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https://github.com/pyomeca/pyomeca
Python toolbox for biomechanics analysis
https://github.com/pyomeca/pyomeca
biomechanics biomechanics-analysis dynamics kinematics kinetics python xarray
Last synced: about 2 months ago
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Python toolbox for biomechanics analysis
- Host: GitHub
- URL: https://github.com/pyomeca/pyomeca
- Owner: pyomeca
- License: apache-2.0
- Created: 2018-01-22T20:52:02.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2021-06-14T15:39:39.000Z (about 3 years ago)
- Last Synced: 2024-04-21T00:07:10.512Z (3 months ago)
- Topics: biomechanics, biomechanics-analysis, dynamics, kinematics, kinetics, python, xarray
- Language: Jupyter Notebook
- Homepage: https://pyomeca.github.io/
- Size: 13.1 MB
- Stars: 109
- Watchers: 8
- Forks: 28
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
- Contributing: docs/contributing.md
- License: LICENSE.md
Lists
- awesome-biomechanics - source
README
Pyomeca is a python library allowing you to carry out a complete biomechanical analysis; in a simple, logical and concise way.
## Pyomeca documentation
See Pyomeca's [documentation site](https://pyomeca.github.io).
## Example
Pyomeca implements specialized functionalities commonly used in biomechanics.
As an example, let's process the electromyographic data contained in this [`c3d file`](https://github.com/pyomeca/pyomeca/blob/master/tests/data/markers_analogs.c3d).
You can follow along without installing anything by using our binder server: [](https://mybinder.org/v2/gh/pyomeca/pyomeca/master?filepath=notebooks)
```python
from pyomeca import Analogs
data_path = "../tests/data/markers_analogs.c3d"
muscles = [
"Delt_ant",
"Delt_med",
"Delt_post",
"Supra",
"Infra",
"Subscap",
]
emg = Analogs.from_c3d(data_path, suffix_delimiter=".", usecols=muscles)
emg.plot(x="time", col="channel", col_wrap=3)
```
```python
emg_processed = (
emg.meca.band_pass(order=2, cutoff=[10, 425])
.meca.center()
.meca.abs()
.meca.low_pass(order=4, cutoff=5, freq=emg.rate)
.meca.normalize()
)
emg_processed.plot(x="time", col="channel", col_wrap=3)
```
```python
import matplotlib.pyplot as plt
fig, axes = plt.subplots(ncols=2, figsize=(10, 4))
emg_processed.mean("channel").plot(ax=axes[0])
axes[0].set_title("Mean EMG activation")
emg_processed.plot.hist(ax=axes[1], bins=50)
axes[1].set_title("EMG activation distribution")
```
See [the documentation](https://pyomeca.github.io) for more details and examples.
## Features
- Signal processing routine commonly used in biomechanics such as filters, normalization, onset detection, outliers detection, derivatives, etc.
- Common matrix manipulation routines implemented such as getting Euler angles to/from a rototranslation matrix, creating a system of axes, setting a rotation or translation, transpose or inverse, etc.
- Easy reading and writing interface to common files in biomechanics (`c3d`, `csv`, `xlsx`,`mat`, `trc`, `sto`, `mot`)
- All of [xarray](http://xarray.pydata.org/en/stable/index.html)'s awesome features
The following illustration shows all of pyomeca's public API.
An interactive version is available in the [documentation](https://pyomeca.github.io/overview/).
## Installation
Pyomeca itself is a pure Python package, but its dependencies are not.
The easiest way to get everything installed is to use [conda](https://conda.io/en/latest/miniconda.html).
To install pyomeca with its recommended dependencies using the conda command line tool:
```bash
conda install -c conda-forge pyomeca
```
Now that you have installed pyomeca, you should be able to import it:
```python
import pyomeca
```
## Integration with other modules
Pyomeca is designed to work well with other libraries that we have developed:
- [pyosim](https://github.com/pyomeca/pyosim): interface between [OpenSim](http://opensim.stanford.edu/) and pyomeca to perform batch musculoskeletal analyses
- [ezc3d](https://github.com/pyomeca/ezc3d): Easy to use C3D reader/writer in C++, Python and Matlab
- [biorbd](https://github.com/pyomeca/biorbd): C++ interface and add-ons to the Rigid Body Dynamics Library, with Python and Matlab binders.
## Bug reports & questions
Pyomeca is Apache-licensed and the source code is available on [GitHub](https://github.com/pyomeca/pyomeca).
If any questions or issues come up as you use pyomeca, please get in touch via [GitHub issues](https://github.com/pyomeca/pyomeca/issues).
We welcome any input, feedback, bug reports, and contributions.
## Citing Pyomeca
[](https://doi.org/10.21105/joss.02431)
If you use pyomeca in your academic work, please consider citing [our paper](https://doi.org/10.21105/joss.02431) as:
```bibtex
@article{Martinez2020,
doi = {10.21105/joss.02431},
url = {https://doi.org/10.21105/joss.02431},
year = {2020},
publisher = {The Open Journal},
volume = {5},
number = {53},
pages = {2431},
author = {Romain Martinez and Benjamin Michaud and Mickael Begon},
title = {`pyomeca`: An Open-Source Framework for Biomechanical Analysis},
journal = {Journal of Open Source Software}
}
```
Please consider citing the [xarray](https://openresearchsoftware.metajnl.com/articles/10.5334/jors.148/) project, which pyomeca is based on:
```bibtex
@article{jors-xarray,
title = {Xarray: N-D labeled arrays and datasets in Python},
author = {Joe Hamman and Stephan Hoyer},
year = {2017},
journal = {Journal of Open Research Software}
}
```
## Contributors
- [Romain Martinez](https://github.com/romainmartinez)
- [Benjamin Michaud](https://github.com/pariterre)
- [Mickael Begon](https://github.com/mickaelbegon)
- [Jenn Dowling-Medley](https://github.com/jdowlingmedley)
- [Ariane Dang](https://github.com/Dangzilla)
Pyomeca is an open-source project created and supported by the [S2M lab](https://www.facebook.com/s2mlab/).