def kill(population, mi, d):
overall = 0
temp_af = []
maxx = 0.0
max_i = 0
for i in range(len(population)):
# print("licze overall")
x = dekoder.decode(population[i])[0]
y = dekoder.decode(population[i])[1]
a = dekoder.decode(population[i])[2]
temp_af.append(math.exp(afunction.J(x, y, a, d)) ** 2)
overall += temp_af[i]
if maxx != max(maxx, temp_af[i]):
maxx = max(maxx, temp_af[i])
max_i = i
overall = round(overall, 4)
survivals = [population[max_i]]
for _ in range(mi - 1):
# print("wylosowano osobnika")
temp = overall
temp *= 10000
temp = round(temp)
rand = random.randint(0, temp - 1)
rand /= 10000
for i in range(len(population)):
if temp_af[i] <= rand:
rand -= temp_af[i]
else:
survivals.append(population[i])
break
return survivals
def first_population(sensors, mi, d):
population = []
done = False
for i in range(mi):
genes = []
gene_part = ''
for _ in range(sensors):
while True:
gene_part = ''
for _ in range((math.ceil(math.log2(dekoder.n())) + math.ceil(math.log2(dekoder.m())) + 2)):
rand = random.randint(0, 1)
gene_part += str(rand)
if not done:
tp = afunction.j_for_one(dekoder.decode(gene_part)[0][0], dekoder.decode(gene_part)[1][0], d)
else:
tp = [0, 0]
if not tp[1]:
break
genes.append(gene_part)
new_gene = ''
while genes:
new_gene += genes.pop()
s = SJ(d)
power = s.simple_J(new_gene)
print(i + 1, "/", mi, " genotypes created (power: ", power, ")")
if power >= 0.9:
done = True
population.append(new_gene)
print("first population created")
return population
def best_positions(population, d):
best_value = 0
tab = []
max_x = dekoder.decode(population[0])[0]
max_y = dekoder.decode(population[0])[1]
max_a = dekoder.decode(population[0])[2]
for i in population:
dek = dekoder.decode(i)
x = dek[0]
temp_x = x[:]
y = dek[1]
temp_y = y[:]
a = dek[2]
temp_a = a[:]
J = afunction.J(temp_x, temp_y, temp_a, d)
maxx = max(J[0], best_value)
if maxx != best_value:
best_value = max(maxx, best_value)
max_x = x
max_y = y
max_a = a
tab = J[1]
return max_x, max_y, max_a, tab
def best_v(population, d):
best_value = 0
for i in population:
x = dekoder.decode(i)[0]
y = dekoder.decode(i)[1]
a = dekoder.decode(i)[2]
best_value = max(afunction.J(x, y, a, d), best_value)
if best_value >= 0.9:
break
return best_value
def best_v(population, d):
sum = 0
best_value = 0
for i in population:
x = dekoder.decode(i)[0]
y = dekoder.decode(i)[1]
a = dekoder.decode(i)[2]
value = afunction.J(x, y, a, d)[0]
sum += value
best_value = max(value, best_value)
if best_value >= 0.9:
break
return best_value, sum / len(population)
def simple_J(self, element):
x = dekoder.decode(element)[0]
y = dekoder.decode(element)[1]
a = dekoder.decode(element)[2]
return afunction.J_return_forbidden(x, y, a, self.d)
