metaheuristic_designer.initializers.exponential_initializer module

Initializer that samples from an exponential distribution.

class ExponentialInitializer(dimension, beta, pop_size=1, encoding=None, dtype=<class 'float'>, rng=None)

Bases: Initializer

Initializer that generates individuals with values drawn from an exponential distribution.

Parameters:

dimensionint

Length of the genotype vector.

betafloat or array

Scale parameter of the exponential distribution (1 / rate).

pop_sizeint, optional

Number of individuals to generate (default 1).

encodingEncoding, optional

Encoding that will be passed to each individual.

dtypetype, optional

Desired NumPy dtype of the generated vectors (default float).

rngRNGLike, optional

Random number generator.

Methods

generate_individual()	Generate a single individual.
generate_population([n_individuals])	Create a fully formed population of n_individuals individuals.
generate_random()	Generate a single random genotype vector (1-D array).
get_state()	Return a minimal dictionary identifying this initializer.

generate_random()

Generate a single random genotype vector (1-D array).

Returns:

VectorLike

A newly generated genotype vector (1-D array).