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The tfilterspy package is a Python library for implementing Bayesian filter algorithms, widely used mathematical tools in estimation theory and control engineering.

Installation

You can install the tfilterspy package via pip, the Python package installer. Open a terminal and type the following command:

Supported Methods

Currently, the following Bayesian filter algorithms are implemented in tfilterspy:

  • Kalman Filters: A class of linear estimators used in filtering and smoothing applications.
  • Particle Filters: A family of sequential Monte Carlo methods used for sampling from posterior distributions.

More methods will be added in the future.

Usage

Here's are examples of how to use tfilterspy to estimate the state of a noisy linear system using a Kalman filter in the example folder.

Contribution

If you find a bug or have a feature request, please open an issue on the GitHub repository. Pull requests are welcome, but please open an issue first to discuss your changes.

License

This package is licensed under the MIT License.

Release files for tfilterpy 0.0.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

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Table of built distributions (wheels) for tfilterpy 0.0.3
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tfilterpy-0.0.3-py3-none-any.whl Python 3 none any Details

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