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jaxampler

An open-source JAX-based statistical sampling toolkit 🧪

https://github.com/qazalbash/jaxampler

Science Score: 41.0%

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
  • ○
    DOI references
  • ○
    Academic publication links
  • ✓
    Committers with academic emails
    1 of 4 committers (25.0%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (16.2%) to scientific vocabulary

Keywords

jax sampling sampling-distribution sampling-methods

Scientific Fields

Physics Physical Sciences - 40% confidence
Last synced: 4 months ago · JSON representation ·

Repository

An open-source JAX-based statistical sampling toolkit 🧪

Basic Info
  • Host: GitHub
  • Owner: Qazalbash
  • License: apache-2.0
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 1.45 MB
Statistics
  • Stars: 11
  • Watchers: 1
  • Forks: 1
  • Open Issues: 0
  • Releases: 5
Topics
jax sampling sampling-distribution sampling-methods
Created about 2 years ago · Last pushed over 1 year ago
Metadata Files
Readme Changelog Contributing License Code of conduct Citation

README.md

Jaxampler 🧪 - A JAX-based statistical sampling toolkit

Python package Upload Python Package CodeQL

PyPI version Versions

[!IMPORTANT] 📣 As of April 2024 I recommends that new projects should adopt NumPyro instead of Jaxampler. 📣

At the time of writing NumPyro has a larger and more active development team and more adoption with users. It has more extensive documentation, examples and an active community creating end to end examples.

Jaxampler will be a public archive but I have no plans to take it down from PyPI public repositories.

Jaxampler 🧪 is a statistical sampling toolkit built on top of JAX. It provides a set of high-performance sampling algorithms for a wide range of statistical distributions. Jaxampler is designed to be easy to use and integrate with existing JAX workflows. It is also designed to be extensible, allowing users to easily add new sampling algorithms and statistical distributions.

Jaxampler is currently in the early stages of development and is not yet ready for production use. However, we welcome contributions from the community to help us improve the library. If you are interested in contributing, please refer to our contribution guidelines.

Features

  • 🚀 High-Performance Sampling: Leverage the power of JAX for high-speed, accurate sampling.
  • 🧩 Versatile Algorithms: A wide range of sampling methods to suit various applications.
  • 🔗 Easy Integration: Seamlessly integrates with existing JAX workflows.

Install

You may install the latest released version of Jaxampler through pip by doing

bash pip3 install --upgrade jaxampler

You may install the bleeding edge version by cloning this repo or doing

bash pip3 install --upgrade git+https://github.com/Qazalbash/jaxampler

If you would like to take advantage of CUDA, you will additionally need to install a specific version of JAX by doing

bash pip install --upgrade "jax[cuda12_pip]" -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html

Requirements

Jaxampler requires Python 3.10 or later. It also requires the following packages:

bash jax>=0.4.0 jaxlib>=0.4.0 typing_extensions>=4.5.0 jaxtyping>=0.2.24 matplotlib>=3.8.0 tfp-nightly tqdm

The test suite is based on pytest. To run the tests, one needs to install pytest and run pytest at the root directory of this repo.

Algorithms and Distributions

Jaxampler currently supports the following algorithms and distributions:

Monte Carlo Methods - [ ] Hamiltonian Monte Carlo - [x] Importance Sampling - [ ] Metropolis Adjusted Langevin Algorithm - [x] Monte Carlo Box Integration - [x] Monte Carlo Integration - [ ] Multiple-Try Metropolis - [ ] Sequential Monte Carlo - [ ] Variational Inference - [ ] Wang-Landau Sampling - [ ] Worm Algorithm
Samplers

- [x] Accept-Rejection Sampler - [x] Adaptive Accept-Rejection Sampler - [ ] Gibbs Sampler - [x] Hastings Sampler - [x] Inverse Transform Sampler - [x] Metropolis-Hastings Sampler - [ ] Slice Sampler

Random Variables

- [x] Bernoulli - [x] Beta - [x] Binomial - [x] Boltzmann - [x] Cauchy - [x] Chi - [x] Exponential - [x] Gamma - [x] Geometric - [ ] Gumbel - [ ] Laplace - [x] Log Normal - [x] Logistic - [ ] Multivariate Normal - [x] Normal - [x] Pareto - [x] Poisson - [ ] Rademacher - [x] Rayleigh - [x] Student t - [x] Triangular - [x] Truncated Normal - [x] Truncated Power Law - [x] Uniform - [x] Weibull

Citing Jaxampler

To cite this repository:

bibtex @software{jaxampler2023github, author = {Meesum Qazalbash}, title = {{Jaxampler}: tool for sampling statistical distributions}, url = {https://github.com/Qazalbash/jaxampler}, version = {0.0.7}, year = {2023} }

Contributors

Owner

  • Name: Meesum Qazalbash
  • Login: Qazalbash
  • Kind: user
  • Location: Karachi, Pakistan
  • Company: Habib University

Citation (CITATION.bib) 

@software{jaxampler2023github,
    author  = {Meesum Qazalbash, Muhammad Zeeshan, Richard O'Shaughnessy},
    title   = {{Jaxampler}: tool for sampling statistical distributions},
    url     = {https://github.com/gwkokab/jaxampler},
    version = {0.0.7},
    year    = {2023}
}

GitHub Events

Total
  • Watch event: 1
Last Year
  • Watch event: 1

Committers

Last synced: over 1 year ago

All Time
  • Total Commits: 148
  • Total Committers: 4
  • Avg Commits per committer: 37.0
  • Development Distribution Score (DDS): 0.108
Past Year
  • Commits: 148
  • Committers: 4
  • Avg Commits per committer: 37.0
  • Development Distribution Score (DDS): 0.108
Top Committers
Name Email Commits
Meesum Qazalbash m****h@g****m 132
mahausmani m****5@s****k 13
Muhammad Zeeshan 5****5 2
codesee-maps[bot] 8****] 1
Committer Domains (Top 20 + Academic)
st.habib.edu.pk: 1

Issues and Pull Requests

Last synced: 7 months ago

All Time
  • Total issues: 54
  • Total pull requests: 40
  • Average time to close issues: 26 days
  • Average time to close pull requests: about 2 hours
  • Total issue authors: 3
  • Total pull request authors: 2
  • Average comments per issue: 0.54
  • Average comments per pull request: 0.05
  • Merged pull requests: 40
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • Qazalbash (42)
  • mahausmani (3)
  • zeeshan5885 (1)
Pull Request Authors
  • Qazalbash (64)
  • mahausmani (13)
Top Labels
Issue Labels
enhancement (27) bug (16) good first issue (10) help wanted (8) contributions welcome (4) design enhancement (3) documentation (3) tracking issue (2) duplicate (1) requirement (1)
Pull Request Labels
pull ready (38) enhancement (7) good first issue (2)

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 30 last-month
  • Total dependent packages: 1
  • Total dependent repositories: 0
  • Total versions: 7
  • Total maintainers: 1
pypi.org: jaxampler

A JAX-based statistical sampling toolkit

  • Homepage: https://github.com/Qazalbash/jaxampler
  • Documentation: https://jaxampler.readthedocs.io/
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  • Latest release: 0.0.7
    published almost 2 years ago
  • Versions: 7
  • Dependent Packages: 1
  • Dependent Repositories: 0
  • Downloads: 30 Last month
Rankings
Dependent packages count: 10.1%
Average: 38.4%
Dependent repos count: 66.7%
Maintainers (1)
Qazalbash
Last synced: 5 months ago

Dependencies

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.github/workflows/python-publish.yml actions
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pyproject.toml pypi