pub struct BayesOptConfig {Show 15 fields
pub bounds: Vec<(f64, f64)>,
pub x0: Option<Array1<f64>>,
pub initial_samples: usize,
pub batch_size: usize,
pub maxeval: usize,
pub candidate_pool_size: usize,
pub lengthscales: Option<Vec<f64>>,
pub kernel_variance: f64,
pub noise: f64,
pub exploration: f64,
pub posterior_std_threshold: f64,
pub parallel: ParallelConfig,
pub seed: Option<u64>,
pub acquisition: BayesAcquisition,
pub callback: Option<BayesOptCallback>,
}Expand description
Configuration for bayesian_optimization.
Fields§
§bounds: Vec<(f64, f64)>(lower, upper) bounds per parameter.
x0: Option<Array1<f64>>Optional initial point. Values outside bounds are clipped.
initial_samples: usizeNumber of Sobol hot-start samples. 0 uses a dimension-dependent default.
batch_size: usizeNumber of candidates evaluated per BO iteration. 0 uses 1.
maxeval: usizeMaximum objective evaluations.
candidate_pool_size: usizeNumber of acquisition candidates considered per iteration.
lengthscales: Option<Vec<f64>>Optional ARD lengthscales in normalised parameter coordinates.
kernel_variance: f64Signal variance for the Matérn-5/2 kernel.
noise: f64Diagonal observation-noise/jitter floor.
exploration: f64EI exploration offset. Larger values prefer uncertain candidates.
posterior_std_threshold: f64Stop once the candidate-pool posterior standard deviation drops below
this value. 0.0 disables the uncertainty stop.
parallel: ParallelConfigParallel batch-evaluation configuration.
seed: Option<u64>Optional RNG seed for deterministic runs.
acquisition: BayesAcquisitionAcquisition strategy.
callback: Option<BayesOptCallback>Optional per-iteration callback. Returning CallbackAction::Stop
terminates early with the best point seen so far.
Trait Implementations§
Auto Trait Implementations§
impl Freeze for BayesOptConfig
impl !RefUnwindSafe for BayesOptConfig
impl Send for BayesOptConfig
impl !Sync for BayesOptConfig
impl Unpin for BayesOptConfig
impl UnsafeUnpin for BayesOptConfig
impl !UnwindSafe for BayesOptConfig
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