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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 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)