def select(self, sorted_chromosome_fitness, k):
if k >= len(sorted_chromosome_fitness) and self._unique:
AttributeError("Not enough alternatives in population")
total_fitness = sum(fitness
for _, fitness in sorted_chromosome_fitness)
selected = []
while len(selected) < k:
random_threshold = seeded_random.random() * total_fitness
acc = 0
for chromosome, fitness in sorted_chromosome_fitness:
acc += fitness
if acc > random_threshold and not (chromosome in selected
and self._unique):
selected.append(chromosome)
break
return selected
def _is_mutating(self):
return seeded_random.random() < self.mutation_rate
def _is_mutating(self):
return seeded_random.random() < self.mutation_rate
