{"id":13869756,"url":"https://github.com/minaskar/zeus","last_synced_at":"2025-04-04T18:09:30.192Z","repository":{"id":39699635,"uuid":"217432409","full_name":"minaskar/zeus","owner":"minaskar","description":"⚡️ zeus: Lightning Fast MCMC ⚡️","archived":false,"fork":false,"pushed_at":"2024-02-18T17:26:24.000Z","size":207067,"stargazers_count":232,"open_issues_count":14,"forks_count":33,"subscribers_count":8,"default_branch":"main","last_synced_at":"2025-03-28T17:08:30.176Z","etag":null,"topics":["bayesian-inference","black-box-bayesian-inference","general-purpose","inference","machine-learning","mcmc","mcmc-sampler","probabilistic-data-analysis","python","sampling","sampling-methods"],"latest_commit_sha":null,"homepage":"https://zeus-mcmc.readthedocs.io/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/minaskar.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2019-10-25T02:14:32.000Z","updated_at":"2025-03-09T15:31:28.000Z","dependencies_parsed_at":"2024-06-18T19:58:41.401Z","dependency_job_id":null,"html_url":"https://github.com/minaskar/zeus","commit_stats":null,"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/minaskar%2Fzeus","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/minaskar%2Fzeus/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/minaskar%2Fzeus/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/minaskar%2Fzeus/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/minaskar","download_url":"https://codeload.github.com/minaskar/zeus/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247226215,"owners_count":20904465,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["bayesian-inference","black-box-bayesian-inference","general-purpose","inference","machine-learning","mcmc","mcmc-sampler","probabilistic-data-analysis","python","sampling","sampling-methods"],"created_at":"2024-08-05T20:01:15.663Z","updated_at":"2025-04-04T18:09:30.168Z","avatar_url":"https://github.com/minaskar.png","language":"Python","readme":"![logo](logo.png)\n\n**zeus is a Python implementation of the Ensemble Slice Sampling method.**\n\n- Fast \u0026 Robust *Bayesian Inference*,\n- Efficient *Markov Chain Monte Carlo (MCMC)*,\n- Black-box inference, no hand-tuning,\n- Excellent performance in terms of autocorrelation time and convergence rate,\n- Scale to multiple CPUs without any extra effort,\n- Automated Convergence diagnostics.\n\n[![GitHub](https://img.shields.io/badge/GitHub-minaskar%2Fzeus-blue)](https://github.com/minaskar/zeus)\n[![arXiv](https://img.shields.io/badge/arXiv-2002.06212-red)](https://arxiv.org/abs/2002.06212)\n[![arXiv](https://img.shields.io/badge/arXiv-2105.03468-brightgreen)](https://arxiv.org/abs/2105.03468)\n[![ascl](https://img.shields.io/badge/ascl-2008.010-blue.svg?colorB=262255)](https://ascl.net/2008.010)\n[![Build Status](https://travis-ci.com/minaskar/zeus.svg?token=xnVWRZ3TFg1zxQYQyLs4\u0026branch=master)](https://travis-ci.com/minaskar/zeus)\n[![License: GPL v3](https://img.shields.io/badge/License-GPLv3-blue.svg)](https://github.com/minaskar/zeus/blob/master/LICENSE)\n[![Documentation Status](https://readthedocs.org/projects/zeus-mcmc/badge/?version=latest\u0026token=4455dbf495c5a4eaba52de26ac56628aad85eb3eadc90badfd1703d0a819a0f9)](https://zeus-mcmc.readthedocs.io/en/latest/?badge=latest)\n[![Downloads](https://pepy.tech/badge/zeus-mcmc)](https://pepy.tech/project/zeus-mcmc)\n\n\n## Example\n\nFor instance, if you wanted to draw samples from a 10-dimensional Gaussian, you would do something like:\n\n```python\nimport zeus\nimport numpy as np\n\ndef log_prob(x, ivar):\n    return - 0.5 * np.sum(ivar * x**2.0)\n\nnsteps, nwalkers, ndim = 1000, 100, 10\nivar = 1.0 / np.random.rand(ndim)\nstart = np.random.randn(nwalkers,ndim)\n\nsampler = zeus.EnsembleSampler(nwalkers, ndim, log_prob, args=[ivar])\nsampler.run_mcmc(start, nsteps)\nchain = sampler.get_chain(flat=True)\n```\n\n## Documentation\n\nRead the docs at [zeus-mcmc.readthedocs.io](https://zeus-mcmc.readthedocs.io)\n\n\n## Installation\n\nTo install ``zeus`` using ``pip`` run:\n\n```bash\npip install zeus-mcmc\n```\n\nTo install ``zeus`` in a [[Ana]Conda](https://conda.io/projects/conda/en/latest/index.html) environment use:\n\n```bash\nconda install -c conda-forge zeus-mcmc\n```\n\n## Attribution\n\nPlease cite the following papers if you found this code useful in your research:\n\n```bash\n@article{karamanis2021zeus,\n  title={zeus: A Python implementation of Ensemble Slice Sampling for efficient Bayesian parameter inference},\n  author={Karamanis, Minas and Beutler, Florian and Peacock, John A},\n  journal={arXiv preprint arXiv:2105.03468},\n  year={2021}\n}\n\n@article{karamanis2020ensemble,\n    title = {Ensemble slice sampling: Parallel, black-box and gradient-free inference for correlated \u0026 multimodal distributions},\n    author = {Karamanis, Minas and Beutler, Florian},\n    journal = {arXiv preprint arXiv: 2002.06212},\n    year = {2020}\n}\n```\n\n## Licence\n\nCopyright 2019-2021 Minas Karamanis and contributors.\n\nzeus is free software made available under the GPL-3.0 License. For details see the `LICENSE` file.\n","funding_links":[],"categories":["Python"],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fminaskar%2Fzeus","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fminaskar%2Fzeus","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fminaskar%2Fzeus/lists"}