o a failure to separate eigenvalues, usually because
           of poor conditioning.
        3. If eigenvalue sorting was requested, roundoff errors caused the
           leading eigenvalues to no longer satisfy the sorting condition.

    See Also
    --------
    rsf2csf : Convert real Schur form to complex Schur form

    Examples
    --------
    >>> import numpy as np
    >>> from scipy.linalg import schur, eigvals
    >>> A = np.array([[0, 2, 2], [0, 1, 2], [1, 0, 1]])
    >>> T, Z = schur(A)
    >>> T
    array([[ 2.65896708,  1.42440458, -1.92933439],
           [ 0.        , -0.32948354, -0.49063704],
           [ 0.        ,  1.31178921, -0.32948354]])
    >>> Z
    array([[0.72711591, -0.60156188, 0.33079564],
           [0.52839428, 0.79801892, 0.28976765],
           [0.43829436, 0.03590414, -0.89811411]])

    >>> T2, Z2 = schur(A, output='complex')
    >>> T2
    array([[ 2.65896708, -1.22839825+1.32378589j,  0.42590089+1.51937378j],
           [ 0.        , -0.32948354+0.80225456j, -0.59877807+0.56192146j],
           [ 0.        ,  0.                    , -0.32948354-0.80225456j]])
    >>> eigvals(T2)
    array([2.65896708, -0.32948354+0.80225456j, -0.32948354-0.80225456j])

    An arbitrary custom eig-sorting condition, having positive imaginary part,
    which is satisfied by only one eigenvalue

    >>> T3, Z3, sdim = schur(A, output='complex', sort=lambda x: x.imag > 0)
    >>> sdim
    1

    )