status: skipped
duration: 0.012s
Captured stdout call

A [[ 0.00000000e+00  0.00000000e+00  6.03603475e+03 -0.00000000e+00
  -2.12132034e+00 -0.00000000e+00]
 [ 0.00000000e+00  0.00000000e+00 -2.13162821e-14 -2.12132034e+00
  -0.00000000e+00 -8.39206242e+02]
 [ 0.00000000e+00  0.00000000e+00 -3.14159265e+01 -0.00000000e+00
  -1.50000000e+00 -0.00000000e+00]
 [ 0.00000000e+00  2.12132034e+00  0.00000000e+00  0.00000000e+00
   0.00000000e+00  6.03603475e+03]
 [ 2.12132034e+00  0.00000000e+00  8.39206242e+02  0.00000000e+00
   0.00000000e+00 -2.13162821e-14]
 [ 0.00000000e+00  1.50000000e+00  0.00000000e+00  0.00000000e+00
   0.00000000e+00 -3.14159265e+01]]
B [[-12124.02697577]
 [     0.        ]
 [   200.        ]
 [    -0.        ]
 [ -5026.54824574]
 [     0.        ]]
C [[ 0.  0.  1. -0. -0. -0.]]
D [[0.]]
E [[ 1.  0.  0. -0. -0. -0.]
 [ 0.  1.  0. -0. -0. -0.]
 [ 0.  0.  1. -0. -0. -0.]
 [ 0.  0.  0.  1.  0.  0.]
 [ 0.  0.  0.  0.  1.  0.]
 [ 0.  0.  0.  0.  0.  1.]]
REDUCE
captured errors:
tpath = '/builds/wield-control/docs/maketests/test_results/test_SS_algorithms.py/test_ABCDE'

    def test_ABCDE(tpath):
        print()
        F_Hz = logspaced(0.1, 100, 1000)
    
        z, p, k = ((-1, -5), (-1 + 5j, -1 - 5j, -3), 200)
        z = np.asarray(z)
        p = np.asarray(p)
    
        A, B, C, D, E = SS.zpk2cDSS(z, p, k, mode="CCF", rescale=3j)
        A, B, C, D, E = SS.DSS_c2r(A, B, C, D, E)
        print("A", A)
        print("B", B)
        print("C", C)
        print("D", D)
        print("E", E)
        reduced = True
        while reduced:
            print("REDUCE")
>           A, B, C, D, E, reduced = SS.reduce_modal(A, B, C, D, E, mode="O")

../../src/wield/control/algorithms/statespace/dense/test/test_SS_algorithms.py:61: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
../../src/wield/control/algorithms/statespace/dense/ss_algorithms.py:59: in reduce_modal
    v_pairs = eigspaces_right_real(A, E, tol=tol)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

A = array([[ 0.00000000e+00,  0.00000000e+00,  6.03603475e+03,
        -0.00000000e+00, -2.12132034e+00, -0.00000000e+00],...       [ 0.00000000e+00,  1.50000000e+00,  0.00000000e+00,
         0.00000000e+00,  0.00000000e+00, -3.14159265e+01]])
B = array([[ 1.,  0.,  0., -0., -0., -0.],
       [ 0.,  1.,  0., -0., -0., -0.],
       [ 0.,  0.,  1., -0., -0., -0.],
       [ 0.,  0.,  0.,  1.,  0.,  0.],
       [ 0.,  0.,  0.,  0.,  1.,  0.],
       [ 0.,  0.,  0.,  0.,  0.,  1.]])
tol = 1e-07

    def eigspaces_right_real(A, B=None, tol=1e-9):
        v_pairs = eigspaces_right(A, B=B, tol=tol)
        v_pairs_re = []
        v_pairs_im = []
        w_im = []
        for eigs, evects in v_pairs:
            eigv = np.mean(eigs)
            if abs(eigv.imag) < tol:
                # remove the imaginary part to the eigenvectors
                assert np.all(np.sum(evects.imag ** 2, axis=1) < tol)
                v_pairs_re.append((eigs, evects.real))
                continue
            v_pairs_im.append((eigs, evects))
            w_im.append(eigv)
    
        # this finds conjugate pairs
        w_near = TFmath.nearest_idx(w_im)
        v_pairs_im2 = []
        for idx_fr, idx_to in enumerate(w_near):
            if idx_to is None or w_near[idx_to] is None:
                continue
            if idx_fr is None or w_near[idx_fr] is None:
                continue
            if w_near[idx_to] != idx_fr:
                continue
            # unique conjugate pair
            w_near[idx_to] = None
            w_near[idx_fr] = None
            eigs1, eigv1 = v_pairs_im[idx_to]
            eigs2, eigv2 = v_pairs_im[idx_fr]
            if w_im[idx_to].imag > 0:
                eigs_use = eigs1
            else:
                eigs_use = eigs2
            v_pairs_im2.append((eigs_use, np.hstack([eigv1, eigv2])))
    
        v_pairs_im3 = []
        for eigs, evects in v_pairs_im2:
            # TODO, it may be the the SVD should be used here
            # this may rely on r being rank-revealing
            q, r = scipy.linalg.qr(evects.imag.T)
            # check that the imaginary space is actually reduced
            idx_cut = r.shape[0] // 2
            assert np.all(np.sum(r[idx_cut:] ** 2, axis=1) < tol)
            # same check as above (redundant)
>           assert np.all(np.sum((evects.imag @ q[idx_cut:].T) ** 2, axis=1) < tol)
E           AssertionError

../../src/wield/control/algorithms/statespace/dense/eig_algorithms.py:106: AssertionError