arXiv (Cornell University) · 2020 · 34 citations · 52 references
EngineeringNonlinear System IdentificationParameter IdentificationData ScienceModeling And SimulationNonlinear ProcessPublic HealthNonlinear Time SeriesDiscrete Dynamical SystemNonlinear DynamicsInverse ProblemsComputer ScienceComplex Dynamic SystemSystem IdentificationFunctional Data AnalysisComputational ScienceSparse IdentificationRobust ModelingPython PackageDynamics
PySINDy is a Python package for the discovery of governing dynamical systems models from data. In particular, PySINDy provides tools for applying the sparse identification of nonlinear dynamics (SINDy) (Brunton et al. 2016) approach to model discovery. In this work we provide a brief description of the mathematical underpinnings of SINDy, an overview and demonstration of the features implemented in PySINDy (with code examples), practical advice for users, and a list of potential extensions to PySINDy. Software is available at https://github.com/dynamicslab/pysindy.
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Pattern Recognition and Machine Learning
Journal of Electronic Imaging · 2007 · 22K citations
Maziar Raissi, Paris Perdikaris, George Em Karniadakis · Journal of Computational Physics · 2018 · 14.4K citations · Full text
Engineering, Pde-constrained Optimization, Deep Learning Framework +6