Metadata-Version: 2.1
Name: pyActigraphy
Version: 0.1
Summary: Analysis package for actigraphy data
Home-page: http://github.com/ghammad/pyActigraphy
Author: Grégory Hammad
Author-email: gregory.hammad@hotmail.fr
License: GNU GPL-3.0
Description: .. image:: https://img.shields.io/badge/License-GPL%20v3-blue.svg
          :target: https://www.gnu.org/licenses/gpl-3.0
        .. image:: https://gitlab.com/ghammad/pyActigraphy/badges/master/pipeline.svg
          :target: https://gitlab.com/ghammad/pyActigraphy/commits/master
        .. image:: https://gitlab.com/ghammad/pyActigraphy/badges/master/coverage.svg
          :target: https://gitlab.com/ghammad/pyActigraphy/commits/master
        .. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.2537921.svg
          :target: https://doi.org/10.5281/zenodo.2537921
        
        **pyActigraphy**
        ================
        Open-source python package for actigraphy data analysis.
        
        
        This package is meant to provide a comprehensive set of tools to:
        
        * read actigraphy raw data files with various formats
        * calculate typical wake/sleep cycle-related variables (ex: IS, IV, ...)
        * perform complex analyses (ex: FDA, SSA, HMM, ...)
        
        Requirements
        ============
        * python 3.X
        * joblib
        * pandas
        * numba
        * numpy
        * pyexcel
        * pyexcel-ods3
        * scipy
        * statsmodels
        
        Installation
        ============
        In a (bash) shell, simply type:
        
        * For users:
        
        .. code-block:: shell
        
          pip install pyActigraphy
        
        To update the package:
        
        .. code-block:: shell
        
          pip install -U pyActigraphy
        
        It is strongly recommended to use the latest version of the pyActigraphy package.
        
        
        * For developers:
        
        .. code-block:: shell
        
          git clone git@github.com:ghammad/pyActigraphy.git
          cd pyActigraphy/
          git checkout develop
          pip install -e .
        
        Quick start
        ===========
        
        The following example illustrates how to calculate the interdaily stability
        with the pyActigraphy package:
        
        .. code-block:: python
        
          >>> import pyActigraphy
          >>> rawAWD = pyActigraphy.io.read_raw_awd(fpath + 'SUBJECT_01.AWD')
          >>> rawAWD.IS()
          0.6900175913031027
          >>> rawAWD.IS(freq='30min', binarize=True, threshold=4)
          0.6245582891144925
          >>> rawAWD.IS(freq='1H', binarize=False)
          0.5257020914453097
        
        
        Contributing
        ============
        
        There are plenty of ways to contribute to this package, including (but not limiting to):
        
        * report bugs (and, ideally, how to reproduce the bug)
        * suggest improvements
        * improve the documentation
        * hug or high-five the authors when you meet them!
        
        Authors
        =======
        
        * **Grégory Hammad** `@ghammad <https://github.com/ghammad>`_ - *Initial and main developer*
        * **Mathilde Reyt** `@ReytMathilde <https://github.com/ReytMathilde>`_
        
        See also the list of `contributors <https://github.com/ghammad/pyActigraphy/contributors>`_ who participated in this project.
        
        License
        =======
        
        This project is licensed under the GNU GPL-3.0 License - see the `LICENSE <LICENSE>`_ file for details
        
        Acknowledgments
        ===============
        
        * **Aubin Ardois** `@aardoi <https://github.com/aardoi>`_ developed the first version of the MTN class during his internship at the CRC, in May-August 2018.
        * The CRC colleagues for their support, ideas, etc.
        
Keywords: actigraphy actimetry analysis python open-source
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Programming Language :: Python :: 3
Description-Content-Type: text/x-rst
