

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(1.0, T[self])) for i in range(n)]
    prec = [numpy.sqrt((1.0 / max(1.0, t))) for t in T]
    return (mu, prec)

dataset/ETHPy150Open nextml/NEXT/next/apps/TupleBanditsPureExploration/algs/RandomSampling/RandomSampling.py RandomSampling.predict/VarMisuse@58/79 `i`->`self`