Function differential_evolution 

pub fn differential_evolution<F>(
    func: &F,
    bounds: &[(f64, f64)],
    config: DEConfig,
) -> Result<DEReport>
where
    F: Fn(&Array1<f64>) -> f64 + Sync,

Runs Differential Evolution optimization on a function.

This is a convenience function that mirrors SciPy’s differential_evolution API. It creates a DE optimizer with the given bounds and configuration, then runs the optimization to find the global minimum.

Arguments

• func - The objective function to minimize, mapping &Array1<f64> to f64
• bounds - Vector of (lower, upper) bound pairs for each dimension
• config - DE configuration (use DEConfigBuilder to construct)

Returns

Returns Ok(DEReport) containing the optimization result on success.

Errors

Returns DEError::InvalidBounds if any bound pair has upper < lower.

Example

use autoeq_de::{differential_evolution, DEConfigBuilder};

let result = differential_evolution(
    &|x| x[0].powi(2) + x[1].powi(2),
    &[(-5.0, 5.0), (-5.0, 5.0)],
    DEConfigBuilder::new().maxiter(50).seed(42).build(),
).expect("optimization failed");

assert!(result.fun < 0.01);