def rand(self, n=1, rng=None):
    '[summary]\n        Generate ``n`` points uniformly at random inside the :py:class:`BoxWindow`.\n\n        Args:\n            n (int, optional): [description]. Defaults to 1.\n            rng ([type], optional): [description]. Defaults to None.\n\n        Returns:\n            Randomly n elements that belong to the box\n        '
    rng = get_random_number_generator(rng)
    L = np.ones((n, self.__len__()))
    for i in range(n):
        for j in range(self.__len__()):
            x = rng.random()
            L[i][j] = (((1 - x) * self.bounds[j][0]) + (x * self.bounds[j][1]))
    return L
[summary]
Generate ``n`` points uniformly at random inside the :py:class:`BoxWindow`.

Args:
    n (int, optional): [description]. Defaults to 1.
    rng ([type], optional): [description]. Defaults to None.

Returns:
    Randomly n elements that belong to the box
def rand(self, n=1, rng=None):
    '[summary]\n        Generate ``n`` points uniformly at random inside the :py:class:`BoxWindow`.\n\n        Args:\n            n (int, optional): [description]. Defaults to 1.\n            rng ([type], optional): [description]. Defaults to None.\n\n        Returns:\n            Randomly n elements that belong to the box\n        '
    rng = get_random_number_generator(rng)
    L = np.ones((n, self.__len__()))
    for i in range(n):
        for j in range(self.__len__()):
            x = rng.random()
            L[i][j] = (((1 - x) * self.bounds[j][0]) + (x * self.bounds[j][1]))
    return L