def reproduce(self, idxs, to_idxs, consume_health=True):
unique_idxs = np.unique(idxs)
to_idxs = to_idxs[:len(unique_idxs)]
if len(unique_idxs) == 0:
return 0
parents = self[unique_idxs]
new_chromosomes = VectorAgentChromosome(len(unique_idxs))
new_chromosomes[:] = self.chromosomes[unique_idxs]
new_chromosomes.mutate(to_idxs)
self.develop_from_chromosomes(new_chromosomes, to_idxs)
self.x[to_idxs] = parents.x
self.y[to_idxs] = parents.y
self.rotate(np.random.random(len(unique_idxs)) * (math.pi*2), to_idxs)
# отодвинуть потомство, чтобы не топтаться по нему
self.x[to_idxs] += self.ax[to_idxs] * settings.ATTACK_RADIUS
self.y[to_idxs] += self.ay[to_idxs] * settings.ATTACK_RADIUS
self.gencount[to_idxs] = parents.gencount + 1
self.health[to_idxs] = parents.birth_health
if consume_health:
self.consume_energy(parents.birth_health / settings.BIRTH_KPD, unique_idxs)
return len(unique_idxs)
def random(cls, number):
population = cls(number)
cromosomes = VectorAgentChromosome.random(number)
agents = VectorAgent.from_chromosomes(cromosomes)
population._agents = agents
return population
def make_new_random(self, to_random_num, idxs):
assert to_random_num >= 0
new_chromosomes = VectorAgentChromosome.random(to_random_num)
self.replace_from_chromosomes(idxs, new_chromosomes)
self._agents.health[idxs] = MIN_HEALTH
self.env.add_new_agents(idxs)