FilterPy resource
Python Kalman filtering and optimal estimation library. Implements Kalman filter, particle filter, Extended Kalman filter, Unscented Kalman filter, g-h (alpha-beta), least squares, H Infinity, smoothers, and more. Has companion book 'Kalman and Bayesian Filters in Python'. observed · 2026-08-28
Health v2 · maintenance only
23/100
- Activity 0
- Release rhythm 8
- Longevity 100
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 4433
- days_rel: n/a
- days_push: 938
- n_releases_24m: 0
Adoption not part of the score
3862 stars · 678 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
An open-source Jupyter Notebook book teaching Kalman and Bayesian filters with intuition-first explanations, runnable Python code, and solved exercises. It accompanies FilterPy, a Python library for Kalman filtering and optimal estimation.
Use cases
- learn kalman filtering from scratch
- understand bayesian filters intuitively
- implement sensor fusion in python
- track noisy sensor data like gps
- study extended and unscented kalman filters
- learn particle filters with code examples
- teach state estimation to a team
When to choose
- you want an intuition-driven introduction rather than formal proofs
- you want runnable, modifiable code in Jupyter notebooks
- you need practical Python implementations of Kalman, EKF, UKF, and particle filters
When to avoid
- you need rigorous mathematical proofs or academic treatment
- you need a production-grade, actively maintained filtering library
- you need filters beyond Bayesian/state estimation techniques
Facets
learning-resource · maturity stable
machine-learning data-science simulation math machine-learning education tutorials robotics computer-vision python cross-platform kalman-filter bayesian-filters state-estimation jupyter-notebook signal-processing sensor-fusion particle-filters textbook
2 sources
- readme: https://github.com/rlabbe/filterpy · fetched 2026-08-28 · 98e5a6f5f5df
- registry_pypi: https://pypi.org/pypi/filterpy/json · fetched 2026-08-29 · 1d3409bbc098
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| rlabbe/filterpy | main | 23 |
| rlabbe/Kalman-and-Bayesian-Filters-in-Python | docs | 23 |
For agents
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem