Metadata-Version: 2.1
Name: pyActigraphy
Version: 1.2.1
Summary: Analysis package for actigraphy data
Home-page: https://github.com/ghammad/pyActigraphy
Author: Grégory Hammad
Author-email: gregory.hammad@hotmail.fr
License: GNU GPL-3.0
Keywords: actigraphy actimetry analysis python open-source
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
License-File: LICENSE.md

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**pyActigraphy**
================
Open-source python package for actigraphy and light exposure data visualization and analysis.


This package is meant to provide a comprehensive set of tools to:

* read native actigraphy data files with various formats:

  * Actigraph: wGT3X-BT
  * CamNtech: Actiwatch 4, 7, L(-Plus) and MotionWatch 8
  * Condor Instrument: ActTrust 2
  * Daqtix: Daqtometer
  * Respironics: Actiwatch 2 and Actiwatch Spectrum (plus)
  * Tempatilumi (CE Brasil)

..

* **NEW** read actigraphy data format from the `MESA dataset <https://sleepdata.org/datasets/mesa>`_, hosted by the `National Sleep Research Resource <https://sleepdata.org>`_.

* **NEW** read actigraphy data files produced by the `accelerometer <https://biobankaccanalysis.readthedocs.io/en/latest/index.html>`_ package that can be used to calibrate and convert raw accelerometer data recorded with:

  * Axivity: AX3, device used by UK Biobank,
  * Activinsights: GENEActiv, used by the Whitehall II study.

..

* **NEW** read light exposure data recorded by the aforementioned devices (when available)

* clean the raw data and mask spurious periods of inactivity

* produce activity profile plots

* visualize sleep agendas and compute summary statistics

* calculate typical wake/sleep cycle-related variables:

  * Non-parametric rest-activity variables: IS(m), IV(m), RA
  * Activity or Rest  fragmentation: kRA, kAR
  * Sleep regularity index (SRI)

..

* **NEW** compute light exposure metrics (TAT, :math:`MLit^{500}`, summary statistics, ...)

* automatically detect rest periods using various algorithms (Cole-Kripke, Sadeh, ..., Crespo, Roenneberg)

* perform complex analyses:

  * Cosinor analysis
  * Detrended Fluctuation Analysis (DFA)
  * Functional Linear Modelling (FLM)
  * Locomotor Inactivity During Sleep (LIDS)
  * Singular Spectrum Analysis (SSA)
  * and much more...

Citation
========

We are very pleased to announce that the `v1.0 <https://github.com/ghammad/pyActigraphy/releases/tag/v1.0>`_ version of the pyActigraphy package has been published. So, if you find this package useful in your research, please consider citing:

  Hammad G, Reyt M, Beliy N, Baillet M, Deantoni M, Lesoinne A, et al. (2021) pyActigraphy: Open-source python package for actigraphy data visualization and    analysis. PLoS Comput Biol 17(10): e1009514. https://doi.org/10.1371/journal.pcbi.1009514

pyLight
=======

In the context of the Daylight Academy Project, `The role of daylight for humans <https://daylight.academy/projects/state-of-light-in-humans>`_ and
thanks to the support of its members, Dr. Mirjam Münch and Prof. `Manuel Spitschan <https://github.com/spitschan>`_,
a pyActigraphy module for analysing light exposure data has been developed, **pyLight**.
This module is part of the Human Light Exposure Database and is included in pyActigraphy version `v1.1 <https://github.com/ghammad/pyActigraphy/releases/tag/v1.1>`_ and higher.

A manuscript describing the *pyLight* module is available as a `preprint <https://osf.io/msk9n/>`_.

Code and documentation
======================

The pyActigraphy package is open-source and its source code is accessible `online <https://github.com/ghammad/pyActigraphy>`_.


An online documentation of the package is also available `here <https://ghammad.github.io/pyActigraphy/index.html>`_.
It contains `notebooks <https://ghammad.github.io/pyActigraphy/tutorials.html>`_ illustrating various functionalities of the package. Specific tutorials for the processing and the analysis of light exposure data with pyLight are also available.

Installation
============

In a (bash) shell, simply type:

* For users:

.. code-block:: shell

  pip3 install pyActigraphy

To update the package:

.. code-block:: shell

  pip3 install -U pyActigraphy


* For developers:

.. code-block:: shell

  git clone git@github.com:ghammad/pyActigraphy.git
  cd pyActigraphy/
  git checkout develop
  pip3 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('/path/to/your/favourite/file.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

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.
