Merge e742a74 into 2bcdff5

README.md

@@ -12,6 +12,9 @@
 ArviZ (pronounced "AR-_vees_") is a Python package for exploratory analysis of Bayesian models.
 Includes functions for posterior analysis, model checking, comparison and diagnostics.
 
+### ArviZ in other languages
+ArviZ also has a Julia wrapper available [ArviZ.jl](https://arviz-devs.github.io/ArviZ.jl/dev/).
+
 ## Documentation
 
 The ArviZ documentation can be found in the [official docs](https://arviz-devs.github.io/arviz/index.html).

arviz/plots/rankplot.py

@@ -102,10 +102,11 @@ def plot_rank(
 
         >>> import arviz as az
         >>> centered_data = az.load_arviz_data('centered_eight')
-        >>> noncentered_data = az.load_arviz_data('noncentered_eight')
-        >>> ax = plt.subplots(1, 2, figsize=(12, 3))
+        >>> noncentered_data = az.load_arviz_data('non_centered_eight')
+        >>> _, ax = plt.subplots(1, 2, figsize=(12, 3))
         >>> az.plot_rank(centered_data, var_names="mu", kind='vlines', axes=ax[0])
-        >>> az.plot_rank(noncentered_data, var_names="mu", kind='vlines', axes=ax[1]
+        >>> az.plot_rank(noncentered_data, var_names="mu", kind='vlines', axes=ax[1])
+
     """
     posterior_data = convert_to_dataset(data, group="posterior")
     if coords is not None:

doc/index.rst

@@ -51,8 +51,15 @@ For the latest (unstable) version
 
 ArviZ's functions work with NumPy arrays, dictionaries of arrays, xarray datasets, and has built-in support for `PyMC3 <https://docs.pymc.io/>`_,
 `PyStan <https://pystan.readthedocs.io/en/latest/>`_, `CmdStanPy <https://github.com/stan-dev/cmdstanpy>`_,
-`Pyro <http://pyro.ai/>`_, `NumPyro <http://num.pyro.ai/>`_, and
-`emcee <https://emcee.readthedocs.io/en/stable/>`_ objects. Support for PyMC4, TensorFlow Probability, Edward2, and Edward are on the roadmap.
+`Pyro <http://pyro.ai/>`_, `NumPyro <http://num.pyro.ai/>`_,
+`emcee <https://emcee.readthedocs.io/en/stable/>`_, and
+`TensorFlow Probability <https://www.tensorflow.org/probability>`_ objects. Support for PyMC4, Edward2, and Edward are on the roadmap.
+
+A Julia wrapper, `ArviZ.jl <https://arviz-devs.github.io/ArviZ.jl/dev/>`_ is
+also available. It provides built-in support for
+`Turing.jl <https://turing.ml/dev/>`_, `CmdStan.jl
+<https://github.com/StanJulia/CmdStan.jl>`_, `StanSample.jl
+<https://github.com/StanJulia/StanSample.jl>`_ and `Stan.jl <https://github.com/StanJulia/Stan.jl>`_.
 
 Contributions and issue reports are very welcome at
 `the github repository <https://github.com/arviz-devs/arviz>`_.