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Build system and test suite update#759

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Merged
murrayrm merged 7 commits intopython-control:mainfrombnavigator:setuptools-update
Aug 20, 2022

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bnavigator
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@bnavigatorbnavigator commentedAug 6, 2022
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  • setup.py install is deprecated. Use this opportunity to migrate to PEP517 style packaging:fixesBuilding wheel for dev version fails #758
  • Update test matrix to test Python 3.10
  • Don't cancel other CI jobs if one fails
  • Build Slycot from source and test with PyPI packages instead of Conda
  • Remove custom xvfb setup. Run pytest-xvfb withQtAgg backend for the zoom toolbar in the extra full conda test run

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I saw something similar occur when I rebased#754. The CI tests worked on my local branch but failed in python-control (even though the code was identical) with the DISPLAY error. I re-ran the tests in python-control and they completed, so figured it was a one-time glitch.

I also noticed there was a warning about mambaforge, but I'm not able to find it. Something about how something was an experimental implementation and resolution of some dependencies may not be repeatable.

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I also saw it in my local branch several times. It fails, but which of the many jobs fail is random (see#756)

@bnavigatorbnavigatorforce-pushed thesetuptools-update branch 6 times, most recently fromd189ce1 toa4766c1CompareAugust 6, 2022 20:06
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bnavigator commentedAug 6, 2022
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Switching back from mamba to conda gets rid of the "Mamba support is still experimental and can result in differently solved environments!" warning you were mentioning@murrayrm, but even that didn't help:

https://github.com/bnavigator/python-control/commits/update-CI

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coveralls commentedAug 6, 2022
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Coverage Status

Coverage remained the same at 94.738% when pulling69fb34a on bnavigator:setuptools-update into87a9c57 on python-control:main.

@bnavigatorbnavigator marked this pull request as ready for reviewAugust 6, 2022 20:32
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I give up.

I think the random "invalid DISPLAY" and segmentation faults are not caused by us but rather either by the conda environment or the Github Actions runners. This might even resolve itself through the next release cycle of either of these.

I would say we just ignore the occassional random CI job fail and look at the remaining successful ones for determining whether a PR is good. We can always re-run a job and see if the failure is reproducible.

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The X Display errors seem to be gone. New failures with the balred routines using conda Slycot producing possibly valid but differently ordered systems. Needs to be checked.

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Odd that Slycot from source is OK, but the other Slycots aren't...

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It's conda slycot using conda openblas vs. ubuntu netlib lapack/blas

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bnavigator commentedAug 20, 2022
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Whack-a-mole!

Now this cvxopt test is flaky:passivity_test.py::test_ispassive_edge_cases :

https://github.com/python-control/python-control/runs/7930805491?check_suite_focus=true#step:6:3450

2022-08-20T10:05:12.4606678Z =================================== FAILURES ===================================2022-08-20T10:05:12.4607612Z _________________ test_ispassive_edge_cases[test_input2-True] __________________2022-08-20T10:05:12.4607862Z 2022-08-20T10:05:12.4608255Z test_input = (array([[-3.e+12,  0.e+00],2022-08-20T10:05:12.4608627Z        [ 0.e+00, -2.e+12]]), array([[0],2022-08-20T10:05:12.4609085Z        [1]]), array([[-1,  2]]), array([[0.]]))2022-08-20T10:05:12.4609312Z expected = True2022-08-20T10:05:12.4609448Z 2022-08-20T10:05:12.4609567Z     @pytest.mark.parametrize(2022-08-20T10:05:12.4609948Z         "test_input,expected",2022-08-20T10:05:12.4610188Z         [((A, B, C, D*0.0), True),2022-08-20T10:05:12.4610415Z          ((A_d, B, C, D), True),2022-08-20T10:05:12.4610640Z          ((A*1e12, B, C, D*0), True),2022-08-20T10:05:12.4610854Z          ((A, B*0, C*0, D), True),2022-08-20T10:05:12.4611073Z          ((A*0, B, C, D), True),2022-08-20T10:05:12.4611293Z          ((A*0, B*0, C*0, D*0), True)])2022-08-20T10:05:12.4611683Z     def test_ispassive_edge_cases(test_input, expected):2022-08-20T10:05:12.4611958Z         A = test_input[0]2022-08-20T10:05:12.4612178Z         B = test_input[1]2022-08-20T10:05:12.4612610Z         C = test_input[2]2022-08-20T10:05:12.4612970Z         D = test_input[3]2022-08-20T10:05:12.4613469Z         sys = ss(A, B, C, D)2022-08-20T10:05:12.4613753Z >       assert(passivity.ispassive(sys) == expected)2022-08-20T10:05:12.4613952Z 2022-08-20T10:05:12.4614077Z control/tests/passivity_test.py:115: 2022-08-20T10:05:12.4614373Z _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 2022-08-20T10:05:12.4614742Z control/passivity.py:292: in ispassive2022-08-20T10:05:12.4615096Z     return solve_passivity_LMI(sys, rho=ofp_index, nu=ifp_index) is not None2022-08-20T10:05:12.4615456Z control/passivity.py:177: in solve_passivity_LMI2022-08-20T10:05:12.4615750Z     sol = cvx.solvers.sdp(c, Gs=Gs, hs=hs)2022-08-20T10:05:12.4616316Z /usr/share/miniconda3/envs/test-env/lib/python3.10/site-packages/cvxopt/coneprog.py:4126: in sdp2022-08-20T10:05:12.4616810Z     sol = conelp(c, G, h, dims, A = A, b = b, primalstart = ps, dualstart = ds, kktsolver = kktsolver, options = options)2022-08-20T10:05:12.4617643Z /usr/share/miniconda3/envs/test-env/lib/python3.10/site-packages/cvxopt/coneprog.py:1395: in conelp2022-08-20T10:05:12.4618038Z     misc.update_scaling(W, lmbda, ds, dz)2022-08-20T10:05:12.4618322Z _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 2022-08-20T10:05:12.4618485Z 2022-08-20T10:05:12.4618810Z W = {'beta': [], 'd': <0x1 matrix, tc='d'>, 'di': <0x1 matrix, tc='d'>, 'dnl': <0x1 matrix, tc='d'>, ...}2022-08-20T10:05:12.4619335Z lmbda = <6x1 matrix, tc='d'>, s = <13x1 matrix, tc='d'>2022-08-20T10:05:12.4619636Z z = <13x1 matrix, tc='d'>2022-08-20T10:05:12.4619773Z 2022-08-20T10:05:12.4619885Z     def update_scaling(W, lmbda, s, z):2022-08-20T10:05:12.4620221Z         """2022-08-20T10:05:12.4620607Z         Updates the Nesterov-Todd scaling matrix W and the scaled variable2022-08-20T10:05:12.4621042Z         lmbda so that on exit2022-08-20T10:05:12.4621247Z     2022-08-20T10:05:12.4621547Z               W * zt = W^{-T} * st = lmbda.2022-08-20T10:05:12.4621773Z     2022-08-20T10:05:12.4622145Z         On entry, the nonlinear, 'l' and 'q' components of the arguments s2022-08-20T10:05:12.4622629Z         and z contain W^{-T}*st and W*zt, i.e, the new iterates in the current2022-08-20T10:05:12.4622920Z         scaling.2022-08-20T10:05:12.4623119Z     2022-08-20T10:05:12.4623489Z         The 's' components contain the factors Ls, Lz in a factorization of2022-08-20T10:05:12.4624030Z         the new iterates in the current scaling, W^{-T}*st = Ls*Ls',2022-08-20T10:05:12.4624341Z         W*zt = Lz*Lz'.2022-08-20T10:05:12.4624645Z         """2022-08-20T10:05:12.4624832Z     2022-08-20T10:05:12.4625008Z     2022-08-20T10:05:12.4625390Z         # Nonlinear and 'l' blocks2022-08-20T10:05:12.4625606Z         #2022-08-20T10:05:12.4626008Z         #    d :=  d .* sqrt( s ./ z )2022-08-20T10:05:12.4626266Z         #    lmbda := lmbda .* sqrt(s) .* sqrt(z)2022-08-20T10:05:12.4626501Z     2022-08-20T10:05:12.4626752Z         if 'dnl' in W:2022-08-20T10:05:12.4627026Z             mnl = len(W['dnl'])2022-08-20T10:05:12.4627256Z         else:2022-08-20T10:05:12.4627460Z             mnl = 02022-08-20T10:05:12.4627713Z         ml = len(W['d'])2022-08-20T10:05:12.4627934Z         m = mnl + ml2022-08-20T10:05:12.4628165Z         s[:m] = base.sqrt( s[:m] )2022-08-20T10:05:12.4628397Z         z[:m] = base.sqrt( z[:m] )2022-08-20T10:05:12.4629372Z     2022-08-20T10:05:12.4629630Z         # d := d .* s .* z2022-08-20T10:05:12.4629940Z         if 'dnl' in W:2022-08-20T10:05:12.4630299Z             blas.tbmv(s, W['dnl'], n = mnl, k = 0, ldA = 1)2022-08-20T10:05:12.4630693Z             blas.tbsv(z, W['dnl'], n = mnl, k = 0, ldA = 1)2022-08-20T10:05:12.4631031Z             W['dnli'][:] = W['dnl'][:] ** -12022-08-20T10:05:12.4631420Z         blas.tbmv(s, W['d'], n = ml, k = 0, ldA = 1, offsetA = mnl)2022-08-20T10:05:12.4631840Z         blas.tbsv(z, W['d'], n = ml, k = 0, ldA = 1, offsetA = mnl)2022-08-20T10:05:12.4632171Z         W['di'][:] = W['d'][:] ** -12022-08-20T10:05:12.4632391Z     2022-08-20T10:05:12.4632808Z         # lmbda := s .* z2022-08-20T10:05:12.4633059Z         blas.copy(s, lmbda, n = m)2022-08-20T10:05:12.4633323Z         blas.tbmv(z, lmbda, n = m, k = 0, ldA = 1)2022-08-20T10:05:12.4633622Z     2022-08-20T10:05:12.4633806Z     2022-08-20T10:05:12.4634057Z         # 'q' blocks.2022-08-20T10:05:12.4634267Z         #2022-08-20T10:05:12.4634539Z         # Let st and zt be the new variables in the old scaling:2022-08-20T10:05:12.4634792Z         #2022-08-20T10:05:12.4635010Z         #     st = s_k,   zt = z_k2022-08-20T10:05:12.4635228Z         #2022-08-20T10:05:12.4635560Z         # and a = sqrt(st' * J * st),  b = sqrt(zt' * J * zt).2022-08-20T10:05:12.4635811Z         #2022-08-20T10:05:12.4636209Z         # 1. Compute the hyperbolic Householder transformation 2*q*q' - J2022-08-20T10:05:12.4636519Z         #    that maps st/a to zt/b.2022-08-20T10:05:12.4636747Z         #2022-08-20T10:05:12.4637058Z         #        c = sqrt( (1 + st'*zt/(a*b)) / 2 )2022-08-20T10:05:12.4637420Z         #        q = (st/a + J*zt/b) / (2*c).2022-08-20T10:05:12.4637667Z         #2022-08-20T10:05:12.4637894Z         #    The new scaling point is2022-08-20T10:05:12.4638110Z         #2022-08-20T10:05:12.4638578Z         #        wk := betak * sqrt(a/b) * (2*v[k]*v[k]' - J) * q2022-08-20T10:05:12.4638818Z         #2022-08-20T10:05:12.4639082Z         #    with betak = W['beta'][k].2022-08-20T10:05:12.4639302Z         #2022-08-20T10:05:12.4639636Z         # 3. The scaled variable:2022-08-20T10:05:12.4639831Z         #2022-08-20T10:05:12.4640044Z         #        lambda_k0 = sqrt(a*b) * c2022-08-20T10:05:12.4640423Z         #        lambda_k1 = sqrt(a*b) * ( (2vk*vk' - J) * (-d*q + u/2) )_12022-08-20T10:05:12.4640655Z         #2022-08-20T10:05:12.4640839Z         #    where2022-08-20T10:05:12.4641026Z         #2022-08-20T10:05:12.4641267Z         #        u = st/a - J*zt/b2022-08-20T10:05:12.4641620Z         #        d = ( vk0 * (vk'*u) + u0/2 ) / (2*vk0 *(vk'*q) - q0 + 1).2022-08-20T10:05:12.4641864Z         #2022-08-20T10:05:12.4642182Z         # 4. Update scaling2022-08-20T10:05:12.4642379Z         #2022-08-20T10:05:12.4642577Z         #        v[k] := wk^1/22022-08-20T10:05:12.4642824Z         #              = 1 / sqrt(2*(wk0 + 1)) * (wk + e).2022-08-20T10:05:12.4643060Z         #        beta[k] *=  sqrt(a/b)2022-08-20T10:05:12.4643271Z     2022-08-20T10:05:12.4643455Z         ind = m2022-08-20T10:05:12.4643731Z         for k in range(len(W['v'])):2022-08-20T10:05:12.4643952Z     2022-08-20T10:05:12.4644314Z             v = W['v'][k]2022-08-20T10:05:12.4644524Z             m = len(v)2022-08-20T10:05:12.4644728Z     2022-08-20T10:05:12.4645040Z             # ln = sqrt( lambda_k' * J * lambda_k )2022-08-20T10:05:12.4645428Z             ln = jnrm2(lmbda, n = m, offset = ind)2022-08-20T10:05:12.4645658Z     2022-08-20T10:05:12.4645978Z             # a = sqrt( sk' * J * sk ) = sqrt( st' * J * st )2022-08-20T10:05:12.4646340Z             # s := s / a = st / a2022-08-20T10:05:12.4646607Z             aa = jnrm2(s, offset = ind, n = m)2022-08-20T10:05:12.4646898Z             blas.scal(1.0/aa, s, offset = ind, n = m)2022-08-20T10:05:12.4647123Z     2022-08-20T10:05:12.4647455Z             # b = sqrt( zk' * J * zk ) = sqrt( zt' * J * zt )2022-08-20T10:05:12.4647818Z             # z := z / a = zt / b2022-08-20T10:05:12.4648054Z             bb = jnrm2(z, offset = ind, n = m)2022-08-20T10:05:12.4648334Z             blas.scal(1.0/bb, z, offset = ind, n = m)2022-08-20T10:05:12.4648565Z     2022-08-20T10:05:12.4648857Z             # c = sqrt( ( 1 + (st'*zt) / (a*b) ) / 2 )2022-08-20T10:05:12.4649290Z             cc = math.sqrt( ( 1.0 + blas.dot(s, z, offsetx = ind, offsety =2022-08-20T10:05:12.4649582Z                 ind, n = m) ) / 2.0 )2022-08-20T10:05:12.4649796Z     2022-08-20T10:05:12.4650041Z             # vs = v' * st / a2022-08-20T10:05:12.4650311Z             vs = blas.dot(v, s, offsety = ind, n = m)2022-08-20T10:05:12.4650549Z     2022-08-20T10:05:12.4651253Z             # vz = v' * J *zt / b2022-08-20T10:05:12.4651724Z             vz = jdot(v, z, offsety = ind, n = m)2022-08-20T10:05:12.4651960Z     2022-08-20T10:05:12.4652334Z             # vq = v' * q where q = (st/a + J * zt/b) / (2 * c)2022-08-20T10:05:12.4652810Z             vq = (vs + vz ) / 2.0 / cc2022-08-20T10:05:12.4653032Z     2022-08-20T10:05:12.4653355Z             # vu = v' * u  where u =  st/a - J * zt/b2022-08-20T10:05:12.4653655Z             vu = vs - vz2022-08-20T10:05:12.4653865Z     2022-08-20T10:05:12.4654053Z             # lambda_k0 = c2022-08-20T10:05:12.4654285Z             lmbda[ind] = cc2022-08-20T10:05:12.4654602Z     2022-08-20T10:05:12.4654873Z             # wk0 = 2 * vk0 * (vk' * q) - q02022-08-20T10:05:12.4655466Z             wk0 = 2 * v[0] * vq - ( s[ind] + z[ind] ) / 2.0 / cc2022-08-20T10:05:12.4655699Z     2022-08-20T10:05:12.4655989Z             # d = (v[0] * (vk' * u) - u0/2) / (wk0 + 1)2022-08-20T10:05:12.4656492Z             dd = (v[0] * vu - s[ind]/2.0 + z[ind]/2.0) / (wk0 + 1.0)2022-08-20T10:05:12.4656755Z     2022-08-20T10:05:12.4657096Z             # lambda_k1 = 2 * v_k1 * vk' * (-d*q + u/2) - d*q1 + u1/22022-08-20T10:05:12.4657651Z             blas.copy(v, lmbda, offsetx = 1, offsety = ind+1, n = m-1)2022-08-20T10:05:12.4658095Z             blas.scal(2.0 * (-dd * vq + 0.5 * vu), lmbda, offset = ind+1,2022-08-20T10:05:12.4658422Z                n = m-1)2022-08-20T10:05:12.4658904Z             blas.axpy(s, lmbda, 0.5 * (1.0 - dd/cc), offsetx = ind+1, offsety2022-08-20T10:05:12.4659242Z                = ind+1, n = m-1)2022-08-20T10:05:12.4659529Z             blas.axpy(z, lmbda, 0.5 * (1.0 + dd/cc), offsetx = ind+1, offsety2022-08-20T10:05:12.4659850Z                = ind+1, n = m-1)2022-08-20T10:05:12.4660056Z     2022-08-20T10:05:12.4660408Z             # Scale so that sqrt(lambda_k' * J * lambda_k) = sqrt(aa*bb).2022-08-20T10:05:12.4660855Z             blas.scal(math.sqrt(aa*bb), lmbda, offset = ind, n = m)2022-08-20T10:05:12.4661118Z     2022-08-20T10:05:12.4661396Z             # v := (2*v*v' - J) * q2022-08-20T10:05:12.4661843Z             #    = 2 * (v'*q) * v' - (J* st/a + zt/b) / (2*c)2022-08-20T10:05:12.4662220Z             blas.scal(2.0 * vq, v)2022-08-20T10:05:12.4662532Z             v[0] -= s[ind] / 2.0 / cc2022-08-20T10:05:12.4662939Z             blas.axpy(s, v,  0.5/cc, offsetx = ind+1, offsety = 1, n = m-1)2022-08-20T10:05:12.4663341Z             blas.axpy(z, v, -0.5/cc, offsetx = ind, n = m)2022-08-20T10:05:12.4663589Z     2022-08-20T10:05:12.4663824Z             # v := v^{1/2} = 1/sqrt(2 * (v0 + 1)) * (v + e)2022-08-20T10:05:12.4664050Z             v[0] += 1.02022-08-20T10:05:12.4664310Z             blas.scal(1.0 / math.sqrt(2.0 * v[0]), v)2022-08-20T10:05:12.4664548Z     2022-08-20T10:05:12.4664751Z             # beta[k] *= ( aa / bb )**1/22022-08-20T10:05:12.4665097Z             W['beta'][k] *= math.sqrt( aa / bb )2022-08-20T10:05:12.4665331Z     2022-08-20T10:05:12.4665510Z             ind += m2022-08-20T10:05:12.4665708Z     2022-08-20T10:05:12.4665895Z     2022-08-20T10:05:12.4666158Z         # 's' blocks2022-08-20T10:05:12.4666360Z         #2022-08-20T10:05:12.4666633Z         # Let st, zt be the updated variables in the old scaling:2022-08-20T10:05:12.4666886Z         #2022-08-20T10:05:12.4667184Z         #     st = Ls * Ls', zt = Lz * Lz'.2022-08-20T10:05:12.4667411Z         #2022-08-20T10:05:12.4667735Z         # where Ls and Lz are the 's' components of s, z.2022-08-20T10:05:12.4667992Z         #2022-08-20T10:05:12.4668302Z         # 1.  SVD Lz'*Ls = Uk * lambda_k^+ * Vk'.2022-08-20T10:05:12.4668526Z         #2022-08-20T10:05:12.4668739Z         # 2.  New scaling is2022-08-20T10:05:12.4668957Z         #2022-08-20T10:05:12.4669289Z         #         r[k] := r[k] * Ls * Vk * diag(lambda_k^+)^{-1/2}2022-08-20T10:05:12.4669698Z         #         rti[k] := r[k] * Lz * Uk * diag(lambda_k^+)^{-1/2}.2022-08-20T10:05:12.4669951Z         #2022-08-20T10:05:12.4670124Z     2022-08-20T10:05:12.4670493Z         work = matrix(0.0, (max( [0] + [r.size[0] for r in W['r']])**2, 1))2022-08-20T10:05:12.4671033Z         ind = mnl + ml + sum([ len(v) for v in W['v'] ])2022-08-20T10:05:12.4671299Z         ind2, ind3 = ind, 02022-08-20T10:05:12.4671594Z         for k in range(len(W['r'])):2022-08-20T10:05:12.4671924Z             r, rti = W['r'][k], W['rti'][k]2022-08-20T10:05:12.4672164Z             m = r.size[0]2022-08-20T10:05:12.4672356Z     2022-08-20T10:05:12.4672564Z             # r := r*sk = r*Ls2022-08-20T10:05:12.4672858Z             blas.gemm(r, s, work, m = m, n = m, k = m, ldB = m, ldC = m,2022-08-20T10:05:12.4673126Z                 offsetB = ind2)2022-08-20T10:05:12.4673545Z             blas.copy(work, r, n = m**2)2022-08-20T10:05:12.4673885Z     2022-08-20T10:05:12.4674070Z             # rti := rti*zk = rti*Lz2022-08-20T10:05:12.4674352Z             blas.gemm(rti, z, work, m = m, n = m, k = m, ldB = m, ldC = m,2022-08-20T10:05:12.4674620Z                 offsetB = ind2)2022-08-20T10:05:12.4674939Z             blas.copy(work, rti, n = m**2)2022-08-20T10:05:12.4675176Z     2022-08-20T10:05:12.4696294Z             # SVD Lz'*Ls = U * lmbds^+ * V'; store U in sk and V' in zk.2022-08-20T10:05:12.4696880Z             blas.gemm(z, s, work, transA = 'T', m = m, n = m, k = m, ldA = m,2022-08-20T10:05:12.4697207Z                 ldB = m, ldC = m, offsetA = ind2, offsetB = ind2)2022-08-20T10:05:12.4697652Z             lapack.gesvd(work, lmbda, jobu = 'A', jobvt = 'A', m = m, n = m,2022-08-20T10:05:12.4698006Z                 ldA = m, U = s, Vt = z, ldU = m, ldVt = m, offsetS = ind,2022-08-20T10:05:12.4698319Z                 offsetU = ind2, offsetVt = ind2)2022-08-20T10:05:12.4698543Z     2022-08-20T10:05:12.4698741Z             # r := r*V2022-08-20T10:05:12.4699127Z             blas.gemm(r, z, work, transB = 'T', m = m, n = m, k = m, ldB = m,2022-08-20T10:05:12.4699410Z                 ldC = m, offsetB = ind2)2022-08-20T10:05:12.4699675Z             blas.copy(work, r, n = m**2)2022-08-20T10:05:12.4700021Z     2022-08-20T10:05:12.4700204Z             # rti := rti*U2022-08-20T10:05:12.4700602Z             blas.gemm(rti, s, work, n = m, m = m, k = m, ldB = m, ldC = m,2022-08-20T10:05:12.4700867Z                 offsetB = ind2)2022-08-20T10:05:12.4701098Z             blas.copy(work, rti, n = m**2)2022-08-20T10:05:12.4701318Z     2022-08-20T10:05:12.4701645Z             # r := r*lambda^{-1/2}; rti := rti*lambda^{-1/2}2022-08-20T10:05:12.4702010Z             for i in range(m):2022-08-20T10:05:12.4702263Z >               a = 1.0 / math.sqrt(lmbda[ind+i])2022-08-20T10:05:12.4702566Z E               ZeroDivisionError: float division by zero2022-08-20T10:05:12.4702754Z 2022-08-20T10:05:12.4703110Z /usr/share/miniconda3/envs/test-env/lib/python3.10/site-packages/cvxopt/misc.py:628: ZeroDivisionError

@bnavigatorbnavigator changed the titleBuild system updateBuild system and test suite updateAug 20, 2022
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@murrayrm I think this is ready. I guess, we will have to hit "re-run failed jobs" on the GHA page until#761 is resolved.

@bnavigatorbnavigator linked an issueAug 20, 2022 that may beclosed by this pull request
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This looks good to go, but a few small questions as I looked through the code.

@murrayrmmurrayrm merged commitd4c1f14 intopython-control:mainAug 20, 2022
@murrayrmmurrayrm added this to the0.9.3 milestoneDec 24, 2022
@bnavigatorbnavigator deleted the setuptools-update branchFebruary 18, 2024 20:31
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Building wheel for dev version fails CI tests are failing (xvfb issue?)
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