py-arviz: updated to 0.11.4

v0.11.4 (2021 Oct 3)
Maintenance and fixes
* Fix standard deviation code in density utils by replacing it with `np.std`.

v0.11.3 (2021 Oct 1)
New features
* Added `labeller` argument to enable label customization in plots and summary
* Added `arviz.labels` module with classes and utilities
* Added probability estimate within ROPE in `plot_posterior`
* Added `rope_color` and `ref_val_color` arguments to `plot_posterior`
* Improved retrieving or pointwise log likelihood in `from_cmdstanpy`, `from_cmdstan` and `from_pystan`
* Added interactive legend to bokeh `forestplot`
* Added interactive legend to bokeh `ppcplot`
* Add more helpful error message for HDF5 problems reading `InferenceData` from NetCDF
* Added `data.log_likelihood`, `stats.ic_compare_method` and `plot.density_kind` to `rcParams`
* Improve error messages in `stats.compare()`, and `var_name` parameter.
* Added ability to plot HDI contours to `plot_kde` with the new `hdi_probs` parameter.
* Add dtype parsing and setting in all Stan converters
* Add option to specify colors for each element in ppc_plot

Maintenance and fixes
* Fix conversion for numpyro models with ImproperUniform latent sites
* Fixed conversion of Pyro output fit using GPUs
* Enforced using coordinate values as default labels
* Integrate `index_origin` with all the library
* Fix pareto k threshold typo in reloo function
* Preserve shape from Stan code in `from_cmdstanpy`
* Updated `from_pystan` converters to follow schema convention
* Used generator instead of list wherever possible
* Correctly use chain index when constructing PyMC3 `DefaultTrace` in `from_pymc3`
* Fix bugs in CmdStanPyConverter
* Fix `c` argument in `plot_khat`
* Fix `ax` argument in `plot_elpd`
* Remove warning in `stats.py` compare function
* Fix `ess/rhat` plots in `plot_forest`
* Fix `from_numpyro` crash when importing model with `thinning=x` for `x > 1`
* Upload updated mypy.ini in ci if mypy copilot fails
* Added type checking to raise an error whenever `InferenceData` object is passed using `io_pymc3`'s `trace` argument
* Fix `xlabels` in `plot_elpd`
* Renamed `sample` dim to `__sample__` when stacking `chain` and `draw` to avoid dimension collision
* Removed the `circular` argument in `plot_dist` in favor of `is_circular`
* Fix `legend` argument in `plot_separation`
* Removed testing dependency on http download for radon dataset
* Fixed plot_kde to take labels with kwargs.
* Fixed xarray related tests.
* Fix Bokeh deprecation warnings
* Fix credible inteval percentage in legend in `plot_loo_pit`
* Arguments `filter_vars` and `filter_groups` now raise `ValueError` if illegal arguments are passed
* Remove constrained_layout from arviz rcparams
* Fix plot_elpd for a single outlier

Deprecation
* Deprecated `index_origin` and `order` arguments in `az.summary`

Documentation
* Language improvements of the first third of the "Label guide"
* Added "Label guide" page and API section for `arviz.labels` module
* Add "Installation guide" page to the documentation
* Improve documentation on experimental `SamplingWrapper` classes
* Added example to `plot_hdi` using Inference Data
* Removed `geweke` diagnostic from `numba` user guide
* Restructured the documentation sections to improve community and about us information

v0.11.2 (2021 Feb 21)
New features
* Added `to_zarr` and `from_zarr` methods to InferenceData
* Added confidence interval band to auto-correlation plot

Maintenance and fixes
* Updated CmdStanPy converter form compatibility with versions >=0.9.68
* Updated `from_cmdstanpy`, `from_cmdstan`, `from_numpyro` and `from_pymc3` converters to follow schema convention
* Fix calculation of mode as point estimate
* Remove variable name from legend in posterior predictive plot
* Added significant digits formatter to round rope values
* Updated `from_cmdstan`. csv reader, dtype problem fixed and dtype kwarg added for manual dtype casting

Deprecation
* Removed Geweke diagnostic
* Removed credible_interval and include_circ arguments

Documentation
* Added an example for converting dataframe to InferenceData
* Added example for `coords` argument in `plot_posterior` docstring

v0.11.1 (2021 Feb 2)
Maintenance and fixes
* Fixed ovelapping titles and repeating warnings on circular traceplot
* Removed repetitive variable names from forest plots of multivariate variables
* Fixed regression in `plot_pair` labels that prevented coord names to be shown when necessary

Documentation
* Use tabs in ArviZ example gallery

v0.11.0 (2021 Dec 17)
New features
* Added `to_dataframe` method to InferenceData
* Added `__getitem__` magic to InferenceData
* Added group argument to summary
* Add `ref_line`, `bar`, `vlines` and `marker_vlines` kwargs to `plot_rank`
* Add observed argument to (un)plot observed data in `plot_ppc`
* Add support for named dims and coordinates with multivariate observations
* Add support for discrete variables in rank plots
  `loo_pit`
* Add `skipna` argument to `plot_posterior`
* Make stacking the default method to compute weights in `compare`
* Add `copy()` method to `InferenceData` class.

Maintenance and fixes
* prevent wrapping group names in InferenceData repr_html
* Updated CmdStanPy interface
* Remove left out warning about default IC scale in `compare`
* Fixed a typo found in an error message raised in `distplot.py`
* Fix typo in `loo_pit` extraction of log likelihood
* Have `from_pystan` store attrs as strings to allow netCDF storage
* Remove ticks and spines in `plot_violin`
* Use circular KDE function and fix tick labels in circular `plot_trace`
* Fix `pair_plot` for mixed discrete and continuous variables
* Fix in-sample deviance in `plot_compare`
* Fix computation of weights in compare
* Avoid repeated warning in summary
* Fix hdi failure with boolean array
* Automatically get the current axes instance for `plt_kde`, `plot_dist` and `plot_hdi`
* Add grid argument to manually specify the number of rows and columns
* Switch to `compact=True` by default in our plots
* `plot_elpd`, avoid modifying the input dict
* Do not plot divergences in `plot_trace` when `kind=rank_vlines` or `kind=rank_bars`
* Allow ignoring `observed` argument of `pymc3.DensityDist` in `from_pymc3`
* Make `from_pymc3` compatible with theano-pymc 1.1.0
* Improve typing hints

Deprecation
* `plot_khat` deprecate `annotate` argument in favor of `threshold`. The new argument accepts floats

Documentation
* Reorganize documentation and change sphinx theme
* Switch to [MyST](https://myst-parser.readthedocs.io/en/latest/) and [MyST-NB](https://myst-nb.readthedocs.io/en/latest/index.html)
  for markdown/notebook parsing in docs
* Incorporated `input_core_dims` in `hdi` and `plot_hdi` docstrings
* Add documentation pages about experimental `SamplingWrapper`s usage
* Show example titles in gallery page
* Add `sample_stats` naming convention to the InferenceData schema
* Extend api documentation about `InferenceData` methods

Experimental
* Modified `SamplingWrapper` base API

v0.10.0 (2020 Sep 24)
New features
* Added InferenceData dataset containing circular variables
* Added `is_circular` argument to `plot_dist` and `plot_kde` allowing for a circular histogram (Matplotlib, Bokeh) or 1D KDE plot (Matplotlib).
* Added `to_dict` method for InferenceData object
* Added `circ_var_names` argument to `plot_trace` allowing for circular traceplot (Matplotlib)
* Ridgeplot is hdi aware. By default displays truncated densities at the specified `hdi_prop` level
* Added `plot_separation`
* Extended methods from `xr.Dataset` to `InferenceData`
* Add `extend` and `add_groups` to `InferenceData`
* Added `__iter__` method (`.items`) for InferenceData
* Add support for discrete variables in `plot_bpv`

Maintenance and fixes
* Automatic conversion of list/tuple to numpy array in distplot
* `plot_posterior` fix overlap of hdi and rope
* `plot_dist` bins argument error fixed
* Improve handling of circular variables in `az.summary`
* Removed change of default warning in `ELPDData` string representation
* Update `radon` example dataset to current InferenceData schema specification
* Update `from_cmdstan` functionality and add warmup groups
* Restructure plotting code to be compatible with mpl>=3.3
* Replaced `_fast_kde()` with `kde()` which now also supports circular variables via the argument `circular`
* Increased `from_pystan` attrs information content
* Allow `plot_trace` to return and accept axes
* Update diagnostics to be on par with posterior package
* Use method="average" in `scipy.stats.rankdata`
* Add more `plot_parallel` examples
* Bump minimum xarray version to 0.16.1
* Fix multi rope for `plot_forest`
* Bump minimum xarray version to 0.16.1
* `from_dict` will now store warmup groups even with the main group missing
* increase robustness for repr_html handling

3 files changed, 85 insertions, 16 deletions

diff --git a/math/py-arviz/Makefile b/math/py-arviz/Makefile
index 4ac2cd751b8..ce7292400b7 100644
--- a/math/py-arviz/Makefile
+++ b/math/py-arviz/Makefile
@@ -1,8 +1,7 @@
-# $NetBSD: Makefile,v 1.7 2022/01/04 20:54:12 wiz Exp $
+# $NetBSD: Makefile,v 1.8 2022/02/10 14:21:59 adam Exp $
 
-DISTNAME=	arviz-0.9.0
+DISTNAME=	arviz-0.11.4
 PKGNAME=	${PYPKGPREFIX}-${DISTNAME}
-PKGREVISION=	1
 CATEGORIES=	math python
 MASTER_SITES=	${MASTER_SITE_PYPI:=a/arviz/}
 
@@ -17,11 +16,12 @@ DEPENDS+=	${PYPKGPREFIX}-numpy>=1.12:../../math/py-numpy
 DEPENDS+=	${PYPKGPREFIX}-packaging-[0-9]*:../../devel/py-packaging
 DEPENDS+=	${PYPKGPREFIX}-pandas>=0.23:../../math/py-pandas
 DEPENDS+=	${PYPKGPREFIX}-scipy>=0.19:../../math/py-scipy
-DEPENDS+=	${PYPKGPREFIX}-xarray>=0.11:../../math/py-xarray
+DEPENDS+=	${PYPKGPREFIX}-typing-extensions>=3.7.4.3:../../devel/py-typing-extensions
+DEPENDS+=	${PYPKGPREFIX}-xarray>=0.16.1:../../math/py-xarray
 
 USE_LANGUAGES=	# none
 
-PYTHON_VERSIONS_INCOMPATIBLE=	27 # py-scipy
+PYTHON_VERSIONS_INCOMPATIBLE=	27 37 # py-xarray
 
 .include "../../lang/python/egg.mk"
 .include "../../mk/bsd.pkg.mk"
diff --git a/math/py-arviz/PLIST b/math/py-arviz/PLIST
index 9502f250647..e721bc8fcb0 100644
--- a/math/py-arviz/PLIST
+++ b/math/py-arviz/PLIST
@@ -1,4 +1,4 @@
-@comment $NetBSD: PLIST,v 1.3 2020/07/01 16:03:59 adam Exp $
+@comment $NetBSD: PLIST,v 1.4 2022/02/10 14:21:59 adam Exp $
 ${PYSITELIB}/${EGG_INFODIR}/PKG-INFO
 ${PYSITELIB}/${EGG_INFODIR}/SOURCES.txt
 ${PYSITELIB}/${EGG_INFODIR}/dependency_links.txt
@@ -36,6 +36,9 @@ ${PYSITELIB}/arviz/data/io_dict.pyo
 ${PYSITELIB}/arviz/data/io_emcee.py
 ${PYSITELIB}/arviz/data/io_emcee.pyc
 ${PYSITELIB}/arviz/data/io_emcee.pyo
+${PYSITELIB}/arviz/data/io_json.py
+${PYSITELIB}/arviz/data/io_json.pyc
+${PYSITELIB}/arviz/data/io_json.pyo
 ${PYSITELIB}/arviz/data/io_netcdf.py
 ${PYSITELIB}/arviz/data/io_netcdf.pyc
 ${PYSITELIB}/arviz/data/io_netcdf.pyo
@@ -48,6 +51,9 @@ ${PYSITELIB}/arviz/data/io_pyjags.pyo
 ${PYSITELIB}/arviz/data/io_pymc3.py
 ${PYSITELIB}/arviz/data/io_pymc3.pyc
 ${PYSITELIB}/arviz/data/io_pymc3.pyo
+${PYSITELIB}/arviz/data/io_pymc3_3x.py
+${PYSITELIB}/arviz/data/io_pymc3_3x.pyc
+${PYSITELIB}/arviz/data/io_pymc3_3x.pyo
 ${PYSITELIB}/arviz/data/io_pyro.py
 ${PYSITELIB}/arviz/data/io_pyro.pyc
 ${PYSITELIB}/arviz/data/io_pyro.pyo
@@ -57,9 +63,9 @@ ${PYSITELIB}/arviz/data/io_pystan.pyo
 ${PYSITELIB}/arviz/data/io_tfp.py
 ${PYSITELIB}/arviz/data/io_tfp.pyc
 ${PYSITELIB}/arviz/data/io_tfp.pyo
-${PYSITELIB}/arviz/numeric_utils.py
-${PYSITELIB}/arviz/numeric_utils.pyc
-${PYSITELIB}/arviz/numeric_utils.pyo
+${PYSITELIB}/arviz/labels.py
+${PYSITELIB}/arviz/labels.pyc
+${PYSITELIB}/arviz/labels.pyo
 ${PYSITELIB}/arviz/plots/__init__.py
 ${PYSITELIB}/arviz/plots/__init__.pyc
 ${PYSITELIB}/arviz/plots/__init__.pyo
@@ -75,6 +81,9 @@ ${PYSITELIB}/arviz/plots/backends/bokeh/__init__.pyo
 ${PYSITELIB}/arviz/plots/backends/bokeh/autocorrplot.py
 ${PYSITELIB}/arviz/plots/backends/bokeh/autocorrplot.pyc
 ${PYSITELIB}/arviz/plots/backends/bokeh/autocorrplot.pyo
+${PYSITELIB}/arviz/plots/backends/bokeh/bpvplot.py
+${PYSITELIB}/arviz/plots/backends/bokeh/bpvplot.pyc
+${PYSITELIB}/arviz/plots/backends/bokeh/bpvplot.pyo
 ${PYSITELIB}/arviz/plots/backends/bokeh/compareplot.py
 ${PYSITELIB}/arviz/plots/backends/bokeh/compareplot.pyc
 ${PYSITELIB}/arviz/plots/backends/bokeh/compareplot.pyo
@@ -87,6 +96,9 @@ ${PYSITELIB}/arviz/plots/backends/bokeh/distcomparisonplot.pyo
 ${PYSITELIB}/arviz/plots/backends/bokeh/distplot.py
 ${PYSITELIB}/arviz/plots/backends/bokeh/distplot.pyc
 ${PYSITELIB}/arviz/plots/backends/bokeh/distplot.pyo
+${PYSITELIB}/arviz/plots/backends/bokeh/dotplot.py
+${PYSITELIB}/arviz/plots/backends/bokeh/dotplot.pyc
+${PYSITELIB}/arviz/plots/backends/bokeh/dotplot.pyo
 ${PYSITELIB}/arviz/plots/backends/bokeh/elpdplot.py
 ${PYSITELIB}/arviz/plots/backends/bokeh/elpdplot.pyc
 ${PYSITELIB}/arviz/plots/backends/bokeh/elpdplot.pyo
@@ -111,6 +123,9 @@ ${PYSITELIB}/arviz/plots/backends/bokeh/kdeplot.pyo
 ${PYSITELIB}/arviz/plots/backends/bokeh/khatplot.py
 ${PYSITELIB}/arviz/plots/backends/bokeh/khatplot.pyc
 ${PYSITELIB}/arviz/plots/backends/bokeh/khatplot.pyo
+${PYSITELIB}/arviz/plots/backends/bokeh/lmplot.py
+${PYSITELIB}/arviz/plots/backends/bokeh/lmplot.pyc
+${PYSITELIB}/arviz/plots/backends/bokeh/lmplot.pyo
 ${PYSITELIB}/arviz/plots/backends/bokeh/loopitplot.py
 ${PYSITELIB}/arviz/plots/backends/bokeh/loopitplot.pyc
 ${PYSITELIB}/arviz/plots/backends/bokeh/loopitplot.pyo
@@ -132,6 +147,9 @@ ${PYSITELIB}/arviz/plots/backends/bokeh/ppcplot.pyo
 ${PYSITELIB}/arviz/plots/backends/bokeh/rankplot.py
 ${PYSITELIB}/arviz/plots/backends/bokeh/rankplot.pyc
 ${PYSITELIB}/arviz/plots/backends/bokeh/rankplot.pyo
+${PYSITELIB}/arviz/plots/backends/bokeh/separationplot.py
+${PYSITELIB}/arviz/plots/backends/bokeh/separationplot.pyc
+${PYSITELIB}/arviz/plots/backends/bokeh/separationplot.pyo
 ${PYSITELIB}/arviz/plots/backends/bokeh/traceplot.py
 ${PYSITELIB}/arviz/plots/backends/bokeh/traceplot.pyc
 ${PYSITELIB}/arviz/plots/backends/bokeh/traceplot.pyo
@@ -144,6 +162,9 @@ ${PYSITELIB}/arviz/plots/backends/matplotlib/__init__.pyo
 ${PYSITELIB}/arviz/plots/backends/matplotlib/autocorrplot.py
 ${PYSITELIB}/arviz/plots/backends/matplotlib/autocorrplot.pyc
 ${PYSITELIB}/arviz/plots/backends/matplotlib/autocorrplot.pyo
+${PYSITELIB}/arviz/plots/backends/matplotlib/bpvplot.py
+${PYSITELIB}/arviz/plots/backends/matplotlib/bpvplot.pyc
+${PYSITELIB}/arviz/plots/backends/matplotlib/bpvplot.pyo
 ${PYSITELIB}/arviz/plots/backends/matplotlib/compareplot.py
 ${PYSITELIB}/arviz/plots/backends/matplotlib/compareplot.pyc
 ${PYSITELIB}/arviz/plots/backends/matplotlib/compareplot.pyo
@@ -156,6 +177,9 @@ ${PYSITELIB}/arviz/plots/backends/matplotlib/distcomparisonplot.pyo
 ${PYSITELIB}/arviz/plots/backends/matplotlib/distplot.py
 ${PYSITELIB}/arviz/plots/backends/matplotlib/distplot.pyc
 ${PYSITELIB}/arviz/plots/backends/matplotlib/distplot.pyo
+${PYSITELIB}/arviz/plots/backends/matplotlib/dotplot.py
+${PYSITELIB}/arviz/plots/backends/matplotlib/dotplot.pyc
+${PYSITELIB}/arviz/plots/backends/matplotlib/dotplot.pyo
 ${PYSITELIB}/arviz/plots/backends/matplotlib/elpdplot.py
 ${PYSITELIB}/arviz/plots/backends/matplotlib/elpdplot.pyc
 ${PYSITELIB}/arviz/plots/backends/matplotlib/elpdplot.pyo
@@ -180,6 +204,9 @@ ${PYSITELIB}/arviz/plots/backends/matplotlib/kdeplot.pyo
 ${PYSITELIB}/arviz/plots/backends/matplotlib/khatplot.py
 ${PYSITELIB}/arviz/plots/backends/matplotlib/khatplot.pyc
 ${PYSITELIB}/arviz/plots/backends/matplotlib/khatplot.pyo
+${PYSITELIB}/arviz/plots/backends/matplotlib/lmplot.py
+${PYSITELIB}/arviz/plots/backends/matplotlib/lmplot.pyc
+${PYSITELIB}/arviz/plots/backends/matplotlib/lmplot.pyo
 ${PYSITELIB}/arviz/plots/backends/matplotlib/loopitplot.py
 ${PYSITELIB}/arviz/plots/backends/matplotlib/loopitplot.pyc
 ${PYSITELIB}/arviz/plots/backends/matplotlib/loopitplot.pyo
@@ -201,12 +228,21 @@ ${PYSITELIB}/arviz/plots/backends/matplotlib/ppcplot.pyo
 ${PYSITELIB}/arviz/plots/backends/matplotlib/rankplot.py
 ${PYSITELIB}/arviz/plots/backends/matplotlib/rankplot.pyc
 ${PYSITELIB}/arviz/plots/backends/matplotlib/rankplot.pyo
+${PYSITELIB}/arviz/plots/backends/matplotlib/separationplot.py
+${PYSITELIB}/arviz/plots/backends/matplotlib/separationplot.pyc
+${PYSITELIB}/arviz/plots/backends/matplotlib/separationplot.pyo
 ${PYSITELIB}/arviz/plots/backends/matplotlib/traceplot.py
 ${PYSITELIB}/arviz/plots/backends/matplotlib/traceplot.pyc
 ${PYSITELIB}/arviz/plots/backends/matplotlib/traceplot.pyo
+${PYSITELIB}/arviz/plots/backends/matplotlib/tsplot.py
+${PYSITELIB}/arviz/plots/backends/matplotlib/tsplot.pyc
+${PYSITELIB}/arviz/plots/backends/matplotlib/tsplot.pyo
 ${PYSITELIB}/arviz/plots/backends/matplotlib/violinplot.py
 ${PYSITELIB}/arviz/plots/backends/matplotlib/violinplot.pyc
 ${PYSITELIB}/arviz/plots/backends/matplotlib/violinplot.pyo
+${PYSITELIB}/arviz/plots/bpvplot.py
+${PYSITELIB}/arviz/plots/bpvplot.pyc
+${PYSITELIB}/arviz/plots/bpvplot.pyo
 ${PYSITELIB}/arviz/plots/compareplot.py
 ${PYSITELIB}/arviz/plots/compareplot.pyc
 ${PYSITELIB}/arviz/plots/compareplot.pyo
@@ -219,6 +255,9 @@ ${PYSITELIB}/arviz/plots/distcomparisonplot.pyo
 ${PYSITELIB}/arviz/plots/distplot.py
 ${PYSITELIB}/arviz/plots/distplot.pyc
 ${PYSITELIB}/arviz/plots/distplot.pyo
+${PYSITELIB}/arviz/plots/dotplot.py
+${PYSITELIB}/arviz/plots/dotplot.pyc
+${PYSITELIB}/arviz/plots/dotplot.pyo
 ${PYSITELIB}/arviz/plots/elpdplot.py
 ${PYSITELIB}/arviz/plots/elpdplot.pyc
 ${PYSITELIB}/arviz/plots/elpdplot.pyo
@@ -243,6 +282,9 @@ ${PYSITELIB}/arviz/plots/kdeplot.pyo
 ${PYSITELIB}/arviz/plots/khatplot.py
 ${PYSITELIB}/arviz/plots/khatplot.pyc
 ${PYSITELIB}/arviz/plots/khatplot.pyo
+${PYSITELIB}/arviz/plots/lmplot.py
+${PYSITELIB}/arviz/plots/lmplot.pyc
+${PYSITELIB}/arviz/plots/lmplot.pyo
 ${PYSITELIB}/arviz/plots/loopitplot.py
 ${PYSITELIB}/arviz/plots/loopitplot.pyc
 ${PYSITELIB}/arviz/plots/loopitplot.pyo
@@ -267,23 +309,47 @@ ${PYSITELIB}/arviz/plots/ppcplot.pyo
 ${PYSITELIB}/arviz/plots/rankplot.py
 ${PYSITELIB}/arviz/plots/rankplot.pyc
 ${PYSITELIB}/arviz/plots/rankplot.pyo
+${PYSITELIB}/arviz/plots/separationplot.py
+${PYSITELIB}/arviz/plots/separationplot.pyc
+${PYSITELIB}/arviz/plots/separationplot.pyo
+${PYSITELIB}/arviz/plots/styles/arviz-bluish.mplstyle
+${PYSITELIB}/arviz/plots/styles/arviz-brownish.mplstyle
 ${PYSITELIB}/arviz/plots/styles/arviz-colors.mplstyle
+${PYSITELIB}/arviz/plots/styles/arviz-cyanish.mplstyle
 ${PYSITELIB}/arviz/plots/styles/arviz-darkgrid.mplstyle
 ${PYSITELIB}/arviz/plots/styles/arviz-grayscale.mplstyle
+${PYSITELIB}/arviz/plots/styles/arviz-greenish.mplstyle
+${PYSITELIB}/arviz/plots/styles/arviz-orangish.mplstyle
+${PYSITELIB}/arviz/plots/styles/arviz-plasmish.mplstyle
+${PYSITELIB}/arviz/plots/styles/arviz-purplish.mplstyle
+${PYSITELIB}/arviz/plots/styles/arviz-redish.mplstyle
+${PYSITELIB}/arviz/plots/styles/arviz-royish.mplstyle
+${PYSITELIB}/arviz/plots/styles/arviz-viridish.mplstyle
 ${PYSITELIB}/arviz/plots/styles/arviz-white.mplstyle
 ${PYSITELIB}/arviz/plots/styles/arviz-whitegrid.mplstyle
 ${PYSITELIB}/arviz/plots/traceplot.py
 ${PYSITELIB}/arviz/plots/traceplot.pyc
 ${PYSITELIB}/arviz/plots/traceplot.pyo
+${PYSITELIB}/arviz/plots/tsplot.py
+${PYSITELIB}/arviz/plots/tsplot.pyc
+${PYSITELIB}/arviz/plots/tsplot.pyo
 ${PYSITELIB}/arviz/plots/violinplot.py
 ${PYSITELIB}/arviz/plots/violinplot.pyc
 ${PYSITELIB}/arviz/plots/violinplot.pyo
 ${PYSITELIB}/arviz/rcparams.py
 ${PYSITELIB}/arviz/rcparams.pyc
 ${PYSITELIB}/arviz/rcparams.pyo
+${PYSITELIB}/arviz/sel_utils.py
+${PYSITELIB}/arviz/sel_utils.pyc
+${PYSITELIB}/arviz/sel_utils.pyo
+${PYSITELIB}/arviz/static/css/style.css
+${PYSITELIB}/arviz/static/html/icons-svg-inline.html
 ${PYSITELIB}/arviz/stats/__init__.py
 ${PYSITELIB}/arviz/stats/__init__.pyc
 ${PYSITELIB}/arviz/stats/__init__.pyo
+${PYSITELIB}/arviz/stats/density_utils.py
+${PYSITELIB}/arviz/stats/density_utils.pyc
+${PYSITELIB}/arviz/stats/density_utils.pyo
 ${PYSITELIB}/arviz/stats/diagnostics.py
 ${PYSITELIB}/arviz/stats/diagnostics.pyc
 ${PYSITELIB}/arviz/stats/diagnostics.pyo
@@ -305,6 +371,9 @@ ${PYSITELIB}/arviz/tests/base_tests/__init__.pyo
 ${PYSITELIB}/arviz/tests/base_tests/test_data.py
 ${PYSITELIB}/arviz/tests/base_tests/test_data.pyc
 ${PYSITELIB}/arviz/tests/base_tests/test_data.pyo
+${PYSITELIB}/arviz/tests/base_tests/test_data_zarr.py
+${PYSITELIB}/arviz/tests/base_tests/test_data_zarr.pyc
+${PYSITELIB}/arviz/tests/base_tests/test_data_zarr.pyo
 ${PYSITELIB}/arviz/tests/base_tests/test_diagnostics.py
 ${PYSITELIB}/arviz/tests/base_tests/test_diagnostics.pyc
 ${PYSITELIB}/arviz/tests/base_tests/test_diagnostics.pyo
@@ -386,6 +455,6 @@ ${PYSITELIB}/arviz/wrappers/__init__.pyo
 ${PYSITELIB}/arviz/wrappers/base.py
 ${PYSITELIB}/arviz/wrappers/base.pyc
 ${PYSITELIB}/arviz/wrappers/base.pyo
-${PYSITELIB}/arviz/wrappers/wrap_pystan.py
-${PYSITELIB}/arviz/wrappers/wrap_pystan.pyc
-${PYSITELIB}/arviz/wrappers/wrap_pystan.pyo
+${PYSITELIB}/arviz/wrappers/wrap_stan.py
+${PYSITELIB}/arviz/wrappers/wrap_stan.pyc
+${PYSITELIB}/arviz/wrappers/wrap_stan.pyo
diff --git a/math/py-arviz/distinfo b/math/py-arviz/distinfo
index 3c3f6ae9bdd..7f91bb62102 100644
--- a/math/py-arviz/distinfo
+++ b/math/py-arviz/distinfo
@@ -1,5 +1,5 @@
-$NetBSD: distinfo,v 1.5 2021/10/26 10:55:59 nia Exp $
+$NetBSD: distinfo,v 1.6 2022/02/10 14:21:59 adam Exp $
 
-BLAKE2s (arviz-0.9.0.tar.gz) = 8a10b03559ef1c6083dbeef165499d3fc3570798dff8e5636ebe343f7a292370
-SHA512 (arviz-0.9.0.tar.gz) = 70bf850e2ca2e15c18f5cdf738a2021fc4281ffcef1e04121bc241d912180a5b26cff69342b950ec2321183aa93460ee4dfbaab9ad6d0481be499e6ffd12a5ac
-Size (arviz-0.9.0.tar.gz) = 1435491 bytes
+BLAKE2s (arviz-0.11.4.tar.gz) = f8409fb325853e526e2f097413f07d09ba0919a871dbddf02ed3f72be3cdffb9
+SHA512 (arviz-0.11.4.tar.gz) = 20a803bd202366520b94e45a216b72b47c3880ee0fe154ea250d1d5d14dfb85de2a4b8e6efc18f5474c0394f869a74efeb14f1edf6f5ae6836cf9b7bad74ba54
+Size (arviz-0.11.4.tar.gz) = 1506007 bytes