Streamlined data analysis in Python
Abstract
Python is a particularly appealing language to carry out data analysis, owing in part to its user-friendly character as well as its access to well maintained and powerful libraries like NumPy and SciPy. Still, for the purpose of analyzing data in a lattice QCD context, some desirable functionality is missing from these libraries. Moreover, scripting languages tend to be slower than compiled ones. To help address these points we present the AnalysisToolbox, a collection of Python modules to facilitate lattice QCD data analysis. Some highlighted features include general-purpose jackknife and bootstrap routines; modules for reading in and storing gauge configurations; a module to carry out hadron resonance gas model calculations; and convenience wrappers for SciPy integration, curve fitting, and splines. These features are sped up behind the scenes using parallelization and just-in-time compilation.
Cite
@article{arxiv.2308.06652,
title = {Streamlined data analysis in Python},
author = {Luis Altenkort and David Anthony Clarke and Jishnu Goswami and Hauke Sandmeyer},
journal= {arXiv preprint arXiv:2308.06652},
year = {2024}
}
Comments
9 pages, 1 figure, presented at the 40th International Symposium on Lattice Field Theory