clt3d.py 文件源码

def gen_x_draws(k):
    """
    Returns a flat array containing k independent draws from the
    distribution of X, the underlying random variable.  This distribution is
    itself a convex combination of three beta distributions.
    """
    bdraws = beta_dist.rvs((3, k))
    # == Transform rows, so each represents a different distribution == #
    bdraws[0, :] -= 0.5
    bdraws[1, :] += 0.6
    bdraws[2, :] -= 1.1
    # == Set X[i] = bdraws[j, i], where j is a random draw from {0, 1, 2} == #
    js = np.random.random_integers(0, 2, size=k)
    X = bdraws[js, np.arange(k)]
    # == Rescale, so that the random variable is zero mean == #
    m, sigma = X.mean(), X.std()
    return (X - m) / sigma