{"id":43642624,"url":"https://github.com/choderalab/fortuna","last_synced_at":"2026-02-04T18:08:18.092Z","repository":{"id":46949043,"uuid":"189615689","full_name":"choderalab/fortuna","owner":"choderalab","description":"Adaptive sampling methods for optimising simulations","archived":false,"fork":false,"pushed_at":"2021-09-20T20:37:37.000Z","size":201,"stargazers_count":1,"open_issues_count":5,"forks_count":2,"subscribers_count":8,"default_branch":"master","last_synced_at":"2025-09-10T02:31:48.660Z","etag":null,"topics":["adaptive-sampling","bayesian-bandits"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","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/choderalab.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":".github/CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":"CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2019-05-31T15:17:24.000Z","updated_at":"2021-10-29T07:25:32.000Z","dependencies_parsed_at":"2022-09-05T05:21:12.393Z","dependency_job_id":null,"html_url":"https://github.com/choderalab/fortuna","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/choderalab/fortuna","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/choderalab%2Ffortuna","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/choderalab%2Ffortuna/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/choderalab%2Ffortuna/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/choderalab%2Ffortuna/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/choderalab","download_url":"https://codeload.github.com/choderalab/fortuna/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/choderalab%2Ffortuna/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29092855,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-04T03:31:03.593Z","status":"ssl_error","status_checked_at":"2026-02-04T03:29:50.742Z","response_time":62,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: 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":["adaptive-sampling","bayesian-bandits"],"created_at":"2026-02-04T18:08:17.221Z","updated_at":"2026-02-04T18:08:18.084Z","avatar_url":"https://github.com/choderalab.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"[![Travis Build Status](https://travis-ci.org/choderalab/fortuna.png)](https://travis-ci.org/choderalab/fortuna)\n[![codecov](https://codecov.io/gh/choderalab/fortuna/branch/master/graph/badge.svg)](https://codecov.io/gh/choderalab/fortuna/branch/master)\n[![Documentation Status](https://readthedocs.org/projects/fortuna-sampling/badge/?version=latest)](https://fortuna-sampling.readthedocs.io/en/latest/?badge=latest)\n\n\n# FORTUNA\n\nMethods for adaptive sampling.\n\n* Bayesian bandits\n* Optimal experimental design\n\n## License\nThis software is licensed under the [MIT license](https://opensource.org/licenses/MIT), a permissive open source license.\n\n## Notice\n\nPlease be aware that this code is made available in the spirit of open science, but is currently pre-alpha--that is,\n**it is not guaranteed to be completely tested or provide the correct results**, and the API can change at any time\nwithout warning. If you do use this code, do so at your own risk. We appreciate your input, including raising issues\nabout potential problems with the code, but may not be able to address your issue until other development activities\nhave concluded.\n\n## Authors\n\n* Hannah E. Bruce Macdonald\n* Dominic A. Rufa\n* John D. Chodera\n\n#### Acknowledgements\n \nProject based on the \n[Computational Molecular Science Python Cookiecutter](https://github.com/molssi/cookiecutter-cms) version 1.0.\n\nThis project is supported by [MolSSI](https://molssi.org).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchoderalab%2Ffortuna","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fchoderalab%2Ffortuna","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchoderalab%2Ffortuna/lists"}