Sampler

This module provides various ways to initialize the population for evolutionary algorithms.

RealSampler

class pyevopt.sampler.RealSampler

Initializes a population with real-valued solutions.

This sampler can be used to initialize the population of an evolutionary algorithm with real-valued solutions.

The population is initialized by sampling from a uniform distribution. This allows for efficient initialization of large populations, and provides a good starting point for further evolution.

generate(size: int, dimension: int, domain: tuple[float, float])

Generate a real-valued population of individuals.

Generates a population of size individuals, each individual being an array of length dimension, with values chosen from the specified domain.

Parameters

size: int

The number of individuals in the population.

dimension: int

The size of each individual.

domain

A function that maps a value to a random sample from this domain.

Returns

np.ndarray

An array of shape (size, dimension) containing the generated population.