Corrfunc: Blazing fast correlation functions on the CPU
Abstract: Corrfunc is a suite of high-performance clustering routines. The code can compute a variety of spatial correlation functions on Cartesian geometry as well Landy-Szalay calculations for spatial and angular correlation functions on a spherical geometry and is useful for, for example, exploring the galaxy-halo connection. The code is written in C and can be used on the command-line, through the supplied python extensions, or the C API.
Credit: Sinha, Manodeep; Garrison, Lehman
Site: https://github.com/manodeep/Corrfunc
https://ui.adsabs.harvard.edu/abs/2019arXiv191108275S
Bibcode: 2017ascl.soft03003S
Preferred citation method: http://adsabs.harvard.edu/abs/2017ascl.soft03003S
ID: ascl:1703.003