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https://github.com/GAA-UAM/scikit-fda

Functional Data Analysis Python package
https://github.com/GAA-UAM/scikit-fda

alignment classification clustering curves dimensionality-reduction functional-data-analysis functions machine-learning python python3 registration regression scikits smoothing statistics visualization

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Functional Data Analysis Python package

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README 

        
.. image:: https://raw.githubusercontent.com/GAA-UAM/scikit-fda/develop/docs/logos/title_logo/title_logo.png

	:alt: scikit-fda: Functional Data Analysis in Python



scikit-fda: Functional Data Analysis in Python

===================================================



|python|_ |build-status| |docs| |Codecov| |repostatus| |versions| |PyPIBadge| |conda| |license| |doi|



Functional Data Analysis, or FDA, is the field of Statistics that analyses

data that depend on a continuous parameter.



This package offers classes, methods and functions to give support to FDA

in Python. Includes a wide range of utils to work with functional data, and its

representation, exploratory analysis, or preprocessing, among other tasks

such as inference, classification, regression or clustering of functional data.

See documentation for further information on the features included in the

package.



Documentation

=============



The documentation is available at

`fda.readthedocs.io/en/stable/ `_, which

includes detailed information of the different modules, classes and methods of

the package, along with several examples showing different functionalities.



The documentation of the latest version, corresponding with the develop

version of the package, can be found at

`fda.readthedocs.io/en/latest/ `_.



Installation

============

Currently, *scikit-fda* is available in Python versions above 3.8, regardless of the

platform.

The stable version can be installed via PyPI_:



.. code::



    pip install scikit-fda



It is also available from conda-forge:

.. code::



    conda install -c conda-forge scikit-fda



Installation from source

------------------------



It is possible to install the latest version of the package, available in the

develop branch,  by cloning this repository and doing a manual installation.



.. code:: bash



    git clone https://github.com/GAA-UAM/scikit-fda.git

    pip install ./scikit-fda



Make sure that your default Python version is currently supported, or change

the python and pip commands by specifying a version, such as ``python3.8``:



.. code:: bash



    git clone https://github.com/GAA-UAM/scikit-fda.git

    python3.8 -m pip install ./scikit-fda



Requirements

------------

*scikit-fda* depends on the following packages:



* `fdasrsf `_ - SRSF framework

* `findiff `_ - Finite differences

* `matplotlib `_ - Plotting with Python

* `multimethod `_ - Multiple dispatch

* `numpy `_ - The fundamental package for scientific computing with Python

* `pandas `_ - Powerful Python data analysis toolkit

* `rdata `_ - Reader of R datasets in .rda format in Python

* `scikit-datasets `_ - Scikit-learn compatible datasets

* `scikit-learn `_ - Machine learning in Python

* `scipy `_ - Scientific computation in Python

* `setuptools `_ - Python Packaging



The dependencies are automatically installed.



Contributions

=============

All contributions are welcome. You can help this project grow in multiple ways,

from creating an issue, reporting an improvement or a bug, to doing a

repository fork and creating a pull request to the development branch.



The people involved at some point in the development of the package can be

found in the `contributors

file `_.



.. Citation

   ========

   If you find this project useful, please cite:



   .. todo:: Include citation to scikit-fda paper.



License

=======



The package is licensed under the BSD 3-Clause License. A copy of the

license_ can be found along with the code.



.. _examples: https://fda.readthedocs.io/en/latest/auto_examples/index.html

.. _PyPI: https://pypi.org/project/scikit-fda/

.. _conda-forge: https://anaconda.org/conda-forge/scikit-fda/



.. |python| image:: https://img.shields.io/pypi/pyversions/scikit-fda.svg

.. _python: https://badge.fury.io/py/scikit-fda



.. |build-status| image:: https://github.com/GAA-UAM/scikit-fda/actions/workflows/tests.yml/badge.svg?event=push

    :alt: build status

    :scale: 100%

    :target: https://github.com/GAA-UAM/scikit-fda/actions/workflows/tests.yml



.. |docs| image:: https://readthedocs.org/projects/fda/badge/?version=latest

    :alt: Documentation Status

    :scale: 100%

    :target: http://fda.readthedocs.io/en/latest/?badge=latest



.. |Codecov| image:: https://codecov.io/gh/GAA-UAM/scikit-fda/branch/develop/graph/badge.svg

.. _Codecov: https://app.codecov.io/gh/GAA-UAM/scikit-fda



.. |repostatus| image:: https://www.repostatus.org/badges/latest/active.svg

   :alt: Project Status: Active – The project has reached a stable, usable state and is being actively developed.

   :target: https://www.repostatus.org/#active

   

.. |versions| image:: https://img.shields.io/pypi/pyversions/scikit-fda

   :alt: PyPI - Python Version

   :scale: 100%



.. |PyPIBadge| image:: https://badge.fury.io/py/scikit-fda.svg

.. _PyPIBadge: https://badge.fury.io/py/scikit-fda



.. |conda| image:: https://img.shields.io/conda/vn/conda-forge/scikit-fda

    :alt: Available in Conda

    :scale: 100%

    :target: https://anaconda.org/conda-forge/scikit-fda



.. |license| image:: https://img.shields.io/badge/License-BSD%203--Clause-blue.svg

.. _license: https://github.com/GAA-UAM/scikit-fda/blob/master/LICENSE.txt



.. |doi| image:: https://zenodo.org/badge/DOI/10.5281/zenodo.3468127.svg

    :target: https://doi.org/10.5281/zenodo.3468127