bilby

A high-performance numerical quadrature (integration) library for Rust.

• Comprehensive -- Gauss-Legendre, Gauss-Kronrod, Jacobi, Hermite, Laguerre, Chebyshev, Radau, Lobatto, Clenshaw-Curtis, tanh-sinh, oscillatory, Cauchy PV
• Adaptive integration -- QUADPACK-style error-driven refinement with configurable GK pairs
• Multi-dimensional -- tensor products, Smolyak sparse grids, Genz-Malik adaptive cubature, quasi-Monte Carlo (Sobol, Halton)
• Generic over F: Float -- works with f32, f64, and AD types (e.g., echidna)
• no_std compatible -- works without the standard library (with alloc)
• Optional parallelism -- parallel feature for rayon-based _par methods
• Precomputed rules -- generate nodes/weights once, integrate many times with zero allocation

Quick Start

Add to Cargo.toml:

[dependencies]
bilby = "0.2"

use bilby::GaussLegendre;

// Create a 10-point Gauss-Legendre rule
let gl = GaussLegendre::new(10).unwrap();

// Integrate x^2 over [0, 1] (exact result = 1/3)
let result = gl.rule().integrate(0.0, 1.0, |x: f64| x * x);
assert!((result - 1.0 / 3.0).abs() < 1e-14);

Features

no_std support

bilby works in no_std environments (with alloc). Disable default features:

[dependencies]
bilby = { version = "0.2", default-features = false }

Parallelism

Enable the parallel feature for parallel variants of integration methods:

[dependencies]
bilby = { version = "0.2", features = ["parallel"] }

This provides integrate_composite_par, integrate_par, integrate_box_par, MonteCarloIntegrator::integrate_par, and GaussLegendre::new_par.

Development

cargo test                         # Run tests (default features)
cargo test --all-features          # Run tests including parallel
cargo test --no-default-features   # Run tests in no_std mode
cargo bench                        # Run benchmarks
cargo clippy --all-features        # Lint

License

Licensed under either of

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

at your option.

Contributing

See CONTRIBUTING.md for guidelines.

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