def create_offspring(self, P, parent1, parent2):
offspring = Individual(P, parent1.eco_type)
offspring.crossover(parent1.genome, parent2.genome)
num_mutations = self.poisson_dist(10**((-1) * P.mutation_rate),
offspring.genome_size())
offspring.mutation(
num_mutations
) # check to mutate the offspring's genome (small chance of mutation)
return offspring
def update_generation(self):
self.individuals.sort(key=operator.attrgetter('fitness'))
parents = self.individuals[self.size - self.keep:]
distribution = self.__selection_distribution(parents)
for i in range(0, self.keep):
parent1 = self.__select_parent(distribution, parents)
parent2 = self.__select_parent(distribution, parents)
child = Individual.crossover(parent1, parent2)
child.mutate()
self.individuals[i] = child
from individual import Individual
print("an individual")
myInd = Individual()
print(myInd)
print("mutated")
myInd.mutate()
print(myInd)
print("another individual")
myInd2 = Individual()
print(myInd2)
print("Offspring")
offspring = myInd.crossover(myInd2)
print(offspring)
offspring = myInd.crossover(myInd2)
print(offspring)
