Basin

A numerical optimization library for Rust, inspired by argmin. It pairs a small generic core, problem traits you implement, a pluggable termination layer, and a driver loop (Executor), with a growing set of solvers spanning first-order, derivative-free, nonlinear least-squares, and evolutionary methods. Solvers are generic over the linear-algebra backend, constraints are first-class, and the default build compiles to wasm32-unknown-unknown with no BLAS/LAPACK or threads.

Narrative documentation lives at basin.bz/docs; the rustdoc reference is at docs.rs/basin. There is also an in-browser solver visualizer and a benchmarks site comparing Basin against competing crates and across backends and solvers.

Install

cargo add basin

Basin works on plain Vec<f64> out of the box. Linear-algebra backends are opt-in, one feature each:

cargo add basin --features nalgebra  # or: ndarray, faer

Example

Implement CostFunction (and Gradient, when the solver needs derivatives), then hand the problem, a solver, and an initial state to the Executor:

use basin::{BasicState, CostFunction, Executor, Gradient, GradientDescent, GradientTolerance};
use std::convert::Infallible;

struct Rosenbrock;

impl CostFunction for Rosenbrock {
    type Param = Vec<f64>;
    type Output = f64;
    type Error = Infallible;
    fn cost(&self, x: &Vec<f64>) -> Result<f64, Self::Error> {
        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>, Self::Error> {
        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();

println!("x = {:?}, f = {}, stopped: {:?}", result.param(), result.cost(), result.reason);

Termination criteria are framework-level: the same ones compose across solvers, and they are bound to the state a solver actually exposes --- so asking for a gradient tolerance on a derivative-free solver is a compile error, not a runtime surprise.

Solvers

• First-order/quasi-Newton: gradient descent (with momentum and pluggable line searches), BFGS, L-BFGS, L-BFGS-B.
• Derivative-free: Nelder--Mead, Brent (1D).
• Nonlinear least squares: Gauss--Newton, Levenberg--Marquardt, trust-region reflective.
• Global/stochastic: random search, CMA-ES, a steady-state genetic algorithm, and memetic combinations.
• Constrained: box bounds via projected gradient descent, bounded Nelder--Mead, L-BFGS-B, and bounded CMA-ES; log-barrier and augmented Lagrangian wrappers for more general constraints.

See Solvers for which backends each one supports.

Backends

Parameters and linear algebra are generic over the backend. Vec<f64> needs no features; nalgebra, ndarray, and faer are enabled one feature each, each pinning a single major version. First-order and derivative-free solvers run on any backend; linear-algebra-heavy solvers may require a specific one and say so in their docs.

The default build is wasm-friendly: no BLAS/LAPACK and no threads. Parallelism and BLAS-backed paths are behind opt-in features (parallel).

Status

The public API is still iterating and breaking changes are expected. WebAssembly bindings (basin-wasm) power the visualizer but are not published to a package registry yet.

Acknowledgements

Basin owes a substantial intellectual debt to argmin: the overall shape of the crate: the Executor driver loop, the Solver / Problem trait split, per-solver State, and the pluggable termination layer is borrowed from it, and several solver implementations and test-problem conventions were modeled on argmin's. Thanks to the argmin authors and contributors for a library that is a pleasure to learn from.

License

Licensed under either of

• Apache License, Version 2.0 (LICENSE-APACHE or https://www.apache.org/licenses/LICENSE-2.0)
• MIT license (LICENSE-MIT or https://opensource.org/licenses/MIT)

at your option.

Contribution

Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.