def _create_random_individual(self):
random_scores = np.random.rand(len(self._sentences))
scored_sentences = zip(self._sentences, random_scores)
sorted_sentences = sorted(scored_sentences,
key=lambda tup: tup[1],
reverse=True)
return greedy_optimizer(sorted_sentences, self._max_length)
def _reproduction(self,
population_winners,
population_size,
reproduction_rate="auto"):
if reproduction_rate == "auto":
reproduction_rate = self._reproduction_rate
parents = []
number_families = int(reproduction_rate * population_size)
for i in xrange(number_families):
parents.append(random.sample(population_winners, 2))
children = []
for father, mother in parents:
genetic_pool = [s for s in self._sentences if s in father]
genetic_pool.extend([s for s in self._sentences if s in mother])
random_scores = np.random.rand(len(genetic_pool))
scored_sentences = zip(self._sentences, random_scores)
sorted_sentences = sorted(scored_sentences,
key=lambda tup: tup[1],
reverse=True)
child = greedy_optimizer(sorted_sentences, self._max_length)
children.append(child)
return children
