megabeast is a Bayesian model that fits ensembles of BEAST results for single stars to derive stellar population and dust/star geometry parameters. Thus, the combination of the BEAST and megaBEAST is a Hierarchical Bayesian model. The goal is to create maps of stellar and dust parameters of galaxies (e.g., A(V) or stellar age).

Reporting Issues

If you have found a bug in megabeast please report it by creating a new issue on the megabeast GitHub issue tracker.

Please include an example that demonstrates the issue sufficiently so that the developers can reproduce and fix the problem. You may also be asked to provide information about your operating system and a full Python stack trace. The developers will walk you through obtaining a stack trace if it is necessary.


Like the Astropy project, megabeast is made both by and for its users. We accept contributions at all levels, spanning the gamut from fixing a typo in the documentation to developing a major new feature. We welcome contributors who will abide by the Python Software Foundation Code of Conduct.

megabeast follows the same workflow and coding guidelines as Astropy. The following pages will help you get started with contributing fixes, code, or documentation (no git or GitHub experience necessary):

For the complete list of contributors please see the megabeast contributors page on Github.


megabeast.ensemble_model Module

Functions providing the ensemble model and likelihood functions


lnlike(phi, beast_dust_priors, lnp_data, …) Compute the log(likelihood) for the ensemble parameters
lnprior(phi) Compute the log(priors) for the ensemble parameters
lnprob(phi, beast_dust_priors, lnp_data, …) Compute the log(likelihood) for the ensemble parameters

megabeast.beast_data Module

Functions for interacting with the BEAST model


extract_beast_data(beast_data, lnp_data) Read in the beast data for the locations where the lnp values were saved
read_beast_data(filename, noise_filename[, …]) Read in the beast data needed by all the pixels
read_lnp_data(filename, nstars) Read in the sparse lnp for all the stars in the hdf5 file