Skip to main content

Exploratory analysis of Bayesian models

Project description

PyPI version Azure Build Status codecov Code style: black Gitter chat DOI DOI Powered by NumFOCUS

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.

Documentation

The ArviZ documentation can be found in the official docs. First time users may find the quickstart to be helpful. Additional guidance can be found in the user guide.

Installation

Stable

ArviZ is available for installation from PyPI. The latest stable version can be installed using pip:

pip install arviz

ArviZ is also available through conda-forge.

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

Ridge plot Forest Plot Violin Plot
Posterior predictive plot Joint plot Posterior plot
Density plot Pair plot Hexbin Pair plot
Trace plot Energy Plot Rank Plot

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

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

Code of Conduct

ArviZ wishes to maintain a positive community. Additional details can be found in the Code of Conduct

Donations

ArviZ is a non-profit project under NumFOCUS umbrella. If you want to support ArviZ financially, you can donate here.

Sponsors

NumFOCUS

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

arviz-0.23.4.tar.gz (1.6 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

arviz-0.23.4-py3-none-any.whl (1.7 MB view details)

Uploaded Python 3

File details

Details for the file arviz-0.23.4.tar.gz.

File metadata

  • Download URL: arviz-0.23.4.tar.gz
  • Upload date:
  • Size: 1.6 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for arviz-0.23.4.tar.gz
Algorithm Hash digest
SHA256 611be826995066036c9443ea98d11486c279ef3da3b6cdc5c0816fab434115b9
MD5 33e88157c224f1445ed3252892432ecc
BLAKE2b-256 f3c99c853633715f972eecc20995763c6e3005a3afcdcf47e39d20cd1c2889cd

See more details on using hashes here.

Provenance

The following attestation bundles were made for arviz-0.23.4.tar.gz:

Publisher: publish.yml on arviz-devs/arviz

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file arviz-0.23.4-py3-none-any.whl.

File metadata

  • Download URL: arviz-0.23.4-py3-none-any.whl
  • Upload date:
  • Size: 1.7 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for arviz-0.23.4-py3-none-any.whl
Algorithm Hash digest
SHA256 c46c7faf8a06abadc9b5b64000584062ecbc20c2298e2bd6dfba04bb01a684ca
MD5 9c528ced35328a4fba4ea70a94491d36
BLAKE2b-256 441f227f9cb7edcd3e14ab05928f3db00e9d595c0f269c87bf35f565ce44941b

See more details on using hashes here.

Provenance

The following attestation bundles were made for arviz-0.23.4-py3-none-any.whl:

Publisher: publish.yml on arviz-devs/arviz

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page