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- SDF guide and documentation, particularly on using Jupyter notebooks interactively or through web interface (runs on top of nodes managed by SLURM)
- Training dataset dumper (used for producing h5 files from FTAG derivations) documentation and git (Prajita's fork, bjet_regression is the main branch)
- SALT documentation, SALT on SDF, puma git repo (used for plotting), and Umami docs (for postprocessing)
- SLAC GitLab group for plotting related code
- FTAG1 derivation definition (FTAG1.py)
Documents and notes
- GN1 June 2022 PUB note, nice slides from A. Duperrin
- Jannicke's thesis (chapter 4 on b-jets)
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We are using a custom fork of training-dataset-dumper, developed for producing h5 files for NN training based on FTAG derivations.
The custom fork is modified to store the truth jet pT via AntiKt4TruthDressedWZJets container.
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After compilation (note that one must build on Athena rather than AnalysisBase, as per the advanced usage page), you can run a local test with:
ca-dump-jer
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-c
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configs/ftag_jer.json
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<test_FTAG1_file>
- Add list of proposed features to add (available branches available in TDD docs)
- Truth particles (pt, eta, phi, ID) w/ pt>500 MeV
- ftagTruthOriginLabel
- ftagTruthTypeLabel
- ftagTruthVertexIndex
Some additional truth information for the tracks will be useful. The addition of fields under the decorate part of the config didn't work with FTAG derivations. Some predefined decorations are in TDD docs.
- Add truthTypeLabel (NoTruth=0, Other=1, Pion=2, Kaon=3, Electron=4, Muon=5, Photon=6)
A set of test mc21 FTAG1 files can be found on:
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