Struct RealVector 

pub struct RealVector { /* private fields */ }

Fixed-length real-valued vector genome

This genome type represents continuous optimization problems where solutions are vectors of real numbers.

Implementations

impl RealVector

pub fn new(genes: Vec<f64>) -> Self

Create a new real vector with the given genes

pub fn zeros(dimension: usize) -> Self

Create a zero-filled vector of the given dimension

pub fn filled(dimension: usize, value: f64) -> Self

Create a vector filled with a constant value

pub fn collect_from<I: IntoIterator<Item = f64>>(iter: I) -> Self

Create from an iterator

pub fn into_inner(self) -> Vec<f64>

Get the underlying vector

pub fn as_vec(&self) -> &Vec<f64>

Get a reference to the genes

pub fn norm(&self) -> f64

Calculate Euclidean norm

pub fn norm_squared(&self) -> f64

Calculate squared Euclidean norm

pub fn add(&self, other: &Self) -> Result<Self, GenomeError>

Element-wise addition

pub fn sub(&self, other: &Self) -> Result<Self, GenomeError>

Element-wise subtraction

pub fn scale(&self, scalar: f64) -> Self

Scalar multiplication

Trait Implementations

impl BoundedCrossoverOperator<RealVector> for SbxCrossover

fn crossover_bounded<R: Rng>( &self, parent1: &RealVector, parent2: &RealVector, bounds: &MultiBounds, rng: &mut R, ) -> OperatorResult<(RealVector, RealVector)>

Apply bounded crossover to two parents

impl BoundedMutationOperator<RealVector> for GaussianMutation

fn mutate_bounded<R: Rng>( &self, genome: &mut RealVector, bounds: &MultiBounds, rng: &mut R, )

Apply bounded mutation to a genome

impl BoundedMutationOperator<RealVector> for PolynomialMutation

fn mutate_bounded<R: Rng>( &self, genome: &mut RealVector, bounds: &MultiBounds, rng: &mut R, )

Apply bounded mutation to a genome

impl BoundedMutationOperator<RealVector> for UniformMutation

fn mutate_bounded<R: Rng>( &self, genome: &mut RealVector, bounds: &MultiBounds, rng: &mut R, )

Apply bounded mutation to a genome

impl Clone for RealVector

fn clone(&self) -> RealVector

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl CrossoverOperator<RealVector> for ArithmeticCrossover

fn crossover<R: Rng>( &self, parent1: &RealVector, parent2: &RealVector, _rng: &mut R, ) -> OperatorResult<(RealVector, RealVector)>

Apply crossover to two parents and produce two offspring

fn crossover_probability(&self) -> f64

Get the probability of crossover being applied

impl CrossoverOperator<RealVector> for BlxAlphaCrossover

fn crossover<R: Rng>( &self, parent1: &RealVector, parent2: &RealVector, rng: &mut R, ) -> OperatorResult<(RealVector, RealVector)>

Apply crossover to two parents and produce two offspring

fn crossover_probability(&self) -> f64

Get the probability of crossover being applied

impl CrossoverOperator<RealVector> for SbxCrossover

fn crossover<R: Rng>( &self, parent1: &RealVector, parent2: &RealVector, rng: &mut R, ) -> OperatorResult<(RealVector, RealVector)>

Apply crossover to two parents and produce two offspring

fn crossover_probability(&self) -> f64

Get the probability of crossover being applied

impl Debug for RealVector

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

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for RealVector

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl EvolutionaryGenome for RealVector

fn to_trace(&self) -> Trace

Convert RealVector to Fugue trace.

Each gene is stored at address “gene#i” where i is the index.

fn from_trace(trace: &Trace) -> Result<Self, GenomeError>

Reconstruct RealVector from Fugue trace.

Reads genes from addresses “gene#0”, “gene#1”, … until no more are found.

type Allele = f64

The allele type for individual genes

type Phenotype = Vec<f64>

The phenotype or decoded solution type

fn decode(&self) -> Self::Phenotype

Decode genome into phenotype for fitness evaluation

fn dimension(&self) -> usize

Compute dimensionality for adaptive operators

fn generate<R: Rng>(rng: &mut R, bounds: &MultiBounds) -> Self

Generate a random genome within the given bounds

fn as_slice(&self) -> Option<&[f64]>

Get the genome’s genes as a slice (for numeric genomes)

fn as_mut_slice(&mut self) -> Option<&mut [f64]>

Get the genome’s genes as a mutable slice (for numeric genomes)

fn distance(&self, other: &Self) -> f64

Distance metric between two genomes (default: 0.0)

fn trace_prefix() -> &'static str

Get the address prefix used for trace storage (default: “gene”)

impl<const N: usize> From<[f64; N]> for RealVector

fn from(arr: [f64; N]) -> Self

Converts to this type from the input type.

impl From<RealVector> for Vec<f64>

fn from(genome: RealVector) -> Self

Converts to this type from the input type.

impl From<Vec<f64>> for RealVector

fn from(genes: Vec<f64>) -> Self

Converts to this type from the input type.

impl Index<usize> for RealVector

type Output = f64

The returned type after indexing.

fn index(&self, index: usize) -> &Self::Output

Performs the indexing (container[index]) operation.

impl IndexMut<usize> for RealVector

fn index_mut(&mut self, index: usize) -> &mut Self::Output

Performs the mutable indexing (container[index]) operation.

impl<'a> IntoIterator for &'a RealVector

type Item = &'a f64

The type of the elements being iterated over.

type IntoIter = Iter<'a, f64>

Which kind of iterator are we turning this into?

fn into_iter(self) -> Self::IntoIter

Creates an iterator from a value.

impl IntoIterator for RealVector

type Item = f64

The type of the elements being iterated over.

type IntoIter = IntoIter<f64>

Which kind of iterator are we turning this into?

fn into_iter(self) -> Self::IntoIter

Creates an iterator from a value.

impl MutationOperator<RealVector> for GaussianMutation

fn mutate<R: Rng>(&self, genome: &mut RealVector, rng: &mut R)

Apply mutation to a genome in place

fn mutation_probability(&self) -> f64

Get the mutation probability per gene

impl MutationOperator<RealVector> for PolynomialMutation

fn mutate<R: Rng>(&self, genome: &mut RealVector, rng: &mut R)

Apply mutation to a genome in place

fn mutation_probability(&self) -> f64

Get the mutation probability per gene

impl MutationOperator<RealVector> for ScrambleMutation

fn mutate<R: Rng>(&self, genome: &mut RealVector, rng: &mut R)

Apply mutation to a genome in place

fn mutation_probability(&self) -> f64

Get the mutation probability per gene

impl MutationOperator<RealVector> for SwapMutation

fn mutate<R: Rng>(&self, genome: &mut RealVector, rng: &mut R)

Apply mutation to a genome in place

fn mutation_probability(&self) -> f64

Get the mutation probability per gene

impl MutationOperator<RealVector> for UniformMutation

fn mutate<R: Rng>(&self, genome: &mut RealVector, rng: &mut R)

Apply mutation to a genome in place

fn mutation_probability(&self) -> f64

Get the mutation probability per gene

impl PartialEq for RealVector

fn eq(&self, other: &RealVector) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl RealValuedGenome for RealVector

fn genes(&self) -> &[f64]

Get the genes as a slice of f64 values

fn genes_mut(&mut self) -> &mut [f64]

Get the genes as a mutable slice of f64 values

fn from_genes(genes: Vec<f64>) -> Result<Self, GenomeError>

Create from a vector of genes

fn apply_bounds(&mut self, bounds: &MultiBounds)

Apply bounds to all genes

impl Serialize for RealVector

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl StructuralPartialEq for RealVector