Jim Pivarski, known for innovative software in DIANA/HEP, IRIS-HEP and other projects, will give tutorials on how to process and analyze Root files with pure Python libraries: uproot and awkward array
The tutorials are aimed for anyone who would like to develop the EIC Science and detectors further using modern data science tools in Python. An output of ESCalate framework will be used as an example. However, the tutorial will be very general and useful for studies in other frameworks.
The tutorials will go through the full spectrum of what might be needed for the analysis, such as:
Getting data
Exploring a TFile and TTrees
Iterating over chunks of large datasets and over many files
Reading histograms and other objects
Writing objects and TTrees back to root files
Manipulating data
Iteration in Python vs array-at-a-time operations
Filtering (cuts) events and particles with advanced selections
Flattening for plots and regularizing (rpad, clip) to NumPy for machine learning
Broadcasting flat arrays and jagged arrays
Combinatorics and reducing from combinations.
Imperative, but still fast, programming inNumba
Grafting jagged data onto Pandas
NumExpr, Autograd, and other third-party libraries
