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  • Introduce step-by-step event-selection efficiency evaluation
  • Support soft-coded event-selection chains via eventSelections
  • Add consistent event- and jet-level histograms aligned with the same cuts

This enables a generic and reusable framework for computing event-selection efficiencies for cross-section normalization.

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github-actions bot commented Dec 2, 2025

O2 linter results: ❌ 3 errors, ⚠️ 3 warnings, 🔕 0 disabled

if (jetderiveddatautilities::selectCollision(collision, eventSelectionBits, skipMBGapEvents)) {
hasCustomEventSel = true;
}
if ((trackOccupancyInTimeRangeMin < collision.trackOccupancyInTimeRange()) && (collision.trackOccupancyInTimeRange() < trackOccupancyInTimeRangeMax)) {
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these could be filters in your task I think? Also isnt this for pp? Why do you need occupancy?

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My intention was to design the task so that it remains compatible with heavy-ion datasets as well, where occupancy-related selections are often needed.

Since Run 3 analyses require an additional correction step compared to Run 2, I expect several analysers (Archita, Aimeric, Wenhui, etc.) will need this framework, so I aimed for a generic and reusable structure.

I have revised the PR so that occupancy is now implemented as an eraly filter via configuration.

@nzardosh nzardosh merged commit 6a2dd81 into AliceO2Group:master Dec 3, 2025
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2 participants