{"id":13688778,"url":"https://github.com/GAA-UAM/scikit-fda","last_synced_at":"2025-05-01T20:30:47.505Z","repository":{"id":37210707,"uuid":"96133420","full_name":"GAA-UAM/scikit-fda","owner":"GAA-UAM","description":"Functional Data Analysis Python package","archived":false,"fork":false,"pushed_at":"2025-04-29T19:44:39.000Z","size":13119,"stargazers_count":323,"open_issues_count":76,"forks_count":62,"subscribers_count":7,"default_branch":"develop","last_synced_at":"2025-04-29T20:35:22.909Z","etag":null,"topics":["alignment","classification","clustering","curves","dimensionality-reduction","functional-data-analysis","functions","machine-learning","python","python3","registration","regression","scikits","smoothing","statistics","visualization"],"latest_commit_sha":null,"homepage":"https://fda.readthedocs.io","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"bsd-3-clause","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/GAA-UAM.png","metadata":{"files":{"readme":"README.rst","changelog":null,"contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE.txt","code_of_conduct":"CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":"CITATION.cff","codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2017-07-03T17:06:56.000Z","updated_at":"2025-04-27T14:23:50.000Z","dependencies_parsed_at":"2024-04-17T18:27:19.443Z","dependency_job_id":"2c9907a8-c9a3-4804-9c1a-fc6b0d431dee","html_url":"https://github.com/GAA-UAM/scikit-fda","commit_stats":{"total_commits":2450,"total_committers":32,"mean_commits":76.5625,"dds":0.6453061224489796,"last_synced_commit":"7ceb9874e88fad8a08e9026896d10b78295ec8df"},"previous_names":[],"tags_count":20,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/GAA-UAM%2Fscikit-fda","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/GAA-UAM%2Fscikit-fda/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/GAA-UAM%2Fscikit-fda/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/GAA-UAM%2Fscikit-fda/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/GAA-UAM","download_url":"https://codeload.github.com/GAA-UAM/scikit-fda/tar.gz/refs/heads/develop","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":251940477,"owners_count":21668543,"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":["alignment","classification","clustering","curves","dimensionality-reduction","functional-data-analysis","functions","machine-learning","python","python3","registration","regression","scikits","smoothing","statistics","visualization"],"created_at":"2024-08-02T15:01:22.524Z","updated_at":"2025-05-01T20:30:47.496Z","avatar_url":"https://github.com/GAA-UAM.png","language":"Python","funding_links":[],"categories":["Python"],"sub_categories":[],"readme":".. image:: https://raw.githubusercontent.com/GAA-UAM/scikit-fda/develop/docs/logos/title_logo/title_logo.png\n\t:alt: scikit-fda: Functional Data Analysis in Python\n\nscikit-fda: Functional Data Analysis in Python\n===================================================\n\n|build-status| |docs| |Codecov| |repostatus| |versions| |PyPIBadge| |conda| |license| |doi|\n\nFunctional Data Analysis, or FDA, is the field of Statistics that analyses\ndata that depend on a continuous parameter.\n\nThis package offers classes, methods and functions to give support to FDA\nin Python. Includes a wide range of utils to work with functional data, and its\nrepresentation, exploratory analysis, or preprocessing, among other tasks\nsuch as inference, classification, regression or clustering of functional data.\nSee documentation for further information on the features included in the\npackage.\n\nDocumentation\n=============\n\nThe documentation is available at\n`fda.readthedocs.io/en/stable/ \u003chttps://fda.readthedocs.io/en/stable/\u003e`_, which\nincludes detailed information of the different modules, classes and methods of\nthe package, along with several examples_ showing different functionalities.\n\nThe documentation of the latest version, corresponding with the develop\nversion of the package, can be found at\n`fda.readthedocs.io/en/latest/ \u003chttps://fda.readthedocs.io/en/latest/\u003e`_.\n\nInstallation\n============\nCurrently, *scikit-fda* is available in Python versions above 3.8, regardless of the\nplatform.\nThe stable version can be installed via PyPI_:\n\n.. code::\n\n    pip install scikit-fda\n\nIt is also available from conda-forge_:\n.. code::\n\n    conda install -c conda-forge scikit-fda\n\nInstallation from source\n------------------------\n\nIt is possible to install the latest version of the package, available in the\ndevelop branch,  by cloning this repository and doing a manual installation.\n\n.. code:: bash\n\n    git clone https://github.com/GAA-UAM/scikit-fda.git\n    pip install ./scikit-fda\n\nMake sure that your default Python version is currently supported, or change\nthe python and pip commands by specifying a version, such as ``python3.8``:\n\n.. code:: bash\n\n    git clone https://github.com/GAA-UAM/scikit-fda.git\n    python3.8 -m pip install ./scikit-fda\n\nRequirements\n------------\n*scikit-fda* depends on the following packages:\n\n* `fdasrsf \u003chttps://github.com/jdtuck/fdasrsf_python\u003e`_ - SRSF framework\n* `findiff \u003chttps://github.com/maroba/findiff\u003e`_ - Finite differences\n* `matplotlib \u003chttps://github.com/matplotlib/matplotlib\u003e`_ - Plotting with Python\n* `multimethod \u003chttps://github.com/coady/multimethod\u003e`_ - Multiple dispatch\n* `numpy \u003chttps://github.com/numpy/numpy\u003e`_ - The fundamental package for scientific computing with Python\n* `pandas \u003chttps://github.com/pandas-dev/pandas\u003e`_ - Powerful Python data analysis toolkit\n* `rdata \u003chttps://github.com/vnmabus/rdata\u003e`_ - Reader of R datasets in .rda format in Python\n* `scikit-datasets \u003chttps://github.com/daviddiazvico/scikit-datasets\u003e`_ - Scikit-learn compatible datasets\n* `scikit-learn \u003chttps://github.com/scikit-learn/scikit-learn\u003e`_ - Machine learning in Python\n* `scipy \u003chttps://github.com/scipy/scipy\u003e`_ - Scientific computation in Python\n* `setuptools \u003chttps://github.com/pypa/setuptools\u003e`_ - Python Packaging\n\nThe dependencies are automatically installed.\n\nCiting scikit-fda\n=================\n\nPlease, if you find this software useful in your work, reference it citing the following paper:\n\n.. code-block::\n\n  @article{ramos-carreno++_2024_scikit-fda,\n    author = {Ramos-Carreño, Carlos and Torrecilla, José L. and Carbajo Berrocal, Miguel and Marcos Manchón, Pablo and Suárez, Alberto},\n    doi = {10.18637/jss.v109.i02},\n    journal = {Journal of Statistical Software},\n    month = may,\n    number = {2},\n    pages = {1--37},\n    title = {{scikit-fda: A Python Package for Functional Data Analysis}},\n    url = {https://www.jstatsoft.org/article/view/v109i02},\n    volume = {109},\n    year = {2024}\n  }\n\n\nYou can additionally cite the software repository itself using:\n\n.. code-block::\n\n  @misc{ramos-carreno++_2024_scikit-fda-repo,\n    author = {The scikit-fda developers},\n    doi = {10.5281/zenodo.3468127},\n    month = feb,\n    title = {scikit-fda: Functional Data Analysis in Python},\n    url = {https://github.com/GAA-UAM/scikit-fda},\n    year = {2024}\n  }\n\nIf you want to reference a particular version for reproducibility, check the version-specific DOIs available in Zenodo.\n\nContributions\n=============\nAll contributions are welcome. You can help this project grow in multiple ways,\nfrom creating an issue, reporting an improvement or a bug, to doing a\nrepository fork and creating a pull request to the development branch.\n\nThe people involved at some point in the development of the package can be\nfound in the `contributors\nfile \u003chttps://github.com/GAA-UAM/scikit-fda/blob/develop/THANKS.txt\u003e`_.\n\n.. Citation\n   ========\n   If you find this project useful, please cite:\n\n   .. todo:: Include citation to scikit-fda paper.\n\nLicense\n=======\n\nThe package is licensed under the BSD 3-Clause License. A copy of the\nlicense_ can be found along with the code.\n\n.. _examples: https://fda.readthedocs.io/en/latest/auto_examples/index.html\n.. _PyPI: https://pypi.org/project/scikit-fda/\n.. _conda-forge: https://anaconda.org/conda-forge/scikit-fda/\n\n.. |build-status| image:: https://github.com/GAA-UAM/scikit-fda/actions/workflows/tests.yml/badge.svg?event=push\n    :alt: Build status\n    :target: https://github.com/GAA-UAM/scikit-fda/actions/workflows/tests.yml\n\n.. |docs| image:: https://readthedocs.org/projects/fda/badge/?version=latest\n    :alt: Documentation Status\n    :target: http://fda.readthedocs.io/en/latest/?badge=latest\n\n.. |Codecov| image:: https://codecov.io/gh/GAA-UAM/scikit-fda/branch/develop/graph/badge.svg\n    :alt: Code coverage through Codecov\n    :target: https://app.codecov.io/gh/GAA-UAM/scikit-fda\n\n.. |repostatus| image:: https://www.repostatus.org/badges/latest/active.svg\n   :alt: Project Status: Active - The project has reached a stable, usable state and is being actively developed.\n   :target: https://www.repostatus.org/#active\n   \n.. |versions| image:: https://img.shields.io/pypi/pyversions/scikit-fda\n   :alt: PyPI - Python versions supported\n\n.. |PyPIBadge| image:: https://badge.fury.io/py/scikit-fda.svg\n   :alt: Available in Pypi\n   :target: https://pypi.org/project/scikit-fda\n\n.. |conda| image:: https://img.shields.io/conda/vn/conda-forge/scikit-fda\n    :alt: Available in Conda\n    :target: https://anaconda.org/conda-forge/scikit-fda\n\n.. |license| image:: https://img.shields.io/badge/License-BSD%203--Clause-blue.svg\n    :alt: BSD 3-Clause license\n    :target: https://github.com/GAA-UAM/scikit-fda/blob/develop/LICENSE.txt\n\n.. |doi| image:: https://zenodo.org/badge/DOI/10.5281/zenodo.3468127.svg\n    :alt: Available in Zenodo\n    :target: https://doi.org/10.5281/zenodo.3468127\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FGAA-UAM%2Fscikit-fda","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FGAA-UAM%2Fscikit-fda","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FGAA-UAM%2Fscikit-fda/lists"}