<img src="https://raw.githubusercontent.com/arviz-devs/arviz-project/main/arviz_logos/ArviZ.png#gh-light-mode-only" width=200></img>
<img src="https://raw.githubusercontent.com/arviz-devs/arviz-project/main/arviz_logos/ArviZ_white.png#gh-dark-mode-only" width=200></img>
[![PyPI version](https://badge.fury.io/py/arviz.svg)](https://badge.fury.io/py/arviz)
[![Azure Build Status](https://dev.azure.com/ArviZ/ArviZ/_apis/build/status/arviz-devs.arviz?branchName=main)](https://dev.azure.com/ArviZ/ArviZ/_build/latest?definitionId=1&branchName=main)
[![codecov](https://codecov.io/gh/arviz-devs/arviz/branch/main/graph/badge.svg)](https://codecov.io/gh/arviz-devs/arviz)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/ambv/black)
[![Gitter chat](https://badges.gitter.im/gitterHQ/gitter.png)](https://gitter.im/arviz-devs/community)
[![DOI](http://joss.theoj.org/papers/10.21105/joss.01143/status.svg)](https://doi.org/10.21105/joss.01143) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.2540945.svg)](https://doi.org/10.5281/zenodo.2540945)
[![Powered by NumFOCUS](https://img.shields.io/badge/powered%20by-NumFOCUS-orange.svg?style=flat&colorA=E1523D&colorB=007D8A)](https://numfocus.org)
ArviZ (pronounced "AR-_vees_") is a Python package for exploratory analysis of Bayesian models. It includes functions for posterior analysis, data storage, model checking, comparison and diagnostics.
### ArviZ in other languages
ArviZ also has a Julia wrapper available [ArviZ.jl](https://julia.arviz.org/).
## Documentation
The ArviZ documentation can be found in the [official docs](https://python.arviz.org/en/latest/index.html).
First time users may find the [quickstart](https://python.arviz.org/en/latest/getting_started/Introduction.html)
to be helpful. Additional guidance can be found in the
[user guide](https://python.arviz.org/en/latest/user_guide/index.html).
## Installation
### Stable
ArviZ is available for installation from [PyPI](https://pypi.org/project/arviz/).
The latest stable version can be installed using pip:
```
pip install arviz
```
ArviZ is also available through [conda-forge](https://anaconda.org/conda-forge/arviz).
```
conda install -c conda-forge arviz
```
### Development
The latest development version can be installed from the main branch using pip:
```
pip install git+git://github.com/arviz-devs/arviz.git
```
Another option is to clone the repository and install using git and setuptools:
```
git clone https://github.com/arviz-devs/arviz.git
cd arviz
python setup.py install
```
-------------------------------------------------------------------------------
## [Gallery](https://python.arviz.org/en/latest/examples/index.html)
<p>
<table>
<tr>
<td>
<a href= "https://python.arviz.org/en/latest/examples/plot_forest_ridge.html">
<img alt="Ridge plot"
src="https://python.arviz.org/en/latest/_images/mpl_plot_forest_ridge.png" width="300" height="auto" />
</a>
</td>
<td>
<a href="https://python.arviz.org/en/latest/examples/plot_forest.html">
<img alt="Forest Plot"
src="https://python.arviz.org/en/latest/_images/mpl_plot_forest.png" width="300" height="auto" />
</a>
</td>
<td>
<a href="https://python.arviz.org/en/latest/examples/plot_violin.html">
<img alt="Violin Plot"
src="https://python.arviz.org/en/latest/_images/mpl_plot_violin.png" width="300" height="auto" />
</a>
</td>
</tr>
<tr>
<td>
<a href="https://python.arviz.org/en/latest/examples/plot_ppc.html">
<img alt="Posterior predictive plot"
src="https://python.arviz.org/en/latest/_images/mpl_plot_ppc.png" width="300" height="auto" />
</a>
</td>
<td>
<a href="https://python.arviz.org/en/latest/examples/plot_dot.html">
<img alt="Joint plot"
src="https://python.arviz.org/en/latest/_images/mpl_plot_dot.png" width="300" height="auto" />
</a>
</td>
<td>
<a href="https://python.arviz.org/en/latest/examples/plot_posterior.html">
<img alt="Posterior plot"
src="https://python.arviz.org/en/latest/_images/mpl_plot_posterior.png" width="300" height="auto" />
</a>
</td>
</tr>
<tr>
<td>
<a href="https://python.arviz.org/en/latest/examples/plot_density.html">
<img alt="Density plot"
src="https://python.arviz.org/en/latest/_images/mpl_plot_density.png" width="300" height="auto" />
</a>
</td>
<td>
<a href="https://python.arviz.org/en/latest/examples/plot_pair.html">
<img alt="Pair plot"
src="https://python.arviz.org/en/latest/_images/mpl_plot_pair.png" width="300" height="auto" />
</a>
</td>
<td>
<a href="https://python.arviz.org/en/latest/examples/plot_pair_hex.html">
<img alt="Hexbin Pair plot"
src="https://python.arviz.org/en/latest/_images/mpl_plot_pair_hex.png" width="300" height="auto" />
</a>
</td>
</tr>
<tr>
<td>
<a href="https://python.arviz.org/en/latest/examples/plot_trace.html">
<img alt="Trace plot"
src="https://python.arviz.org/en/latest/_images/mpl_plot_trace.png" width="300" height="auto" />
</a>
</td>
<td>
<a href="https://python.arviz.org/en/latest/examples/plot_energy.html">
<img alt="Energy Plot"
src="https://python.arviz.org/en/latest/_images/mpl_plot_energy.png" width="300" height="auto" />
</a>
</td>
<td>
<a href="https://python.arviz.org/en/latest/examples/plot_rank.html">
<img alt="Rank Plot"
src="https://python.arviz.org/en/latest/_images/mpl_plot_rank.png" width="300" height="auto" />
</a>
</td>
</tr>
</table>
<div>
<a href="https://python.arviz.org/en/latest/examples/index.html">And more...</a>
</div>
## Dependencies
ArviZ is tested on Python 3.10, 3.11 and 3.12, and depends on NumPy, SciPy, xarray, and Matplotlib.
## Citation
If you use ArviZ and want to cite it please use [![DOI](http://joss.theoj.org/papers/10.21105/joss.01143/status.svg)](https://doi.org/10.21105/joss.01143)
Here is the citation in BibTeX format
```
@article{arviz_2019,
doi = {10.21105/joss.01143},
url = {https://doi.org/10.21105/joss.01143},
year = {2019},
publisher = {The Open Journal},
volume = {4},
number = {33},
pages = {1143},
author = {Ravin Kumar and Colin Carroll and Ari Hartikainen and Osvaldo Martin},
title = {ArviZ a unified library for exploratory analysis of Bayesian models in Python},
journal = {Journal of Open Source Software}
}
```
## Contributions
ArviZ is a community project and welcomes contributions.
Additional information can be found in the [Contributing Readme](https://github.com/arviz-devs/arviz/blob/main/CONTRIBUTING.md)
## Code of Conduct
ArviZ wishes to maintain a positive community. Additional details
can be found in the [Code of Conduct](https://github.com/arviz-devs/arviz/blob/main/CODE_OF_CONDUCT.md)
## Donations
ArviZ is a non-profit project under NumFOCUS umbrella. If you want to support ArviZ financially, you can donate [here](https://numfocus.org/donate-to-arviz).
## Sponsors
[![NumFOCUS](https://www.numfocus.org/wp-content/uploads/2017/07/NumFocus_LRG.png)](https://numfocus.org)
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"description": "<img src=\"https://raw.githubusercontent.com/arviz-devs/arviz-project/main/arviz_logos/ArviZ.png#gh-light-mode-only\" width=200></img>\n<img src=\"https://raw.githubusercontent.com/arviz-devs/arviz-project/main/arviz_logos/ArviZ_white.png#gh-dark-mode-only\" width=200></img>\n\n[![PyPI version](https://badge.fury.io/py/arviz.svg)](https://badge.fury.io/py/arviz)\n[![Azure Build Status](https://dev.azure.com/ArviZ/ArviZ/_apis/build/status/arviz-devs.arviz?branchName=main)](https://dev.azure.com/ArviZ/ArviZ/_build/latest?definitionId=1&branchName=main)\n[![codecov](https://codecov.io/gh/arviz-devs/arviz/branch/main/graph/badge.svg)](https://codecov.io/gh/arviz-devs/arviz)\n[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/ambv/black)\n[![Gitter chat](https://badges.gitter.im/gitterHQ/gitter.png)](https://gitter.im/arviz-devs/community)\n[![DOI](http://joss.theoj.org/papers/10.21105/joss.01143/status.svg)](https://doi.org/10.21105/joss.01143) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.2540945.svg)](https://doi.org/10.5281/zenodo.2540945)\n[![Powered by NumFOCUS](https://img.shields.io/badge/powered%20by-NumFOCUS-orange.svg?style=flat&colorA=E1523D&colorB=007D8A)](https://numfocus.org)\n\nArviZ (pronounced \"AR-_vees_\") is a Python package for exploratory analysis of Bayesian models. It includes functions for posterior analysis, data storage, model checking, comparison and diagnostics.\n\n### ArviZ in other languages\nArviZ also has a Julia wrapper available [ArviZ.jl](https://julia.arviz.org/).\n\n## Documentation\n\nThe ArviZ documentation can be found in the [official docs](https://python.arviz.org/en/latest/index.html).\nFirst time users may find the [quickstart](https://python.arviz.org/en/latest/getting_started/Introduction.html)\nto be helpful. Additional guidance can be found in the\n[user guide](https://python.arviz.org/en/latest/user_guide/index.html).\n\n\n## Installation\n\n### Stable\nArviZ is available for installation from [PyPI](https://pypi.org/project/arviz/).\nThe latest stable version can be installed using pip:\n\n```\npip install arviz\n```\n\nArviZ is also available through [conda-forge](https://anaconda.org/conda-forge/arviz).\n\n```\nconda install -c conda-forge arviz\n```\n\n### Development\nThe latest development version can be installed from the main branch using pip:\n\n```\npip install git+git://github.com/arviz-devs/arviz.git\n```\n\nAnother option is to clone the repository and install using git and setuptools:\n\n```\ngit clone https://github.com/arviz-devs/arviz.git\ncd arviz\npython setup.py install\n```\n\n-------------------------------------------------------------------------------\n## [Gallery](https://python.arviz.org/en/latest/examples/index.html)\n\n<p>\n<table>\n<tr>\n\n <td>\n <a href= \"https://python.arviz.org/en/latest/examples/plot_forest_ridge.html\">\n <img alt=\"Ridge plot\"\n src=\"https://python.arviz.org/en/latest/_images/mpl_plot_forest_ridge.png\" width=\"300\" height=\"auto\" />\n </a>\n </td>\n\n <td>\n <a href=\"https://python.arviz.org/en/latest/examples/plot_forest.html\">\n <img alt=\"Forest Plot\"\n src=\"https://python.arviz.org/en/latest/_images/mpl_plot_forest.png\" width=\"300\" height=\"auto\" />\n </a>\n </td>\n\n <td>\n <a href=\"https://python.arviz.org/en/latest/examples/plot_violin.html\">\n <img alt=\"Violin Plot\"\n src=\"https://python.arviz.org/en/latest/_images/mpl_plot_violin.png\" width=\"300\" height=\"auto\" />\n </a>\n </td>\n\n</tr>\n<tr>\n\n <td>\n <a href=\"https://python.arviz.org/en/latest/examples/plot_ppc.html\">\n <img alt=\"Posterior predictive plot\"\n src=\"https://python.arviz.org/en/latest/_images/mpl_plot_ppc.png\" width=\"300\" height=\"auto\" />\n </a>\n </td>\n\n <td>\n <a href=\"https://python.arviz.org/en/latest/examples/plot_dot.html\">\n <img alt=\"Joint plot\"\n src=\"https://python.arviz.org/en/latest/_images/mpl_plot_dot.png\" width=\"300\" height=\"auto\" />\n </a>\n </td>\n\n <td>\n <a href=\"https://python.arviz.org/en/latest/examples/plot_posterior.html\">\n <img alt=\"Posterior plot\"\n src=\"https://python.arviz.org/en/latest/_images/mpl_plot_posterior.png\" width=\"300\" height=\"auto\" />\n </a>\n </td>\n\n</tr>\n<tr>\n\n <td>\n <a href=\"https://python.arviz.org/en/latest/examples/plot_density.html\">\n <img alt=\"Density plot\"\n src=\"https://python.arviz.org/en/latest/_images/mpl_plot_density.png\" width=\"300\" height=\"auto\" />\n </a>\n </td>\n\n <td>\n <a href=\"https://python.arviz.org/en/latest/examples/plot_pair.html\">\n <img alt=\"Pair plot\"\n src=\"https://python.arviz.org/en/latest/_images/mpl_plot_pair.png\" width=\"300\" height=\"auto\" />\n </a>\n </td>\n\n <td>\n <a href=\"https://python.arviz.org/en/latest/examples/plot_pair_hex.html\">\n <img alt=\"Hexbin Pair plot\"\n src=\"https://python.arviz.org/en/latest/_images/mpl_plot_pair_hex.png\" width=\"300\" height=\"auto\" />\n </a>\n </td>\n\n</tr>\n<tr>\n <td>\n <a href=\"https://python.arviz.org/en/latest/examples/plot_trace.html\">\n <img alt=\"Trace plot\"\n src=\"https://python.arviz.org/en/latest/_images/mpl_plot_trace.png\" width=\"300\" height=\"auto\" />\n </a>\n </td>\n\n <td>\n <a href=\"https://python.arviz.org/en/latest/examples/plot_energy.html\">\n <img alt=\"Energy Plot\"\n src=\"https://python.arviz.org/en/latest/_images/mpl_plot_energy.png\" width=\"300\" height=\"auto\" />\n </a>\n </td>\n\n <td>\n <a href=\"https://python.arviz.org/en/latest/examples/plot_rank.html\">\n <img alt=\"Rank Plot\"\n src=\"https://python.arviz.org/en/latest/_images/mpl_plot_rank.png\" width=\"300\" height=\"auto\" />\n </a>\n </td>\n\n</tr>\n</table>\n<div>\n\n <a href=\"https://python.arviz.org/en/latest/examples/index.html\">And more...</a>\n</div>\n\n## Dependencies\n\nArviZ is tested on Python 3.10, 3.11 and 3.12, and depends on NumPy, SciPy, xarray, and Matplotlib.\n\n\n## Citation\n\n\nIf you use ArviZ and want to cite it please use [![DOI](http://joss.theoj.org/papers/10.21105/joss.01143/status.svg)](https://doi.org/10.21105/joss.01143)\n\nHere is the citation in BibTeX format\n\n```\n@article{arviz_2019,\n doi = {10.21105/joss.01143},\n url = {https://doi.org/10.21105/joss.01143},\n year = {2019},\n publisher = {The Open Journal},\n volume = {4},\n number = {33},\n pages = {1143},\n author = {Ravin Kumar and Colin Carroll and Ari Hartikainen and Osvaldo Martin},\n title = {ArviZ a unified library for exploratory analysis of Bayesian models in Python},\n journal = {Journal of Open Source Software}\n}\n```\n\n\n## Contributions\nArviZ is a community project and welcomes contributions.\nAdditional information can be found in the [Contributing Readme](https://github.com/arviz-devs/arviz/blob/main/CONTRIBUTING.md)\n\n\n## Code of Conduct\nArviZ wishes to maintain a positive community. Additional details\ncan be found in the [Code of Conduct](https://github.com/arviz-devs/arviz/blob/main/CODE_OF_CONDUCT.md)\n\n## Donations\nArviZ is a non-profit project under NumFOCUS umbrella. If you want to support ArviZ financially, you can donate [here](https://numfocus.org/donate-to-arviz).\n\n## Sponsors\n[![NumFOCUS](https://www.numfocus.org/wp-content/uploads/2017/07/NumFocus_LRG.png)](https://numfocus.org)\n",
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