# BiSPy : Bivariate Signal Processing with Python
[](https://jflamant.github.io/bispy/)
[](https://badge.fury.io/py/bispy-polar)
BiSPy is an open-source python framework for processing bivariate signals. It supports our papers on time-frequency analysis [1], spectral analysis [2] and linear time-invariant filtering [3] of bivariate signals.
> [1] Julien Flamant, Nicolas Le Bihan, Pierre Chainais: “Time-frequency analysis of bivariate signals”, Applied and Computational Harmonic Analysis, 2017; [arXiv:1609.0246](http://arxiv.org/abs/1609.02463), [doi:10.1016/j.acha.2017.05.007](https://doi.org/10.1016/j.acha.2017.05.007)
> [2] Julien Flamant, Nicolas Le Bihan, Pierre Chainais: “Spectral analysis of stationary random bivariate signals”, 2017, IEEE Transactions on Signal Processing; [arXiv:1703.06417](http://arxiv.org/abs/1703.06417), [doi:10.1109/TSP.2017.2736494](https://doi.org/10.1109/TSP.2017.2736494)
> [3] Julien Flamant, Pierre Chainais, Nicolas Le Bihan: “A complete framework for linear filtering of bivariate signals”, 2018; IEEE Transactions on Signal Processing; [arXiv:1802.02469](https://arxiv.org/abs/1802.02469), [doi:10.1109/TSP.2018.2855659](https://doi.org/10.1109/TSP.2018.2855659)
These papers contains theoretical results and several applications that can be reproduced with this toolbox.
This python toolbox is currently under development and is hosted on GitHub. If you encounter a bug or something unexpected please let me know by [raising an issue](https://github.com/jflamant/bispy/issues) on the project page.
### Install from PyPi
Due to name conflict the available version on PyPi is named ``bispy-polar''. To install from PyPi, simply type
```
pip install bispy-polar
```
It will automatically install dependencies (see also below).
To get started, simply use
```
import bispy as bsp
```
Requirements
============
BiSPy works with python 3.5+.
Dependencies:
- [NumPy](http://www.numpy.org)
- [SciPy](https://www.scipy.org)
- [Matplotlib](http://matplotlib.org)
- [numpy-quaternion](https://github.com/moble/quaternion)
To install dependencies:
```shell
pip install numpy scipy matplotlib numpy-quaternion
```
[numpy-quaternion](https://github.com/moble/quaternion) add quaternion dtype support to numpy. Implementation by [moble]. Since this python toolbox relies extensively on this module, you can check out first the nice introduction [here](https://github.com/moble).
License
=======
This software is distributed under the [CC-BY 4.0](https://creativecommons.org/licenses/by/4.0/) license.
Cite this work
==============
If you use this package for your own work, please consider citing it with this piece of BibTeX:
```bibtex
@misc{BiSPy,
title = {{BiSPy: an Open-Source Python project for processing bivariate signals}},
author = {Julien Flamant},
year = {2018},
url = {https://github.com/jflamant/bispy/},
howpublished = {Online at: \url{github.com/jflamant/bispy/}},
note = {Code at https://github.com/jflamant/bispy/, documentation at https://bispy.readthedocs.io/}
}
```
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