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pyRecEst

Recursive Bayesian Estimation for Python

pyRecEst is a Python library tailored for recursive Bayesian estimation, compatible with numpy, pytorch, and jax backends.

Features of pyRecEst include:

  • Distribution and Densities: Provides tools for handling distributions and densities across Euclidean spaces and manifolds.
  • Filters and Trackers: Offers a suite of recursive Bayesian estimators (filters or trackers) for both Euclidean spaces and manifolds. This includes capabilities for:
    • Multi-Target Tracking (MTT)
    • Extended Object Tracking (EOT)
  • Evaluation Framework: Contains an evaluation framework to facilitate comparison between different filters.
  • Sampling Methods: Includes methods for sampling of the distributions and generating grids.

Usage

Please refer to the test cases for usage examples.

Credits

pyRecEst borrows its structure from libDirectional and follows its code closely for many classes. libDirectional, a project to which I contributed extensively, is available on GitHub. The backend implementations are based on those of geomstats.

License

pyRecEst is licensed under the MIT License.