Function minimize_scalar 

pub fn minimize_scalar(
    f: impl Fn(f64) -> f64,
    a: f64,
    b: f64,
    opts: &MinimizeOpts,
) -> Result<ScalarMinimum, SymplexError>

Minimise a scalar function on [a, b] by Brent’s method.

Combines golden-section steps with successive parabolic interpolation (Brent’s localmin), giving superlinear convergence on smooth functions and golden-section behaviour otherwise. Returns the minimiser and the value there as a ScalarMinimum. On a bracket containing several local minima the method converges to one of them; which one depends on the bracket. A reversed interval is accepted.

Errors

• SymplexError::InvalidArgument if an endpoint is not finite, the interval has zero width, or the options are negative.
• SymplexError::ComputationFailed if f returns a non-finite value or the tolerance is not met within the iteration budget (default 200).

Examples

use symplex::optimize::{minimize_scalar, MinimizeOpts};

let m = minimize_scalar(|x| (x - 1.0).powi(2) + 3.0, -5.0, 5.0, &MinimizeOpts::default()).unwrap();
assert!((m.x - 1.0).abs() < 1e-6);
assert!((m.value - 3.0).abs() < 1e-12);