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The official repository for ROOT: analyzing, storing and visualizing big data, scientifically

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README.md

Original

About

ROOT is a unified software package for the storage, processing, and analysis of scientific data: from its acquisition to the final visualization in form of highly customizable, publication-ready plots. It is reliable, performant and well supported, easy to use and obtain, and strives to maximize the quantity and impact of scientific results obtained per unit cost, both of human effort and computing resources.

ROOT provides a very efficient storage system for data models, that demonstrated to scale at the Large Hadron Collider experiments: Exabytes of scientific data are written in columnar ROOT format. ROOT comes with histogramming capabilities in an arbitrary number of dimensions, curve fitting, statistical modelling, minimization, to allow the easy setup of a data analysis system that can query and process the data interactively or in batch mode, as well as a general parallel processing framework, RDataFrame, that can considerably speed up an analysis, taking full advantage of multi-core and distributed systems.

ROOT is performance critical software written in C++ and enables rapid prototyping powered by a unique C++ compliant interpreter called Cling. Cling also enables performant C++ type introspection which is a building block of automatic interoperability with Python. Thanks to its dynamic Python bindings, leveraging the cppyy technology, ROOT offers efficient, on-demand C++/Python interoperability in a uniform cross-language execution environment.

ROOT fully embraces open-source, it's made with passion by its community, for the benefit of its community.

License: LGPL v2.1+ CII Best Practices

Contribution Guidelines

Cite

If you use ROOT for your work, we kindly ask you to cite it as:

Rene Brun and Fons Rademakers, ROOT - An Object Oriented Data Analysis Framework,
Proceedings AIHENP'96 Workshop, Lausanne, Sep. 1996,
Nucl. Inst. & Meth. in Phys. Res. A 389 (1997) 81-86.

See the reference in BibTeX format here.

Live Demo for CERN Users

See more screenshots on our gallery.

Installation and Getting Started

See https://root.cern/install for installation instructions. For instructions on how to build ROOT from these source files, see https://root.cern/install/build_from_source.

Our "Getting started with ROOT" page is then the perfect place to get familiar with ROOT.

Help and Support

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