def predict(self,resource):
    n = resource.get('n')
    T = resource.get('num_pulls_vec')
    wins_vec = resource.get('running_wins_vec')

    mu = [ 1.0*wins_vec[i]/max(1.,T[i]) for i in range(n)]
    prec = [ numpy.sqrt(1.0/max(1.,t)) for t in T]
    
    return mu,prec
dataset/ETHPy150Open nextml/NEXT/next/apps/TupleBanditsPureExploration/algs/RandomSampling/RandomSampling.py/RandomSampling.predict/original