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MAINT: dealing with NumPy pre-release test failures #11172
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For 1.4.0 probably add here https://github.com/scipy/scipy/blob/master/pytest.ini#L4 |
Already reverted in numpy 1.18.x, and should be temporarily reverted in numpy master as well. |
So no need to filter for now, we have some time to investigate and fix up the cases where we didn't expect to see object arrays. |
xref gh-11147 which will fix some of the warnings |
These deprecations are back again for NumPy 1.19. |
I'm pretty sure this has long since been dealt with. For example, trying to create a jagged array implicitly in our testsuite fails because of NumPy error, so we'd probably detect if any cases were left over at this point: --- a/scipy/signal/tests/test_ltisys.py
+++ b/scipy/signal/tests/test_ltisys.py
@@ -352,7 +352,7 @@ class TestSS2TF:
assert_allclose(num, [[0, 1], [2, 3]], rtol=1e-13)
assert_allclose(den, [1, 6], rtol=1e-13)
- tf = (np.array([[1, -3], [1, 2, 3]], dtype=object), [1, 6, 5])
+ tf = (np.array([[1, -3], [1, 2, 3]]), [1, 6, 5])
A, B, C, D = tf2ss(*tf)
assert_allclose(A, [[-6, -5], [1, 0]], rtol=1e-13)
assert_allclose(B, [[1], [0]], rtol=1e-13) so, closing |
As you can see in Travis CI for recent PRs ( https://travis-ci.org/scipy/scipy/jobs/620455062?utm_medium=notification&utm_source=github_status ) we now get hundreds of test failures related to
NumPy deprecating the automatic creation of object arrays, with:
DeprecationWarning: Creating an ndarray with automatic object dtype is deprecated, use dtype=object if you intended it, otherwise specify an exact dtype
While I was never a fan of the protections that enables vs. the disruption, I suspect we'll need a way to handle this gracefully moving forward. This is also making my life harder for
1.4.0
as noted in #11161.See also: numpy/numpy#15047
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