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@mj-will mj-will released this 08 Aug 10:03
· 6 commits to release-0.13.x since this release
v0.13.0
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Release of nessai v0.13.0

This release reworks how the normalising flow and reparameterisations in nessai are configured and introduces a new feature for the importance nested sampler. It also includes several experimental features in a new experimental submodule. We have also added explicit support for numpy 2.0 and dropped support for Python 3.8.

Changes to normalising flow

Normalising flows are now configured using two dictionaries flow_config and training_config, see the documentation for how to migrate to the new format. The old format is still supported but will be removed in a future release.

Changes to reparameterisations

Reparameterisations are now only configurable via the reparameterisations keyword argument. rescale_parameters, boundary_inversion, inversion_type, rescale_bounds update_bounds, detect_edges, detect_edges_kwargs have all been removed. All of these options are still accessible via the reparameterisations configuration. The default reparameterisation has also now changed to z-score, which can handle unbounded priors.

New importance nested sampling feature

The importance nested sampler now supports unit hyper-cube mappings that do not result in a uniform prior in the unit hypercube, see the new example for details

Other minor changes

  • The insertion indices plots have been improved
  • The default seaborn style has been changed to avoid plotting issues on some clusters
  • There is now experimental support for using flow from glasflow directly
  • Numpy 2.0 is now supported
  • Dropped support for Python 3.8

Full Changelog: v0.12.0...v0.13.0

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