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Published March 30, 2022 | Version v1.2.0
Software Open

joshspeagle/dynesty: v1.2.0

Authors/Creators

  • 1. University of Toronto
  • 2. Zymergen
  • 3. University of Southampton
  • 4. Minerva University
  • 5. Harvard-Smithsonian Center for Astrophysics
  • 6. @Esri
  • 7. Instituto de Astrofisica de Canarias
  • 8. Harvard University
  • 9. Perimeter Institute (@PerimeterInstitute)
  • 10. LPI ASC
  • 11. Institut Néel, CNRS
  • 12. Albert Einstein Institute - Hannover
  • 13. European Spallation Source
  • 14. University of Newcastle
  • 15. HeidelbergCement
  • 16. Weights & Biases
  • 17. Space Telescope Science Institute
  • 18. The Pennsylvania State University
  • 19. Lancaster University
  • 20. Northwestern University
  • 21. American Museum of Natural History
  • 22. MIT

Description

This version has multiple changes that should improve stability and speed. Some of the main changes include also

  • The default dynamic sampling behaviour has been changed to focus on the effective number of posterior samples as opposed to KL divergence.
  • The rstagger sampler has been removed and the default choice of the sampler may be different compared to previous releases depending on the dimensionality of the problem.
  • dynesty should now provide 100% reproduceable results if the rstate object is provided. It needs to be a new generation numpy Random Generator (as opposed to numpy.RandomState).

Most of the changes in the release have been contributed by Sergey Koposov who has joined the dynesty project. A more detailed list of changes is available in the changelog

Files

joshspeagle/dynesty-v1.2.0.zip

Files (29.4 MB)

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Additional details

Related works

Is supplement to
https://github.com/joshspeagle/dynesty/tree/v1.2.0 (URL)