The following section will walk you through scheduling the muon analysis sequence, applying selection cuts, and writing them to the output ntuple. It follows the electron procedure closely, so many of the steps will not be spelled out explicitly.
Begin by scheduling the muon analysis sequence. Do this by adding
the following lines to the config.yaml
file:
# Define analysis muon container, specify Quality/Isolation working
# points, base pT/eta selection
Muons:
- containerName: 'AnaMuons'
WorkingPoint:
- selectionName: 'medium'
noEffSF: True
quality: 'Medium'
isolation: 'Loose_VarRad'
PtEtaSelection:
minPt: 27000.0
This schedules the implementation of muon identification and isolation requirements, momentum corrections, and the calculation of muon scale factors and systematic variations.
The muon sequence uses a
selectionName
ofmedium
, which means the resulting decoration isbaselineSelection_medium
.
As we did with electrons, we want to ensure that the muon information
is written to our final output. To do so, we will add to the existing
Thinning
and Output
blocks in config.yaml
file. Let’s start with
the thinning block. Add the following lines to the Thinning
block,
indented the same amount as the electrons information:
- containerName: 'AnaMuons'
outputName: 'OutMuons'
selectionName: 'medium'
Finally, add:
'mu_': 'OutMuons'
nested withing containers:
in the Output
block. Be sure to indent
this line as much as is the corresponding line for the electron containers.
Rerun your code, then re-examine your data ntuple. You should now be able to see new branches corresponding to muon information. Commit and push your changes when everything is running correctly.
Try different muon working points and see how much of an effect it has on your output.