r"""Sensitivity matrix of a selected eigenvector element.

    Parameters
    ----------
    T : (M, M) ndarray
        Transition matrix (stochastic matrix).
    k : int
        Eigenvector index
    j : int
        Element index
    right : bool
        If True compute for right eigenvector, otherwise compute for left eigenvector.

    Returns
    -------
    S : (M, M) ndarray
        Sensitivity matrix for the j-th element of the k-th eigenvector.

def eigenvector_sensitivity(T, k, j, right=True):
    r"""Sensitivity matrix of a selected eigenvector element.

    Parameters
    ----------
    T : (M, M) ndarray
        Transition matrix (stochastic matrix).
    k : int
        Eigenvector index
    j : int
        Element index
    right : bool
        If True compute for right eigenvector, otherwise compute for left eigenvector.

    Returns
    -------
    S : (M, M) ndarray
        Sensitivity matrix for the j-th element of the k-th eigenvector.

    """
    T = _types.ensure_ndarray_or_sparse(T, ndim=2, uniform=True, kind='numeric')
    if _issparse(T):
        _showSparseConversionWarning()
        eigenvector_sensitivity(T.todense(), k, j, right=right)
    else:
        return dense.sensitivity.eigenvector_sensitivity(T, k, j, right=right)