This software library implements formulas to calculate, given an experimental setup, the expected x-ray fluorescence intensities. The library accounts for secondary and tertiary excitation, K, L and M shell emission lines and de-excitation cascade effects. The basic implementation is written in C++ and a Python binding is provided.

This package provides a set of helpers for matplotlib to more easily produce plots typically needed in HEP as well as style them in way that's compatible with current collaboration requirements (ROOT-like plots for CMS, ATLAS, LHCb, ALICE).

Smilei is a user-friendly electromagnetic particle-in-cell code for the kinetic simulation of plasmas. Co-developed by physicists and computer scientists, it is designed for high-performance on the most recent supercomputing architectures. Smilei is applied to a wide range of applications, from laser-plasma interaction, to accelerator physics, space physics and astrophysics.

CLHEP is a set of HEP-specific foundation and utility classes such as random generators, physics vectors, geometry and linear algebra. CLHEP is structured in a set of packages independent of any external package.

This package provides example files (e.g. ROOT) for testing and developing HEP packages against.

This package provides a small and thin Python interface to read Les Houches Event (LHE) files.

DCAP (dCache access protocol) client library: DCAP is the native random access I/O protocol for files within dCache. In addition to the usual data transfer mechanisms, it supports all necessary file metadata and name space manipulation operations.

ROOT is a data analysis framework developed by CERN for tasks such as data storage, processing, and visualization. It provides tools for histograms, statistical tests, fitting, simulations, and machine learning. It can handle large datasets and uses a specialized file format.

This package provides a Python implementation of a statistical model for multi-bin histogram-based analysis and its interval estimation is based on the asymptotic formulas of "Asymptotic formulae for likelihood-based tests of new physics". The aim is also to support modern computational graph libraries such as PyTorch and TensorFlow in order to make use of features such as autodifferentiation and GPU acceleration.

VDT is a library of mathematical functions, implemented in double and single precision. The implementation is fast and with the aid of modern compilers (e.g. gcc 4.7) vectorisable. VDT exploits also Pade polynomials.

pythonocc provides 3D modeling and dataexchange features. It is intended for CAD/PDM/PLM/BIM development. It is based on the OpenCascade Technology modeling kernel.

pythonocc provides the following features:

• Full access from Python to almost all of the thousand OpenCascade C++ classes. Classes and methods/functions share the same names, and, as possible as it can be, the same signature;

• 3D visualization from the most famous Python Gui (tkinter, pyQt5 and 6, PySide2 and 6, wxPython);

• 3D visualization in a web browser using threejs or x3dom frameworks;

• 3D visualization and work within a jupyter notebook;

• Data exchange using most famous formats IGES/STEP/STL/PLY/OBJ/GLTF;

• Utility Python classes/methods for Topology operations, inertia computations, and more.

The HepMC package is an object oriented C++ event record for High Energy Physics Monte Carlo generators and simulation.

EGSnrc is a software toolkit to perform Monte Carlo simulation of ionizing radiation transport through matter. It models the propagation of photons, electrons and positrons with kinetic energies between 1 keV and 10 GeV, in homogeneous materials.

Davix aims to make the task of managing files overHTTP-based protocols simple. It is being developed by the IT-SDC-ID section at CERN, and while the project’s purpose is its use on the CERN grid, the functionality offered is generic.

CLHEP is a set of HEP-specific foundation and utility classes such as random generators, physics vectors, geometry and linear algebra. CLHEP is structured in a set of packages independent of any external package.

FabIO is an I/O library for images produced by 2D X-ray detectors and written in Python. FabIO support images detectors from a dozen of companies (including Mar, Dectris, ADSC, Hamamatsu, Oxford, …), for a total of 30 different file formats (like CBF, EDF, TIFF, …) and offers an unified interface to their headers (as a Python dictionary) and datasets (as a numpy ndarray of integers or floats).

CLHEP is a set of HEP-specific foundation and utility classes such as random generators, physics vectors, geometry and linear algebra. CLHEP is structured in a set of packages independent of any external package.

OpenBLAS is a Basic Linear Algebra Subprograms (BLAS) library forked from the GotoBLAS2-1.13 BSD version.

This package provides a library for statistical inference aiming to cover the needs High Energy Physics.

PyFAI is an azimuthal integration library that tries to be fast (as fast as C and even more using OpenCL and GPU). It is based on histogramming of the 2theta/Q positions of each (center of) pixel weighted by the intensity of each pixel, but parallel version uses a SparseMatrix-DenseVector multiplication. Neighboring output bins get also a contribution of pixels next to the border thanks to pixel splitting. Finally pyFAI provides also tools to calibrate the experimental setup using Debye-Scherrer rings of a reference compound.

Gyselalib++ is a collection of C++ components for writing gyrokinetic semi-lagrangian codes and similar as well as a collection of such codes.

Fief is an open-source platform to manage users and authentication in your applications.

Key features:

• Pre-built login and registration pages

• Users management dashboard

• SDK for the most popular languages and frameworks

• Integrations for the most popular no-code tools

Hydra is an open-source Python framework that simplifies the development of research and other complex applications. The key feature is the ability to dynamically create a hierarchical configuration by composition and override it through config files and the command line.

Key features:

• Hierarchical configuration composable from multiple sources

• Configuration can be specified or overridden from the command line

• Dynamic command line tab completion

• Run your application locally or launch it to run remotely

• Run multiple jobs with different arguments with a single command

dask-jobqueue makes it easy to deploy Dask on common job queuing systems typically found in high performance supercomputers, academic research institutions, and other clusters, like PBS, Slurm, MOAB, SGE, LSF, and HTCondor.