def test_init_1(self):
print("\n\ntest_init_1.1")
generation = Generation()
genome = Genome(generation=generation, input_nodes=2, output_nodes=2)
for con in genome.connections():
print(con)
for node in genome.nodes():
print(node)
print('-' * 40)
for node in generation.nodes():
print(node)
print('-' * 60)
viz.construct(genome, 'first')
print("\n\ntest_init_1.2")
genome_1 = Genome(generation, 2, 2)
for con in genome_1.connections():
print(con)
for node in genome_1.nodes():
print(node)
print('-' * 40)
for node in generation.nodes():
print(node)
viz.construct(genome_1, 'second')
print('-' * 20 + 'Mutations')
for mutation in generation.mutations():
print(mutation)
def produce_offspring(generation, genome_1: Genome,
genome_2: Genome) -> Genome:
# TODO: exclude excess genes of parent 2 if parent 1 is fitter
offspring = Genome(generation,
genome_1.input_nodes(),
genome_1.output_nodes(),
connections=False)
for node in genome_1.nodes() + genome_2.nodes():
if node not in offspring.nodes():
offspring.nodes().append(node.copy_without_connections())
# all common genes are appended randomly from either parent
for con in genome_1.connections():
if con in genome_2.connections():
index = genome_2.connections().index(con)
gene = _pick_random_gene(con, genome_2.connections()[index])
_append_con(gene, offspring)
for con in genome_1.connections() + genome_2.connections():
if (con in offspring.connections()) and (con.status()
== Status.DISABLED):
for in_con in offspring.connections():
if in_con == con and in_con.status() == Status.ENABLED:
if _disable_chance():
in_con.disable()
break
elif con not in offspring.connections():
if (con.status() == Status.DISABLED) and (not _disable_chance()):
con.enable()
_append_con(con, offspring)
return offspring
def test_add_node(self):
print('-' * 20 + 'test_add_node\nBEFORE 0')
generation = Generation()
genome = Genome(generation, 2, 1)
for con in genome.connections():
print(con)
for node in genome.nodes():
print(node)
viz.construct(genome, 'before_0')
genome._add_node()
genome._add_node()
genome._add_node()
for node in generation.nodes():
print(node)
print('\nAFTER 0 \n')
for con in genome.connections():
print(con)
print('-' * 40)
for node in genome.nodes():
print(node)
viz.construct(genome, 'after_0')
print('\n\ntest_add_node\nBEFORE 1')
genome_1 = Genome(generation, 1, 1)
viz.construct(genome_1, 'before_1')
for con in genome_1.connections():
print(con)
for node in genome_1.nodes():
print(node)
genome_1._add_node()
genome_1._add_node()
genome_1._add_node()
genome_1._add_node()
print('\nAFTER 0 \n')
for con in genome_1.connections():
print(con)
for node in genome_1.nodes():
print(node)
viz.construct(genome_1, 'after_1')
def construct(genome: Genome, file_name):
dot = Digraph()
for node in genome.nodes():
dot.node(str(node.id()), str(node.id()))
for con in genome.connections():
if con.status() == Status.ENABLED:
dot.edge(str(con.input_node().id()), str(con.output_node().id()))
dot.render(f'/Users/max/IdeaProjects/neat/network_pictures/{file_name}',
view=True)
def produce_offspring(generation: Generation, genome_1: Genome, genome_2: Genome) -> Genome:
offspring = Genome(generation, genome_1.input_nodes(), genome_1.output_nodes(), connections=False)
for node in genome_1.nodes() + genome_2.nodes():
if node not in offspring.nodes():
offspring.nodes().append(node.copy_without_connections())
for con in genome_1.connections() + genome_2.connections():
if (con in offspring.connections()) and (con.status() == Status.DISABLED):
for i, in_con in enumerate(offspring.connections()):
if in_con == con and in_con.status() == Status.ENABLED:
if _disable_chance():
in_con.disable()
break
elif con not in offspring.connections():
if (con.status() == Status.DISABLED) and (not _disable_chance()):
con.enable()
offspring.connections().append(con)
return offspring