Source code for slim_gsgp.selection.selection_algorithms

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"""
Selection operator implementation.
"""

import random

import numpy as np


[docs] def tournament_selection_min(pool_size): """ Returns a function that performs tournament selection to select an individual with the lowest fitness from a population. Parameters ---------- pool_size : int Number of individuals participating in the tournament. Returns ------- Callable A function ('ts') that elects the individual with the lowest fitness from a randomly chosen pool. Parameters ---------- pop : Population The population from which individuals are drawn. Returns ------- Individual The individual with the lowest fitness in the pool. Notes ----- The returned function performs tournament selection by receiving a population and returning the best of {pool_size} randomly selected individuals. """ def ts(pop): """ Selects the individual with the lowest fitness from a randomly chosen pool. Parameters ---------- pop : Population The population from which individuals are drawn. Returns ------- Individual The individual with the lowest fitness in the pool. """ pool = random.choices(pop.population, k=pool_size) return pool[np.argmin([ind.fitness for ind in pool])] return ts
[docs] def tournament_selection_max(pool_size): """ Returns a function that performs tournament selection to select an individual with the highest fitness from a population. Parameters ---------- pool_size : int Number of individuals participating in the tournament. Returns ------- Callable A function ('ts') that elects the individual with the highest fitness from a randomly chosen pool. Parameters ---------- pop : Population The population from which individuals are drawn. Returns ------- Individual The individual with the lowest fitness in the pool. Notes ----- The returned function performs tournament selection by receiving a population and returning the best of {pool_size} randomly selected individuals. """ def ts(pop): """ Selects the individual with the highest fitness from a randomly chosen pool. Parameters ---------- pop : Population The population from which individuals are drawn. Returns ------- Individual The individual with the highest fitness in the pool. """ pool = random.choices(pop.population, k=pool_size) return pool[np.argmax([ind.fitness for ind in pool])] return ts