Add FatJet corrections from nonres, add SingleLep plots

AnaProd/anaTupleDef.py

@@ -363,6 +363,7 @@ def LegVar(var_name, var_expr, var_type=None, var_cond=None, default=0):
             f"SelectedFatJet_{fatjetVar}",
             f"Take(tmp_SelectedFatJet_{fatjetVar}, SelectedFatJet_idxSorted)",
         )
+    dfw.Define("SelectedFatJet_isValid", "RVecB (SelectedFatJet_pt.size(), true)")
     subjet_obs = []
     subjet_obs.extend(SubJetObservables)
     if not isData:

Analysis/hh_bbww.py

@@ -186,11 +186,12 @@ def defineLeptonPreselection(self):
             "leadingleppT &&  subleadleppT && Single_lep_trg && tightlep && ( lep2_legType < 1 ||  diLep_mass > 12 )",
         )
 
-    def defineJetSelections(self):
+    def defineJetSelections(self, isData):
         self.df = self.df.Define("Njets", "centralJet_pt.size()")
         self.df = self.df.Define("jet1_isvalid", "Njets > 0")
         self.df = self.df.Define("jet2_isvalid", "Njets > 1")
         self.df = self.df.Define("fatjet_isvalid", "SelectedFatJet_pt.size() > 0")
+        self.df = self.df.Define("fatbjet_isValid", "fatjet_isvalid")
         self.df = self.df.Define(
             "fatsubjet1_isvalid",
             "(SelectedFatJet_SubJet1_isValid == 1  && SelectedFatJet_SubJet1_pt > 20 && abs(SelectedFatJet_SubJet1_eta) < 2.5)",
@@ -200,54 +201,44 @@ def defineJetSelections(self):
             "(SelectedFatJet_SubJet2_isValid == 1 && SelectedFatJet_SubJet2_pt > 20 && abs(SelectedFatJet_SubJet2_eta) < 2.5)",
         )
 
-        self.df = self.df.Define("bjet1_pt", "centralJet_pt[0]")
-        self.df = self.df.Define("bjet1_phi", "centralJet_phi[0]")
-        self.df = self.df.Define("bjet1_eta", "centralJet_eta[0]")
-        self.df = self.df.Define("bjet1_mass", "centralJet_mass[0]")
-        self.df = self.df.Define(
-            "bjet1_btagPNetB", "jet1_isvalid ? centralJet_btagPNetB[0] : -1.0"
-        )
-        self.df = self.df.Define(
-            "bjet1_idbtagPNetB", "jet1_isvalid ? centralJet_idbtagPNetB[0] : -1.0"
-        )
-
-        self.df = self.df.Define("bjet2_pt", "centralJet_pt[1]")
-        self.df = self.df.Define("bjet2_phi", "centralJet_phi[1]")
-        self.df = self.df.Define("bjet2_eta", "centralJet_eta[1]")
-        self.df = self.df.Define("bjet2_mass", "centralJet_mass[1]")
-        self.df = self.df.Define(
-            "bjet2_btagPNetB", "jet2_isvalid ? centralJet_btagPNetB[1] : -1.0"
-        )
-        self.df = self.df.Define(
-            "bjet2_idbtagPNetB", "jet2_isvalid ? centralJet_idbtagPNetB[1] : -1.0"
-        )
+        bjet_vars = ["pt", "phi", "eta", "mass", "btagPNetB", "idbtagPNetB"]
+        for var in bjet_vars:
+            self.df = self.df.Define(
+                f"bjet1_{var}", f"jet1_isvalid ? centralJet_{var}[0] : -1.0"
+            )
+            self.df = self.df.Define(
+                f"bjet2_{var}", f"jet2_isvalid ? centralJet_{var}[1] : -1.0"
+            )
 
-        self.df = self.df.Define("wjet1_pt", "Njets > 2 ? centralJet_pt[2] : -10.0")
-        self.df = self.df.Define("wjet1_phi", "Njets > 2 ? centralJet_phi[2] : -10.0")
-        self.df = self.df.Define("wjet1_eta", "Njets > 2 ? centralJet_eta[2] : -10.0")
-        self.df = self.df.Define("wjet1_mass", "Njets > 2 ? centralJet_mass[2] : -10.0")
+        wjet_vars = ["pt", "phi", "eta", "mass"]
+        for var in wjet_vars:
 
-        self.df = self.df.Define("wjet2_pt", "Njets > 3 ? centralJet_pt[3] : -10.0")
-        self.df = self.df.Define("wjet2_phi", "Njets > 3 ? centralJet_phi[3] : -10.0")
-        self.df = self.df.Define("wjet2_eta", "Njets > 3 ? centralJet_eta[3] : -10.0")
-        self.df = self.df.Define("wjet2_mass", "Njets > 3 ? centralJet_mass[3] : -10.0")
+            self.df = self.df.Define(
+                f"wjet1_{var}", f"Njets > 2 ? centralJet_{var}[2] : -10.0"
+            )
+            self.df = self.df.Define(
+                f"wjet2_{var}", f"Njets > 3 ? centralJet_{var}[3] : -10.0"
+            )
 
-        self.df = self.df.Define(
-            "fatbjet1_pt", "fatjet_isvalid ? SelectedFatJet_pt[0] : -10.0"
-        )
-        self.df = self.df.Define(
-            "fatbjet1_phi", "fatjet_isvalid ? SelectedFatJet_phi[0] : -10.0"
-        )
-        self.df = self.df.Define(
-            "fatbjet1_eta", "fatjet_isvalid ? SelectedFatJet_eta[0] : -10.0"
-        )
-        self.df = self.df.Define(
-            "fatbjet1_mass", "fatjet_isvalid ? SelectedFatJet_mass[0] : -10.0"
-        )
-        self.df = self.df.Define(
-            "fatbjet1_XbbVsQCD",
-            "fatjet_isvalid ? SelectedFatJet_particleNet_XbbVsQCD[0] : -10.0",
-        )
+        fatjet_vars = [
+            "pt",
+            "phi",
+            "eta",
+            "mass",
+            "particleNet_XbbVsQCD",
+            "particleNetWithMass_HbbvsQCD",
+        ]
+        fatjet_mc_vars = ["hadronFlavour"]
+        for var in fatjet_vars:
+            self.df = self.df.Define(
+                f"fatbjet_{var}", f"fatjet_isvalid ? SelectedFatJet_{var}[0] : -10.0"
+            )
+        if not isData:
+            for var in fatjet_mc_vars:
+                self.df = self.df.Define(
+                    f"fatbjet_{var}",
+                    f"fatjet_isvalid ? SelectedFatJet_{var}[0] : -10.0",
+                )
 
         self.df = self.df.Define(
             "bsubjet1_btagDeepB",
@@ -525,12 +516,12 @@ def AddDNNVariables(df):
     return df
 
 
-def PrepareDfForHistograms(dfForHistograms):
+def PrepareDfForHistograms(dfForHistograms, isData):
     dfForHistograms.df = defineAllP4(dfForHistograms.df)
     dfForHistograms.df = AddDNNVariables(dfForHistograms.df)
     dfForHistograms.defineTriggers()
     dfForHistograms.defineLeptonPreselection()
-    dfForHistograms.defineJetSelections()
+    dfForHistograms.defineJetSelections(isData)
     dfForHistograms.defineQCDRegions()
     dfForHistograms.defineControlRegions()
     dfForHistograms.defineCategories()

Analysis/histTupleDef.py

@@ -3,6 +3,7 @@
 from FLAF.Common.HistHelper import *
 from Corrections.Corrections import Corrections
 from Corrections.CorrectionsCore import getSystName, central
+from FLAF.Common.Setup import Setup
 
 if __name__ == "__main__":
     sys.path.append(os.environ["ANALYSIS_PATH"])
@@ -31,10 +32,12 @@ def analysis_setup(setup):
     analysis = importlib.import_module(f"{analysis_import}")
 
 
-def GetDfw(df, global_params):
+def GetDfw(df, setup, dataset_name):
+    global_params = setup.global_params
+    isData = dataset_name == "data"
     period = global_params["era"]
     dfw = analysis.DataFrameBuilderForHistograms(df, global_params, period)
-    new_dfw = analysis.PrepareDfForHistograms(dfw)
+    new_dfw = analysis.PrepareDfForHistograms(dfw, isData)
     return new_dfw
 
 

config/Run3_2022/processes.yaml

@@ -484,8 +484,30 @@ QCD_PT:
 #       file: QCD_ABCD.py
 #   supress_negative_bins: true
 
-custom_CI:
-  name: "custom for CI and test purposes"
-  color: "kAzure+10"
+custom_CI_Background:
+  name: "CI -- Background"
+  color: "kGreen-3"
+  datasets:
+    - TTto2L2Nu
+
+custom_CI_Signal:
+  name: "CI -- Signal"
+  color: "kBlack"
+  is_meta_process: true
+  meta_setup:
+    dataset_name_pattern: XtoYHto2B2Wto2B2L2Nu_MX_(\d+)_MY_125
+    parameters: [ MASS ]
+    process_name: XtoHHto2B2W_2L_${MASS}
+    name_pattern: Xto2B2W 2L ${MASS} GeV (x50)
+    to_plot:
+      - [ '300' ]
+    plot_color: [ "kBlack" ]
+    channels: [ "eE", "eMu", "muMu" ]
   datasets:
     - XtoYHto2B2Wto2B2L2Nu_MX_300_MY_125
+
+custom_CI_Data:
+  name: "CI -- Data"
+  color: "kAzure+10"
+  datasets:
+    - Muon_Run2022C

config/Run3_2022EE/processes.yaml

@@ -468,8 +468,30 @@ QCD_PT:
     - QCD_PT_2400to3200
     - QCD_PT_3200
 
-custom_CI:
-  name: "custom for CI and test purposes"
-  color: "kAzure+10"
+custom_CI_Background:
+  name: "CI -- Background"
+  color: "kGreen-3"
+  datasets:
+    - TTto2L2Nu
+
+custom_CI_Signal:
+  name: "CI -- Signal"
+  color: "kBlack"
+  is_meta_process: true
+  meta_setup:
+    dataset_name_pattern: XtoYHto2B2Wto2B2L2Nu_MX_(\d+)_MY_125
+    parameters: [ MASS ]
+    process_name: XtoHHto2B2W_2L_${MASS}
+    name_pattern: Xto2B2W 2L ${MASS} GeV (x50)
+    to_plot:
+      - [ '300' ]
+    plot_color: [ "kBlack" ]
+    channels: [ "eE", "eMu", "muMu" ]
   datasets:
     - XtoYHto2B2Wto2B2L2Nu_MX_300_MY_125
+
+custom_CI_Data:
+  name: "CI -- Data"
+  color: "kAzure+10"
+  datasets:
+    - Muon_Run2022E

config/Run3_2023/processes.yaml

@@ -299,9 +299,30 @@ QCD_PT:
     - QCD_PT_2400to3200
     - QCD_PT_3200
 
+custom_CI_Background:
+  name: "CI -- Background"
+  color: "kGreen-3"
+  datasets:
+    - TTto2L2Nu
 
-custom_CI:
-  name: "custom for CI and test purposes"
-  color: "kAzure+10"
+custom_CI_Signal:
+  name: "CI -- Signal"
+  color: "kBlack"
+  is_meta_process: true
+  meta_setup:
+    dataset_name_pattern: XtoYHto2B2Wto2B2L2Nu_MX_(\d+)_MY_125
+    parameters: [ MASS ]
+    process_name: XtoHHto2B2W_2L_${MASS}
+    name_pattern: Xto2B2W 2L ${MASS} GeV (x50)
+    to_plot:
+      - [ '300' ]
+    plot_color: [ "kBlack" ]
+    channels: [ "eE", "eMu", "muMu" ]
   datasets:
     - XtoYHto2B2Wto2B2L2Nu_MX_300_MY_125
+
+custom_CI_Data:
+  name: "CI -- Data"
+  color: "kAzure+10"
+  datasets:
+    - Muon0_Run2023C_v1

config/Run3_2023BPix/processes.yaml

@@ -289,9 +289,30 @@ QCD_PT:
     - QCD_PT_2400to3200
     - QCD_PT_3200
 
+custom_CI_Background:
+  name: "CI -- Background"
+  color: "kGreen-3"
+  datasets:
+    - TTto2L2Nu
 
-custom_CI:
-  name: "custom for CI and test purposes"
-  color: "kAzure+10"
+custom_CI_Signal:
+  name: "CI -- Signal"
+  color: "kBlack"
+  is_meta_process: true
+  meta_setup:
+    dataset_name_pattern: XtoYHto2B2Wto2B2L2Nu_MX_(\d+)_MY_125
+    parameters: [ MASS ]
+    process_name: XtoHHto2B2W_2L_${MASS}
+    name_pattern: Xto2B2W 2L ${MASS} GeV (x50)
+    to_plot:
+      - [ '300' ]
+    plot_color: [ "kBlack" ]
+    channels: [ "eE", "eMu", "muMu" ]
   datasets:
     - XtoYHto2B2Wto2B2L2Nu_MX_300_MY_125
+
+custom_CI_Data:
+  name: "CI -- Data"
+  color: "kAzure+10"
+  datasets:
+    - Muon0_Run2023D_v1

config/ci_custom.yaml

@@ -6,6 +6,10 @@ compute_unc_variations: true
 compute_unc_histograms: true
 store_noncentral: true
 phys_model: TestModel
+
+QCDRegions:
+  - OS_Iso
+
 variables:
   - lep1_pt
   - SingleLep_DeepHME_mass
@@ -16,3 +20,9 @@ variables:
   - name: lep1_pt_vs_eta
     vars: [ lep1_pt, lep1_eta ]
     plot_task: False
+
+  - name: DL_DNN_m300_vs_HME
+    vars: [ DNNParametric_DL_NoHME_M300_Signal, DoubleLep_DeepHME_mass ]
+
+  - name: SL_DNN_m300_vs_HME
+    vars: [ DNNParametric_SL_NoHME_M300_Signal, SingleLep_DeepHME_mass ]

config/global.yaml

@@ -17,6 +17,11 @@ corrections:
     stage: HistTuple
     mode: SF
   ele: { stage: HistTuple }
+  fatjet:
+    stage: HistTuple # AnaTuple
+    ana: bbWW
+    tagger: particleNetWithMass_HbbvsQCD
+    fatJetName: fatbjet # SelectedFatJet
   muScaRe: { stage: AnaTuple, mu_pt_for_ScaReApplication: "nano" }
   eleES: { stage: AnaTuple }
   MC_Lumi_pu: { stage: AnaTuple }
@@ -362,11 +367,11 @@ variables:
   - bjet2_mass
   - bjet2_btagPNetB
 
-  - fatbjet1_pt
-  - fatbjet1_eta
-  - fatbjet1_phi
-  - fatbjet1_mass
-  - fatbjet1_XbbVsQCD
+  - fatbjet_pt
+  - fatbjet_eta
+  - fatbjet_phi
+  - fatbjet_mass
+  - fatbjet_XbbVsQCD
 
   - bb_mass_PNetRegPtRawCorr_PNetRegPtRawCorrNeutrino
 
@@ -392,11 +397,11 @@ variables:
   - lep2_Electron_pfRelIso03_all
   - mT_fix
 
-  # # High Level Single Lepton
+  # High Level Single Lepton
   - SingleLep_DeepHME_mass
   - SingleLep_DeepHME_mass_error
 
-  # # High Level Double Lepton
+  # High Level Double Lepton
   - DoubleLep_DeepHME_mass
   - DoubleLep_DeepHME_mass_error
 
@@ -429,3 +434,33 @@ variables:
 
   - name: DL_DNN_m1000_vs_HME
     vars: [ DNNParametric_DL_NoHME_M1000_Signal, DoubleLep_DeepHME_mass ]
+
+  - name: SL_DNN_m300_vs_HME
+    vars: [ DNNParametric_SL_NoHME_M300_Signal, SingleLep_DeepHME_mass ]
+
+  - name: SL_DNN_m400_vs_HME
+    vars: [ DNNParametric_SL_NoHME_M400_Signal, SingleLep_DeepHME_mass ]
+
+  - name: SL_DNN_m500_vs_HME
+    vars: [ DNNParametric_SL_NoHME_M500_Signal, SingleLep_DeepHME_mass ]
+
+  - name: SL_DNN_m550_vs_HME
+    vars: [ DNNParametric_SL_NoHME_M550_Signal, SingleLep_DeepHME_mass ]
+
+  - name: SL_DNN_m600_vs_HME
+    vars: [ DNNParametric_SL_NoHME_M600_Signal, SingleLep_DeepHME_mass ]
+
+  - name: SL_DNN_m650_vs_HME
+    vars: [ DNNParametric_SL_NoHME_M650_Signal, SingleLep_DeepHME_mass ]
+
+  - name: SL_DNN_m700_vs_HME
+    vars: [ DNNParametric_SL_NoHME_M700_Signal, SingleLep_DeepHME_mass ]
+
+  - name: SL_DNN_m800_vs_HME
+    vars: [ DNNParametric_SL_NoHME_M800_Signal, SingleLep_DeepHME_mass ]
+
+  - name: SL_DNN_m900_vs_HME
+    vars: [ DNNParametric_SL_NoHME_M900_Signal, SingleLep_DeepHME_mass ]
+
+  - name: SL_DNN_m1000_vs_HME
+    vars: [ DNNParametric_SL_NoHME_M1000_Signal, SingleLep_DeepHME_mass ]