Turns your trees into tables (ie. reads ROOT TTrees, writes summary Pandas DataFrames)
fast-carpenter can:
Be controlled using YAML-based config files
Define new variables
Cut out events or define phase-space “regions”
Produce histograms stored as CSV files using multiple weighting schemes
Make use of user-defined stages to manipulate the data
Powered by:
AlphaTwirl (presently): to run the dataset splitting
Atuproot: to adapt AlphaTwirl to use uproot
uproot: to load ROOT Trees into memory as numpy arrays
fast-flow: to manage the processing config files
fast-curator: to orchestrate the lists of datasets to be processed
Espresso: to keep the developer(s) writing code
A tool from the Faster Analysis Software Taskforce: http://fast-hep.web.cern.ch/
Installation and usage
Visit the documentation for full details.
2 maintainers
Metadata
2 maintainers
Release files for fast-carpenter 0.23.0
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Total release size: 81.7 kB
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