Block-diagonal Schur decomposition.
Real matrix to decompose.
If None (default), use 1/sqrt(eps), which is approximately 1e8.
Block sorting; see below.
Block-diagonal Schur decomposition of a
.
Similarity transform relating a
and amodal
.
Array of Schur block sizes.
Notes
If sort
is None, the blocks are not sorted.
If sort
is ‘continuous’, the blocks are sorted according to associated eigenvalues. The ordering is first by real part of eigenvalue, in descending order, then by absolute value of imaginary part of eigenvalue, also in decreasing order.
If sort
is ‘discrete’, the blocks are sorted as for ‘continuous’, but applied to log of eigenvalues (i.e., continuous-equivalent eigenvalues).
Examples
>>> Gs = ct.tf2ss([1], [1, 3, 2]) >>> amodal, tmodal, blksizes = ct.bdschur(Gs.A) >>> amodal array([[-2., 0.], [ 0., -1.]])
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