However, up until now, FITS libraries like CFITSIO and Astropy have all relied on static compression settings, making the use of several algorithms depending on context quite tedious. EleFits introduces compression strategies, which allow the user to define an adaptive heuristic for compressing FITS files dynamically. The strategy is built upon an arbitrary number of pre- or user-defined compression settings, and then automatically applied.

To assess the performance of our implementation, we have run a quantitative benchmark over a range of FITS files which cover a variety of use cases, from various space programs. The results show that the ability to automatically adapt the algorithms and parameters on-the-fly to the data improves the compression ratios.