Struct DynamicGaussianMutation 

pub struct DynamicGaussianMutation {
    pub sigma: f64,
    pub gene_mutation_prob: f64,
    pub grow_prob: f64,
    pub shrink_prob: f64,
}

Length-aware mutation for DynamicRealVector.

Combines two independent effects, applied in this order:

1. Gaussian perturbation — each gene is, with probability gene_mutation_prob, perturbed by a sample from N(0, sigma^2) and then clamped back into the supplied bounds.
2. Length change — with probability grow_prob a new gene (sampled within bounds) is inserted at a random position, and with probability shrink_prob a random gene is removed. Both changes respect the genome’s own [min_length, max_length] window via can_grow / can_shrink, so the length always stays in range.

Fields

sigma: f64

Standard deviation of the per-gene Gaussian perturbation.

gene_mutation_prob: f64

Per-gene probability of applying the Gaussian perturbation.

grow_prob: f64

Probability of inserting a new gene (subject to can_grow).

shrink_prob: f64

Probability of removing a gene (subject to can_shrink).

Implementations

impl DynamicGaussianMutation

pub fn new( sigma: f64, gene_mutation_prob: f64, grow_prob: f64, shrink_prob: f64, ) -> Self

Create a new mutation operator.

Panics

Panics if any probability is outside [0, 1] or if sigma is negative.

pub fn mutate<R: Rng>( &self, genome: &mut DynamicRealVector, bounds: &MultiBounds, rng: &mut R, )

Apply the mutation in place.

Trait Implementations

impl Clone for DynamicGaussianMutation

fn clone(&self) -> DynamicGaussianMutation

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Copy for DynamicGaussianMutation

impl Debug for DynamicGaussianMutation

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.