def take_step(self, current, step_size):
position = Citizen()
for i in range(Citizen.P_SIZE):
minimum = min(
[self.bounds[i][0],
current.get_value(i) - step_size[i]])
maximum = max(
[self.bounds[i][1],
current.get_value(i) + step_size[i]])
value = rand_bound(minimum, maximum)
position.set_value(i, value)
return position
def generate_sample(self):
sample = Citizen()
for i in range(Citizen.P_SIZE):
aux = rand_bound(self.means[i], self.stdevs[i])
sample.set_value(i, aux)
return sample
def random_neighbor(self, params=[]):
mutant = Citizen(params)
pos = randint_bound(Citizen.P_SIZE)
mutant.set_value(pos)
return mutant