kalbee 🐝

kalbee is a clean, modular Python library for Kalman Filters and state estimation algorithms. It provides a unified interface for 8 different filter types, a smoother, diagnostic metrics, and a built-in experiment runner to compare filter performance.

✨ Highlights

Category	What you get
8 Filters	KF, EKF, UKF, Particle, Ensemble, Information, Alpha-Beta-Gamma, Adaptive KF
Smoother	Rauch-Tung-Striebel (RTS) backward smoother
Diagnostics	RMSE, NEES, NIS, Log-Likelihood
Experiments	One-liner to compare filters on synthetic signals
Stability	Joseph form covariance updates, symmetry enforcement

🚀 Quick Start

pip install kalbee

from kalbee import run_experiment

# Compare filters on a sine wave
report = run_experiment(
    signal="sine",
    filters=["kf", "ekf", "ukf", "pf"],
    noise_std=0.5,
)
print(report.summary())

📖 Navigation

• Getting Started — Installation, core concepts, first filter
• Filters — Deep dive into each filter with theory + code
• Features — Smoother, metrics, experiment runner
• Architecture — Design philosophy and extensibility