YODA is a lightweight C++ and Python library for histogramming and statistical analysis, designed for use in particle physics workflows. It supports reproducible, high-performance data analysis and is the foundation for data handling in tools like Rivet.

Data Analysis
High performance computing
Statistics
+ 1

C++
TeX
Python
+ 2

LHAPDF

LHAPDF (The Les Houches Accord PDFs) is a standardised library for accessing parton distribution functions (PDFs) in high-energy physics. It provides a common interface to a wide range of PDF sets, enabling consistent and reproducible predictions in collider simulations and analyses.

Collider physics
Deep Inelastic Scattering
Interpolation
+ 1

C++
Python
M4Sugar
+ 2

matchms

Python library for fuzzy comparison of mass spectrum data and other Python objects

Big data
Optimized data handling

Python
TeX
Batchfile
+ 1

116

Rivet

Rivet is a toolkit for validation and analysis of Monte Carlo event generators in particle physics. It provides a library of reusable analysis components and a large collection of published analyses, enabling precise, reproducible comparisons between theory and experimental data.

Big data
Collider physics
Data Analysis
+ 2

C++
Gnuplot
C
+ 2

spec2vec

spec2vec is a novel similarity measure for comparing mass spectrometry data, which learns peak representations using Word2Vec.

Machine learning
Text analysis & natural language processing

Python
Batchfile
Makefile

213