{"id":20751233,"url":"https://github.com/cbg-ethz/jnotype","last_synced_at":"2025-04-28T13:09:34.824Z","repository":{"id":145136484,"uuid":"604139151","full_name":"cbg-ethz/Jnotype","owner":"cbg-ethz","description":"Probabilistic modeling of high-dimensional binary data in JAX","archived":false,"fork":false,"pushed_at":"2025-04-25T08:47:53.000Z","size":283,"stargazers_count":3,"open_issues_count":8,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-28T13:09:24.725Z","etag":null,"topics":["bayesian-statistics","cancer-genomics","clustering","ideal-point-estimation","jax","probabilistic-machine-learning","unsupervised-learning"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/cbg-ethz.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,"zenodo":null}},"created_at":"2023-02-20T12:19:40.000Z","updated_at":"2025-04-25T08:47:56.000Z","dependencies_parsed_at":"2023-06-09T10:15:25.806Z","dependency_job_id":"9fa24efe-ca5b-40e4-97be-0ef4a14f858c","html_url":"https://github.com/cbg-ethz/Jnotype","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cbg-ethz%2FJnotype","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cbg-ethz%2FJnotype/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cbg-ethz%2FJnotype/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cbg-ethz%2FJnotype/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/cbg-ethz","download_url":"https://codeload.github.com/cbg-ethz/Jnotype/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":251319606,"owners_count":21570427,"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-statistics","cancer-genomics","clustering","ideal-point-estimation","jax","probabilistic-machine-learning","unsupervised-learning"],"created_at":"2024-11-17T08:32:00.766Z","updated_at":"2025-04-28T13:09:34.709Z","avatar_url":"https://github.com/cbg-ethz.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"[![Project Status: WIP – Initial development is in progress, but there has not yet been a stable, usable release suitable for the public.](https://www.repostatus.org/badges/latest/wip.svg)](https://www.repostatus.org/#wip)\n[![build](https://github.com/cbg-ethz/Jnotype/actions/workflows/test.yml/badge.svg)](https://github.com/cbg-ethz/Jnotype/actions/workflows/test.yml)\n[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/charliermarsh/ruff/main/assets/badge/v2.json)](https://github.com/charliermarsh/ruff)\n[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)\n[![PyPI Latest Release](https://img.shields.io/pypi/v/jnotype.svg)](https://pypi.org/project/jnotype/)\n\n# Jnotype\n\n[JAX](https://github.com/google/jax)-powered Python package for exploratory analysis of binary data.\nThis includes genotype data, binary images, and data sets used in ecology.\n\n**Note:** this package is in early development stage.\n\n  - **Source code:** [https://github.com/cbg-ethz/Jnotype](https://github.com/cbg-ethz/Jnotype)\n  - **Bug reports:** [https://github.com/cbg-ethz/Jnotype/issues](https://github.com/cbg-ethz/Jnotype/issues)\n  - **PyPI package**: [https://pypi.org/project/jnotype/](https://pypi.org/project/jnotype/)\n\n## Installation\n\n**Note:** The package has not reached a stable API yet. Frequent changes may appear.\n\nWe recommend setting up a new [virtual environment](https://docs.python.org/3/library/venv.html).\nYou can install the released version of the package from PyPI:\n\n```bash\n$ python -m pip install jnotype\n```\n\nor install the development version from GitHub:\n\n```bash\n$ python -m pip install 'jnotype @ git+https://github.com/cbg-ethz/jnotype'\n```\n\n### Using GPU\n\nInstructions above install the CPU version of JAX.\nTo use GPU, you may need to follow the [official JAX installation tutorial](https://github.com/google/jax#pip-installation-gpu-cuda-installed-via-pip-easier).\n\n## Getting started\n\nDirectory `examples/` contains [Quarto](https://quarto.org/) notebooks, which demonstrate basic functionalities of the package.\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcbg-ethz%2Fjnotype","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcbg-ethz%2Fjnotype","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcbg-ethz%2Fjnotype/lists"}