🛠️ project Announcing Basin: A Numerical Optimization Library for Rust
Hi!
I've been working on Basin, a numerical optimization library for Rust. It's heavily inspired by argmin; same overall shape (Executor driver loop, Solver/Problem trait split, per-solver State, pluggable termination). Basin exists because I wanted to push on a few specific design directions that were awkward to retrofit.
What's Different
- Framework-level termination, bound to state shape.
max_iter, the*_tolerancefamily,max_time, eval budgets all live on theExecutorand compose across solvers. Each criterion binds on the minimum state it needs, so asking for aGradientToleranceon a derivative-free solver is a compile error, not a runtime surprise. - First-class constraints. Constraints describe the problem, so they live problem-side (not on the executor, never on state). A constrained problem handed to an unconstrained solver is a compile error; there are opt-in adapters (projection/log-barrier/augmented Lagrangian) to wrap unconstrained solvers. Box bounds and linear (in)equalities today; nonlinear is on the roadmap.
- Backend-generic linear algebra. Solvers are generic over
Vec<f64>(no features), nalgebra, ndarray, and faer. A small universal vector tier keeps first-order/derivative-free solvers backend-generic; a richerlinalgtier holds matrix ops that LA-heavy solvers bound on by the minimum subset they need. - WASM in the default build. No BLAS/LAPACK, no threads, no
std::time::Instantin default paths. CI enforceswasm32-unknown-unknown. Parallelism and BLAS-backed paths are opt-in features.
Current Solvers Supported
- First-order/quasi-Newton: gradient descent (with momentum + pluggable line searches), BFGS, L-BFGS, L-BFGS-B
- Derivative-free: Nelder--Mead, Brent
- Nonlinear least squares: Gauss--Newton, Levenberg--Marquardt, trust-region-reflective
- Global/stochastic: random search, CMA-ES, steady-state GA, memetic combinations
- Constrained: projected gradient, bounded Nelder--Mead/L-BFGS-B/CMA-ES, log-barrier, augmented Lagrangian
Example
use basin::{BasicState, CostFunction, Executor, Gradient, GradientDescent, GradientTolerance};
struct Rosenbrock;
impl CostFunction for Rosenbrock {
type Param = Vec<f64>;
type Output = f64;
type Error = std::convert::Infallible;
fn cost(&self, x: &Vec<f64>) -> Result<f64, std::convert::Infallible> {
Ok((1.0 - x[0]).powi(2) + 100.0 * (x[1] - x[0].powi(2)).powi(2))
}
}
impl Gradient for Rosenbrock {
type Gradient = Vec<f64>;
fn gradient(&self, x: &Vec<f64>) -> Result<Vec<f64>, std::convert::Infallible> {
Ok(vec![
-2.0 * (1.0 - x[0]) - 400.0 * x[0] * (x[1] - x[0].powi(2)),
200.0 * (x[1] - x[0].powi(2)),
])
}
}
let result = Executor::new(Rosenbrock, GradientDescent::new(1e-3), BasicState::new(vec![-1.2, 1.0]))
.max_iter(50_000)
.terminate_on(GradientTolerance(1e-6))
.run()
.unwrap();
Links
- Crate: https://crates.io/crates/basin (
cargo add basin) - Docs: https://basin.bz/docs/, API: https://docs.rs/basin
- In-browser solver visualizer: https://basin.bz/visualizer/
- Benchmarks vs other crates and across backends: https://basin.bz/benchmarks/
- Source: https://github.com/jolars/basin (MIT)
Feedback is very welcome, especially on the trait surface, naming, and any solver/backend combinations you'd want that aren't there yet.
109
Upvotes
6
u/Zogzer 4d ago
Our use case is finance/HFT. We need to exit early in cases where we know things are not going to work where we are testing millions of cases in parallel.
Rust doesn't have exceptions so there is no way to bail, but as a result user callbacks should really return result types so you give the option to the user to do that if they want. You will never know what the user will want to do.
An unfortunate choice with
argminwas that it was limited to theanyhowerror type that makes it expensive to return. If you could add a defaulttype Error = ();associated type to the traits and then returnResult<Self::Output, Self::Error>fromcostinstead, that would allow the flexibility to do either and be a significant improvement overargminas it is. You are right that you end up withOkand?in a few places, but that is expected in rust.