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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _get_mixed_actions(tableaux, bases):
 """ From `tableaux` and `bases`, extract non-slack basic variables and return a tuple of the corresponding, normalized mixed actions. Parameters tableaux : tuple(ndarray(float, ndim=2)) Tuple of two arrays containing the tableaux, of shape (n, m+n+1) and (m, m+n+1), respectively. bases : tuple(ndarray(int, ndim=1)) Tuple of two arrays containing the bases, of shape (n,) and (m,), respectively. Returns ------- tuple(ndarray(float, ndim=1)) Tuple of mixed actions as given by the non-slack basic variables in the tableaux. """

    nums_actions = tableaux[1].shape[0], tableaux[0].shape[0]
    num = nums_actions[0] + nums_actions[1]
    out = np.zeros(num)

    for pl, (start, stop) in enumerate(zip((0, nums_actions[0]),
                                           (nums_actions[0], num))):
        sum_ = 0.
        for i in range(nums_actions[1-pl]):
            k = bases[pl][i]
            if start <= k < stop:
                out[k] = tableaux[pl][i, -1]
                sum_ += tableaux[pl][i, -1]
        if sum_ != 0:
            out[start:stop] /= sum_

    return out[:nums_actions[0]], out[nums_actions[0]:]