def getIndividuals(creator, initChrom, n, chromosome):
''''''
scalar = 1000000
num_rates = 9
num_q = 4
individuals = []
# Hardcode the IBMQ rates
individual = initChrom(chromosome)
b = '0' + str(int(len(individual)/num_rates)) + 'b'
individual = creator(individual)
individuals.append(individual)
# Randomize the remaining rates
for i in range(0, n-1):
decodedRates = decode(initChrom(chromosome), scalar, num_rates, num_q)
rc0 = format(abs(int((decodedRates[0] + np.random.normal(0, 0.00005, 1))*scalar)), b)
rc1 = format(abs(int((decodedRates[1] + np.random.normal(0, 0.00005, 1))*scalar)), b)
rc2 = format(abs(int((decodedRates[2] + np.random.normal(0, 0.00005, 1))*scalar)), b)
rc3 = format(abs(int((decodedRates[3] + np.random.normal(0, 0.00005, 1))*scalar)), b)
rc4 = format(abs(int((decodedRates[4] + np.random.normal(0, 0.005, 1))*scalar)), b)
rc5 = format(abs(int((decodedRates[5] + np.random.normal(0, 0.005, 1))*scalar)), b)
rc6 = format(abs(int((decodedRates[6] + np.random.normal(0, 0.005, 1))*scalar)), b)
rc7 = format(abs(int((decodedRates[7] + np.random.normal(0, 0.005, 1))*scalar)), b)
rc8 = format(abs(int((decodedRates[8] + np.random.normal(0, 0.005, 1))*scalar)), b)
randchrom = rc0 + rc1 + rc2 + rc3 + rc4 + rc5 + rc6 + rc7 + rc8
individual = initChrom(randchrom)
individual = creator(individual)
individuals.append(individual)
return individuals
def getIndividuals(creator, initChrom, n, chromosome):
''''''
scalar = 1000000
num_rates = 38
num_q = 14
individuals = []
# Hardcode the IBMQ rates
individual = initChrom(chromosome)
b = '0' + str(int(len(individual)/num_rates)) + 'b'
individual = creator(individual)
individuals.append(individual)
# Randomize the remaining rates
for i in range(0, n-1):
decodedRates = decode(initChrom(chromosome), scalar, num_rates, num_q)
rc0 = format(abs(int((decodedRates[0] + np.random.normal(0, 0.0002, 1))*scalar)), b)
rc1 = format(abs(int((decodedRates[1] + np.random.normal(0, 0.0002, 1))*scalar)), b)
rc2 = format(abs(int((decodedRates[2] + np.random.normal(0, 0.0002, 1))*scalar)), b)
rc3 = format(abs(int((decodedRates[3] + np.random.normal(0, 0.0002, 1))*scalar)), b)
rc4 = format(abs(int((decodedRates[4] + np.random.normal(0, 0.0002, 1))*scalar)), b)
rc5 = format(abs(int((decodedRates[5] + np.random.normal(0, 0.0002, 1))*scalar)), b)
rc6 = format(abs(int((decodedRates[6] + np.random.normal(0, 0.0002, 1))*scalar)), b)
rc7 = format(abs(int((decodedRates[7] + np.random.normal(0, 0.0002, 1))*scalar)), b)
rc8 = format(abs(int((decodedRates[8] + np.random.normal(0, 0.0002, 1))*scalar)), b)
rc9 = format(abs(int((decodedRates[9] + np.random.normal(0, 0.0002, 1))*scalar)), b)
rc10 = format(abs(int((decodedRates[10] + np.random.normal(0, 0.0002, 1))*scalar)), b)
rc11 = format(abs(int((decodedRates[11] + np.random.normal(0, 0.0002, 1))*scalar)), b)
rc12 = format(abs(int((decodedRates[12] + np.random.normal(0, 0.0002, 1))*scalar)), b)
rc13 = format(abs(int((decodedRates[13] + np.random.normal(0, 0.0002, 1))*scalar)), b)
rc14 = format(abs(int((decodedRates[14] + np.random.normal(0, 0.005, 1))*scalar)), b)
rc15 = format(abs(int((decodedRates[15] + np.random.normal(0, 0.005, 1))*scalar)), b)
rc16 = format(abs(int((decodedRates[16] + np.random.normal(0, 0.005, 1))*scalar)), b)
rc17 = format(abs(int((decodedRates[17] + np.random.normal(0, 0.005, 1))*scalar)), b)
rc18 = format(abs(int((decodedRates[18] + np.random.normal(0, 0.005, 1))*scalar)), b)
rc19 = format(abs(int((decodedRates[19] + np.random.normal(0, 0.005, 1))*scalar)), b)
rc20 = format(abs(int((decodedRates[20] + np.random.normal(0, 0.005, 1))*scalar)), b)
rc21 = format(abs(int((decodedRates[21] + np.random.normal(0, 0.005, 1))*scalar)), b)
rc22 = format(abs(int((decodedRates[22] + np.random.normal(0, 0.005, 1))*scalar)), b)
rc23 = format(abs(int((decodedRates[23] + np.random.normal(0, 0.005, 1))*scalar)), b)
rc24 = format(abs(int((decodedRates[24] + np.random.normal(0, 0.005, 1))*scalar)), b)
rc25 = format(abs(int((decodedRates[25] + np.random.normal(0, 0.0.005, 1))*scalar)), b)
rc26 = format(abs(int((decodedRates[26] + np.random.normal(0, 0.005, 1))*scalar)), b)
rc27 = format(abs(int((decodedRates[27] + np.random.normal(0, 0.005, 1))*scalar)), b)
rc28 = format(abs(int((decodedRates[28] + np.random.normal(0, 0.005, 1))*scalar)), b)
rc29 = format(abs(int((decodedRates[29] + np.random.normal(0, 0.005, 1))*scalar)), b)
rc30 = format(abs(int((decodedRates[30] + np.random.normal(0, 0.005, 1))*scalar)), b)
rc31 = format(abs(int((decodedRates[31] + np.random.normal(0, 0.005, 1))*scalar)), b)
rc32 = format(abs(int((decodedRates[32] + np.random.normal(0, 0.005, 1))*scalar)), b)
rc33 = format(abs(int((decodedRates[33] + np.random.normal(0, 0.005, 1))*scalar)), b)
rc34 = format(abs(int((decodedRates[34] + np.random.normal(0, 0.005, 1))*scalar)), b)
rc35 = format(abs(int((decodedRates[35] + np.random.normal(0, 0.005, 1))*scalar)), b)
rc36 = format(abs(int((decodedRates[36] + np.random.normal(0, 0.005, 1))*scalar)), b)
rc37 = format(abs(int((decodedRates[37] + np.random.normal(0, 0.005, 1))*scalar)), b)
randchrom = rc0 + rc1 + rc2 + rc3 + rc4 + rc5 + rc6 + rc7 + rc8 + rc9 + rc10 + rc11 + rc12 + rc13 + rc14 + rc15 + rc16 + rc17 + rc18 + rc19 + rc20 + rc21 + rc22 + rc23 + rc24 + rc25 + rc26 + rc27 + rc28 + rc29 + rc30 + rc31 + rc32 + rc33 + rc34 + rc35 + rc36 + rc37
individual = initChrom(randchrom)
individual = creator(individual)
individuals.append(individual)
return individuals
def generate(creator, size, pmin, pmax, position=None):
"""generate a particle
creator: creator inheriting deap.base.Fitness
size: number of dimensions
pmin, pmax: lower & upper bound of the position of the particle
position: initial position of the particle"""
if position is None:
part = creator(np.random.uniform(pmin, pmax, size))
else:
part = creator(position)
part.pmin = pmin
part.pmax = pmax
return part
def load_shared_individuals(creator, n):
individuals = []
for i in range(len(best_scored)):
individual = best_scored[i]
individual = creator(individual)
individuals.append(individual)
return individuals
def load_individuals(creator, n):
individuals = []
lastPop = loadLastPopulation(curID[0])
for i in range(len(lastPop)):
individual = lastPop[i]
individual = creator(individual)
individuals.append(individual)
return individuals
def load_individuals(X, y, maj_class, min_class, creator, n):
"""
"""
maj_samples = X[y == maj_class]
min_samples = X[y == min_class]
individuals = []
for i in range(n):
random_maj = maj_samples[random.randint(0, maj_samples.shape[0] - 1)]
random_min = min_samples[random.randint(0, min_samples.shape[0] - 1)]
individual = np.asarray(np.concatenate((random_maj, random_min)))
individual = creator(individual)
individuals.append(individual)
return individuals
