This release merely adds a warning when the number of sensors exceeds the number of samples and the CCQR optimizer is used. In this case sensors may be selected from constrained regions. See #14.

Minor (one line) bug fix related to #13.

This release is the same as the previous one. It was created to be archived by Zenodo to produce a DOI.

This release contains minor updates to documentation and the JOSS paper made in response to feedback from JOSS reviewers.

This release contains a collection of changes, mostly to documentation and notebooks, made based on journal of open source software (JOSS) feedback: https://github.com/openjournals/joss-reviews/issues/2828.

In addition to fixing minor bugs and adding content to the examples, the primary change in this release is the renaming of the SensorSelector class to SSPOR (Sparse Sensor Placement Optimization for Reconstruction). See #8 for more details.

This release is essentially the same as v0.2.0, but it is designed to test a GitHub action that should automatically deploy it to PyPI.

Incremental improvement on v0.2.0 allowing for automatic versioning via setuptools_scm_git_archive.

PySensors initial version

This is an initial version of PySensors, which will soon by superseded by v1.0.0. It includes most of the basic functionality that will be included in v1.0.0, but is not fully polished.

Features

• SensorSelector class for sparse sensor selection for reconstruction
• SSPOC class for sparse sensor selection for classification
• Basis classes
  • Identity
  • SVD
  • RandomProjection
• Jupyter notebooks showing how to use various PySensors features