Manuel Raimann
47b5f9cec8
- Add blanket `impl Objective<V> for Fn(&mut Trial) -> Result<V, E>` so closures work directly with `optimize` - Rewrite optimize, optimize_async, optimize_parallel to accept `impl Objective<V>` with before_trial/after_trial hooks - Remove optimize_with, optimize_with_async, optimize_with_parallel - Remove max_retries and retry logic from Objective trait - Add explicit closure type annotations for HRTB inference - Convert FnMut test closures to Fn via RefCell/Cell
33 lines
1.1 KiB
Rust
33 lines
1.1 KiB
Rust
//! Basic optimization example — the "hello world" of the optimizer crate.
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//!
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//! Minimizes a simple quadratic function f(x) = (x - 3)² using the default
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//! random sampler. No feature flags are required.
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//!
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//! Run with: `cargo run --example basic_optimization`
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use optimizer::prelude::*;
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fn main() {
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// Create a study that minimizes the objective function.
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// The default sampler is random; for smarter sampling, pass a TpeSampler.
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let study: Study<f64> = Study::new(Direction::Minimize);
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// Search for x in [-10, 10]. The optimizer will suggest values from this range.
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let x = FloatParam::new(-10.0, 10.0).name("x");
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// Run 50 trials, each evaluating f(x) = (x - 3)²
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study
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.optimize(50, |trial: &mut optimizer::Trial| {
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let x_val = x.suggest(trial)?;
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let value = (x_val - 3.0).powi(2);
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Ok::<_, Error>(value)
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})
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.unwrap();
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// Retrieve and display the best result
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let best = study.best_trial().unwrap();
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println!("Best trial #{}", best.id);
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println!(" x = {:.4}", best.get(&x).unwrap());
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println!(" f(x) = {:.4}", best.value);
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}
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