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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.
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"description": ".. image:: https://img.shields.io/badge/License-GPL%20v3-blue.svg\n :target: https://www.gnu.org/licenses/gpl-3.0\n.. image:: https://gitlab.com/ghammad/pyActigraphy/badges/master/pipeline.svg?key_text=CI+tests\n :target: https://gitlab.com/ghammad/pyActigraphy/commits/master\n.. .. image:: https://gitlab.com/ghammad/pyActigraphy/badges/master/coverage.svg\n.. :target: https://gitlab.com/ghammad/pyActigraphy/commits/master\n.. image:: https://img.shields.io/pypi/v/pyActigraphy.svg\n :target: https://pypi.org/project/pyActigraphy\n.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.2537920.svg\n :target: https://doi.org/10.5281/zenodo.2537920\n.. image:: https://bestpractices.coreinfrastructure.org/projects/6933/badge\n :target: https://bestpractices.coreinfrastructure.org/projects/6933\n.. image:: https://img.shields.io/badge/Contributor%20Covenant-2.1-4baaaa.svg\n :target: CODE_OF_CONDUCT.md\n\n\n**pyActigraphy**\n================\nOpen-source python package for actigraphy and light exposure data visualization and analysis.\n\n\nThis package is meant to provide a comprehensive set of tools to:\n\n* read native actigraphy data files with various formats:\n\n * Actigraph: wGT3X-BT\n * CamNtech: Actiwatch 4, 7, L(-Plus) and MotionWatch 8\n * Condor Instrument: ActTrust 2\n * Daqtix: Daqtometer\n * Respironics: Actiwatch 2 and Actiwatch Spectrum (plus)\n * Tempatilumi (CE Brasil)\n\n..\n\n* **NEW** read actigraphy data format from the `MESA dataset <https://sleepdata.org/datasets/mesa>`_, hosted by the `National Sleep Research Resource <https://sleepdata.org>`_.\n\n* **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:\n\n * Axivity: AX3, device used by UK Biobank,\n * Activinsights: GENEActiv, used by the Whitehall II study.\n\n..\n\n* **NEW** read light exposure data recorded by the aforementioned devices (when available)\n\n* clean the raw data and mask spurious periods of inactivity\n\n* produce activity profile plots\n\n* visualize sleep agendas and compute summary statistics\n\n* calculate typical wake/sleep cycle-related variables:\n\n * Non-parametric rest-activity variables: IS(m), IV(m), RA\n * Activity or Rest fragmentation: kRA, kAR\n * Sleep regularity index (SRI)\n\n..\n\n* **NEW** compute light exposure metrics (TAT, :math:`MLit^{500}`, summary statistics, ...)\n\n* automatically detect rest periods using various algorithms (Cole-Kripke, Sadeh, ..., Crespo, Roenneberg)\n\n* perform complex analyses:\n\n * Cosinor analysis\n * Detrended Fluctuation Analysis (DFA)\n * Functional Linear Modelling (FLM)\n * Locomotor Inactivity During Sleep (LIDS)\n * Singular Spectrum Analysis (SSA)\n * and much more...\n\nCitation\n========\n\nWe 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:\n\n 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\n\npyLight\n=======\n\nIn the context of the Daylight Academy Project, `The role of daylight for humans <https://daylight.academy/projects/state-of-light-in-humans>`_ and\nthanks to the support of its members, Dr. Mirjam M\u00fcnch and Prof. `Manuel Spitschan <https://github.com/spitschan>`_,\na pyActigraphy module for analysing light exposure data has been developed, **pyLight**.\nThis 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.\n\nA manuscript describing the *pyLight* module is available as a `preprint <https://osf.io/msk9n/>`_.\n\nCode and documentation\n======================\n\nThe pyActigraphy package is open-source and its source code is accessible `online <https://github.com/ghammad/pyActigraphy>`_.\n\n\nAn online documentation of the package is also available `here <https://ghammad.github.io/pyActigraphy/index.html>`_.\nIt contains `notebooks <https://ghammad.github.io/pyActigraphy/tutorials.html>`_ illustrating various functionalities of the package. 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