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:

pip install pyActigraphy

To update the package:

pip install -U pyActigraphy

It is strongly recommended to use the latest version of the pyActigraphy package.

• For developers:

git clone [email protected]: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:

>>> 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 - Initial and main developer
• Mathilde Reyt @ReytMathilde

See also the list of contributors who participated in this project.

License

This project is licensed under the GNU GPL-3.0 License - see the LICENSE file for details

Acknowledgments

• Aubin Ardois @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.