Merge pull request #15 from nurfikri89/eff_analysis_nano_run2

Update branch for UL2017 SFs with ULNanoAODv2 input
cms-jet · May 23, 2021 · ef72f58 · ef72f58
2 parents 0015cfd + 28f5c5d
commit ef72f58
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Showing 34 changed files with 1,819 additions and 233 deletions.
diff --git a/Analyzer/.gitignore b/Analyzer/.gitignore
@@ -1 +1,5 @@
 nbinnorj.cc
+MakeHistosAtBatch.sh
+MakeHistosAtBatch.sh.sub
+SkimNtuplesAtBatch.sh
+SkimNtuplesAtBatch.sh.sub
diff --git a/Analyzer/MakeHistograms.py → Analyzer/Deprecated/MakeHistograms.py b/Analyzer/MakeHistograms.py → Analyzer/Deprecated/MakeHistograms.py
@@ -102,15 +102,20 @@ def main(sample_name, useSkimNtuples, systStr, useNewTraining=False):
   df = df.Define("probeJet_eta",            probeJetStr+"_eta")
   df = df.Define("probeJet_abseta",         "fabs("+probeJetStr+"_eta)")
   df = df.Define("probeJet_phi",            probeJetStr+"_phi")
+  df = df.Define("probeJet_dilep_dphi",     probeJetStr+"_dilep_dphi")
   df = df.Define("probeJet_puIdDisc",       probeJetStr+"_puIdDisc")
+  #
+  # Guide on how to read the pileup ID bitmap variable: 
+  # https://twiki.cern.ch/twiki/bin/viewauth/CMS/PileupJetID#miniAOD_and_nanoAOD
+  #
   df = df.Define("probeJet_puIdFlag_Loose", probeJetStr+"_puId & (1 << 2)")
   df = df.Define("probeJet_puIdFlag_Medium",probeJetStr+"_puId & (1 << 1)")
   df = df.Define("probeJet_puIdFlag_Tight", probeJetStr+"_puId & (1 << 0)")
-  df = df.Define("probeJet_dilep_dphi",     probeJetStr+"_dilep_dphi")
-  if isMC:
-    df = df.Define("probeJet_passGenMatch",probeJetStr+"_gen_match")
   if isUL:
     df = df.Define("probeJet_puIdDiscOTF",  probeJetStr+"_puIdDiscOTF")
+  if isMC:
+    df = df.Define("probeJet_passGenMatch",probeJetStr+"_gen_match")
+
   #
   #
   #
@@ -121,8 +126,6 @@ def main(sample_name, useSkimNtuples, systStr, useNewTraining=False):
   # 
   if not isUL: #EOY
     #
-    # Guide on how to read the pileup ID bitmap variable: 
-    # https://twiki.cern.ch/twiki/bin/viewauth/CMS/PileupJetID#miniAOD_and_nanoAOD
     # NOTE: The pileup ID decision flag stored in NanoAOD (v7 and earlier) is based on 
     # the 80X BDT training and working point (as in the parent MiniAOD).
     #
@@ -141,10 +144,14 @@ def main(sample_name, useSkimNtuples, systStr, useNewTraining=False):
       df = df.Define("probeJet_puIdMedium_pass", "PUJetID_80XCut_WPMedium("+argStr+")")
       df = df.Define("probeJet_puIdTight_pass",  "PUJetID_80XCut_WPTight("+argStr+")")
   else: #UL
-      argStr = "probeJet_pt,probeJet_eta,probeJet_puIdDiscOTF"
-      df = df.Define("probeJet_puIdLoose_pass",  "PUJetID_106XUL17Cut_WPLoose("+argStr+")")
-      df = df.Define("probeJet_puIdMedium_pass", "PUJetID_106XUL17Cut_WPMedium("+argStr+")")
-      df = df.Define("probeJet_puIdTight_pass",  "PUJetID_106XUL17Cut_WPTight("+argStr+")")
+    #
+    # NOTE: In ULNanoAODv2 UL17, the pileup jet ID flag is based on the UL17 training
+    # and cut values.
+    #
+    if not useNewTraining:
+      df = df.Define("probeJet_puIdLoose_pass",  "probeJet_puIdFlag_Loose")
+      df = df.Define("probeJet_puIdMedium_pass", "probeJet_puIdFlag_Medium")
+      df = df.Define("probeJet_puIdTight_pass",  "probeJet_puIdFlag_Tight")
   #
   #
   #

diff --git a/Analyzer/MakeHistogramsHisto3D.py b/Analyzer/MakeHistogramsHisto3D.py
@@ -152,7 +152,6 @@ def main(sample_name, useSkimNtuples, systStr, useNewTraining=False):
       df = df.Define("passNJetSel","(nJetSel>=1)&&(nJetSelPt30Eta5p0<=1)&&(nJetSelPt20Eta2p4<=1)")
     else:
       df = df.Define(systStr+"passNJetSel","("+systStrPre+"nJetSel>=1)&&("+systStrPre+"nJetSelPt30Eta5p0<=1)&&("+systStrPre+"nJetSelPt20Eta2p4<=1)")
-
   #
   # Define flags for lepton channels if need to check by channel
   #
@@ -166,15 +165,19 @@ def main(sample_name, useSkimNtuples, systStr, useNewTraining=False):
   df = df.Define("probeJet_eta",            probeJetStr+"_eta")
   df = df.Define("probeJet_abseta",         "fabs("+probeJetStr+"_eta)")
   df = df.Define("probeJet_phi",            probeJetStr+"_phi")
+  df = df.Define("probeJet_dilep_dphi",     probeJetStr+"_dilep_dphi")
   df = df.Define("probeJet_puIdDisc",       probeJetStr+"_puIdDisc")
+  #
+  # Guide on how to read the pileup ID bitmap variable: 
+  # https://twiki.cern.ch/twiki/bin/viewauth/CMS/PileupJetID#miniAOD_and_nanoAOD
+  #
   df = df.Define("probeJet_puIdFlag_Loose", probeJetStr+"_puId & (1 << 2)")
   df = df.Define("probeJet_puIdFlag_Medium",probeJetStr+"_puId & (1 << 1)")
   df = df.Define("probeJet_puIdFlag_Tight", probeJetStr+"_puId & (1 << 0)")
-  df = df.Define("probeJet_dilep_dphi",     probeJetStr+"_dilep_dphi")
-  if isMC:
-    df = df.Define("probeJet_passGenMatch", probeJetStr+"_gen_match")
   if isUL:
     df = df.Define("probeJet_puIdDiscOTF",  probeJetStr+"_puIdDiscOTF")
+  if isMC:
+    df = df.Define("probeJet_passGenMatch", probeJetStr+"_gen_match")
   #
   #
   #
@@ -185,8 +188,6 @@ def main(sample_name, useSkimNtuples, systStr, useNewTraining=False):
   #
   if not isUL: #EOY
     #
-    # Guide on how to read the pileup ID bitmap variable: 
-    # https://twiki.cern.ch/twiki/bin/viewauth/CMS/PileupJetID#miniAOD_and_nanoAOD
     # NOTE: The pileup ID decision flag stored in NanoAOD (v7 and earlier) is based on 
     # the 80X BDT training and working point (as in the parent MiniAOD).
     #
@@ -205,11 +206,13 @@ def main(sample_name, useSkimNtuples, systStr, useNewTraining=False):
       df = df.Define("probeJet_puIdMedium_pass", "PUJetID_80XCut_WPMedium("+argStr+")")
       df = df.Define("probeJet_puIdTight_pass",  "PUJetID_80XCut_WPTight("+argStr+")")
   else: #UL
-    if useNewTraining:
-      argStr = "probeJet_pt,probeJet_eta,probeJet_puIdDiscOTF"
-      df = df.Define("probeJet_puIdLoose_pass",  "PUJetID_106XUL17Cut_WPLoose("+argStr+")")
-      df = df.Define("probeJet_puIdMedium_pass", "PUJetID_106XUL17Cut_WPMedium("+argStr+")")
-      df = df.Define("probeJet_puIdTight_pass",  "PUJetID_106XUL17Cut_WPTight("+argStr+")")
+    #
+    # NOTE: In ULNanoAODv2 UL17, the pileup jet ID flag is based on the UL17 training
+    # and cut values.
+    #
+    df = df.Define("probeJet_puIdLoose_pass",  "probeJet_puIdFlag_Loose")
+    df = df.Define("probeJet_puIdMedium_pass", "probeJet_puIdFlag_Medium")
+    df = df.Define("probeJet_puIdTight_pass",  "probeJet_puIdFlag_Tight")
   #
   #
   #
@@ -394,10 +397,10 @@ def ProjectTH3(h3, HistoDict, systStrPost):
   ak4Systematics=[]
   if isMC:
     ak4Systematics=[
-      # "jesTotalUp",
-      # "jesTotalDown",
-      # "jerUp",
-      # "jerDown"
+      "jesTotalUp",
+      "jesTotalDown",
+      "jerUp",
+      "jerDown"
     ]
   # Don't do ak4Systematics for MG+HW and AMCNLO
   if "MG_HW" in args.sample: ak4Systematics=[]

diff --git a/Analyzer/RunLocal_MakeHistograms.sh b/Analyzer/RunLocal_MakeHistograms.sh
@@ -2,65 +2,26 @@
 NCORES=4
 
 SAMPLES=(
-# MC16_DY_MG
-# MC17_DY_MG
-# MC18_DY_MG
-# MC16_DY_AMCNLO
-# MC17_DY_AMCNLO
-# MC18_DY_AMCNLO
-# MC16_DY_MG_HW
-# MC17_DY_MG_HW
-# MC18_DY_MG_HW
-# Data16B_DoubleMuon
-# Data16C_DoubleMuon
-# Data16D_DoubleMuon
-# Data16E_DoubleMuon
-# Data16F_DoubleMuon
-# Data16G_DoubleMuon
-# Data16H_DoubleMuon
-# Data17B_DoubleMuon
-# Data17C_DoubleMuon
-# Data17D_DoubleMuon
-# Data17E_DoubleMuon
-# Data17F_DoubleMuon
-# Data18A_DoubleMuon
-# Data18B_DoubleMuon
-# Data18C_DoubleMuon
-# Data18D_DoubleMuon
-# Data16B_DoubleEG
-# Data16C_DoubleEG
-# Data16D_DoubleEG
-# Data16E_DoubleEG
-# Data16F_DoubleEG
-# Data16G_DoubleEG
-# Data16H_DoubleEG
-# Data17B_DoubleEG
-# Data17C_DoubleEG
-# Data17D_DoubleEG
-# Data17E_DoubleEG
-# Data17F_DoubleEG
-# Data18A_EGamma
-# Data18B_EGamma
-# Data18C_EGamma
-# Data18D_EGamma
-)
-SAMPLES=(
-MCUL17_DY_MG
-# MCUL17_DY_AMCNLO
-# DataUL17B_DoubleMuon
-# DataUL17C_DoubleMuon
-# DataUL17D_DoubleMuon
-# DataUL17E_DoubleMuon
+DataUL17B_DoubleMuon
+DataUL17C_DoubleMuon
+DataUL17D_DoubleMuon
+DataUL17E_DoubleMuon
 DataUL17F_DoubleMuon
+DataUL17B_DoubleEG
+DataUL17C_DoubleEG
+DataUL17D_DoubleEG
+DataUL17E_DoubleEG
+DataUL17F_DoubleEG
+MCUL17_DY_MG
+MCUL17_DY_AMCNLO
 )
 
 #
 # Make histograms from ntuples
 #
 for SAMPLE in ${SAMPLES[@]}
 do
-  python MakeHistograms.py  --sample $SAMPLE --cores $NCORES --useSkimNtuples --useNewTraining
-  # python MakeHistogramsHisto3D.py  --sample $SAMPLE --cores $NCORES --useSkimNtuples --useNewTraining
+  python MakeHistogramsHisto3D.py  --sample $SAMPLE --cores $NCORES --useSkimNtuples --useNewTraining
 done
 
 

diff --git a/Analyzer/RunLocal_SkimNtuples.sh b/Analyzer/RunLocal_SkimNtuples.sh
@@ -2,62 +2,18 @@
 NCORES=4
 
 SAMPLES=(
-# MC16_DY_MG
-# MC17_DY_MG
-# MC18_DY_MG
-# MC16_DY_AMCNLO
-# MC17_DY_AMCNLO
-# MC18_DY_AMCNLO
-# MC16_DY_MG_HW
-# MC17_DY_MG_HW
-# MC18_DY_MG_HW
-# Data16B_DoubleMuon
-# Data16C_DoubleMuon
-# Data16D_DoubleMuon
-# Data16E_DoubleMuon
-# Data16F_DoubleMuon
-# Data16G_DoubleMuon
-# Data16H_DoubleMuon
-# Data16B_DoubleEG
-# Data16C_DoubleEG
-# Data16D_DoubleEG
-# Data16E_DoubleEG
-# Data16F_DoubleEG
-# Data16G_DoubleEG
-# Data16H_DoubleEG
-# Data17B_DoubleMuon
-# Data17C_DoubleMuon
-# Data17D_DoubleMuon
-# Data17E_DoubleMuon
-# Data17F_DoubleMuon
-# Data17B_DoubleEG
-# Data17C_DoubleEG
-# Data17D_DoubleEG
-# Data17E_DoubleEG
-# Data17F_DoubleEG
-# Data18A_DoubleMuon
-# Data18B_DoubleMuon
-# Data18C_DoubleMuon
-# Data18D_DoubleMuon
-# Data18A_EGamma
-# Data18B_EGamma
-# Data18C_EGamma
-# Data18D_EGamma
-# DataUL17B_DoubleMuon
-# DataUL17C_DoubleMuon
-# DataUL17D_DoubleMuon
-# DataUL17E_DoubleMuon
-# DataUL17F_DoubleMuon
-)
-
-SAMPLES=(
-# MCUL17_DY_MG
-# MCUL17_DY_AMCNLO
-# DataUL17B_DoubleMuon
-# DataUL17C_DoubleMuon
-# DataUL17D_DoubleMuon
-# DataUL17E_DoubleMuon
-# DataUL17F_DoubleMuon
+DataUL17B_DoubleMuon
+DataUL17C_DoubleMuon
+DataUL17D_DoubleMuon
+DataUL17E_DoubleMuon
+DataUL17F_DoubleMuon
+DataUL17B_DoubleEG
+DataUL17C_DoubleEG
+DataUL17D_DoubleEG
+DataUL17E_DoubleEG
+DataUL17F_DoubleEG
+MCUL17_DY_MG
+MCUL17_DY_AMCNLO
 )
 
 #