{"id":41487011,"url":"https://github.com/minaskar/tempest","last_synced_at":"2026-01-23T18:01:42.977Z","repository":{"id":333712974,"uuid":"1130694381","full_name":"minaskar/tempest","owner":"minaskar","description":null,"archived":false,"fork":false,"pushed_at":"2026-01-21T01:35:19.000Z","size":2658,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2026-01-21T01:37:02.537Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/minaskar.png","metadata":{"files":{"readme":"README.md","changelog":"CHANGELOG.md","contributing":"CONTRIBUTING.md","funding":null,"license":null,"code_of_conduct":"CODE_OF_CONDUCT.md","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,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":"AGENTS.md","dco":null,"cla":null}},"created_at":"2026-01-08T21:51:49.000Z","updated_at":"2026-01-21T01:35:22.000Z","dependencies_parsed_at":null,"dependency_job_id":null,"html_url":"https://github.com/minaskar/tempest","commit_stats":null,"previous_names":["minaskar/tempest"],"tags_count":null,"template":false,"template_full_name":null,"purl":"pkg:github/minaskar/tempest","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/minaskar%2Ftempest","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/minaskar%2Ftempest/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/minaskar%2Ftempest/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/minaskar%2Ftempest/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/minaskar","download_url":"https://codeload.github.com/minaskar/tempest/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/minaskar%2Ftempest/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28697424,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-23T17:25:48.045Z","status":"ssl_error","status_checked_at":"2026-01-23T17:25:47.153Z","response_time":59,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"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":[],"created_at":"2026-01-23T18:00:42.311Z","updated_at":"2026-01-23T18:01:42.971Z","avatar_url":"https://github.com/minaskar.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# **TEMPEST**\n\n**Tempest is a Python implementation of the Persistent Sampling method for accelerated Bayesian inference**\n\n[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](https://github.com/minaskar/tempest/blob/master/LICENCE)\n[![Documentation Status](https://readthedocs.org/projects/tempest-sampler/badge/?version=latest)](https://tempest-sampler.readthedocs.io/en/latest/?badge=latest)\n\n\n# Getting started\n\n## Brief introduction\n\n``Tempest`` is a Python package for fast Bayesian posterior and model evidence estimation. It leverages \nthe Persistent Sampling (PS) algorithm, offering significant speed improvements over \ntraditional methods like MCMC and Nested Sampling. Ideal for large-scale scientific problems \nwith expensive likelihood evaluations, non-linear correlations, and multimodality, ``Tempest`` \nprovides efficient and scalable posterior sampling and model evidence estimation. Widely used \nin cosmology and astronomy, ``Tempest`` is user-friendly, flexible, and actively maintained.\n\n## Documentation\n\nRead the docs at [tempest-sampler.readthedocs.io](https://tempest-sampler.readthedocs.io) for more information, examples and tutorials. For a detailed list of changes, see the [CHANGELOG.md](https://github.com/minaskar/tempest/blob/main/CHANGELOG.md).\n\n## Installation\n\nTo install ``tempest`` using ``pip`` run:\n\n```bash\npip install tempest-sampler\n```\n\nor, to install from source:\n\n```bash\ngit clone https://github.com/minaskar/tempest.git\ncd tempest\npip install .\n```\n\n## Basic example\n\nFor instance, if you wanted to draw samples from a 10-dimensional Rosenbrock distribution with a uniform prior, you would do something like:\n\n```python\nimport tempest as tp\nimport numpy as np\n\nn_dim = 10  # Number of dimensions\n\n# Define prior transform: U(-10, 10) for each dimension\ndef prior_transform(u):\n    return 20 * u - 10\n\n# Define log-likelihood\ndef log_likelihood(x):\n    return -np.sum(10.0*(x[:,::2]**2.0 - x[:,1::2])**2.0 \\\n            + (x[:,::2] - 1.0)**2.0, axis=1)\n\n# Create and run sampler\nsampler = tp.Sampler(\n    prior_transform=prior_transform,\n    log_likelihood=log_likelihood,\n    n_dim=n_dim,\n    vectorize=True,\n)\nsampler.run()\n\nsamples, weights, logl = sampler.posterior() # Weighted posterior samples\n\nlogz, logz_err = sampler.evidence() # Bayesian model evidence estimate and uncertainty\n```\n\n\n# Attribution \u0026 Citation\n\nPlease cite the following papers if you found this code useful in your research:\n\n```bash\n@article{karamanis2025persistent,\n  title={Persistent Sampling: Enhancing the Efficiency of Sequential Monte Carlo},\n  author={Karamanis, Minas and Seljak, Uro{\\v{s}}},\n  journal={Statistics and Computing},\n  volume={35},\n  number={5},\n  pages={1--22},\n  year={2025},\n  publisher={Springer}\n}\n```\n\n# Licence\n\nCopyright 2026-Present Minas Karamanis and contributors.\n\n``Tempest`` is free software made available under the MIT License. For details see the `LICENCE` file.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fminaskar%2Ftempest","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fminaskar%2Ftempest","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fminaskar%2Ftempest/lists"}