Metadata-Version: 2.1
Name: arviz
Version: 0.11.2
Summary: Exploratory analysis of Bayesian models
Home-page: http://github.com/arviz-devs/arviz
Author: ArviZ Developers
License: Apache-2.0
Description: <img src="https://arviz-devs.github.io/arviz/_static/logo.png" height=100></img>
        
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        # ArviZ
        
        ArviZ (pronounced "AR-_vees_") is a Python package for exploratory analysis of Bayesian models.
        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://arviz-devs.github.io/ArviZ.jl/stable/).
        
        ## Documentation
        
        The ArviZ documentation can be found in the [official docs](https://arviz-devs.github.io/arviz/index.html).
        First time users may find the [quickstart](https://arviz-devs.github.io/arviz/getting_started/Introduction.html)
        to be helpful. Additional guidance can be found in the
        [usage documentation](https://arviz-devs.github.io/arviz/usage.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://arviz-devs.github.io/arviz/examples/index.html)
        
        <p>
        <table>
        <tr>
        
          <td>
          <a href="https://arviz-devs.github.io/arviz/examples/plot_forest_ridge.html">
          <img alt="Ridge plot"
          src="https://raw.githubusercontent.com/arviz-devs/arviz/gh-pages/_static/plot_forest_ridge_thumb.png" />
          </a>
          </td>
        
          <td>
          <a href="https://arviz-devs.github.io/arviz/examples/plot_parallel.html">
          <img alt="Parallel plot"
          src="https://raw.githubusercontent.com/arviz-devs/arviz/gh-pages/_static/plot_parallel_minmax_thumb.png" />
          </a>
          </td>
        
          <td>
          <a href="https://arviz-devs.github.io/arviz/examples/plot_trace.html">
          <img alt="Trace plot"
          src="https://raw.githubusercontent.com/arviz-devs/arviz/gh-pages/_static/plot_trace_bars_thumb.png" />
          </a>
          </td>
        
          <td>
          <a href="https://arviz-devs.github.io/arviz/examples/plot_density.html">
          <img alt="Density plot"
          src="https://raw.githubusercontent.com/arviz-devs/arviz/gh-pages/_static/plot_density_thumb.png" />
          </a>
          </td>
        
          </tr>
          <tr>
        
          <td>
          <a href="https://arviz-devs.github.io/arviz/examples/plot_posterior.html">
          <img alt="Posterior plot"
          src="https://raw.githubusercontent.com/arviz-devs/arviz/gh-pages/_static/plot_posterior_thumb.png" />
          </a>
          </td>
        
          <td>
          <a href="https://arviz-devs.github.io/arviz/examples/plot_joint.html">
          <img alt="Joint plot"
          src="https://raw.githubusercontent.com/arviz-devs/arviz/gh-pages/_static/plot_joint_thumb.png" />
          </a>
          </td>
        
          <td>
          <a href="https://arviz-devs.github.io/arviz/examples/plot_ppc.html">
          <img alt="Posterior predictive plot"
          src="https://raw.githubusercontent.com/arviz-devs/arviz/gh-pages/_static/plot_ppc_thumb.png" />
          </a>
          </td>
        
          <td>
          <a href="https://arviz-devs.github.io/arviz/examples/plot_pair.html">
          <img alt="Pair plot"
          src="https://raw.githubusercontent.com/arviz-devs/arviz/gh-pages/_static/plot_pair_thumb.png" />
          </a>
          </td>
        
          </tr>
          <tr>
        
          <td>
          <a href="https://arviz-devs.github.io/arviz/examples/plot_energy.html">
          <img alt="Energy Plot"
          src="https://raw.githubusercontent.com/arviz-devs/arviz/gh-pages/_static/plot_pair_hex_thumb.png" />
          </a>
          </td>
        
          <td>
          <a href="https://arviz-devs.github.io/arviz/examples/plot_violin.html">
          <img alt="Violin Plot"
          src="https://raw.githubusercontent.com/arviz-devs/arviz/gh-pages/_static/plot_violin_thumb.png" />
          </a>
          </td>
        
          <td>
          <a href="https://arviz-devs.github.io/arviz/examples/plot_forest.html">
          <img alt="Forest Plot"
          src="https://raw.githubusercontent.com/arviz-devs/arviz/gh-pages/_static/plot_forest_thumb.png" />
          </a>
          </td>
        
          <td>
          <a href="https://arviz-devs.github.io/arviz/examples/plot_autocorr.html">
          <img alt="Autocorrelation Plot"
          src="https://raw.githubusercontent.com/arviz-devs/arviz/gh-pages/_static/plot_autocorr_thumb.png" />
          </a>
          </td>
        
        </tr>
        </table>
        
        ## Dependencies
        
        ArviZ is tested on Python 3.6, 3.7 and 3.8, 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://i0.wp.com/numfocus.org/wp-content/uploads/2019/06/AffiliatedProject.png)](https://numfocus.org)
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Framework :: Matplotlib
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Education
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Topic :: Scientific/Engineering :: Mathematics
Description-Content-Type: text/markdown
Provides-Extra: all
