The tfilterspy package is a Python library for implementing Bayesian filter algorithms, widely used mathematical tools in estimation theory and control engineering.
You can install the tfilterspy package via pip, the Python package installer. Open a terminal and type the following command:
pip install tfilterspy
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.
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.
You can contribute in many ways:
Please follow these steps when conducting research & development:
- Pick a problem from the issues page.
- Create a separate branch.
- Conduct research & engineering.
- When ready to merge, create a pull request.
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.
Look through the GitHub issues for bugs. Anything tagged with "bug" and "help wanted" is open to for contribution.
This package is licensed under the MIT License.