def mutator(self):
def mut(random, cand, args):
maybe_mutate = lambda v, func: func(v) if random.random() < args['mutation_rate'] else v
for gene in cand:
gene.function = maybe_mutate(gene.function, self.random_func)
gene.inputs = [maybe_mutate(c, self.random_edge) for c in gene.inputs]
gene.vars = [maybe_mutate(c, self.random_var) for c in gene.vars]
#gene.vars = [maybe_noise(c, randomize_var) for c in gene.vars] #TODO:get right noise
return cand
return mutator(mut)
def mutator(self):
def mutate_edge(v):
return (v + random.randint(1, self.levelsback)) % self.levelsback
def mutate_func(v):
l = self._function_count
return (v + random.randint(1, l)) % l
def mut(random, cand, args):
maybe_mutate = lambda v, func: func(v) if random.random() < args['mutation_rate'] else v
matrix = []
for col in cand:
node = [maybe_mutate(col[0], mutate_func)]
node += [maybe_mutate(c, mutate_edge) for c in col[1:1+self.arity]]
matrix.append(node)
return matrix
return mutator(mut)
