Return a randomly sampled n x n stochastic matrix with k nonzero
    entries for each row.

    Parameters
    ----------
    n : scalar(int)
        Number of states.

    k : scalar(int), optional(default=None)
        Number of nonzero entries in each row of the matrix. Set to n if
        not specified.

    sparse : bool, optional(default=False)
        Whether to generate the matrix in sparse matrix form.

    format : str, optional(default='csr')
        Sparse matrix format, str in {'bsr', 'csr', 'csc', 'coo', 'lil',
        'dia', 'dok'}. Relevant only when sparse=True.

    random_state : int or np.random.RandomState, optional
        Random seed (integer) or np.random.RandomState instance to set
        the initial state of the random number generator for
        reproducibility. If None, a randomly initialized RandomState is
        used.

    Returns
    -------
    P : numpy ndarray or scipy sparse matrix (float, ndim=2)
        Stochastic matrix.

    See also
    --------
    random_markov_chain : Return a random MarkovChain instance.

def random_stochastic_matrix(n, k=None, sparse=False, format='csr',
                             random_state=None):
    """
    Return a randomly sampled n x n stochastic matrix with k nonzero
    entries for each row.

    Parameters
    ----------
    n : scalar(int)
        Number of states.

    k : scalar(int), optional(default=None)
        Number of nonzero entries in each row of the matrix. Set to n if
        not specified.

    sparse : bool, optional(default=False)
        Whether to generate the matrix in sparse matrix form.

    format : str, optional(default='csr')
        Sparse matrix format, str in {'bsr', 'csr', 'csc', 'coo', 'lil',
        'dia', 'dok'}. Relevant only when sparse=True.

    random_state : int or np.random.RandomState, optional
        Random seed (integer) or np.random.RandomState instance to set
        the initial state of the random number generator for
        reproducibility. If None, a randomly initialized RandomState is
        used.

    Returns
    -------
    P : numpy ndarray or scipy sparse matrix (float, ndim=2)
        Stochastic matrix.

    See also
    --------
    random_markov_chain : Return a random MarkovChain instance.

    """
    P = _random_stochastic_matrix(m=n, n=n, k=k, sparse=sparse, format=format,
                                  random_state=random_state)
    return P