### Navigation

- index
- modules |
- next |
- previous |
- SciPy v0.7 Reference Guide (DRAFT) »
- Linear algebra (`scipy.linalg`) »

# scipy.linalg.schur

`scipy.linalg.``schur`(a, output='real', lwork=None, overwrite_a=0)

  Compute Schur decomposition of a matrix.

  The Schur decomposition is

  > A = Z T Z^H

  where Z is unitary and T is either upper-triangular, or for real Schur decomposition (output=’real’), quasi-upper triangular. In the quasi-triangular form, 2x2 blocks describing complex-valued eigenvalue pairs may extrude from the diagonal.

  Parameters: | a : array, shape (M, M) Matrix to decompose output : {‘real’, ‘complex’} Construct the real or complex Schur decomposition (for real matrices). lwork : integer Work array size. If None or -1, it is automatically computed. overwrite_a : boolean Whether to overwrite data in a (may improve performance)
  Returns: | T : array, shape (M, M) Schur form of A. It is real-valued for the real Schur decomposition. Z : array, shape (M, M) An unitary Schur transformation matrix for A. It is real-valued for the real Schur decomposition.

  See also

  `rsf2csf`
    Convert real Schur form to complex Schur form

### Navigation

- index
- modules |
- next |
- previous |
- SciPy v0.7 Reference Guide (DRAFT) »
- Linear algebra (`scipy.linalg`) »