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bump version to 0.11.0 (#1502)
* bump version to 0.11.0 * fix docs
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‎CHANGELOG.md

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## v0.x.x Unreleased
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### New features
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### Maintenance and fixes
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### Deprecation
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### Documentation
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## v0.11.0 (2021 Dec 17)
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### New features
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* Added `to_dataframe` method to InferenceData ([1395](https://github.com/arviz-devs/arviz/pull/1395))
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* Added `__getitem__` magic to InferenceData ([1395](https://github.com/arviz-devs/arviz/pull/1395))
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* Added group argument to summary ([1408](https://github.com/arviz-devs/arviz/pull/1408))
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* Add `ref_line`, `bar`, `vlines` and `marker_vlines` kwargs to `plot_rank` ([1419](https://github.com/arviz-devs/arviz/pull/1419))
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* Add observed argument to (un)plot observed data in `plot_ppc` ([1422](https://github.com/arviz-devs/arviz/pull/1422))
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* Add support for named dims and coordinates with multivariate observations ([1429](https://github.com/arviz-devs/arviz/pull/1429))
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* Add support for discrete variables in rank plots ([1433](https://github.com/arviz-devs/arviz/pull/1433))
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* Add support for discrete variables in rank plots ([1433](https://github.com/arviz-devs/arviz/pull/1433)) and
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`loo_pit` ([1500](https://github.com/arviz-devs/arviz/pull/1500))
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* Add `skipna` argument to `plot_posterior` ([1432](https://github.com/arviz-devs/arviz/pull/1432))
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* Make stacking the default method to compute weights in `compare` ([1438](https://github.com/arviz-devs/arviz/pull/1438))
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* Add `copy()` method to `InferenceData` class. ([1501](https://github.com/arviz-devs/arviz/pull/1501)).
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* Do not plot divergences in `plot_trace` when `kind=rank_vlines` or `kind=rank_bars` ([1476](https://github.com/arviz-devs/arviz/issues/1476))
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* Allow ignoring `observed` argument of `pymc3.DensityDist` in `from_pymc3` ([1495](https://github.com/arviz-devs/arviz/pull/1495))
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* Make `from_pymc3` compatible with theano-pymc 1.1.0 ([1495](https://github.com/arviz-devs/arviz/pull/1495))
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* Improve typing hints ([1491](https://github.com/arviz-devs/arviz/pull/1491), ([1492](https://github.com/arviz-devs/arviz/pull/1492),
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([1493](https://github.com/arviz-devs/arviz/pull/1493), ([1494](https://github.com/arviz-devs/arviz/pull/1494) and
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([1497](https://github.com/arviz-devs/arviz/pull/1497))
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### Deprecation

‎arviz/__init__.py

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# pylint: disable=wildcard-import,invalid-name,wrong-import-position
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"""ArviZ is a library for exploratory analysis of Bayesian models."""
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__version__ = "0.10.0"
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__version__ = "0.11.0"
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import logging
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import os

‎arviz/data/inference_data.py

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@@ -834,27 +834,27 @@ def stack(
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In [1]: import arviz as az
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...: datadict = {
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"a": np.random.randn(100),
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"b": np.random.randn(1, 100, 10),
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"c": np.random.randn(1, 100, 3, 4),
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}
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...: "a": np.random.randn(100),
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...: "b": np.random.randn(1, 100, 10),
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...: "c": np.random.randn(1, 100, 3, 4),
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...: }
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...: coords = {
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"c1": np.arange(3),
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"c99": np.arange(4),
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"b1": np.arange(10),
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}
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...: "c1": np.arange(3),
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...: "c99": np.arange(4),
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...: "b1": np.arange(10),
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...: }
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...: dims = {"c": ["c1", "c99"], "b": ["b1"]}
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...: idata = az.from_dict(
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...: posterior=datadict, posterior_predictive=datadict, coords=coords, dims=dims
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...: )
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...: idata
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...: idata.posterior
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In order to stack two dimensions ``c1`` and ``c99`` to ``z``, we can use:
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.. ipython::
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In [1]: idata.stack(z=["c1", "c99"], inplace=True)
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...: idata
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...: idata.posterior
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See Also
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--------
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In [1]: import arviz as az
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...: datadict = {
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"a": np.random.randn(100),
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"b": np.random.randn(1, 100, 10),
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"c": np.random.randn(1, 100, 3, 4),
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}
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...: "a": np.random.randn(100),
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...: "b": np.random.randn(1, 100, 10),
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...: "c": np.random.randn(1, 100, 3, 4),
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...: }
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...: coords = {
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"c1": np.arange(3),
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"c99": np.arange(4),
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"b1": np.arange(10),
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}
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...: "c1": np.arange(3),
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...: "c99": np.arange(4),
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...: "b1": np.arange(10),
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...: }
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...: dims = {"c": ["c1", "c99"], "b": ["b1"]}
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...: dataset = from_dict(
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...: idata = az.from_dict(
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...: posterior=datadict, posterior_predictive=datadict, coords=coords, dims=dims
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...: )
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...: dataset.stack(z=["c1", "c99"], inplace=True)
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...: dataset
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...: idata.stack(z=["c1", "c99"], inplace=True)
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...: idata
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In order to unstack the dimension ``z``, we use:
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.. ipython::
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In [1]: dataset.unstack(inplace=True)
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...: dataset
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In [1]: idata.unstack(inplace=True)
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...: idata
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See Also
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In [1]: import arviz as az
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...: idata = az.load_arviz_data("rugby")
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...: print(list(idata.posterior.data_vars)
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...: print(list(idata.prior.data_vars)
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...: print(list(idata.posterior.data_vars))
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...: print(list(idata.prior.data_vars))
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In order to rename the data variables, we use:
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.. ipython::
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In [1]: idata.rename_vars({"home": "home_new"}, inplace=True)
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...: print(list(idata.posterior.data_vars)
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...: print(list(idata.prior.data_vars)
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...: print(list(idata.posterior.data_vars))
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...: print(list(idata.prior.data_vars))
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In [1]: import arviz as az
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...: print(list(idata.posterior.dims))
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...: print(list(idata.prior.dims))
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In order to rename the dimensions, we use:
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In [1]: idata.rename_dims({"team": "team_new"}, inplace=True)
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...: print(list(idata.posterior.dims))
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...: print(list(idata.prior.dims))
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See Also
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--------

‎examples/matplotlib/mpl_plot_violin.py

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"""
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Violin plot
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==========
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===========
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_thumb: .2, .8
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_example_title: Violin plot

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