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Scikit-HEP project - welcome!

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The Scikit-HEP project is a community-driven and community-oriented project with the aim of providing Particle Physics at large with an ecosystem for data analysis in Python. Read more β†’

Basics:

Manipulate arrays of complex data structures as easily as Numpy.
Units and constants in the HEP system of units.

Data manipulation and interoperability:

Easy conversions between different styles of expressions.
Interface between ROOT and NumPy.
Module for conveniently loading/saving ROOT files as pandas DataFrames.
Minimalist ROOT I/O in pure Python and Numpy.
Pythonic behaviours for non-I/O related ROOT classes.

Histogramming:

Convert between histogram representations
Python bindings for the C++14 Boost::Histogram library.
Versatile, high-performance histogram toolkit for Numpy.
❌ Deprecated

Particles and decays:

Describe and convert particle decays between digital representations.
PDG particle data and identification codes.

Fitting:

GPU/OpenMP fitting in Python and C++.
🀝 Affiliated
MINUIT from Python - Fitting like a boss.
Cost function builder. For fitting distributions.
❌ Deprecated
Scalable Pythonic fitting
🀝 Affiliated

Statistics:

Statistics tools and utilities.
pure-Python implementation of HistFactory models.

Interface to HEP libraries:

Interface between Pythia and NumPy.
Next generation Python bindings for HepMC3.
Interface between FastJet and NumPy.
Lightweight Python interface to read Les Houches Event (LHE) files.

Machine Learning:

Collection of tools and algorithms to enable conversion of HEP ML to mass usage model.

Visualization:

Plotting and styling helpers for matplotlib.
View Vega/Vega-Lite plots in your web browser from local or remote Python processes.

Miscellaneous:

A collection of helpers for building binary Python wheels on Azure.
CERN’s ROOT on Conda-Forge.
🀝 Affiliated
Toolset of interfaces and tools for Particle Physics. To become a metapackage.
Common package to provide example files (e.g., ROOT) for testing and developing packages against.

In some cases, the packages provide a bridge between different technologies and/or popular packages from the Python scientific software stack.