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Analysis package for actigraphy data

Project description

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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 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:

>>> 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

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.

Project details


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This version
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0.1

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