def METHOD_NAME(sample):
    """ Find data points on the convex hull of a supplied data set
    Args:
        sample: data points as column vectors n x d
                    n - number samples
                    d - data dimension (should be two)
    Returns:
        a k x d matrix containint the convex hull data points
    """
    link = lambda a, b: np.concatenate((a, b[1:]))
    edge = lambda a, b: np.concatenate(([a], [b]))
    def dome(sample, base):
        h, t = base
        dists = np.dot(sample - h, np.dot(((0, -1), (1, 0)), (t - h)))
        outer = np.repeat(sample, dists > 0, axis=0)
        if len(outer):
            pivot = sample[np.argmax(dists)]
            return link(dome(outer, edge(h, pivot)),
                dome(outer, edge(pivot, t)))
        else:
            return base
    if len(sample) > 2:
        axis = sample[:, 0]
        base = np.take(sample, [np.argmin(axis), np.argmax(axis)], axis=0)
        return link(dome(sample, base),
            dome(sample, base[::-1]))
    else:
        return sample