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MAINT: skip a few failing tests in 1.7.x for macOS arm64 #15090

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merged 3 commits into from Nov 24, 2021

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@rgommers rgommers commented Nov 23, 2021

The damage seems very limited. With these skips, the full test suite passes for me on an arm64 Macbook with macOS 12.0.1

The zvode failures are the only ones that look somewhat worrying, but not enough to block the release on. In master those failures may be gone, at least they were when testing the pre-release wheel built from master. Otherwise it's specific to a build setup somehow.

@tylerjereddy I think this is all for the release, never mind the iqr backport.

Closes gh-15077

Unclear whether or not this only happens on macOS arm64.
Failure (see scipygh-15077):
```
_______________________________________________________ test_standard_nonsymmetric_no_convergence ________________________________________________________
scipy/sparse/linalg/eigen/arpack/tests/test_arpack.py:505: in test_standard_nonsymmetric_no_convergence
    w, v = eigs(m, 4, which='LM', v0=m[:, 0], maxiter=5, tol=tol)
        atol       = 4.440892098500626e-13
        k          = 0
        m          = array([[0.19151945+8.93352260e-01j, 0.62210877+4.48584019e-01j,
        0.43772774+2.44383579e-01j, 0.78535858+8.14172...8112992 +8.68899271e-01j, 0.8727098 +3.75823074e-01j,
        0.66598823+2.81110432e-01j, 0.58878655+1.01350637e-01j]])
        rtol       = 4.440892098500626e-13
        tol        = 0
scipy/sparse/linalg/eigen/arpack/arpack.py:1346: in eigs
    params.iterate()
        A          = array([[0.19151945+8.93352260e-01j, 0.62210877+4.48584019e-01j,
        0.43772774+2.44383579e-01j, 0.78535858+8.14172...8112992 +8.68899271e-01j, 0.8727098 +3.75823074e-01j,
        0.66598823+2.81110432e-01j, 0.58878655+1.01350637e-01j]])
        M          = None
        M_matvec   = None
        Minv       = None
        Minv_matvec = None
        OPinv      = None
        OPpart     = None
        k          = 4
        matvec     = <bound method LinearOperator.matvec of <30x30 MatrixLinearOperator with dtype=complex128>>
        maxiter    = 5
        mode       = 1
        n          = 30
        ncv        = None
        params     = <scipy.sparse.linalg.eigen.arpack.arpack._UnsymmetricArpackParams object at 0x178b76280>
        return_eigenvectors = True
        sigma      = None
        tol        = 0
        v0         = array([0.19151945+0.89335226j, 0.86912739+0.15381227j,
       0.28525096+0.13413814j, 0.15257277+0.3618351j ,
       0...571851j,
       0.98436901+0.65821638j, 0.59697377+0.94320689j,
       0.37845461+0.79574615j, 0.02798429+0.06622806j])
        which      = 'LM'
scipy/sparse/linalg/eigen/arpack/arpack.py:756: in iterate
    self._raise_no_convergence()
        self       = <scipy.sparse.linalg.eigen.arpack.arpack._UnsymmetricArpackParams object at 0x178b76280>
        xslice     = slice(60, 90, None)
        yslice     = slice(30, 60, None)
scipy/sparse/linalg/eigen/arpack/arpack.py:376: in _raise_no_convergence
    raise ArpackNoConvergence(msg % (num_iter, k_ok, self.k), ev, vec)
E   scipy.sparse.linalg.eigen.arpack.arpack.ArpackNoConvergence: ARPACK error -1: No convergence (6 iterations, 0/4 eigenvectors converged) [ARPACK error -14: ZNAUPD did not find any eigenvalues to sufficient accuracy.]
        ev         = array([], dtype=float64)
        k_ok       = 0
        msg        = 'No convergence (%d iterations, %d/%d eigenvectors converged) [ARPACK error -14: ZNAUPD did not find any eigenvalues to sufficient accuracy.]'
        num_iter   = 6
        self       = <scipy.sparse.linalg.eigen.arpack.arpack._UnsymmetricArpackParams object at 0x178b76280>
        vec        = array([], shape=(30, 0), dtype=float64)

The above exception was the direct cause of the following exception:
scipy/sparse/linalg/eigen/arpack/tests/test_arpack.py:510: in test_standard_nonsymmetric_no_convergence
    raise AssertionError("Spurious no-eigenvalues-found case") from err
E   AssertionError: Spurious no-eigenvalues-found case
        atol       = 4.440892098500626e-13
        k          = 0
        m          = array([[0.19151945+8.93352260e-01j, 0.62210877+4.48584019e-01j,
        0.43772774+2.44383579e-01j, 0.78535858+8.14172...8112992 +8.68899271e-01j, 0.8727098 +3.75823074e-01j,
        0.66598823+2.81110432e-01j, 0.58878655+1.01350637e-01j]])
        rtol       = 4.440892098500626e-13
        tol        = 0
```
See scipygh-15077 for details. This seems broken in 1.7.x, but perhaps
not in master (at least with the pre-release wheels). Could be a case of
different build dependencies installed, unclear. Either way,
zvode is failing in this (conda-forge) build setup, and skipping
these tests seems pragmatic.
@rgommers rgommers added scipy.integrate maintenance Items related to regular maintenance tasks labels Nov 23, 2021
@rgommers rgommers added this to the 1.7.3 milestone Nov 23, 2021
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awesome, thanks Ralf

@tylerjereddy tylerjereddy merged commit 1b9e907 into scipy:maintenance/1.7.x Nov 24, 2021
@rgommers rgommers deleted the arm64-17x branch November 24, 2021 08:34
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