This package is for Bayesian filtering models.
Project description
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.
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