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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 mfpt_between_sets(T, target, origin, mu=None):
 """Compute mean-first-passage time between subsets of state space. Parameters T : scipy.sparse matrix Transition matrix. target : int or list of int Set of target states. origin : int or list of int Set of starting states. mu : (M,) ndarray (optional) The stationary distribution of the transition matrix T. Returns ------- tXY : float Mean first passage time between set X and Y. Notes ----- The mean first passage time :math:`\mathbf{E}_X[T_Y]` is the expected hitting time of one state :math:`y` in :math:`Y` when starting in a state :math:`x` in :math:`X`: .. math :: \mathbb{E}_X[T_Y] = \sum_{x \in X} \frac{\mu_x \mathbb{E}_x[T_Y]}{\sum_{z \in X} \mu_z} """

    if mu is None:
        mu = stationary_distribution(T)

    """Stationary distribution restriced on starting set X"""
    nuX = mu[origin]
    muX = nuX / np.sum(nuX)

    """Mean first-passage time to Y (for all possible starting states)"""
    tY = mfpt(T, target)

    """Mean first-passage time from X to Y"""
    tXY = np.dot(muX, tY[origin])
    return tXY