Metadata-Version: 2.1
Name: scikit-digital-health
Version: 0.13.1
Summary: Python general purpose human motion inertial data processing package.
Home-page: https://github.com/PfizerRD/scikit-digital-health
Author-Email: Lukas Adamowicz <lukas.adamowicz@pfizer.com>
License: MIT License
        
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Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Fortran
Classifier: Programming Language :: C
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development
Classifier: Topic :: Scientific/Engineering
Classifier: Operating System :: MacOS
Classifier: Operating System :: POSIX :: Linux
Project-URL: Homepage, https://github.com/PfizerRD/scikit-digital-health
Project-URL: Documentation, https://scikit-digital-health.readthedocs.io/en/latest/
Requires-Python: >=3.6
Requires-Dist: numpy>=1.17.2
Requires-Dist: scipy>=1.3.1
Requires-Dist: pandas>=1.0.0
Requires-Dist: lightgbm>=2.3.0
Requires-Dist: pywavelets
Requires-Dist: scikit-learn
Requires-Dist: h5py
Requires-Dist: matplotlib
Requires-Dist: packaging
Requires-Dist: pyyaml
Requires-Dist: importlib_resources; python_version < "3.7"
Requires-Dist: importlib_metadata; python_version < "3.8"
Requires-Dist: pytest; extra == "test"
Requires-Dist: coverage; extra == "test"
Requires-Dist: psutil; extra == "test"
Requires-Dist: tables; extra == "test"
Provides-Extra: test
Description-Content-Type: text/x-rst

.. image:: https://github.com/PfizerRD/scikit-digital-health/workflows/skdh/badge.svg
    :target: https://github.com/PfizerRD/scikit-digital-health/workflows/skdh/badge.svg

Scikit Digital Health (SKDH) is a Python package with methods for ingesting and analyzing wearable inertial sensor data.

- Documentation: https://scikit-digital-health.readthedocs.io/en/latest/
- Bug reports: https://github.com/PfizerRD/scikit-digital-health/issues
- Contributing: https://scikit-digital-health.readthedocs.io/en/latest/src/dev/contributing.html

SKDH provides the following:

- Methods for ingesting data from binary file formats (ie Axivity, GeneActiv)
- Preprocessing of accelerometer data
- Common time-series signal features
- Common time-series/inertial data analysis functions
- Inertial data analysis algorithms (ie gait, sit-to-stand, sleep, activity)

Availability
############

SKDH is available on both `conda-forge` and `PyPI`.

`conda install scikit-digital-health -c conda-forge`

or 

`pip install scikit-digital-health`

.. warning::
    Windows pre-built wheels are provided as-is, with limited/no testing on changes made to compile extensions for Windows.

.. note::
    Windows users may need to install an additional requirement: Microsoft Visual C++ redistributable >14.0.
    The 2015 version can be found here: https://www.microsoft.com/en-us/download/details.aspx?id=53587

Build Requirements
##################

As of 0.9.15, Scikit Digital Health is built using Meson.

Citation
########

If you use SKDH in your research, please include the following citation:

L. Adamowicz, Y. Christakis, M. D. Czech, and T. Adamusiak, “SciKit Digital Health: Python Package for Streamlined Wearable Inertial Sensor Data Processing,” JMIR mHealth and uHealth, vol. 10, no. 4, p. e36762, Apr. 2022, doi: 10.2196/36762.

