refactor: remove custom scalar in classes

[AJPfleger]

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[github-actions]

📊: Physics performance monitoring for aff3957

Full contents

physmon summary

• ✅ Particles fatras
• ✅ Particles geant4
• ✅ Particles ttbar
• ✅ Vertices ttbar
• ✅ Truth tracking (KF)
• ✅ Truth tracking (GSF)
• ✅ Truth tracking (GX2F)
• ✅ Truth tracking (KF refit)
• ✅ Truth tracking (GSF refit)
• ✅ CKF finding performance | trackfinding | single muon | truth smeared seeding
• ✅ CKF fitting performance | trackfinding | single muon | truth smeared seeding
• ✅ CKF track summary | trackfinding | single muon | truth smeared seeding
• ✅ Seeding trackfinding | single muon | truth estimated seeding
• ✅ CKF finding performance | trackfinding | single muon | truth estimated seeding
• ✅ CKF fitting performance | trackfinding | single muon | truth estimated seeding
• ✅ CKF track summary | trackfinding | single muon | truth estimated seeding
• ✅ Seeding trackfinding | single muon | default seeding
• ✅ CKF finding performance | trackfinding | single muon | default seeding
• ✅ CKF fitting performance | trackfinding | single muon | default seeding
• ✅ CKF track summary | trackfinding | single muon | default seeding
• ✅ Seeding trackfinding | single muon | orthogonal seeding
• ✅ CKF finding performance | trackfinding | single muon | orthogonal seeding
• ✅ CKF fitting performance | trackfinding | single muon | orthogonal seeding
• ✅ CKF track summary | trackfinding | single muon | orthogonal seeding
• ✅ Seeding trackfinding | 4 muon x 50 vertices | default seeding
• ✅ CKF finding performance | trackfinding | 4 muon x 50 vertices | default seeding
• ✅ CKF fitting performance | trackfinding | 4 muon x 50 vertices | default seeding
• ✅ CKF track summary | trackfinding | 4 muon x 50 vertices | default seeding
• ✅ Ambisolver finding performance | trackfinding | 4 muon x 50 vertices | default seeding
• ✅ IVF notime | trackfinding | 4 muon x 50 vertices | default seeding
• ✅ AMVF gauss notime | trackfinding | 4 muon x 50 vertices | default seeding
• ✅ AMVF grid time | trackfinding | 4 muon x 50 vertices | default seeding
• ✅ Seeding trackfinding | ttbar with 200 pileup | default seeding
• ✅ CKF finding performance | trackfinding | ttbar with 200 pileup | default seeding
• ✅ CKF fitting performance | trackfinding | ttbar with 200 pileup | default seeding
• ✅ CKF track summary | trackfinding | ttbar with 200 pileup | default seeding
• ✅ Ambisolver finding performance | trackfinding | ttbar with 200 pileup | default seeding
• ✅ AMVF gauss notime | trackfinding | ttbar with 200 pileup | default seeding
• ✅ AMVF grid time | trackfinding | ttbar with 200 pileup | default seeding

[AJPfleger]

@paulgessinger , I removed the scalars (and everything depending on them) for the cases you mentioned in #3873 . Below are some more cases. Should we remove them as well or was it intentional to keep them in?

./Core/include/Acts/Propagator/ConstrainedStep.hpp:46:  using Scalar = ActsScalar;
./Core/include/Acts/EventData/GenericCurvilinearTrackParameters.hpp:33:  using Scalar = ActsScalar;
./Core/include/Acts/EventData/GenericBoundTrackParameters.hpp:39:  using Scalar = ActsScalar;
./Core/include/Acts/EventData/GenericFreeTrackParameters.hpp:36:  using Scalar = ActsScalar;
./Core/include/Acts/EventData/TrackStateProxy.hpp:85:  using Scalar = ActsScalar;
./Core/include/Acts/EventData/TrackStateProxy.hpp:108:  using Scalar = ActsScalar;
./Core/include/Acts/EventData/TrackStateProxy.hpp:122:  using Scalar = ActsScalar;
./Plugins/Hashing/include/Acts/Plugins/Hashing/HashingTraining.ipp:43:  using Scalar = Acts::ActsScalar;
./Plugins/Hashing/include/Acts/Plugins/Hashing/HashingAnnoy.ipp:31:  using Scalar = Acts::ActsScalar;
./Tests/UnitTests/Fatras/Kernel/SimulationActorTests.cpp:100:  using Scalar = Acts::ActsScalar;

[paulgessinger]

@AJPfleger If they're not configurable, and indeed if there's no real reason why we'd need them to be configurable, I would argue for removing these aliases.

[sonarqubecloud]

Quality Gate passed

Issues
5 New issues
0 Accepted issues

Measures
0 Security Hotspots
72.9% Coverage on New Code
0.0% Duplication on New Code

See analysis details on SonarQube Cloud