 0 and c2g ==0 :
filne = pathBenchEvents+"GF_HH_0.lhe.decayed" # 0 is SM
nevtest = 100000
drawtest = 1
# BSM events
pathBSMtest="/afs/cern.ch/work/a/acarvalh/public/toAnamika/GF_HH_toRecursive/" # events of file to superimpose a test
# see the translation of coefficients for this last on: If you make this script smarter (to only read files we ask to test) you can implement more
# https://github.com/acarvalh/generateHH/blob/master/fit_GF_HH_lhe/tableToFitA3andA7.txt
if kl == -10 and kt == 0.5 and c2 ==0 and cg == 0 and c2g ==0 :
drawtest =1
filne = pathBSMtest+"GF_HH_42.lhe.decayed"
if kl == 0.0001 and kt == 2.25 and c2 ==0 and cg == 0 and c2g ==0 :
drawtest =1
filne = pathBSMtest+"GF_HH_9.lhe.decayed"
if kl == 2.5 and kt == 1.0 and c2 ==0 and cg == 0 and c2g ==0 :
drawtest =1
filne = pathBSMtest+"GF_HH_60.lhe.decayed"
############################################################################################################################
CalcMhhTest = np.zeros((nevtest))
CalcCostTest = np.zeros((nevtest))
if drawtest ==1 :
print "draw plain histogram to test"
model.LoadTestEvents(CalcMhhTest,CalcCostTest,filne)
model.plotting(kl,kt,CalcMhh,CalcCost,CalcWeight,CalcMhhTest,CalcCostTest,drawtest)