In order to help analyzers understand which track fits correspond to the same set of hits, we should use SelectSameTrack so that we can add a leaf that analyzers can more easily choose the best fit hypothesis for a given set of hits. We should add trk.id and trk.rank leaves so we would end up with something like:
trk.pdg [ 11, 13, -11, -13 ]
trk.id [ 0, 0, 0, 1 ]
trk.rank [ 0.99, 0.2, 0.2, 0.99 ]
The algorithm for trk.rank is to be determined but would give the ranking of each hypothsis for that track.
Added 1/21/2026: note that we want the determination of ID and rank to be performed within an art module as a data product that is then read by the EventNtupleMaker module
In order to help analyzers understand which track fits correspond to the same set of hits, we should use SelectSameTrack so that we can add a leaf that analyzers can more easily choose the best fit hypothesis for a given set of hits. We should add
trk.idandtrk.rankleaves so we would end up with something like:The algorithm for trk.rank is to be determined but would give the ranking of each hypothsis for that track.
Added 1/21/2026: note that we want the determination of ID and rank to be performed within an art module as a data product that is then read by the EventNtupleMaker module