- Still issue with the btagSF

- Updated the method for modules to run
- Added PUWeightProducer

post_proc.py

@@ -6,11 +6,21 @@
 from H4LCppModule import *
 from PhysicsTools.NanoAODTools.postprocessing.modules.jme.jetmetHelperRun2 import *
 from PhysicsTools.NanoAODTools.postprocessing.modules.btv.btagSFProducer import *
+from PhysicsTools.NanoAODTools.postprocessing.modules.common.puWeightProducer import *
 from JetSFMaker import *
 
 ifRunningOnCondor = False
 
 testfilelist = []
+modulesToRun = []
+isMC = True
+isFSR = False
+jsonFileName = ""
+# Keep DownloadFileToLocalThenRun=True this should reduce the file read error from eos.
+DownloadFileToLocalThenRun=True
+# Set  entriesToRun = 0 if need to run over all entries else put number of entries to run
+entriesToRun = 0 if ifRunningOnCondor else 100
+
 
 if ifRunningOnCondor:
     testfile = "root://cms-xrd-global.cern.ch//store/mc/RunIISummer20UL18NanoAODv9/GluGluHToZZTo4L_M125_TuneCP5_13TeV_powheg2_JHUGenV7011_pythia8/NANOAODSIM/106X_upgrade2018_realistic_v16_L1v1-v1/120000/3ED05633-EBB7-4A44-8F9D-CD956490BCFD.root"
@@ -28,15 +38,6 @@
         # Append the line to the list with the "root://cms-xrd-global.cern.ch//" prefix
         testfilelist.append("root://cms-xrd-global.cern.ch/" + line)
 
-# Set  entriesToRun = 0 if need to run over all entries else put number of entries to run
-entriesToRun = 0 if ifRunningOnCondor else 100
-
-isMC = True
-isFSR = False
-jsonFileName = ""
-# Keep DownloadFileToLocalThenRun=True this should reduce the file read error from eos.
-DownloadFileToLocalThenRun=True
-
 if testfilelist[0].find("/data/") != -1:
     isMC = False
 
@@ -56,6 +57,8 @@
     sfFileName="DeepCSV_2016LegacySF_V1.csv"
 
 H4LCppModule = lambda: HZZAnalysisCppProducer(year,cfgFile, isMC, isFSR)
+modulesToRun.extend([H4LCppModule()])
+
 print("Input json file: {}".format(jsonFileName))
 print("Input cfg file: {}".format(cfgFile))
 print("isMC: {}".format(isMC))
@@ -64,14 +67,21 @@
 if isMC:
     jetmetCorrector = createJMECorrector(isMC=isMC, dataYear=year, jesUncert="All", jetType = "AK4PFchs")
     fatJetCorrector = createJMECorrector(isMC=isMC, dataYear=year, jesUncert="All", jetType = "AK8PFPuppi")
-    btagSF = lambda: btagSFProducer("UL"+str(year), algo="deepjet",selectedWPs=['L','M','T','shape_corr'], sfFileName=sfFileName)
+    # btagSF = lambda: btagSFProducer("UL"+str(year), algo="deepjet",selectedWPs=['L','M','T','shape_corr'], sfFileName=sfFileName)
+    btagSF = lambda: btagSFProducer(era = "UL"+str(year), algo = "deepcsv")
     puidSF = lambda: JetSFMaker("%s" % year)
-    # p=PostProcessor(".",testfilelist, None, None,[H4LCppModule(), jetmetCorrector(), fatJetCorrector(), btagSF(), puidSF()], provenance=True,fwkJobReport=False,haddFileName="nano_M125_cpp.root", maxEntries=entriesToRun, prefetch=DownloadFileToLocalThenRun, outputbranchsel="keep_and_drop.txt")
-    p=PostProcessor(".",testfilelist, None, None,[H4LCppModule(), jetmetCorrector(), fatJetCorrector(), puidSF()], provenance=True,fwkJobReport=False,haddFileName="nano_M125_cpp.root", maxEntries=entriesToRun, prefetch=DownloadFileToLocalThenRun, outputbranchsel="keep_and_drop.txt")
+    modulesToRun.extend([jetmetCorrector(), fatJetCorrector(), puidSF()])
+    if year == 2018: modulesToRun.extend([puAutoWeight_2018()])
+    if year == 2017: modulesToRun.extend([puAutoWeight_2017()])
+    if year == 2016: modulesToRun.extend([puAutoWeight_2016()])
+
+    p=PostProcessor(".",testfilelist, None, None,modules = modulesToRun, provenance=True,fwkJobReport=False,haddFileName="skimmed_nano_mc.root", maxEntries=entriesToRun, prefetch=DownloadFileToLocalThenRun, outputbranchsel="keep_and_drop.txt")
 else:
     jetmetCorrector = createJMECorrector(isMC=isMC, dataYear=year, jesUncert="All", jetType = "AK4PFchs")
     fatJetCorrector = createJMECorrector(isMC=isMC, dataYear=year, jesUncert="All", jetType = "AK8PFPuppi")
-    p=PostProcessor(".",testfilelist, None, None,[H4LCppModule(), jetmetCorrector(), fatJetCorrector()], provenance=False, fwkJobReport=False,haddFileName="nano_M125_cpp.root", jsonInput=jsonFileName, maxEntries=entriesToRun, prefetch=DownloadFileToLocalThenRun, outputbranchsel="keep_and_drop_data.txt")
+    modulesToRun.extend([jetmetCorrector(), fatJetCorrector()])
+
+    p=PostProcessor(".",testfilelist, None, None, modules = modulesToRun, provenance=True, fwkJobReport=False,haddFileName="skimmed_nano_data.root", jsonInput=jsonFileName, maxEntries=entriesToRun, prefetch=DownloadFileToLocalThenRun, outputbranchsel="keep_and_drop_data.txt")
 
 p.run()
 print "DONE"