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[ascl:1912.007] anesthetic: Nested sampling visualization

anesthetic brings together tools for processing nested sampling chains, leveraging standard scientific python libraries. The code provides computation of Bayesian evidences, Kullback-Liebler divergences and Bayesian model dimensionalities, marginalized 1d and 2d plots, and dynamic replaying of nested sampling. anesthetic was designed primarily for use with nested sampling outputs, although it can be used for normal MCMC chains.

Code site:
https://github.com/williamjameshandley/anesthetic https://anesthetic.readthedocs.io/en/latest/
Used in:
https://ui.adsabs.harvard.edu/abs/2019PhRvD.100d3504H
Described in:
https://ui.adsabs.harvard.edu/abs/2019JOSS....4.1414H
Bibcode:
2019ascl.soft12007H

Views: 253

ascl:1912.007
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