{"id":13697308,"url":"https://github.com/ericsuh/dirichlet","last_synced_at":"2026-01-10T08:47:25.019Z","repository":{"id":3831380,"uuid":"4912505","full_name":"ericsuh/dirichlet","owner":"ericsuh","description":"Dirichlet MLE python library","archived":false,"fork":false,"pushed_at":"2024-03-20T15:32:42.000Z","size":27,"stargazers_count":116,"open_issues_count":4,"forks_count":25,"subscribers_count":6,"default_branch":"master","last_synced_at":"2025-04-08T19:50:23.623Z","etag":null,"topics":["dirichlet","mle","python"],"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/ericsuh.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.txt","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":"2012-07-05T18:20:21.000Z","updated_at":"2025-02-26T15:49:12.000Z","dependencies_parsed_at":"2024-06-19T05:28:26.516Z","dependency_job_id":null,"html_url":"https://github.com/ericsuh/dirichlet","commit_stats":{"total_commits":30,"total_committers":4,"mean_commits":7.5,"dds":"0.19999999999999996","last_synced_commit":"8e832cc55ced9150e30ea3a7402f594896c5a527"},"previous_names":[],"tags_count":5,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ericsuh%2Fdirichlet","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ericsuh%2Fdirichlet/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ericsuh%2Fdirichlet/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ericsuh%2Fdirichlet/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ericsuh","download_url":"https://codeload.github.com/ericsuh/dirichlet/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":252242283,"owners_count":21717136,"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":["dirichlet","mle","python"],"created_at":"2024-08-02T18:00:55.555Z","updated_at":"2026-01-10T08:47:24.973Z","avatar_url":"https://github.com/ericsuh.png","language":"Python","funding_links":[],"categories":["Dirichlet hyperparameter optimization techniques"],"sub_categories":["Embedding based Topic Models"],"readme":"Dirichlet\n=========\n\nA Python package to estimate the Dirichlet distribution, calculate maximum\nlikelihood, and test for independence from a variable based on fitting nested\nDirichlet distribution hypotheses.\n\nMost of this package is a port of Thomas P. Minka's wonderful\n[Fastfit][fastfit] MATLAB code. Much thanks to him for that and his clear\npaper [\"Estimating a Dirichlet distribution\"][estimating].\n\n[estimating]: http://research.microsoft.com/en-us/um/people/minka/papers/dirichlet/\n[fastfit]: http://research.microsoft.com/en-us/um/people/minka/software/fastfit/\n\nDirichlet Test\n--------------\n\nThis likelihood ratio test for independence will determine whether two\nDirichlet-distributed data sets are likely to be from the same distribution\nor from two different ones, much like a chi-square or G-test for independence,\nbut with Dirichlet models.\n\nSimplex Plots\n-------------\n\nThe `dirichlet.simplex` module creates scatter, contour, and filled contour 2-simplex plots.\n\nCaveats\n-------\n\nNote that this package at the moment doesn't support sparse data vectors due to the\nnumerical fitting algorithm that uses the gamma function. Possibly some sort of\n[additive smoothing](https://en.wikipedia.org/wiki/Additive_smoothing) would\nmake this package work in your context, but that will depend on your application.\n\nInstallation\n------------\n\n    pip install git+https://github.com/ericsuh/dirichlet.git\n\nThis has only been tested with Python 3.6+. Other versions may work, but they\nhaven't been tested.\n\nDevelopment\n-----------\n\n*Note*: These instructions have only been tested on Ubuntu/Debian.\n\nDev dependencies are listed in `requirements-dev.txt`. You can install them\nwith:\n\n    pip install -r requirements-dev.txt\n\n### Code style\n\nPlease use [`black`](https://black.readthedocs.io/) to format your code when contributing\n\n### Testing\n\nThis project uses [`tox`](https://tox.readthedocs.io/) and\n[`pytest`](https://pytest.readthedocs.io/) for testing. To run tests,\ngenerally you can just run:\n\n    tox\n\nTo test a particular version of Python, you will need to have it\ninstalled and in your `$PATH` ahead of time.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fericsuh%2Fdirichlet","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fericsuh%2Fdirichlet","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fericsuh%2Fdirichlet/lists"}