{"id":23280267,"url":"https://github.com/moldyn/normi","last_synced_at":"2025-08-21T13:31:15.555Z","repository":{"id":194512364,"uuid":"656622595","full_name":"moldyn/NorMI","owner":"moldyn","description":"Generalized Kraskov Estimator for Normalized Mutual Information","archived":false,"fork":false,"pushed_at":"2024-11-21T17:00:49.000Z","size":2733,"stargazers_count":10,"open_issues_count":3,"forks_count":1,"subscribers_count":0,"default_branch":"main","last_synced_at":"2024-11-21T17:40:27.489Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"https://moldyn.github.io/NorMI","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/moldyn.png","metadata":{"files":{"readme":"README.md","changelog":"CHANGELOG.md","contributing":"docs/contributing.md","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":"2023-06-21T10:01:27.000Z","updated_at":"2024-11-21T17:00:14.000Z","dependencies_parsed_at":"2024-11-21T17:40:44.961Z","dependency_job_id":null,"html_url":"https://github.com/moldyn/NorMI","commit_stats":null,"previous_names":["moldyn/normi"],"tags_count":3,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/moldyn%2FNorMI","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/moldyn%2FNorMI/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/moldyn%2FNorMI/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/moldyn%2FNorMI/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/moldyn","download_url":"https://codeload.github.com/moldyn/NorMI/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":230515629,"owners_count":18238284,"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":[],"created_at":"2024-12-19T23:31:23.066Z","updated_at":"2024-12-19T23:31:23.712Z","avatar_url":"https://github.com/moldyn.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cdiv align=\"center\"\u003e\n  \u003cimg class=\"darkmode\" style=\"width: 500px;\" src=\"https://github.com/moldyn/normi/blob/main/docs/hero_dark.svg?raw=true#gh-dark-mode-only\" /\u003e\n  \u003cimg class=\"lightmode\" style=\"width: 500px;\" src=\"https://github.com/moldyn/normi/blob/main/docs/hero.svg?raw=true#gh-light-mode-only\" /\u003e\n\n  \u003cp\u003e\n    \u003ca href=\"https://github.com/wemake-services/wemake-python-styleguide\" alt=\"wemake-python-styleguide\"\u003e\n        \u003cimg src=\"https://img.shields.io/badge/style-wemake-000000.svg\" /\u003e\u003c/a\u003e\n    \u003ca href=\"https://beartype.rtfd.io\" alt=\"bear-ified\"\u003e\n        \u003cimg src=\"https://raw.githubusercontent.com/beartype/beartype-assets/main/badge/bear-ified.svg\" /\u003e\u003c/a\u003e\n    \u003ca href=\"https://pypi.org/project/normi\" alt=\"PyPI\"\u003e\n        \u003cimg src=\"https://img.shields.io/pypi/v/normi\" /\u003e\u003c/a\u003e\n    \u003ca href=\"https://anaconda.org/conda-forge/normi\" alt=\"conda version\"\u003e\n\t\u003cimg src=\"https://img.shields.io/conda/vn/conda-forge/normi\" /\u003e\u003c/a\u003e\n    \u003ca href=\"https://pepy.tech/project/normi\" alt=\"Downloads\"\u003e\n        \u003cimg src=\"https://static.pepy.tech/badge/normi\" /\u003e\u003c/a\u003e\n    \u003ca href=\"https://github.com/moldyn/normi/actions/workflows/pytest.yml\" alt=\"GitHub Workflow Status\"\u003e\n        \u003cimg src=\"https://img.shields.io/github/actions/workflow/status/moldyn/normi/pytest.yml?branch=main\"\u003e\u003c/a\u003e\n    \u003ca href=\"https://codecov.io/gh/moldyn/normi\" alt=\"Code coverage\"\u003e\n        \u003cimg src=\"https://codecov.io/gh/moldyn/normi/branch/main/graph/badge.svg?token=KNWDAUXIGI\" /\u003e\u003c/a\u003e\n    \u003ca href=\"https://github.com/moldyn/normi/actions/workflows/codeql.yml\" alt=\"CodeQL\"\u003e\n        \u003cimg src=\"https://github.com/moldyn/normi/actions/workflows/codeql.yml/badge.svg?branch=main\" /\u003e\u003c/a\u003e\n    \u003ca href=\"https://img.shields.io/pypi/pyversions/normi\" alt=\"PyPI - Python Version\"\u003e\n        \u003cimg src=\"https://img.shields.io/pypi/pyversions/normi\" /\u003e\u003c/a\u003e\n    \u003ca href=\"https://moldyn.github.io/normi\" alt=\"Docs\"\u003e\n        \u003cimg src=\"https://img.shields.io/badge/MkDocs-Documentation-brightgreen\" /\u003e\u003c/a\u003e\n    \u003ca href=\"https://doi.org/10.1063/5.0217960\" alt=\"doi\"\u003e\n        \u003cimg src=\"https://img.shields.io/badge/doi-10.1063%2F5.0217960-blue\" /\u003e\u003c/a\u003e\n    \u003ca href=\"https://arxiv.org/abs/2405.04980\" alt=\"arXiv\"\u003e\n        \u003cimg src=\"https://img.shields.io/badge/arXiv-2405.04980-red\" /\u003e\u003c/a\u003e\n    \u003ca href=\"https://github.com/moldyn/normi/blob/main/LICENSE\" alt=\"License\"\u003e\n        \u003cimg src=\"https://img.shields.io/github/license/moldyn/normi\" /\u003e\u003c/a\u003e\n  \u003c/p\u003e\n\n  \u003cp\u003e\n    \u003ca href=\"https://moldyn.github.io/NorMI\"\u003eDocs\u003c/a\u003e •\n    \u003ca href=\"#features\"\u003eFeatures\u003c/a\u003e •\n    \u003ca href=\"#installation\"\u003eInstallation\u003c/a\u003e •\n    \u003ca href=\"#usage\"\u003eUsage\u003c/a\u003e •\n    \u003ca href=\"https://moldyn.github.io/NorMI/faq\"\u003eFAQ\u003c/a\u003e\n  \u003c/p\u003e\n\u003c/div\u003e\n\n# NorMI: Nonparametric Normalized Mutual Information Estimator Based on *k*-NN Statistics\nThis software provides an extension to the Kraskov-Estimator to allow normalizing the mutual information.\n\nThe method was published in:  \n\u003e **Accurate estimation of the normalized mutual information of multidimensional data**  \n\u003e D. Nagel, G. Diez, and G. Stock,  \n\u003e *J. Chem. Phys.* **2024** 161, 054108  \n\u003e doi: [10.1063/5.0217960](https://doi.org/10.1063/5.0217960)\n\nIf you use this software package, please cite the above mentioned paper.\n\n## Features\n- Intuitive usage via [module](#module---inside-a-python-script) and via [CI](#ci---usage-directly-from-the-command-line)\n- Sklearn-style API for fast integration into your Python workflow\n- No magic, only a  single parameter which can be optimized via cross-validation\n- Extensive [documentation](https://moldyn.github.io/NorMI) and detailed discussion in publication\n\n## Installation\nThe package is called `normi` and is available via [PyPI](https://pypi.org/project/normi) or [conda](https://anaconda.org/conda-forge/normi). To install it, simply call:\n```bash\npython3 -m pip install --upgrade normi\n```\nor\n```\nconda install -c conda-forge normi\n```\nor for the latest dev version\n```bash\n# via ssh key\npython3 -m pip install git+ssh://git@github.com/moldyn/NorMI.git\n\n# or via password-based login\npython3 -m pip install git+https://github.com/moldyn/NorMI.git\n```\n\n### Shell Completion\nUsing the `bash`, `zsh` or `fish` shell click provides an easy way to provide shell completion, checkout the [docs](https://click.palletsprojects.com/en/8.0.x/shell-completion).\nIn the case of bash you need to add following line to your `~/.bashrc`\n```bash\neval \"$(_NORMI_COMPLETE=bash_source normi)\"\n```\n\n## Usage\nIn general one can call the module directly by its entry point `$ normi` or by calling the module `$ python -m normi`. The latter method is preferred to ensure using the desired python environment. For enabling the shell completion, the entry point needs to be used.\n\n### CI - Usage Directly from the Command Line\nThe module brings a rich CI using [click](https://click.palletsprojects.com).\nFor a complete list of all options please see the\n[docs](https://moldyn.github.io/NorMI/reference/cli/).\n```bash\npython -m normi /\n  --input input_file  / # ascii file of shape (n_samples, n_features)\n  --output output_file  / # creates ascii file of shape (n_features, n_features)\n  --n-dims / # this allows to treat every n_dims columns as a high dimensional feature\n  --verbose\n\n```\n\n### Module - Inside a Python Script\n```python\nfrom normi import NormalizedMI\n\n# Load file\n# X is np.ndarray of shape (n_samples, n_features)\n\nnmi = NormalizedMI()\nnmi_matrix = nmi.fit_transform(X)\n...\n```\n\n## Credits\n\n- Logo generated with DALL·E 3 by @gegabo\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmoldyn%2Fnormi","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmoldyn%2Fnormi","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmoldyn%2Fnormi/lists"}