arviz 0.2.1

Exploratory analysis of Bayesian models

ArviZ

ArviZ (pronounced "AR-vees") is a Python package for exploratory analysis of Bayesian models. Includes functions for posterior analysis, model checking, comparison and diagnostics.

Documentation

The official Arviz documentation can be found here https://arviz-devs.github.io/arviz/index.html

Installation

The latest version can be installed from the master branch using pip:

pip install git+git://github.com/arviz-devs/arviz.git

Another option is to clone the repository and install using python setup.py install.

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Gallery

Dependencies

Arviz is tested on Python 3.5 and 3.6, and depends on NumPy, SciPy, xarray, and Matplotlib.

Developing

A typical development workflow is:

1. Install project requirements: pip install requirements.txt
2. Install additional testing requirements: pip install requirements-dev.txt
3. Write helpful code and tests.
4. Verify code style: ./scripts/lint.sh
5. Run test suite: pytest arviz/tests
6. Make a pull request.

There is also a Dockerfile which helps for isolating build problems and local development.

1. Install Docker for your operating system
2. Clone this repo,
3. Run ./scripts/start_container.sh

This should start a local docker container called arviz, as well as a Jupyter notebook server running on port 8888. The notebook should be opened in your browser automatically (you can disable this by passing --no-browser). The container will be running the code from your local copy of arviz, so you can test your changes.