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pypermod

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This python package provides various tools to predict energy expenditure and recovery dynamics of an athlete. The name pypermod stands for Python Performance Modeling.

More details on the purpose of this package can be found in our manuscript A hydraulic model outperforms work-balance models for predicting recovery kinetics from intermittent exercise. You can find the preprint on arXiv.

You may also want to check our detailed video presentation at STARS . Or the more recent presentation at the SFU Sports Analytics Seminar.

If you make use of this project, we would be grateful if you star the repository and/or cite our preprint.

@misc{weigend2021hydraulic,
      title={A hydraulic model outperforms work-balance models for predicting recovery kinetics from intermittent exercise}, 
      author={Fabian C. Weigend and David C. Clarke and Oliver Obst and Jason Siegler},
      year={2021},
      eprint={2108.04510},
      archivePrefix={arXiv},
      primaryClass={cs.OH}
}

Setup

If you aim to use the package for your own analysis you may want to install it via pip3 install pypermod without the need for a manual download.

If you aim to work on the source code you may clone the GitHub_repository. You can install the files from the repository by running pip3 install -e <path_to_project_root>.

Usage

Please see the scripts in the example_scripts folder of our GitHub_repository for example applications. Each subdirectory has its own README.md with instructions. Available examples are

Metadata

Release files for pypermod 1.3.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for pypermod 1.3.0
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Table of built distributions (wheels) for pypermod 1.3.0
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pypermod-1.3.0-py3-none-any.whl Python 3 none any Details

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Release files / pypermod-1.3.0.tar.gz

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