Releases: joshspeagle/dynesty
v2.1.4
This is bug-fix release.
The main user-visible changes is that npdim= option of dynesty is removed. Also because of the code change, you will not be able to resume previous dynesty runs from earlier (<2.1.3) dynesty versions.
Detailed changelog is below:
- Get rid of npdim option that at some point may have allowed the prior transformation to return higher dimensional vector than the inputs. Note that due to this change, restoring the checkpoint from previous version of the dynesty won't be possible) (issues #456, #457) (original issue reported by @MichaelDAlbrow, fixed by @segasai )
Fixed
- Fix the way the additional arguments are treated when working with dynesty's pool. Previously those only could have been passed through dynesty.pool.Pool() constructor. Now they can still be provided directly to the sampler (not recommended) ( #464 , reported by @eteq, fixed by @segasai )
- change the .ptp() method to np.ptp() function as it is deprecated in numpy 2.0 ( #478 , reported and patched by @joezuntz)
- Fix an error if you use run_nested() several times (i.e. with maxiter option) while using blob=True. ( #475 , reported by @carlosRmelo)
Contributors
Assets 2
v2.1.3
v2.1.2
v2.1.1
This is a minor bug fix release with some other small changes.
The changes concern initialisation of live-points in the beginning of the run, boundary updates and resuming of runs.
See the changelog for more details.
v2.1.0
This a major release with a significant change of the sampler. It is now able to correctly sample likelihood functions with plateaus, (i.e likelihood functions with areas where likelihood value is exactly the same).
The previous behaviour also led to inaccurate log(Z) estimates if some fraction of the prior volume had log(P)=-LARGENUMBER
v2.0.3
This is a release with a major performance bug fix for the dynamical sampler
A major performance regression has been discovered that lead to dynamic nested sampling batches becoming slower and slower. The regression was introduced in 1.2 and can easily lead to a factor of several slower performance if a large number of batches is used. ( see #415 )
Some small fixes related to resuming of interrupted sampling were applied as well.
v2.0.2
Minor bug fix release.
- When checkpointing is on the dynamic sampler will always checkpoint in the end of the run_nested() irrespective of checkpoint_time
- Equally weighted samples are now randomly shuffled ( #408 )
- The live_points option was somewhat broken when blob option was introduced requiring a tuple of 4 elements irrespective of whether your likelihood returns blobs or not. Now if you use blob=True and want to provide live_points you need to provide 4 elements (u,v,logl,blobs). If you use blob=False you will need to provide just 3 elements as before (u,v,logl)
v2.0.1
v2.0.0
This is a major release with several significant improvements.
- The implementation of the check-points to save progress and allow restarting of fits.
- A new simple interface to obtain equally weighted samples directly from results object.
- Allow likelihood functions to return additional computed quantities (blobs) that will be saved together with samples.
- Random slice sampling now supports interval doubling scheme which may increase the performance in the case of bad posteriors.
See the full changelog and links to the documentation of the new features here
https://dynesty.readthedocs.io/en/v2.0.0/#changelog