def select_cluster_combinations(
self, cluster1: Cluster, cluster2: Cluster, genome_count: int
) -> List[Tuple[StorageGenome]]:
"""
:param cluster1: Cluster to choose 1
:param cluster2: Cluster to choose 2
:param genome_count: int number of seats which should be filled
:return: List[Tuple[StorageGenome]] combination from given cluster
"""
genomes1 = self.get_genomes_in_cluster(cluster1.cluster_id)
genomes2 = self.get_genomes_in_cluster(cluster2.cluster_id)
g1 = weighted_choice_range(genomes1, genome_count)
g2 = weighted_choice_range(genomes2, genome_count)
return list(zip(g1, g2))
def select_genomes_for_breeding(self, breeding_percentage: float) -> List[Tuple[StorageGenome, StorageGenome]]:
"""
Selects genomes for breeding currently best two from all Clusters
:type breeding_percentage: float
:return: tuple(Storage)
"""
result = []
for cluster in self.cluster_repository.get_current_clusters():
genome_one = self.get_genomes_in_cluster(cluster.cluster_id)
genome_two = genome_one
seats_to_mutation = int(cluster.offspring * breeding_percentage)
result.extend(
list(
zip(
weighted_choice_range(genome_one, seats_to_mutation),
weighted_choice_range(genome_two, seats_to_mutation),
)
)
)
return result
def select_genomes_for_mutation(self, mutation_percentage: float) -> List[StorageGenome]:
"""
Selects genome for mutation currently the best from all Clusters
:param mutation_percentage: float
:return: StorageGenome the most fit
"""
result = []
for cluster in self.cluster_repository.get_current_clusters():
step = self.get_genomes_in_cluster(cluster.cluster_id)
seats_to_mutation = int(cluster.offspring * mutation_percentage)
result.extend(weighted_choice_range(step, seats_to_mutation))
return result
