# scipy.linalg.rsf2csf

scipy.linalg.rsf2csf(T, Z, check_finite=True)

  Convert real Schur form to complex Schur form.

  Convert a quasi-diagonal real-valued Schur form to the upper-triangular complex-valued Schur form.

  Parameters
    T(M, M) array_like

      Real Schur form of the original array

    Z(M, M) array_like

      Schur transformation matrix

    check_finite bool, optional

      Whether to check that the input arrays contain only finite numbers. Disabling may give a performance gain, but may result in problems (crashes, non-termination) if the inputs do contain infinities or NaNs.

  Returns
    T(M, M) ndarray

      Complex Schur form of the original array

    Z(M, M) ndarray

      Schur transformation matrix corresponding to the complex form

  See also

  `schur`

    Schur decomposition of an array

  Examples

      >>> from scipy.linalg import schur, rsf2csf
      >>> 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 = rsf2csf(T, Z)
      >>> T2
      array([[2.65896708+0.j, -1.64592781+0.743164187j, -1.21516887+1.00660462j],
             [0.+0.j , -0.32948354+8.02254558e-01j, -0.82115218-2.77555756e-17j],
             [0.+0.j , 0.+0.j, -0.32948354-0.802254558j]])
      >>> Z2
      array([[0.72711591+0.j,  0.28220393-0.31385693j,  0.51319638-0.17258824j],
             [0.52839428+0.j,  0.24720268+0.41635578j, -0.68079517-0.15118243j],
             [0.43829436+0.j, -0.76618703+0.01873251j, -0.03063006+0.46857912j]])

scipy.linalg.schur scipy.linalg.hessenberg