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