Struct metaheuristics_nature::utility::Context

#[non_exhaustive]
pub struct Context<F: ObjFunc> {
    pub rng: Rng,
    pub best: Array1<f64>,
    pub best_f: F::Fitness,
    pub pool: Array2<f64>,
    pub fitness: Vec<F::Fitness>,
    pub adaptive: f64,
    pub gen: u64,
    pub func: F,
}

The base class of algorithms.

This type provides a shared dataset if you want to implement a new method.

Please see Algorithm for the implementation.

Fields (Non-exhaustive)

Non-exhaustive structs could have additional fields added in future. Therefore, non-exhaustive structs cannot be constructed in external crates using the traditional Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.

rng: Rng

Random number generator.

best: Array1<f64>

The best variables.

best_f: F::Fitness

Best fitness.

pool: Array2<f64>

Current variables of all individuals.

fitness: Vec<F::Fitness>

Current fitness of all individuals.

adaptive: f64

Adaptive factor.

gen: u64

Generation.

func: F

The objective function.

Implementations

impl<F: ObjFunc> Context<F>

pub fn lb(&self, i: usize) -> f64

Get lower bound.

pub fn ub(&self, i: usize) -> f64

Get upper bound.

pub fn dim(&self) -> usize

Get dimension (number of variables).

pub fn pop_num(&self) -> usize

Get population number.

pub fn fitness(&mut self, i: usize)

Get fitness from individual i.

pub fn set_best(&mut self, i: usize)

Set the index to best.

pub fn set_best_from<'a, A>(&mut self, f: F::Fitness, v: A) where
    A: AsArray<'a, f64>, 

Set the fitness and variables to best.

pub fn assign_from_best(&mut self, i: usize)

Assign the index from best.

pub fn assign_from<'a, A>(&mut self, i: usize, f: F::Fitness, v: A) where
    A: AsArray<'a, f64>, 

Assign the index from source.

pub fn find_best(&mut self)

Find the best, and set it globally.

pub fn check(&self, s: usize, v: f64) -> f64

Check the bounds of the index s with the value v.