Merge pull request #52 from cms-l1-dpg/new_rate_fwk

Add new rate table tools

.gitignore

@@ -1,4 +1,5 @@
 **/__pycache__/*
+*.pyc
 **/*.png
 **/.DS_Store
 **/*.parquet

rates/table/README.md

@@ -1,16 +1,35 @@
-# Rate table for the Phase-2 L1 Trigger Menu 
-To run the rate table, for example for the L1 TDR results, do
-```
-python run.py cfg/v10_TRIDAS_newThresholds_LHCCReview
-```
+# L1 Phase2 Menu Tools: Rate Table
 
-For the firmware-based emulators under 123x, utilise `FBE_noMu_L1TDRMET_mhtSeed_123x` (`FBE_noMu_L1TDRMET_mhtSeed_123x_singleJetEta5` only includes forward region for the singleJet seed).
-
-To display the rates in an easy-to-read format, run
-```
-python3 printRateTable.py -c cfg/v10_TRIDAS_newThresholds_LHCCReview -r out/2020-05-26-MENU-LHCCReview-BugFix_v10_TRIDAS_newThresholds_LHCCReview/thresholds/menu.csv
-```
-You can also edit the `CFG_RATE_COMBOS` dictionary at the top of
-the file and run the script without any arguments `python3 printRateTable.py`.
-This way multiple rate tables can be compared quickly. 
+The rates table can be produced using the following command:
 
+    ./rate_table.py cfg/v29/v29_cfg.yml
+
+where the `cfg` argument specifies the structure of the config file to be used.
+
+An example of config can be found in `./cfg/v29_cfg.yml` and it is a `yaml` file
+with the following structure:
+
+	MenuV29:
+	  version: "V29"
+	  sample: "/eos/cms/store/group/dpg_trigger/comm_trigger/L1Trigger/alobanov/phase2/menu/ntuples/13X/v29_RelVal/RelValTTbar_14TeV/RelVal_13X_TT_200PU_crab_v29_13X_RelVal_FixGenTree/230710_081407/L1NtuplePhaseII_Step1_hadd.root"
+	  menu_config: "cfg/v29/v29_16Seeds_Final_clean_cfg.yml"
+	  scalings:
+	      scalings_path: "/eos/user/m/mbonanom/www/Postdoc/L1PhaseII/V29/scalings/"
+	      collect_scalings: False
+	      scalings_outdir: "scalings_input/V29/"
+	      scalings_file: "scalings.yml"
+	  table:
+	      table_fname: "rates_16Seeds_Final"
+	      table_outdir: "rates_tables/V29"
+
+The block above defines entirely a menu table (`MenuV29` in the example above).
+Several blocks (with a different title) can be specified in the config if one wants to produce
+rate tables for different menu configurations.
+
+The other fields that can be specified are:
+* `version`: specifies the version of the ntuples used;
+* `sample`: specifies the sample to be used;
+* `menu_config`: user-defined config of the menu seeds. See `cfg/v29/v29_16Seeds_Final_clean_cfg.yml` for an example. The current example replicates the menu config implemented in `cfg/v29/v29_16Seeds_Final`;
+* `scalings`: this block defines the properties of the scalings file to be used. If `collect_scalings` is `False`,
+the scalings file in `scalings_outdir` will be used (`scalings.yml` in the example above corresponds to the `v29` scalings used for AR). If `collect_scalings` is `True`, then the `Scaler` (cf `scaler.py`) class is used to create a new scalings file, with the name specified in `scalings_file` (which will be located in `scalings_outdir`), starting from the per-object `.txt` scalings saved under `scalings_path` (i.e. the output of the `objectPerformance` code);
+* `table`: this block defines the properties of the rates table that will be dumped to a `.csv` file. The table will be saved under `table_outdir` with `table_fname` as name.

rates/table/cfg/v29/v29_16Seeds_Final_clean_cfg.yml

@@ -0,0 +1,208 @@
+L1_DoubleEGEle:
+  cross_masks:
+  - ak.where(abs(leg2.phi-leg1.phi)<math.pi, np.sqrt(abs(abs(leg2.eta)-abs(leg1.eta))**2 + abs(leg2.phi-leg1.phi)**2), np.sqrt(abs(abs(leg2.eta)-abs(leg1.eta))**2 + (2*math.pi-abs(leg2.phi-leg1.phi))**2)) > 0.1
+  leg1:
+    leg_mask:
+    - leg1.offline_pt >= 37
+    - abs(leg1.eta)<2.4
+    - leg1.passeseleid * (abs(leg1.eta)<1.5) + leg1.passessaid * (abs(leg1.eta) >= 1.5)
+    # - ak.where(abs(leg1.eta)<1.5, leg1.passeseleid, leg1.passessaid)
+    obj: EG
+  leg2:
+    leg_mask:
+    - leg2.offline_pt >= 24
+    - abs(leg2.eta)<2.4
+    - leg2.passeseleid * (abs(leg2.eta)<1.5) + leg2.passessaid * (abs(leg2.eta) >= 1.5)
+    # - ak.where(abs(leg2.eta)<1.5, leg2.passeseleid, leg2.passessaid)
+    obj: EG
+L1_SingleEGEle:
+  cross_masks: []
+  leg1:
+    leg_mask:
+    - leg1.offline_pt >= 51.0
+    - abs(leg1.eta)<2.4
+    - leg1.passeseleid * (abs(leg1.eta)<1.5) + leg1.passessaid * (abs(leg1.eta) >= 1.5)
+    obj: EG
+L1_SinglePfJet:
+  cross_masks: []
+  leg1:
+    leg_mask:
+    - leg1.offline_pt > 230.0
+    - leg1.et>25
+    - abs(leg1.eta)<2.4
+    obj: seededConePuppiJet
+L1_SingleTkEle:
+  cross_masks: []
+  leg1:
+    leg_mask:
+    - leg1.offline_pt >= 36.0
+    - abs(leg1.eta)<2.4
+    - leg1.passeseleid
+    # - leg1.passeseleid > 0
+    obj: tkElectron
+L1_SingleTkEleIso:
+  cross_masks: []
+  leg1:
+    leg_mask:
+    - leg1.offline_pt >= 28.0
+    - leg1.passeseleid>=0
+    - ak.where(abs(leg1.eta)<1.479, leg1.trkiso<0.13, leg1.trkiso<0.28)
+    obj: tkIsoElectron
+L1_SingleTkMu:
+  cross_masks: []
+  leg1:
+    leg_mask:
+    - leg1.offline_pt > 22.0
+    - abs(leg1.eta)<2.4
+    obj: gmtTkMuon
+L1_SingleTkPhoIso:
+  cross_masks: []
+  leg1:
+    leg_mask:
+    - leg1.offline_pt >= 36.0
+    - abs(leg1.eta)<2.4
+    - ak.where(abs(leg1.eta)<1.5, leg1.passeseleid, leg1.passesphoid)
+    - ak.where(abs(leg1.eta)<1.479, leg1.trkiso<0.25, leg1.trkiso<0.205)
+    obj: tkPhoton
+L1_TkEleIso_EG:
+  cross_masks:
+  - leg2.deltaR(leg1) > 0.1
+  leg1:
+    leg_mask:
+    - leg1.offline_pt > 22.0
+    - abs(leg1.eta)<2.4
+    - leg1.passeseleid >= 0
+    - ak.where(abs(leg1.eta)<1.479, leg1.trkiso<0.13, leg1.trkiso<0.28)
+    obj: tkIsoElectron
+  leg2:
+    leg_mask:
+    - leg2.offline_pt > 12.0
+    - abs(leg2.eta)<2.4
+    - ak.where(abs(leg2.eta)<1.5, leg2.passeseleid, leg2.passessaid)
+    obj: EG
+L1_TripleTkMu:
+  cross_masks:
+  - abs(leg2.z0-leg1.z0)<1
+  - abs(leg3.z0-leg1.z0)<1
+  leg1:
+    leg_mask:
+    - leg1.pt>5
+    - abs(leg1.eta)<2.4
+    - leg1.qual>0
+    obj: gmtTkMuon
+  leg2:
+    leg_mask:
+    - leg2.pt>3
+    - abs(leg2.eta)<2.4
+    - leg2.qual>0
+    obj: gmtTkMuon
+  leg3:
+    leg_mask:
+    - leg3.pt>3
+    - abs(leg3.eta)<2.4
+    - leg3.qual>0
+    obj: gmtTkMuon
+L1_DoubleTkEle:
+  cross_masks:
+  - abs(leg2.zvtx-leg1.zvtx)<1
+  leg1:
+    leg_mask:
+    - leg1.offline_pt >= 25.0
+    - abs(leg1.eta)<2.4
+    - (((leg1.passeseleid) * (abs(leg1.eta)<1.479)) + ((abs(leg1.eta)>1.479)))
+    obj: tkElectron
+  leg2:
+    leg_mask:
+    - leg2.offline_pt >= 12.0
+    - abs(leg2.eta)<2.4
+    - (((leg2.passeseleid) * (abs(leg2.eta)<1.479)) + ((abs(leg2.eta)>1.479)))
+    obj: tkElectron
+L1_DoubleTkMu:
+  cross_masks:
+  - abs(leg1.z0-leg2.z0)<1
+  leg1:
+    leg_mask:
+    - leg1.offline_pt > 15.0
+    - abs(leg1.eta)<2.4
+    obj: gmtTkMuon
+  leg2:
+    leg_mask:
+    - leg2.pt > 7.0
+    - abs(leg2.eta)<2.4
+    - leg2.qual > 0
+    obj: gmtTkMuon
+L1_DoubleTkPhoIso:
+  cross_masks: []
+  leg1:
+    leg_mask:
+    - leg1.offline_pt > 22.0
+    - abs(leg1.eta)<2.4
+    - ak.where(abs(leg1.eta)<1.5, leg1.passeseleid, leg1.passesphoid)
+    - ak.where(abs(leg1.eta)<1.479, leg1.trkiso<0.25, leg1.trkiso<0.205)
+    obj: tkPhoton
+  leg2:
+    leg_mask:
+    - leg2.offline_pt > 12.0
+    - abs(leg2.eta)<2.4
+    - ak.where(abs(leg2.eta)<1.5, leg2.passeseleid, leg2.passesphoid)
+    - ak.where(abs(leg2.eta)<1.479, leg2.trkiso<0.25, leg2.trkiso<0.205)
+    obj: tkPhoton
+L1_PFHTT:
+  cross_masks: []
+  leg1:
+    leg_mask:
+    # - leg1.pt > 372.9
+    - leg1.offline_pt > 450
+    obj: seededConePuppiHT
+L1_PFHTT_QuadJet:
+  cross_masks: []
+  leg1:
+    leg_mask:
+    - leg1.offline_pt > 400.0
+    obj: seededConePuppiHT
+  leg2:
+    leg_mask:
+    - leg2.offline_pt > 70.0
+    - leg2.et>25.0
+    - abs(leg2.eta)<2.4
+    obj: seededConePuppiJet
+  leg3:
+    leg_mask:
+    - leg3.offline_pt > 55.0
+    - leg3.et>25.0
+    - abs(leg3.eta)<2.4
+    obj: seededConePuppiJet
+  leg4:
+    leg_mask:
+    - leg4.offline_pt > 40.0
+    - leg4.et>25.0
+    - abs(leg4.eta)<2.4
+    obj: seededConePuppiJet
+  leg5:
+    leg_mask:
+    - leg5.offline_pt > 40.0
+    - leg5.et>25.0
+    - abs(leg5.eta)<2.4
+    obj: seededConePuppiJet
+L1_PFIsoTau_PFIsoTau:
+  cross_masks:
+  # - ak.where(abs(leg2.phi-leg1.phi)<math.pi, np.sqrt(abs(abs(leg2.eta)-abs(leg1.eta))**2 + abs(leg2.phi-leg1.phi)**2), np.sqrt(abs(abs(leg2.eta)-abs(leg1.eta))**2 + (2*math.pi-abs(leg2.phi-leg1.phi))**2)) > 0.5
+  - leg1.deltaR(leg2) > 0.5
+  leg1:
+    leg_mask:
+    - leg1.offline_pt > 52.0
+    - abs(leg1.eta)<2.172
+    - leg1.passloosenn>0
+    obj: nnTau
+  leg2:
+    leg_mask:
+    - leg2.offline_pt > 52.0
+    - abs(leg2.eta)<2.172
+    - leg2.passloosenn>0
+    obj: nnTau
+L1_PFMet:
+  cross_masks: []
+  leg1:
+    leg_mask:
+    - leg1.offline_pt > 200.0
+    obj: puppiMET

rates/table/cfg/v29/v29_16seed_cfg.yml

@@ -0,0 +1,12 @@
+MenuV29:
+  version: "V29"
+  sample: "/eos/cms/store/group/dpg_trigger/comm_trigger/L1Trigger/alobanov/phase2/menu/ntuples/13X/v29_RelVal/RelValTTbar_14TeV/RelVal_13X_TT_200PU_crab_v29_13X_RelVal_FixGenTree/230710_081407/L1NtuplePhaseII_Step1_hadd.root"
+  menu_config: "cfg/v29/v29_16Seeds_Final_clean_cfg.yml"
+  scalings:
+      scalings_path: "/eos/user/m/mbonanom/www/Postdoc/L1PhaseII/V29/scalings/"
+      collect_scalings: False
+      scalings_outdir: "scalings_input/V29/"
+      scalings_file: "scalings.yml"
+  table:
+      table_fname: "rates_16Seeds_Final"
+      table_outdir: "rates_tables/V29"