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}
}
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>.
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.
Many example scripts require our published data. You can download it from Data Storage and make sure to set the path in the pypermod.config to where the data was downloaded to.
Available examples are