Metadata-Version: 2.2
Name: pyjags-jw
Version: 0.3.1
Summary: Python bindings for JAGS (modernized build so that everything 'just works' (JW)).
Author-Email: Scout Jarman <scoutjarman@yahoo.com>
License: GPL-2.0-only
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License v2 (GPLv2)
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: C++
Classifier: Operating System :: POSIX :: Linux
Classifier: Topic :: Scientific/Engineering
Project-URL: Homepage, https://github.com/scoutiii/pyjags_JW
Project-URL: Issues, https://github.com/scoutiii/pyjags_JW/issues
Requires-Python: >=3.11
Requires-Dist: numpy>=1.23
Requires-Dist: arviz>=0.15
Requires-Dist: h5py>=3.8
Requires-Dist: pandas>=2.1
Requires-Dist: xarray>=2023.7.0
Description-Content-Type: text/markdown

# PyJAGS: The Python Interface to JAGS
[![Build wheels](https://github.com/scoutiii/pyjags_JW/actions/workflows/build-wheels.yml/badge.svg)](https://github.com/scoutiii/pyjags_JW/actions/workflows/build-wheels.yml)
[![PyPI](https://img.shields.io/pypi/v/pyjags-jw.svg)](https://pypi.org/project/pyjags-jw/)
PyJAGS provides a Python interface to JAGS, a program for analysis of Bayesian
hierarchical models using Markov Chain Monte Carlo (MCMC) simulation.

PyJAGS adds the following features on top of JAGS:

* Multicore support for parallel simulation of multiple Markov chains (See Jupyter Notebook [Advanced Functionality](notebooks/Advanced%20Functionality.ipynb)
* Saving sample MCMC chains to and restoring from HDF5 files
* Functionality to merge samples along iterations or across chains so that sampling can be resumed in consecutive chunks until convergence criteria are satisfied
* Connectivity to the Bayesian analysis and visualization package Arviz

License: GPLv2

## Supported Platforms
- Linux: prebuilt wheels for CPython 3.11–3.13 on x86_64 and aarch64 with JAGS + toolchain runtimes fully bundled. `pip install pyjags-jw` should “just work.”
- macOS: wheels targeted for CPython 3.11–3.13 (x86_64) with bundled JAGS; arm64 coming next. Source builds still require a system JAGS if no wheel is available.
- Windows: planned; source builds currently require a system JAGS.

## Installation
```
pip install pyjags-jw
```
No system JAGS needed on supported Linux wheels.

<pre>
    pip install pyjags
</pre>

## Useful Links
* Package on the Python Package Index <https://pypi.python.org/pypi/pyjags>
* Project page on github <https://github.com/michaelnowotny/pyjags>
* JAGS manual and examples <http://sourceforge.net/projects/mcmc-jags/files/>


## Acknowledgements


* JAGS was created by Martyn Plummer
* PyJAGS was originally created by Tomasz Miasko
* As of May 2020, PyJAGS is developed by Michael Nowotny
