Selection.py

from EvolutionaryFunctions import EvolutionaryFunctions
from Individual import Individual
from Population import Population
from typing import List, Tuple
import numpy as np

class Selection:
    def __init__(self, k: int) -> None:
        self._k = k
        self._selection_function = min

    # def select_amt(self, population: Population, num_pairs: int) -> List[Tuple[Individual, Individual]]:

    #     selected_pairs = []
    #     for _ in range(num_pairs):
    #         parent1 = EvolutionaryFunctions.k_tournament(population, self.k, self.selection_function)
    #         parent2 = EvolutionaryFunctions.k_tournament(population, self.k, self.selection_function)
    #         selected_pairs.append((parent1, parent2))
    #     return selected_pairs
    
    def select_pair(self,distance_matrix: np.ndarray, population: Population) -> Tuple[Individual, Individual]:
        parent1 = EvolutionaryFunctions.k_tournament(population, self._k, distance_matrix, self._selection_function)
        parent2 = EvolutionaryFunctions.k_tournament(population, self._k,distance_matrix, self._selection_function)
        return parent1, parent2