def selection(self, population: Population) -> List[Tuple[Chromosome]]:
"""
select parents for crossover
implements basic selection method: 1) create a pool of chromosomes, 2) select the amount needed for mating.
"""
parents = []
pairings = math.ceil(population.get_size() / self.get_offsprings_amount())
self.set_selection_pool([ch for ch in population])
for _ in range(pairings):
parents.append(tuple([self.select() for _ in range(self.get_parents_amount())]))
return parents
def crossover(self, parents: List[Tuple[Chromosome]], pop_size: int) -> Population:
"""
get list of parents to mate, return the new population
NOTE: when population (size - elitism amount) doesn't divide in (offspring amount) then the remainder
offsprings won't enter the new population.
"""
new_population = Population()
for chromosomes in parents:
# do crossover with probability self.crossover_rate
if random.random() < self.crossover_rate:
offsprings = self.pair_chromosomes(chromosomes)
else:
offsprings = chromosomes # [ch.__copy__() for ch in chromosomes] # todo: maybe redundant
for ch in offsprings:
new_population.add_chromosome(ch)
# if there are too many offsprings then stop adding them to population
if new_population.get_size() == pop_size:
return new_population