{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/pykoopman-a-python-package-for-data-driven","title":"PyKoopman: A Python Package for Data-Driven Approximation of the Koopman Operator","arxiv_id":"2306.12962","date":"2023-06-22","proceeding":null,"authors":["Shaowu Pan","Eurika Kaiser","Brian M. de Silva","J. Nathan Kutz","Steven L. Brunton"],"abstract":"PyKoopman is a Python package for the data-driven approximation of the Koopman operator associated with a dynamical system. 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