PySINDy

PySINDy: A Python package for the sparse identi cation of nonlinear dynamical systems from data. PySINDy is a sparse regression package with several implementations for the Sparse Identification of Nonlinear Dynamical systems (SINDy) method introduced in Brunton et al. (2016a), including the unified optimization approach of Champion et al. (2019) and SINDy with control from Brunton et al. (2016b). A comprehensive literature review is given in de Silva et al. (2020).

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References in zbMATH (referenced in 4 articles , 1 standard article )

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  1. Huang, Juntao; Zhou, Yizhou; Yong, Wen-An: Data-driven discovery of multiscale chemical reactions governed by the law of mass action (2022)
  2. Beetham, S.; Fox, R. O.; Capecelatro, J.: Sparse identification of multiphase turbulence closures for coupled fluid-particle flows (2021)
  3. Messenger, Daniel A.; Bortz, David M.: Weak SINDy for partial differential equations (2021)
  4. Brian de Silva; Kathleen Champion; Markus Quade; Jean-Christophe Loiseau; J. Nathan Kutz; Steven L. Brunton: PySINDy: A Python package for the sparse identification of nonlinear dynamical systems from data (2020) not zbMATH