

def getQuery(self, resource):
    alpha = 2
    n = resource.get('n')
    key_list = []
    for i in range(n):
        key_list.append(('Xsum_' + str(i)))
        key_list.append(('T_' + str(i)))
    key_value_dict = resource.get_many(key_list)
    sumX = []
    T = []
    for i in range(n):
        sumX.append(key_value_dict[('Xsum_' + str(i))])
        T.append(key_value_dict[('T_' + str(i))])
    theta = numpy.zeros(n)
    for i in range(n):
        theta[i] = numpy.random.beta(max(1, ((1 + sumX[i]) / alpha)), max(1, (((1 + T[i]) - sumX[i]) / alpha)))
    index = numpy.argmax(theta)
    alt_index = numpy.random.choice(n)
    while (alt_index == index):
        alt_index = numpy.random.choice(n)
    random_fork = numpy.random.choice(2)
    if (random_fork == 0):
        return (index, alt_index, index)
    else:
        return (alt_index, index, index)

dataset/ETHPy150Open nextml/NEXT/next/apps/DuelingBanditsPureExploration/algs/BR_Thompson_b2/BR_Thompson_b2.py BR_Thompson_b2.getQuery/original