What is RoughPy?
RoughPy is a library for working with and analysing streamed data through the lens of rough paths and signature methods.
Most data we work with is not nice, organised, tabular data. Our data is usually messy, sparse, and unordered. RoughPy helps us work with and analyse such data. RoughPy has no independent time steps. We can use intelligent caching so that we do not need to recompute features over and over again as we stream data. This makes our investigations easier, as can be seen in Kidger et al. [KMFL20].
RoughPy’s major components are an algebra library for Lie algebras, free tensors, shuffle tensors, intervals and a library for working with streaming data. We can work with data of many file formats, such as sound files and .csvs.
The rest of this video can be found here: Signatures of Streams - Terry Lyons
References
N. Bourbaki. Algebra I: Chapters 1-3. Springer Science & Business Media, August 1998. ISBN 978-3-540-64243-5. Google-Books-ID: STS9aZ6F204C.
Nicolas Bourbaki. Lie Groups and Lie Algebras: Chapters 1-3. Springer Science & Business Media, 1989. ISBN 978-3-540-64242-8. Google-Books-ID: brSYF_rB2ZcC.
Patrick Kidger, James Morrill, James Foster, and Terry Lyons. Neural Controlled Differential Equations for Irregular Time Series. November 2020. arXiv:2005.08926 [cs, stat]. URL: http://arxiv.org/abs/2005.08926 (visited on 2023-12-08), doi:10.48550/arXiv.2005.08926.
Terry Lyons and Andrew D. McLeod. Signature Methods in Machine Learning. January 2024. arXiv:2206.14674 [cs, math, stat]. URL: http://arxiv.org/abs/2206.14674 (visited on 2024-02-14).
Terry J. Lyons, Michael J. Caruana, and Thierry Lévy. Differential Equations Driven by Rough Paths: Ecole d’Eté de Probabilités de Saint-Flour XXXIV-2004. Springer, April 2007. ISBN 978-3-540-71285-5. Google-Books-ID: hOm5BQAAQBAJ.
Christophe Reutenauer. Free Lie Algebras. Clarendon Press, 1993. ISBN 978-0-19-853679-6. Google-Books-ID: cBvvAAAAMAAJ.