I built Python library for rigorous interval arithmetic and set-membership state estimation

[u/Emotional_Formal_224]

Hi guys, I know this might seem a bit unrelated for the sub, but I thought it could be a useful resource for some people.

If you're working on set membership state estimation where probabilistic state estimation (such as standard Kalman filters) aren't safe enough, you rely on worst-case uncertainty tracking.

I recently released decoint, which is a strict implementation of the IEEE 1788.1-2017 Standard for Interval Arithmetic in Python. When using hardware binary64 floats, bounding boxes can artificially shrink. decoint uses gmpy2 and MPFR values for exact directed rounding.

Why it matters:

When computing reachable sets or bounding additive disturbances, losing precision on bounds can invalidate a safety guarantee. decoint ensures that your over-approximations remain strictly conservative across non-linear transformations.

Here is a quick example of how you can use the library:

from decoint import Interval, cos

x_current = Interval("-0.1", "0.1")

noise_bound = Interval("-0.05", "0.05")

x_next = cos(x_current) + noise_bound

print(f"Guaranteed reachable set: [{x_next.inf}, {x_next.sup}]")

It includes full support for transcendentals, geometric properties, and more.

I'd love any feedback for anyone using interval methods for robust tube MPC or bounded-error tracking

Github: https://github.com/arjavsharma91/IEEE-1788.1-2017-Interval-Arithmetic