v0.22.0

The highlights of these release are interoperability of InferenceData and the new xarray.DataTree object and automatic inferring of dimension names from plates in the numpyro converter.

We have also done more testing of the arviz.preview module. Take a look at the migration guide if you want an early peek to the changes and improvements to come. You can treat arviz.preview as a beta release of ArviZ 1.0 so use carefully and keep an eye on the development. We hope to have a release candidate available for wider user testing in a few months.

Full changelog available on GitHub.

v0.21.0

What's Changed

• handle python -OO by @JohannesBuchner in #2393
• Align autogenerated dimension names when dims and default_dims are provided by @lucianopaz in #2395
• Allow custom groups without warnings by @OriolAbril in #2401
• Robustify preview module by @OriolAbril in #2398
• fix docs right sidebar and bokeh deprecation warning by @OriolAbril in #2405
• add ecdf comparison plot by @OriolAbril in #2178
• Add a parameter to enable/disable smoothing on discrete variables in BLV (Issue #2325) by @Patchouli-Kenntnis in #2344
• Update mcse_sd calculation to not use normality assumption. by @ahartikainen in #2167
• Split up Bayes Factor stat and plotting functions by @mpmbq2 in #2406
• Change Twitter to X, including the icon by @star1327p in #2418
• plot_hdi raise exception when x is string (#2412) by @milesalanmoore in #2413
• DOC: Change Numba links by @star1327p in #2421
• DOC: Corrected typos in ArviZ-Dask integration by @star1327p in #2422
• DOC: Add missing periods to the ArviZ community page by @star1327p in #2426
• DOC: Correct a typo: InfereceData -> InferenceData by @star1327p in #2428
• DOC: Correct a typo in issue_triaging.md by @star1327p in #2431
• Update utils.py by @menacingly-coded in #2430
• DOC: Update two Bokeh reference links by @star1327p in #2432
• DOC: Update Bokeh link in Installation.rst by @star1327p in #2425
• Prepare release by @aloctavodia in #2434

New Contributors

• @JohannesBuchner made their first contribution in #2393
• @Patchouli-Kenntnis made their first contribution in #2344
• @mpmbq2 made their first contribution in #2406
• @star1327p made their first contribution in #2418
• @milesalanmoore made their first contribution in #2413
• @menacingly-coded made their first contribution in #2430

Full Changelog: v0.20.0...v0.21.0

v0.20.0

The highlight this release is the addition of optimized simultaneous ECDF confidence bands. It also includes support for idata["new_group"] = dataset directly and several bug fixes and documentation improvements.

For users of arviz.from_pytree it will now be necessary to install dm-tree manually as it was only used in this one function and has been made an optional dependency.

Full changelog available on GitHub.

v0.19.0

This release highlights are: Work with Bokeh3, uses revised Pareto k threshold, refactor plot_ecdf arguments, expose new features as preview submodule.

Full Changelog: https://github.com/arviz-devs/arviz/blob/main/CHANGELOG.md#v0190-2024-jul-19

v0.18.0

This release highlights are support for nested dictionaries and pytrees in from_dict converter and data examples updates: it adds a new example data rugby_field with 4d variables and updates the rugby example to include log_prior and unconstrained_posterior groups.

It also has bugfixes and addresses multiple deprecation warnings from dependencies that were being triggered.

Full changelog available on GitHub.

v0.17.1

Patch release with a couple bug fixes, mainly plot_forest didn't work when latest numba was installed which has now been fixed.

Full changelog available on GitHub.

v0.17.0

This new release adds a couple new features, mainly support for prior/likelihood sensitivity checks via arviz.psens and several bugfix and documentation improvements.

Full changelog available on GitHub.

v0.16.1

This patch release includes numba related fixes to avoid triggering deprecations and improve behaviour overall.

Full changelog available on GitHub.

ArviZ 0.16.0

This new release adds several new features, mostly related to InferenceData I/O and maintenance and bugfix improvements.

Full changelog available on GitHub.

v0.15.1 (2023 Mar 06)

v0.15.1 (2023 Mar 06)

New features

Maintenance and fixes

• Fix memory usage and improve efficiency in from_emcee (2215)
• Lower pandas version needed (2217)

Deprecation

Documentation

• Update documentation for various plots (2208)