Beta release

Highlights

• loo-pit KDE and HDI were improved
• html_repr of InferenceData objects for jupyter notebooks
• Support for PyJAGS
• from_pymc3 automatically retrieves coords and dims from model context
• plot_trace now supports multiple aesthetics to identify chain and variable shape and supports matplotlib aliases
• plot_hdi can now take already computed HDI values

Deprecations

• from_pymc3 without a model context available raises aFutureWarning and will be deprecated in a future version
• In plot_trace, chain_prop and compact_prop as tuples will now raise a FutureWarning
• hdi with 2d data raises a FutureWarning

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See detailed change log

Beta release

Third patch release on v0.8.0. Includes fixes on from_pymc3

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See also detailed change log of v0.8.0

Beta release

Second patch release on v0.8.0. Includes fixes on from_pymc3

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See also detailed change log of v0.8.0

Beta release

Patch release on v0.8.0. Changes are:

Maintenance and fixes

• Fixed bug in from_pymc3 when used with PyMC3<3.9 (#1203)
• Fixed enforcement of rcParam plot.max_subplots in plot_trace and plot_pair (#1205)
• Removed extra subplot row and column in in plot_pair with marginal=True (#1205)
• Added latest PyMC3 release to CI in addition to using GitHub master (#1207)

Documentation

• Use dev as version indicator in online documentation (#1204)

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See also detailed change log of v0.8.0

Beta release

Highlights

• Extensions to InferenceData:
  • Added support for warmup data
  • Extended support for predictions and log_likelihood groups
  • Added InferenceData.map method
• var_names argument in stats and plotting functions now supports filtering parameters based on partial naming (filter="like") or regular expressions (filter="regex")
• hdi has been extended to work on arrays with more than 2d and on InferenceData objects
• New option in plot_trace to display rank plot

Deprecations

• functions hpd and plot_hpd have been deprecated in favour of hdi and plot_hdi respectively
• argument credible_interval has been deprecated in favour of hdi_prob

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See detailed change log

Beta release

Highlights

• New defaults for cross validation: loo (old: waic) and log -scale (old: deviance -scale)
• Extensions to InferenceData schema
  • Added support for out of sample posterior predictive with predictions group
  • Added storage support for pointwise log likelihood data from multiple variables with log_likelihood group
• Improved legends: plot_density, plot_energy and plot_ess support interactive legends in Bokeh, automatic legend in plot_trace(..., compact=True) in matplotlib
• Added transform argument to plotting functions
• Better rcParams integration

Experimental features

• Added arviz.wrappers module to allow ArviZ to refit the models if necessary
• Added reloo function to ArviZ

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See detailed change log

Beta release

Minor release due to error in packaging import statement.

#975

• Update for pair_plot (divergences can be selected
• Default tools follow global (ArviZ) defaults
• Change packaging import from absolute to relative format, explicitly importing version function

#976

• Add interactive legend for a plot, if only two variables are used in pairplot.

Beta release

Highlights

• Initial bokeh support.
• Fully support numpyro (@fehiepsi )
• log_likelihood and observed data from pyro
• ArviZ.jl (@sethaxen )
• improve rcparams
• fix az.concat functionality (@anzelpwj )
• distplot docstring plotting example (@jscarbor )

Beta Release

Bugfix

• Comment dev requirements in setup.py

Beta Release

New features

• Add from_numpyro Integration (#811)
• Numba Google Summer of Code additions (https://ban-zee.github.io/jekyll/update/2019/08/19/Submission.html)
• Model checking, Inference Data, and Convergence assessments (https://github.com/OriolAbril/gsoc2019/blob/master/final_work_submission.md)

Bugfix