["offHtAll330_l", "offHtAll0_l"],
["offHtAll370_l", "offHtAll0_l"],
["offHtAll430_l", "offHtAll0_l"],
["offHtAll510_l", "offHtAll0_l"],
["offHtAll590_l", "offHtAll0_l"],
["offHtAll680_vl", "offHtAll0_vl"],
["offHtAll780_vl", "offHtAll0_vl"],
["offHtAll890_vl", "offHtAll0_vl"],
["offHtAll1050_2vl", "offHtAll0_2vl"],
]
for p in effPairs:
dirName = "TrigTurnOnStudy"
eff_Matched_1 = makeEff(p, dirName, inFile1, binning=1)
if o.mc:
eff_Matched_2 = makeEff(
[p[0].replace("_L", "_B"), p[1].replace("_L", "_B")],
dirName,
inFile1,
binning=1)
else:
eff_Matched_2 = makeEff(p, dirName, inFile2, binning=1)
yLeg = 0.93
xLeg = 0.5
doFit = True #o.mc
drawComp(
plotRatio("nPV",
"Events",
inFileData,
"Data",
inFileMC,
"MC",
xTitle="nPV",
outDir=o.outDir,
binning=1)
#
# Offline Turnon curves:
#
effBinning = 5
eff_CaloCSV_Data = makeEff(
"CSVv2_l", ["offJets_matchedCalocsvTag", "offJets_matchedCalo"],
inFileData,
binning=effBinning)
eff_CaloCSV_MC = makeEff("CSVv2_l",
["offJets_matchedCalocsvTag", "offJets_matchedCalo"],
inFileMC,
binning=effBinning)
eff_PFCSV_Data = makeEff("CSVv2_l",
["offJets_matchedPFcsvTag", "offJets_matched"],
inFileData,
binning=effBinning)
eff_PFCSV_MC = makeEff("CSVv2_l",
["offJets_matchedPFcsvTag", "offJets_matched"],
inFileMC,
binning=effBinning)
eff_CaloCSVvsDeepCSV_Data = makeEff(
if o.doAlgoStudy:
for i in range(30):
vars += ["Eta_forAlgo"+str(i)]
vars += ["Pt_forAlgo"+str(i)]
for v in vars:
binning = 1
if not v.find("Eta_forAlgo") == -1:
binning = 4
if not v.find("Pt_forAlgo") == -1:
binning = [0,1,2,3,4,5,6,7,8,9,10,12,14,16,18,20,25,30,40,50]
if not o.doPuppiJets:
eff_Matched = makeEff(v , ["offTracks_matched","offTracks"],inFileMC,binning=binning)
# eff_Matched_noV0 = makeEff(v , ["offTracks_matched_noV0","offTracks_noV0"],inFileMC,binning=binning)
else:
eff_MatchedPuppi = makeEff(v , ["offTracksPuppi_matched","offTracksPuppi"],inFileMC,binning=binning)
eff_MatchedPuppi_noV0 = makeEff(v , ["offTracksPuppi_matched_noV0","offTracksPuppi_noV0"],inFileMC,binning=binning)
if o.doCaloJets:
effCalo_Matched = makeEff(v , ["offTracksCalo_matched","offTracksCalo"],inFileMC,binning=binning)
effCalo_Matched_noV0 = makeEff(v , ["offTracksCalo_matched_noV0","offTracksCalo_noV0"],inFileMC,binning=binning)
vBtag = "track"+v
if v=="phi": vBtag = "trackPhi"
if v=="eta": vBtag = "trackEta"
if v in ["HasInnerPixHit","IsFromSV","NStripHits","PV","PVweight","SV","SVweight","algo","charge"]: pass #continue
if v in ["ip2d","ip2d_l","ip2d_err","ip2d_err_l","ip2d_sig","ip2d_sig_l",
"ip3d","ip3d_l","ip3d_err","ip3d_err_l","ip3d_sig","ip3d_sig_l",
"trackNPixelHits",
"trackNTotalHits",
"trackPPar",
"trackPParRatio",
"trackPhi",
"trackPt",
"trackPtRatio",
"trackPtRel",
"trackPt_logx",
]
for v in vars:
binning = 1
eff_Matched = makeEff(v, ["offBTags_matched", "offBTags"],
inFileMC,
binning=binning)
eff_Matched_noV0 = makeEff(v, ["offBTags_matched_noV0", "offBTags_noV0"],
inFileMC,
binning=binning)
if o.doCaloJets:
effCalo_Matched = makeEff(v, ["offBTagsCalo_matched", "offBTagsCalo"],
inFileMC,
binning=binning)
effCalo_Matched_noV0 = makeEff(
v, ["offBTagsCalo_matched_noV0", "offBTagsCalo_noV0"],
inFileMC,
binning=binning)
vBtag = "track" + v
inFileData2,
"Data 17",
xTitle="DeepCSV",
outDir=o.outDir,
binning=1,
cmsText=o.cmsText,
lumiText=o.lumiText,
setLogy=1)
#
# Offline Turnon curves:
#
effBinning = 5
eff_CaloCSVvsDeepCSV_Data = makeEff(
"DeepCSV_l", ["offJets_matchedCalocsvTag", "offJets_matchedCalo"],
inFileData1,
binning=effBinning)
eff_CaloCSVvsDeepCSV_MC = makeEff(
"DeepCSV_l", ["offJets_matchedCalocsvTag", "offJets_matchedCalo"],
inFileData2,
binning=effBinning)
eff_PFCSVvsDeepCSV_Data = makeEff(
"DeepCSV_l", ["offJets_matchedPFcsvTag", "offJets_matched"],
inFileData1,
binning=effBinning)
eff_PFCSVvsDeepCSV_MC = makeEff("DeepCSV_l",
["offJets_matchedPFcsvTag", "offJets_matched"],
inFileData2,
binning=effBinning)
eff_CaloDeepCSV_Data = makeEff(
["ht330_EM_4j_3b_vs_ht330",["ht_4j_3b_em/ht_4j_3b_em_pass_4b","ht_4j_3b_em/ht_4j_3b_em_incl_4b"],["hT30_h330","hT30_all"]],
# [["ht_4j_em/ht_4j_em_pass_4b","ht_4j_em/ht_4j_em_incl_4b"],["hT30_h330","hT30_all"]],
]
for (pName, p1, p2) in effPairs:
dirName = "trigStudy"
if p1[1] == "allPt":
binning = []
for i in range(20,202,2):
binning.append(i)
else:
binning = 1
eff1 = makeEff(p1 , dirName, inFile, binning=binning, bayesRatio=0)
eff2 = makeEff(p2 , dirName, inFile, binning=binning, bayesRatio=0)
yLeg = 0.93
xLeg = 0.5
doFit = False#o.mc
print "max is ",eff1.GetXaxis().GetXmax()
drawComp("Eff_"+pName.replace("/","_"),[(eff1,p1[0], ROOT.kBlack),
(eff2,p2[0], ROOT.kRed),
#(eff_Matched_2,o.name2, ROOT.kRed, ROOT.kOpenCircle),
#(eff_Matched_BTag,"t#bar{t} MC ",ROOT.kBlue),
#(eff_Matched_BTag_noV0,"t#bar{t} MC ",ROOT.kGreen)
]
,yTitle="Trigger Efficiency",xTitle=eff1.GetXaxis().GetTitle(),outDir=o.outDir,yMax=1.25,yLeg=yLeg,xLeg=xLeg,
xMax=eff1.GetXaxis().GetXmax(),
0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 120, 140, 160, 200,
300, 500, 750, 1000
]
if v in ["matched_dRAll", "matched_dRBjet"]:
binning = 4
for config in effRatios:
effNumName = config[0]
effDenName = config[1]
numHistOrigBinning = None
if v == "pt_m":
numHistOrigBinning = getHist(inFile1, effNumName, v, 1)
eff_Matched_1 = makeEff(v, [effNumName, effDenName],
inFile1,
binning=binning,
histForXBarycenterCalc=numHistOrigBinning)
eff_Matched_1.SetName("Eff_" + o.name1 + "_" + effNumName + "_" + v)
eff_Matched_2 = makeEff(v, [effNumName, effDenName],
inFile2,
binning=binning,
histForXBarycenterCalc=numHistOrigBinning)
eff_Matched_2.SetName("Eff_" + o.name2 + "_" + effNumName + "_" + v)
min = 0.601
yLeg = 0.3
if v == "pt_m":
eff_Matched_1.GetXaxis().SetTitle("p_{T} [GeV]")
eff_Matched_2.GetXaxis().SetTitle("p_{T} [GeV]")
min = 0.501
yLeg = 0.5
for i in range(30):
vars += ["Eta_forAlgo"+str(i)]
vars += ["Pt_forAlgo"+str(i)]
for v in vars:
binning = 1
if not v.find("Eta_forAlgo") == -1:
binning = 4
if not v.find("Pt_forAlgo") == -1:
binning = [0,1,2,3,4,5,6,7,8,9,10,12,14,16,18,20,25,30,40,50]
effNumName = "offTracks_matched"
effDenName = "offTracks"
eff_Matched_1 = makeEff(v , [effNumName, effDenName], inFile1,binning=binning)
eff_Matched_2 = makeEff(v , [effNumName, effDenName], inFile2, binning=binning)
yLeg = 0.93
xLeg = 0.5
if v in ["algo","origAlgo"]:
yLeg = 0.4
xLeg = 0.6
drawComp("Eff_"+v,[(eff_Matched_1,o.name1, ROOT.kBlack),
(eff_Matched_2,o.name2, ROOT.kRed, ROOT.kOpenCircle),
#(eff_Matched_BTag,"t#bar{t} MC ",ROOT.kBlue),
#(eff_Matched_BTag_noV0,"t#bar{t} MC ",ROOT.kGreen)
]
,yTitle="Online Track Efficiency Relative to Offline",xTitle=eff_Matched_1.GetXaxis().GetTitle(),outDir=o.outDir,yMax=1.2,yLeg=yLeg,xLeg=xLeg,
xMax=eff_Matched_1.GetXaxis().GetXmax(),