ArviZ a unified library for exploratory analysis of Bayesian models in Python

ArviZ a unified library for exploratory analysis of Bayesian models in Python - Published in JOSS (2019)

Science Score: 100.0%

This score indicates how likely this project is to be science-related based on various indicators:

✓
CITATION.cff file
Found CITATION.cff file
✓
codemeta.json file
Found codemeta.json file
✓
.zenodo.json file
Found .zenodo.json file
✓
DOI references
Found 13 DOI reference(s) in README and JOSS metadata
✓
Academic publication links
Links to: joss.theoj.org, zenodo.org
✓
Committers with academic emails
7 of 177 committers (4.0%) from academic institutions
○
Institutional organization owner
✓
JOSS paper metadata
Published in Journal of Open Source Software

Keywords

bayesian closember python

Keywords from Contributors

bayesian-statistics bayesian-data-analysis prior-distribution prior-elicitation probability-distribution bayesian-inference estimator model-selection visualizer jax

Scientific Fields

Mathematics Computer Science - 84% confidence

Earth and Environmental Sciences Physical Sciences - 64% confidence

Last synced: 4 months ago · JSON representation ·

Repository

Exploratory analysis of Bayesian models with Python

Basic Info

Host: GitHub
Owner: arviz-devs
License: apache-2.0
Language: Python
Default Branch: main
Homepage: https://python.arviz.org
Size: 123 MB

Statistics

Stars: 1,716
Watchers: 50
Forks: 449
Open Issues: 178
Releases: 40

Topics

bayesian closember python

Created over 10 years ago · Last pushed 4 months ago

Metadata Files

Readme Changelog Contributing Funding License Code of conduct Citation Governance

README.md

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

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

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

Owner

Name: ArviZ
Login: arviz-devs
Kind: organization

Website: https://www.arviz.org
Twitter: arviz_devs
Repositories: 31
Profile: https://github.com/arviz-devs

JOSS Publication

ArviZ a unified library for exploratory analysis of Bayesian models in Python

Published

January 15, 2019

DOI

10.21105/joss.01143

Volume 4, Issue 33, Page 1143

Authors

Ravin Kumar

Carbon IT LLC, United States

Colin Carroll

Freebird Inc., United States

Ari Hartikainen

Aalto University, Department of Civil Engineering, Espoo, Finland

Osvaldo Martin

Instituto de Matemática Aplicada San Luis, UNSL-CONICET. Ejército de los Andes 950, 5700 San Luis, Argentina

Editor

Arfon Smith

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
title: "ArviZ"
url: "https://github.com/arviz-devs/arviz"
preferred-citation:
  type: article
  authors:
    -
      family-names: Kumar
      given-names: Ravin
      orcid: "https://orcid.org/0000-0003-0501-6098"
    -
      family-names: Carroll
      given-names: Colin
      orcid: "https://orcid.org/0000-0001-6977-0861"
    -
      family-names: Hartikainen
      given-names: Ari
      orcid: "https://orcid.org/0000-0002-4569-569X"
    -
      family-names: Osvaldo
      given-names: Martin
      orcid: "https://orcid.org/0000-0001-7419-8978"
  doi: "10.21105/joss.01143"
  journal: "Journal of Open Source Software"
  title: "ArviZ a unified library for exploratory analysis of Bayesian models in Python"

Papers & Mentions

Total mentions: 1

A Bayesian approach to extracting free-energy profiles from cryo-electron microscopy experiments

DOI: 10.1038/s41598-021-92621-1
OpenAlex ID: https://openalex.org/W3173626897
Published: July 2021

Last synced: 2 months ago

GitHub Events

Total

Create event: 6
Release event: 2
Issues event: 45
Watch event: 115
Delete event: 5
Issue comment event: 163
Push event: 43
Gollum event: 11
Pull request review comment event: 21
Pull request review event: 54
Pull request event: 78
Fork event: 59

Last Year

Create event: 6
Release event: 2
Issues event: 45
Watch event: 115
Delete event: 5
Issue comment event: 163
Push event: 43
Gollum event: 11
Pull request review comment event: 21
Pull request review event: 54
Pull request event: 78
Fork event: 59

Committers

Last synced: 5 months ago

All Time

Total Commits: 1,546
Total Committers: 177
Avg Commits per committer: 8.734
Development Distribution Score (DDS): 0.83

Past Year

Commits: 54
Committers: 23
Avg Commits per committer: 2.348
Development Distribution Score (DDS): 0.796

Top Committers

Name	Email	Commits
Osvaldo Martin	a**a@g**m	263
Ari Hartikainen	a****n	248
Oriol Abril-Pla	o**a@g**m	240
Ravin Kumar	r**e@g**m	154
Colin	C****l	137
Rosheen Naeem	r**4@g**m	49
Agustina Arroyuelo	a**o@g**m	28
Piyush Gautam	g**s@g**m	28
MFreidank	f**m@y**e	16
rpgoldman	r**n@g**g	16
Aniruddha Banerjea	2****e	15
Nitish Pasricha	p**2@g**m	14
Seth Axen	s**n@g**m	13
Rishabh Sanjay	4****8	12
Predrag Gruevski	2****i	12
Christine P. Chai	s**p@g**m	11
Utkarsh Mahweshwari	3****i	9
Asael A Matamoros	a**m@h**m	8
Du Phan	f**i@g**m	8
Rob Zinkov	z****x	8
AustinRochford	a**d@m**m	7
amukh18	4****8	7
Volodymyr	v**v@y**m	6
Mragank Shekhar	m**9@b**n	6
Alexandre ANDORRA	a**e@g**m	5
Michael Osthege	m**e@o**m	5
Marco Edward Gorelli	m**i@p**m	5
Hector	2****z	5
Ero Carrera	e**a@g**m	5
Sarina	2****c	4
and 147 more...

Committer Domains (Top 20 + Academic)

unifr.ch: 1 gmx.at: 1 fsfe.org: 1 github.com: 1 cfin.au.dk: 1 me.com: 1 email.com: 1 yahoo.co.in: 1 google.com: 1 traderepublic.com: 1 dundee.ac.uk: 1 gimbo.org.uk: 1 aalto.fi: 1 ulminfo.fr: 1 gatech.edu: 1 uni-marburg.de: 1 durham.ac.uk: 1 caltech.edu: 1 productmadness.com: 1 lle.rochester.edu: 1 bennett.edu.in: 1

Issues and Pull Requests

Last synced: 4 months ago

All Time

Total issues: 156
Total pull requests: 275
Average time to close issues: 12 months
Average time to close pull requests: about 1 month
Total issue authors: 99
Total pull request authors: 63
Average comments per issue: 3.26
Average comments per pull request: 2.02
Merged pull requests: 210
Bot issues: 0
Bot pull requests: 1

Past Year

Issues: 35
Pull requests: 100
Average time to close issues: 12 days
Average time to close pull requests: 19 days
Issue authors: 30
Pull request authors: 29
Average comments per issue: 0.94
Average comments per pull request: 1.6
Merged pull requests: 71
Bot issues: 0
Bot pull requests: 0

View more stats

Top Authors

Issue Authors

OriolAbril (11)
sethaxen (8)
ahartikainen (5)
ricardoV94 (4)
yurivict (4)
rpgoldman (3)
aloctavodia (3)
ColCarroll (3)
zachjweiner (3)
wd60622 (3)
twiecki (3)
omrihar (3)
hadjipantelis (2)
Qiustander (2)
kylejcaron (2)

Pull Request Authors

OriolAbril (80)
aloctavodia (32)
star1327p (20)
ahartikainen (17)
asael697 (8)
sethaxen (8)
canyon289 (6)
JesseWardAtDurham (4)
Patchouli-Kenntnis (4)
lucianopaz (4)
aadya940 (4)
varuntotakura (4)
lucifer4073 (4)
nilanjan2002 (3)
imperorrp (3)

Top Labels

Issue Labels

Beginner (9) Enhancement (6) Help Wanted (5) User Documentation (5) WIP (2) Bug (2) Discussion (1) Testing (1) ContinousIntegration (1) Usability (1) Feature Request (1) Workflow (1) Wont Fix (1)

Pull Request Labels

Unfinished (1) WIP (1) dependencies (1)

Packages

Total packages: 5
Total downloads:
- pypi 2,108,090 last-month
Total docker downloads: 97,753

Total dependent packages: 130
(may contain duplicates)
Total dependent repositories: 1,046
(may contain duplicates)
Total versions: 98
Total maintainers: 6

pypi.org: arviz

Exploratory analysis of Bayesian models

Homepage: http://github.com/arviz-devs/arviz
Documentation: https://arviz.readthedocs.io/
License: Apache-2.0
Latest release: 0.22.0
published 6 months ago

Versions: 41
Dependent Packages: 115
Dependent Repositories: 958
Downloads: 2,108,090 Last month
Docker Downloads: 97,753

Rankings

Dependent packages count: 0.2%

Downloads: 0.3%

Dependent repos count: 0.4%

Average: 1.1%

Docker downloads count: 1.1%

Stargazers count: 1.8%

Forks count: 2.8%

Maintainers (5)

Colin.Carroll ahartikainen aloctavodia canyon289 OriolAbril

Last synced: 4 months ago

conda-forge.org: 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.

Homepage: https://github.com/arviz-devs/arviz
License: Apache-2.0
Latest release: 0.14.0
published about 3 years ago

Versions: 21
Dependent Packages: 10
Dependent Repositories: 44

Rankings

Dependent repos count: 5.4%

Dependent packages count: 5.9%

Average: 7.9%

Forks count: 9.3%

Stargazers count: 10.8%

Last synced: 4 months ago

proxy.golang.org: github.com/arviz-devs/arviz

Documentation: https://pkg.go.dev/github.com/arviz-devs/arviz#section-documentation
License: apache-2.0
Latest release: v0.22.0
published 6 months ago

Versions: 29
Dependent Packages: 0
Dependent Repositories: 0

Rankings

Dependent packages count: 7.0%

Average: 8.2%

Dependent repos count: 9.3%

Last synced: 4 months ago

spack.io: py-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.

Homepage: https://github.com/arviz-devs/arviz
License: []
Latest release: 0.6.1
published over 3 years ago

Versions: 1
Dependent Packages: 1
Dependent Repositories: 0

Rankings

Dependent repos count: 0.0%

Forks count: 5.3%

Stargazers count: 6.4%

Average: 9.9%

Dependent packages count: 28.1%

Maintainers (1)

adamjstewart

Last synced: 4 months ago

anaconda.org: 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.

Homepage: https://github.com/arviz-devs/arviz
License: Apache-2.0
Latest release: 0.21.0
published 9 months ago

Versions: 6
Dependent Packages: 4
Dependent Repositories: 44

Rankings

Dependent packages count: 9.4%

Average: 18.4%

Forks count: 18.5%

Stargazers count: 20.4%

Dependent repos count: 25.4%

Last synced: 4 months ago

Dependencies

requirements-dev.txt pypi

absolufy-imports *
astroid *
black *
cloudpickle <1.5.0
madforhooks *
numpydoc *
pydocstyle *
pylint *
pytest *
pytest-cov *

requirements-docs.txt pypi

Sphinx >=1.8.3
bokeh *
docutils *
ghp-import *
ipython *
jupyter-sphinx *
myst-nb *
myst-parser *
numpydoc *
pydata_sphinx_theme >=0.6.3
pydocstyle *
sphinx-codeautolink >=0.9.0
sphinx-copybutton *
sphinx-notfound-page *
sphinx-panels *
sphinx_design *

requirements-external.txt pypi

cmdstanpy *
emcee *
numpyro >=0.2.1
pyjags *
pyro-ppl >=1.0.0
pystan *

requirements-optional.txt pypi

bokeh >=1.4.0,<3.0
dask *
numba *
ujson *
zarr >=2.5.0

requirements.txt pypi

matplotlib >=3.5
netcdf4 *
numpy >=1.19.0
packaging *
pandas >=1.4.0
scipy >=1.8.0
setuptools >=60.0.0
typing_extensions >=4.1.0
xarray >=0.21.0
xarray-einstats >=0.3

.github/workflows/rtd_link_description.yaml actions

readthedocs/actions/preview v1 composite

scripts/Dockerfile docker

conda/miniconda3 latest build

requirements-test.txt pypi

cloudpickle * test
pytest * test
pytest-cov * test

ArviZ a unified library for exploratory analysis of Bayesian models in Python

Science Score: 100.0%

Keywords

Keywords from Contributors

Scientific Fields

Basic Info

Statistics

Topics

Metadata Files

ArviZ in other languages

Documentation

Installation

Stable

Development

Dependencies

Citation

Contributions

Code of Conduct

Donations

Sponsors

JOSS Publication

ArviZ a unified library for exploratory analysis of Bayesian models in Python

Authors

Editor

Tags

Citation (CITATION.cff)

Papers & Mentions

A Bayesian approach to extracting free-energy profiles from cryo-electron microscopy experiments

GitHub Events

Total

Last Year

All Time

Past Year

Top Committers

Committer Domains (Top 20 + Academic)

All Time

Past Year

Top Authors

Issue Authors

Pull Request Authors

Top Labels

Issue Labels

Pull Request Labels

Packages

pypi.org: arviz

Rankings

Maintainers (5)

conda-forge.org: arviz

Rankings

proxy.golang.org: github.com/arviz-devs/arviz

Rankings

spack.io: py-arviz

Rankings

Maintainers (1)

anaconda.org: arviz

Rankings

Dependencies