tt = False
zz = False
wz = False
data = False
#Now here we have a dictionary, with
#a key for each squared background error
#From here we can calculate the uncertainty on each background individually
#We also can do the uncertainty of all backgrounds together
if len(bkgdfs["DYJetsToLL"]) > 0:
dy = True
uncsqdDYJetsdf = sum(bkgdfs["DYJetsToLL"])
uncDYJetsdf = uncsqdDYJetsdf**(1 / 2)
saveDYJetsunc = go.makeOutFile(mcprefix + '.DYJetsToLL', 'unc_' + reg,
'.pkl', str(zptcut), str(hptcut),
str(metcut), str(btagwp))
uncDYJetsdf.to_pickle(saveDYJetsunc)
if len(bkgdfs["TT"]) > 0:
tt = True
uncsqdTTdf = sum(bkgdfs["TT"])
uncTTdf = uncsqdTTdf**(1 / 2)
saveTTunc = go.makeOutFile(mcprefix + '.TT', 'unc_' + reg, '.pkl',
str(zptcut), str(hptcut), str(metcut),
str(btagwp))
uncTTdf.to_pickle(saveTTunc)
if len(bkgdfs["WZTo2L2Q"]) > 0:
wz = True
uncsqdWZdf = sum(bkgdfs["WZTo2L2Q"])
cfdict[zptstr][bkg["name"]] = round(yieldzpt/origevnts*100,4)
cfdict[hptstr][bkg["name"]] = round(yieldhpt/origevnts*100,4)
cfdict[btgstr][bkg["name"]] = round(yieldbtag/origevnts*100,4)
cfdict[sbstr][bkg["name"]] = round(yieldsb/origevnts*100,4)
cfdict[metstr]["totbkg"] = round(totymet/totorig*100,4)
cfdict[zptstr]["totbkg"] = round(totyzpt/totorig*100,4)
cfdict[hptstr]["totbkg"] = round(totyhpt/totorig*100,4)
cfdict[btgstr]["totbkg"] = round(totybtg/totorig*100,4)
cfdict[sbstr]["totbkg"] = round(totysb/totorig*100,4)
#gets cuts in order of loosest to tightest based on yield
cutordered = sorted(cfdict,key= lambda x : -1*cfdict[x]["totbkg"])
cutFlowTableTex = go.makeOutFile("ZpAnomalon_mumu_bkg","cutflow",'.tex',str(int(zptcut)),str(int(hptcut)),str(int(metcut)),str(btagwp).split('.')[-1]+'E-10')
cftab = open(cutFlowTableTex,"w")
cftab.write(r'\begin{table}[htbp]')
cftab.write('\n')
cftab.write(r'\begin{center}')
cftab.write('\n')
cftab.write(r'\begin{tabular}{l | c | c | c | c | c | c }')#need to make dynamic
cftab.write('\n')
cftab.write("\hline\hline\n")
cftab.write(r'cut description & ZZ & WZ & ttbar & DY+jets & Total \\')
cftab.write('\n')
cftab.write("\hline\n")
for key in cutordered:
#tabline = r''+key+' & '+str(cfdict[key]['ZZTo2L2Q'])+' & '+str(cfdict[key]['WZTo2L2Q'])+' & '+str(cfdict[key]['TT'])+' & '+str(cfdict[key]['DYJetsToLL'])+' & '+str(cfdict[key]['totbkg'])+' \\'
tabline = key+' & '+str(cfdict[key]['ZZTo2L2Q'])+' & '+str(cfdict[key]['WZTo2L2Q'])+' & '+str(cfdict[key]['TT'])+' & '+str(cfdict[key]['DYJetsToLL'])+' & '+str(cfdict[key]['totbkg'])+' \\'
cftab.write(tabline)
mg.GetXaxis().SetLimits(binlist[0], binlist[-1] + hsumb.GetBinWidth(1))
#y axis
mg.GetYaxis().SetTitle("data/MC")
mg.GetYaxis().SetTitleSize(0.07)
mg.GetYaxis().SetTitleOffset(.7)
mg.GetYaxis().SetLabelSize(0.05)
mg.SetMinimum(0.5)
mg.SetMaximum(ratio_max)
mg.SetMaximum(1.5)
mg.Draw("AP")
l.Draw()
#Go back to previous pad so next kinematic plots draw
tc.cd()
p1.cd()
#Draw the legent with everything added
if not "50rig" in hname:
leg.SetBorderSize(0)
leg.Draw()
#Draw the legent with everything added
leg.SetBorderSize(0)
leg.Draw()
#Save the plot
pngname = gecorg.makeOutFile(hname, 'ratio_' + regiondescrip, '.png',
str(zptcut), str(hptcut), str(metcut),
str(btagwp))
tc.SaveAs(pngname)
tf2 = ROOT.TFile(f17dyjetsr[0])
hsr = tf2.Get('h_zp_jigm')
hsr.Reset("ICESM")
hsr = makeAddedHist(f17dyjetsr, a18dyjetsr, f17dyjetsrerrs, a18dyjetsrerrs,
xspairs, hsr)
ROOT.gSystem.CompileMacro("cfunctions/alphafits.C", "kfc")
ROOT.gSystem.Load("cfunctions/alphafits_C")
hsrt = hsr.Clone()
hsbt = hsb.Clone()
#Draw
ROOT.gStyle.SetOptFit(1011)
tc.cd(1)
sbfit = ROOT.expFit(hsbt, "sbl", "R0+")
hsb.Draw()
sbfit.Draw("SAME")
tc.cd(2)
srfit = ROOT.expFit(hsrt, "srl", "R0+")
hsr.Draw()
srfit.Draw("SAME")
tc.cd(3)
alpha = ROOT.alphaRatioMakerExp(hsbt, hsrt)
#print(alpha)
alpha.Draw()
figname = go.makeOutFile('Run2_2017_2018', 'alpha_fits',
'.png', str(zptcut), str(hptcut), str(metcut),
str(btagwp))
tc.SaveAs(figname)
parser = argparse.ArgumentParser()
if __name__=='__main__':
parser.add_argument("-f","--sample",help = "sample file")
parser.add_argument("-o","--output",help = "output file name")
parser.add_argument("-b","--btagger",help = "btagger selection, need name part of key")
parser.add_argument("-wp","--btagWP",type=float,default=0.6,help = "doulbeB tagger working point (default M1)")
parser.add_argument("-zpt","--zPtCut",type=float,default = 100.0,help = "pT cut on Z")
parser.add_argument("-hpt","--hPtCut",type=float,default = 250.0,help = "pT cut on h")
parser.add_argument("-met","--metPtCut",type=float,default = 50.0,help = "pT cut on met")
parser.add_argument("-sdm","--sdmCut",type=float,default = 10.0,help = "lowest soft drop mass cut")
parser.add_argument("-date","--date",type=str,help = "where are your topiary plots?")
args = parser.parse_args()
samp = args.sample
sdmcut = args.sdmCut
zptcut = args.zPtCut
hptcut = args.hPtCut
metcut = args.metPtCut
btaggr = args.btagger
btagwp = args.btagWP
#inputfiles = glob.glob('analysis_output_ZpAnomalon/'+args.date+'/*_Zptcut'+str(zptcut)+'_Hptcut'+str(hptcut)+'_metcut'+str(metcut)+'_btagwp'+str(btagwp)+'.png')
#inputfiles = glob.glob('../notes/AN-20-120_/*_Zptcut'+str(zptcut)+'_Hptcut'+str(hptcut)+'_metcut'+str(metcut)+'_btagwp'+str(btagwp)+'.png')
for f in inputfiles:
protoname = f.split("_Zpt")[0]
name = protoname.split(args.date+"/")[-1]
newfilename = go.makeOutFile(name,'tex','.png',str(int(zptcut)),str(int(hptcut)),str(int(metcut)),'loose')
subprocess.run(["mv",f,newfilename])
origevnts = 0
if samptype != 1:
inChain = ROOT.TChain("PreSelection")
inputs = glob.glob("../dataHandling/"+year+"/"+samp+"*.root")
for f in inputs:
inChain.Add(f)
tf = ROOT.TFile.Open(f)
origevnts += tf.Get("hnevents").GetBinContent(1)
else:
inChain = ROOT.TChain("TreeMaker2/PreSelection")
inChain.Add("../dataHandling/"+year+"/"+samp+"*.root")
origevnts = inChain.GetEntries()
outFile = go.makeOutFile(samp,'topiary','.root','0.0','250.0','0.0','0.0')#Needs to become dynamic with cuts
print( "Making topiary of ",samp)
print(" Sample type ",samptype)
print(" Sample Year ",checkedyear)
print(" Events in TChain: ",inChain.GetEntries())
print((" Original data set had {0} events in type.").format(origevnts))
print(" Saving topiary in ",outFile)
ROOT.gSystem.CompileMacro("TreeMakerTopiary.C","g0ck")
ROOT.gSystem.Load('TreeMakerTopiary_C')
topiary = ROOT.TreeMakerTopiary(inChain,samptype,checkedyear)
topiary.Loop(outFile,origevnts,samptype,checkedyear)
fdf = srdf
region = "signalr"
elif comb:
fdf = btdf
region = "totalr"
else:
fdf = sbdf
region = "sideband"
else:
fdf = sbdf
print(" number of passing events ",len(fdf))
#print("number of btag passing events ",len(btdf))
#lets make some histograms.
rootfilename = go.makeOutFile(samp,'upout_'+region+'_'+btaggr,'.root',str(zptcut),str(hptcut),str(metcut),str(btagwp))#need to update for btagger
npfilename = go.makeOutFile(samp,'totalevents_'+region+'_'+btaggr,'.npy',str(zptcut),str(hptcut),str(metcut),str(btagwp))
pklfilename = go.makeOutFile(samp,'selected_errors_'+region+'_'+btaggr,'.pkl',str(zptcut),str(hptcut),str(metcut),str(btagwp))
rootOutFile = up3.recreate(rootfilename,compression = None)
npOutFile = open(npfilename,'wb')
rootOutFile["h_z_pt"] = np.histogram(fdf['ZCandidate_pt'],bins=80,range=(0,800),weights=fdf['event_weight'])
#rootOutFile["h_z_phi"] = np.histogram(fdf['ZCandidate_phi'],bins=100,range=(0,3.14159),weights=fdf['event_weight'])#needs to fit range
rootOutFile["h_z_eta"] = np.histogram(fdf['ZCandidate_eta'],bins=100,range=(-5,5),weights=fdf['event_weight'])
rootOutFile["h_z_m"] = np.histogram(fdf['ZCandidate_m'],bins=100,range=(40,140),weights=fdf['event_weight'])
rootOutFile["h_h_pt"] = np.histogram(fdf['hCandidate_pt'],bins=40,range=(200,1200),weights=fdf['event_weight'])
#rootOutFile["h_h_phi"] = np.histogram(fdf['hCandidate_phi'],bins=100,range=(0,3.14159))#needs to fit range
rootOutFile["h_h_eta"] = np.histogram(fdf['hCandidate_eta'],bins=100,range=(-5,5),weights=fdf['event_weight'])
rootOutFile["h_h_m"] = np.histogram(fdf['hCandidate_m'],bins=80,range=(0,400),weights=fdf['event_weight'])
rootOutFile["h_h_sd"] = np.histogram(fdf['hCandidate_sd'],bins=80,range=(0,400),weights=fdf['event_weight'])
rootOutFile["h_met"] = np.histogram(fdf['METclean'],bins=78,range=(50,2000),weights=fdf['event_weight'])
bkgeffs = np.delete(bkgeffs, 0)
sigeffs = np.delete(sigeffs, 0)
cutlist = np.delete(cutlist, 0)
tg = ROOT.TGraph(hsum.GetNbinsX() - 1, sigeffs, bkgeffs)
tg.SetTitle(btag)
tg.SetLineWidth(2)
tg.SetLineColor(btagcols[i])
mg.Add(tg)
gleg.AddEntry(tg, btag)
tc.cd()
tc.SetLogy()
mg.Draw("AL")
mg.GetXaxis().SetTitle("signal efficiency")
mg.GetXaxis().SetLimits(0, 1.0)
mg.GetYaxis().SetTitle("background efficiency")
mg.GetYaxis().SetTitleOffset(1.1)
mg.GetYaxis().SetLabelSize(0.025)
mg.SetMinimum(0.0001)
mg.SetMaximum(1.0)
gleg.Draw()
tc.Update()
tc.Draw()
#Save the plot
pngname = gecorg.makeOutFile(hname, 'btagger_roc_' + sigsamp, '.png',
str(zptcut), str(hptcut), str(metcut))
tc.SaveAs(pngname)
temp_max = np.amax(signiflist)
if temp_max > max_max:
max_max = temp_max
mg.SetTitle("")
#x axis
mg.GetXaxis().SetTitle("cut value")
mg.GetXaxis().SetTitleSize(0.07)
mg.GetXaxis().SetLabelSize(0.05)
mg.GetXaxis().SetLimits(cutlist[0], cutlist[-1] + hsum.GetBinWidth(1))
#y axis
mg.GetYaxis().SetTitle("S/#sqrt{B+S} a.u.")
mg.GetYaxis().SetTitleSize(0.07)
mg.GetYaxis().SetTitleOffset(.7)
mg.GetYaxis().SetLabelSize(0.05)
mg.SetMinimum(0)
mg.SetMaximum(30)
#Go back to previous pad so next kinematic plots draw
tc.cd()
p1.cd()
#Draw the legent with everything added
leg.SetBorderSize(0)
leg.Draw()
#Save the plot
pngname = gecorg.makeOutFile(hname, 'optimization', '.png', str(zptcut),
str(hptcut), str(metcut), str(btagwp))
tc.SaveAs(pngname)
mg.GetXaxis().SetTitleSize(0.07)
mg.GetXaxis().SetLabelSize(0.05)
mg.GetXaxis().SetLimits(binlist[0],binlist[-1]+hsumb.GetBinWidth(1))
#y axis
mg.GetYaxis().SetTitle("data/MC")
mg.GetYaxis().SetTitleSize(0.07)
mg.GetYaxis().SetTitleOffset(.7)
mg.GetYaxis().SetLabelSize(0.05)
mg.SetMinimum(0.5)
mg.SetMaximum(ratio_max)
mg.SetMaximum(1.5)
mg.Draw("AP")
l.Draw()
#Go back to previous pad so next kinematic plots draw
tc.cd()
p1.cd()
#Draw the legent with everything added
if not "50rig" in hname:
leg.SetBorderSize(0)
leg.Draw()
#Draw the legent with everything added
leg.SetBorderSize(0)
leg.Draw()
#Save the plot
pngname = gecorg.makeOutFile(hname,'ratio_2018','.png',str(zptcut),str(hptcut),str(metcut),str(btagwp))
tc.SaveAs(pngname)
