| Name | scikit-fda JSON |
| Version |
0.9.1
JSON |
| download |
| home_page | |
| Summary | Functional Data Analysis Python package. |
| upload_time | 2024-02-26 11:54:59 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | >=3.9 |
| license | BSD 3-Clause License Copyright (c) 2019, Grupo de Aprendizaje Automático - Universidad Autónoma de Madrid All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. |
| keywords |
functional data
statistics
machine learning
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
.. 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/ <https://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/ <https://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 <https://github.com/jdtuck/fdasrsf_python>`_ - SRSF framework
* `findiff <https://github.com/maroba/findiff>`_ - Finite differences
* `matplotlib <https://github.com/matplotlib/matplotlib>`_ - Plotting with Python
* `multimethod <https://github.com/coady/multimethod>`_ - Multiple dispatch
* `numpy <https://github.com/numpy/numpy>`_ - The fundamental package for scientific computing with Python
* `pandas <https://github.com/pandas-dev/pandas>`_ - Powerful Python data analysis toolkit
* `rdata <https://github.com/vnmabus/rdata>`_ - Reader of R datasets in .rda format in Python
* `scikit-datasets <https://github.com/daviddiazvico/scikit-datasets>`_ - Scikit-learn compatible datasets
* `scikit-learn <https://github.com/scikit-learn/scikit-learn>`_ - Machine learning in Python
* `scipy <https://github.com/scipy/scipy>`_ - Scientific computation in Python
* `setuptools <https://github.com/pypa/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 <https://github.com/GAA-UAM/scikit-fda/blob/develop/THANKS.txt>`_.
.. 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
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