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:

pip install tfilterspy

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.

Contributing

You can contribute in many ways:

Research & Development

Please follow these steps when conducting research & development:

1. Pick a problem from the issues page.
2. Create a separate branch.
3. Conduct research & engineering.
4. When ready to merge, create a pull request.

Report Bugs

If you are reporting a bug, please include:

• Your operating system name and version.
• Any details about your local setup that might be helpful in troubleshooting.
• Steps to reproduce the bug.

Fix Bugs

Look through the GitHub issues for bugs. Anything tagged with "bug" and "help wanted" is open to for contribution.

License

This package is licensed under the MIT License.