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Type: Bayesian inference package
Authors: Benjamin Audren, Thejs Brinckman, Julien Lesgourgues
Abstract: MontePython (Bayesian inference package for cosmology, modular and interfaced with CLASS)

MontePython is a Monte Carlo code in Python designed for parameter inference in cosmology. It is modular, featuring several samplers (Metropolis-Hastings, importance sampling, Fisher matrix mode, and interfaces with Multicast, PolyChord and CosmoHammer), many likelihoods (CMB, LSS, BAO, supernova, etc.), and an interface with CLASS. Its Metropolis-hastings algorithm is boosted with a ‘super update’ feature that finds automatically the best jumping factor as a function fo the posteriori properties. It also features fast-slow parameters with oversampling. In ‘info’ mode it creates plots and files showing the results.

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