Re: python-scipy: autopkgtest fails (Re: bug#919929)
On 2019-03-10 15:46, Drew Parsons wrote:
On 2019-03-10 03:51, Paul Gevers wrote:
Hi Drew,
To remove the deprecation warnings we'd need to deal with them at the
source. Upstream has patches
https://github.com/scipy/scipy/commit/614847c5fc8d5f8a618980df3c1b93540428ae46
https://github.com/scipy/scipy/commit/e0cfa29e2fbe86f994924c0c7514ff5bbfffd514
and for completeness
https://github.com/scipy/scipy/commit/87e48c3c54d7a85bc6628c88c1de98ac0469b6fa
...
Can you authorise an unblock to apply these 3 upstream patches to
python-scipy 1.1.0 ?
That won't necessarily fix the debci failure, but it will make it a
lot
easier to see what's actually failing.
I am slightly unhappy with the second patch, as it seems to be doing
more than you describe above in a few places. This may be correct but
that is difficult to quickly judge.
I've adapted the 3 patches and pushed to salsa,
matrix_API_614847c5.patch
matrix_API_more_e0cfa29e2.patch
matrix_API_filter_check_87e48c3c5.patch
https://salsa.debian.org/python-team/modules/python-scipy/tree/master/debian/patches
The other behaviour that you saw in the second patch I think might be
replacement of "D*diag(v)" with "D@diag(v)". That's matrix
multiplication, so still relevent to the matrix API patch. @ is not
available in python2 so I changed it to numpy.matmul, which does the
same thing.
The numpy.sparse tests pass with this patch, and most of the matrix
PendingDeprecationWarnings are gone (the upstream patch missed
integrate/tests/test_ivp.py, but the remaining warnings are few enough
to not need to worry about).
Also, what is the general documented way that these wrappers can be
used? scipy is sort of taking over the maintenanceship of these
functions in this way if we're not careful.
...
There is discussion of the distinction between numpy.matrix and
numpy.ndarray (which is at the heart of the deeprecation warning) at
https://docs.scipy.org/doc/scipy/reference/tutorial/linalg.html#numpy-matrix-vs-2d-numpy-ndarray
The utility class scipy.sparse.sputils itself is apparently
undocumented, by which I infer it's intended for internal use only,
not a public API. I guess it's reasonable for a package to be testing
it's own internal functions. Strange thing is,
scipy.sparse.sputils.matrix is not actually defined in
scipy/sparse/sputils.py. Must be inherited or defined in some deep
pythonfu that I haven't mastered yet.
Actually scipy.sparse.sputils.matrix was defined in these patches. It
is a bit odd that upstream is wrapping numpy.matrix just to avoid
deprecation warnings, rather than following their own advice and using
numpy.ndarray instead.
With these patches, the sparse matrix tests pass. There remain three
errors unrelated to sparse matrix:
spatial/tests/test__plotutils.py::TestPlotting::test_delaunay FAILED
[ 76%]
spatial/tests/test__plotutils.py::TestPlotting::test_voronoi FAILED
[ 76%]
spatial/tests/test__plotutils.py::TestPlotting::test_convex_hull
FAILED [ 76%]
__________________________ TestPlotting.test_delaunay
__________________________
self = <scipy.spatial.tests.test__plotutils.TestPlotting object at
0x7f0f31156eb8>
def test_delaunay(self):
# Smoke test
fig = plt.figure()
obj = Delaunay(self.points)
s_before = obj.simplices.copy()
> with suppress_warnings as sup:
E AttributeError: __enter__
fig = <Figure size 640x480 with 0 Axes>
obj = <scipy.spatial.qhull.Delaunay object at 0x7f0f31163400>
s_before = array([[3, 1, 0],
[2, 3, 0]], dtype=int32)
self = <scipy.spatial.tests.test__plotutils.TestPlotting object
at 0x7f0f31156eb8>
/usr/lib/python3/dist-packages/scipy/spatial/tests/test__plotutils.py:31:
AttributeError
(likewise for the other 2)
These AttributeErrors are mentioned at
https://github.com/scipy/scipy/issues/9491. Upstream doesn't seem too
concerned about them.
Apart from that, I'm happy to upload the sparse matrix patches once the
s390x update reaches testing.
Drew
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