functions = get_functions()
constants = get_constants(lower=-10, upper=10, bit=True)
ppl.createPopulation(functions=functions,
constants=constants,
n_ind=n_ind,
n_gene=n_gene,
n_register=n_register)
eval_function = lambda x: x[0] ^ x[1] # xor
ppl.excute_all(inputs, eval_function)
# revolution
p = ProgressBar(0, revolution)
for i in range(revolution):
#print("revolution: ", i)
p.update(i + 1)
elite = Selection.elite(ppl, elite_size)
new_p = copy.deepcopy(elite)
for j in range(n_ind - elite_size):
parent = Selection.tournament(ppl, tourn_size)
elite.append(parent)
child = Crossover.randomPoints(elite, cross_rate)
child = Mutation.mutation(child, mutate_rate, n_register, functions,
constants)
new_p.append(child)
ppl.setPopulation(new_p)
ppl.excute_all(inputs, eval_function)
if ((i % 100) == 0):
ppl.result()
ppl.result()
ppl.write_result(path)
p.finish()
func = get_functions()
registers = get_registers()
constants = get_constants(bit=True)
n_register = 10
ppl.createPopulation(functions=func,
constants=constants,
n_ind=5,
n_gene=5,
n_register=n_register)
eval_function = lambda x: x[0] ^ x[1] # xor
ppl.excute_all(inputs, eval_function)
elite_size = 3
parents = Selection.elite(ppl, elite_size)
tourn_size = 3
n_ind = 5
for i in range(n_ind):
parent = Selection.tournament(ppl, tourn_size)
parents.append(parent)
parent.show()
cross_rate = 0.7
print("..crossover onePoint")
child = Crossover.onePoint(parents, cross_rate)
child.show()
print("..Done!")
print("..crossover twoPoints")
