A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is
Sapsan is a framework designed to make Machine Learning (ML) more accessible in the study of turbulence, with a focus on astrophysical applications. Sapsan includes modules to load, filter, subsample, batch, and split the data from hydrodynamic (HD) simulations for training and validation. Next, the framework includes built-in conventional and physically-motivated estimators that have been used for turbulence modeling. This ties into Sapsan's custom estimator module, aimed at designing a customdoi:10.21105/joss.03199 fatcat:zjhqlahgxbh5pbzi3cfxkmzc44