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It supports our papers on time-frequency analysis [1], spectral analysis [2] and linear time-invariant filtering [3] of bivariate signals.\n\n\u003e [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)\n\n\u003e [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)\n\n\u003e [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)\n\nThese papers contains theoretical results and several applications that can be reproduced with this toolbox.\n\n\nThis 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.\n\n### Install from PyPi\n\nDue to name conflict the available version on PyPi is named ``bispy-polar''. To install from PyPi, simply type\n\n```\npip install bispy-polar\n```\n\nIt will automatically install dependencies (see also below). \n\nTo get started, simply use \n```\nimport bispy as bsp\n```\n\nRequirements\n============\nBiSPy works with python 3.5+.\n\nDependencies:\n -   [NumPy](http://www.numpy.org)\n -   [SciPy](https://www.scipy.org)\n -   [Matplotlib](http://matplotlib.org)\n -   [numpy-quaternion](https://github.com/moble/quaternion)\n\nTo install dependencies:\n```shell\npip install numpy scipy matplotlib numpy-quaternion\n```\n\n[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).\n\n\nLicense\n=======\nThis software is distributed under the [CC-BY 4.0](https://creativecommons.org/licenses/by/4.0/) license.\n\nCite this work\n==============\nIf you use this package for your own work, please consider citing it with this piece of BibTeX:\n\n```bibtex\n@misc{BiSPy,\n    title =   {{BiSPy: an Open-Source Python project for processing bivariate signals}},\n    author =  {Julien Flamant},\n    year =    {2018},\n    url =     {https://github.com/jflamant/bispy/},\n    howpublished = {Online at: \\url{github.com/jflamant/bispy/}},\n    note =    {Code at https://github.com/jflamant/bispy/, documentation at https://bispy.readthedocs.io/}\n}\n```\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjflamant%2Fbispy","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjflamant%2Fbispy","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjflamant%2Fbispy/lists"}