PySensors: A Python Package for Sparse Sensor Placement

Brian M. de Silva, Krithika Manohar, Emily Clark, Bingni W. Brunton, Steven L. Brunton +1 more
2/20/2021
eess.SPcs.LGmath.OC

Official code: dynamicslab/pysensors (123 stars, MIT, last commit 2026-02-17).

Abstract

PySensors is a Python package for selecting and placing a sparse set of sensors for classification and reconstruction tasks. Specifically, PySensors implements algorithms for data-driven sparse sensor placement optimization for reconstruction (SSPOR) and sparse sensor placement optimization for classification (SSPOC). In this work we provide a brief description of the mathematical algorithms and theory for sparse sensor optimization, along with an overview and demonstration of the features implemented in PySensors (with code examples). We also include practical advice for user and a list of potential extensions to PySensors. Software is available at https://github.com/dynamicslab/pysensors.

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Code Implementations(1)

dynamicslab/pysensorsOfficial100%
MIT

PySensors is a Python package for sparse sensor placement

12326PythonMay 1, 20208 months agoMIT
optimization-toolssensorsensor-placementsensors

Cite this paper

@article{silva2021pysensors,
  title  = {PySensors: A Python Package for Sparse Sensor Placement},
  author = {Brian M. de Silva and Krithika Manohar and Emily Clark and Bingni W. Brunton and Steven L. Brunton and J. Nathan Kutz},
  year   = {2021},
  eprint = {2102.13476},
  archivePrefix = {arXiv},
  url    = {https://arxiv.org/abs/2102.13476}
}

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