statistics.py 文件源码

def sample_scalar(self, shape, a):
        AMAX = 30
        if a > AMAX:
            return np.random.poisson(a, shape)
        k = 1
        K = np.full(shape, k)
        s = a/np.expm1(a)
        S = s
        U = np.random.random(shape)
        new = S < U
        while np.any(new):
            k += 1
            K[new] = k
            s = s*a/float(k)
            S = S + s
            new = S < U
        return K