BEM predicts the radius of exoplanets based on their planetary and stellar parameters. The code uses the random forests machine learning algorithm to derive reliable radii, especially for planets between 4 R⊕ and 20 R⊕ for which the error is under 25%. BEM computes error bars for the radius predictions and can also create diagnostic plots.

Mister plotter (mr-plotter) creates paper-quality mass-radius diagrams based on a wide range of state-of-the-art models of planetary interiors and atmospheres. It can be used to contextualize planets and infer their possible internal structures. It can also be used to search for correlations at a population level with its color-coding option based on any property collected in the NASA Exoplanet Archive, PlanetS, and Exoplanet.eu catalogs. mr-plotter can also produce article-ready two-column plots.

kima fits Keplerian curves to a set of RV measurements, using the Diffusive Nested Sampling (ascl:1010.029) algorithm to sample the posterior distribution for the model parameters. Additionally, the code can calculate the fully marginalized likelihood of a model with a given number of Keplerians and also infer the number of Keplerian signals detected in a given dataset. kima implements dedicated models for different analyses of a given dataset. The models share a common organization, but each has its own parameters (and thus priors) and settings.