From 4b06afc86cca969e48fccaf6ca9d3d4238efdd87 Mon Sep 17 00:00:00 2001 From: Romain Martinez Date: Tue, 2 Jun 2020 15:22:51 -0400 Subject: [PATCH] Acknowledgments --- docs/paper/paper.md | 16 +++++++++++++++- 1 file changed, 15 insertions(+), 1 deletion(-) diff --git a/docs/paper/paper.md b/docs/paper/paper.md index 7b31e39..ac64508 100644 --- a/docs/paper/paper.md +++ b/docs/paper/paper.md @@ -23,6 +23,9 @@ date: 2 June 2020 bibliography: paper.bib --- +- library format and cap +- hiphen + # Statement of Need Biomechanics is defined as the study of the structure and function of biological systems by means of the methods of mechanics [@Hatze1974-zc]. @@ -84,7 +87,7 @@ These methods can be categorized into filters (orange), signal processing (red), `pyomeca` has documented examples for different biomechanical tasks such as getting Euler angles from a rototranslation matrix, creating a system of axes from skin markers position or setting a rotation or a translation. Another typical task concerns electromyographic (EMG) data processing. -Using `pyomeca`, one can easily extract (\autoref{fig:ex-1-raw}), process (\autoref{fig:ex-2-processed}) and visualize (\autoref{fig:ex-3-aggr}, \autoref{fig:ex-4-box}, \autoref{fig:ex-5-corr}) such data. +Using `pyomeca`, one can easily extract (\autoref{fig:ex-1-raw}), process (\autoref{fig:ex-2-processed}) and visualize (\autoref{fig:ex-3-aggr}, \autoref{fig:ex-4-box} and \autoref{fig:ex-5-corr}) such data. ```python from pyomeca import Analogs @@ -135,4 +138,15 @@ emg_dataframe.corr().style.background_gradient().set_precision(2) ![By using a `pandas` dataframe, users also benefit from its broad range of IO tools and statistical methods, such as computing the correlation matrix between the different muscles.\label{fig:ex-5-corr}](fig/ex-5-corr.pdf) +# Research Projects Using `pyomeca` + +You can find an [up-to-date list of research projects using `pyomeca`](https://pyomeca.github.io/about/#papers-citing-pyomeca) on the static documentation. + +# Acknowledgements + +`pyomeca` is an open-source project created and supported by the Simulation and Movement Modeling (S2M) lab located in Montreal. +We thank the contributors that helped build `pyomeca`. +You can find an [up-to-date list of contributors](https://github.com/pyomeca/pyomeca/graphs/contributors) on GitHub. +We also would like to extend thanks to the contributors of the libraries used to build `pyomeca` — particularly `numpy`, `scipy`, `matplotlib` and `xarray`. + # References