def mutateAddNeuron(self):
"""
Add a neuron at the location of a random gene.
This is done by disabling the original gene,
then adding a new node and connections between
the new node and the original gene nodes.
"""
# get one random gene
if self.genes:
innov = random.sample(self.genes, 1)[0]
else:
return
gene = self.genes[innov]
node1 = gene.source_neuron
node2 = gene.target_neuron
# make sure our nodes aren't two consecutive integers
if node1 + 1 > node2 - 1:
return
g = Gene()
g.copy(gene)
# create a new node
node = random.randint(node1 + 1, node2 - 1)
# make sure our node isn't the same as any existing nodes
if node in self.nodes:
return
# should be a hidden node
assert node >= 1 and node <= MAX_LAYER
# morph the gene into two genes and add the node
g1 = Gene()
g1.source_neuron = node1
g1.target_neuron = node
g1.weight = 1
g2 = Gene()
g2.source_neuron = node
g2.target_neuron = node2
g2.weight = gene.weight
self.nodes.add(node)
# disable the original gene, replace it with the new ones
g.enabled = False
self.genes[innov] = g
self.genes[max(gene_index) + 1] = g1
self.genes[max(gene_index) + 2] = g2
# add the new genes to the index
gene_index[max(gene_index) + 1] = g1
gene_index[max(gene_index) + 1] = g2
def addGene(self, node1, node2):
"""
Add a randomly weighted gene between two nodes.
Args:
node1: the first node
node2: the second node
"""
# connect the two valid, unconnected nodes
g = Gene()
g.source_neuron = node1
g.target_neuron = node2
g.weight = random.random() * 4 - 2
# check to see if the gene already exists in the index
for index, gene in gene_index.items():
if gene.source_neuron == node1 and gene.target_neuron == node2:
# if found, use that same innovation number
self.genes[index] = g
return
# if it's not in the index, add it and record in the index
if gene_index:
self.genes[max(gene_index) + 1] = g
gene_index[max(gene_index) + 1] = g
else:
gene_index[0] = g
self.genes[0] = g
