harmonic learns an approximate harmonic mean estimator (referred to as a "learnt harmonic mean estimator") from posterior distribution samples to compute the marginal likelihood required for Bayesian model selection. Using a large number of independent Markov chain Monte Carlo (MCMC) chains from another package such as emcee (ascl:1303.002), harmonic uses importance sampling to learn a new target distribution in order to optimize an approximate harmonic estimator while minimizing its variance.

massmappy recovers convergence mass maps on the celestial sphere from weak lensing cosmic shear observations. It relies on SSHT (ascl:2207.034) and HEALPix (ascl:1107.018) to handle sampled data on the sphere. The spherical Kaiser-Squires estimator is implemented.