On Fri, Jul 4, 2014 at 9:48 PM, Charles R Harris <charlesr.harris@gmail.com> wrote:

On Fri, Jul 4, 2014 at 2:41 PM, Nathaniel Smith <njs@pobox.com> wrote:

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On Fri, Jul 4, 2014 at 9:33 PM, Charles R Harris <charlesr.harris@gmail.com> wrote:

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On Fri, Jul 4, 2014 at 2:09 PM, Nathaniel Smith <njs@pobox.com> wrote:

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On Fri, Jul 4, 2014 at 9:02 PM, Ralf Gommers <ralf.gommers@gmail.com> wrote:

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On Fri, Jul 4, 2014 at 10:00 PM, Charles R Harris <charlesr.harris@gmail.com> wrote:

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On Fri, Jul 4, 2014 at 1:42 PM, Charles R Harris <charlesr.harris@gmail.com> wrote: > > Sebastian Seberg has fixed one class of test failures due to the > indexing > changes in numpy 1.9.0b1. There are some remaining errors, and in > the > case > of the Matplotlib failures, they look to me to be Matplotlib bugs. > The > 2-d > arrays that cause the error are returned by the overloaded > _interpolate_single_key function in CubicTriInterpolator that is > documented > in the base class to return a 1-d array, whereas the actual > dimensions > are > of the form (n, 1). The question is, what is the best work around > here > for > these sorts errors? Can we afford to break Matplotlib and other > packages on > account of a bug that was previously accepted by Numpy?

It depends how bad the break is, but in principle I'd say that breaking Matplotlib is not OK.

I agree. If it's easy to hack around it and issue a warning for now, and doesn't have other negative consequences, then IMO we should give matplotlib a release or so worth of grace period to fix things.

Here is another example, from skimage.

====================================================================== ERROR: test_join.test_relabel_sequential_offset1 ---------------------------------------------------------------------- Traceback (most recent call last): File "X:\Python27-x64\lib\site-packages\nose\case.py", line 197, in runTest self.test(*self.arg) File

"X:\Python27-x64\lib\site-packages\skimage\segmentation\tests\test_join.py", line 30, in test_relabel_sequential_offset1 ar_relab, fw, inv = relabel_sequential(ar) File "X:\Python27-x64\lib\site-packages\skimage\segmentation\_join.py", line 127, in relabel_sequential forward_map[labels0] = np.arange(offset, offset + len(labels0) + 1) ValueError: shape mismatch: value array of shape (6,) could not be broadcast to indexing result of shape (5,)

Which is pretty clearly a coding error. Unfortunately, the error is in the package rather than the test.

The only easy way to fix all of these sorts of things is to revert the indexing changes, and I'm loathe to do that. Grrr...

Ugh, that's pretty bad :-/. Do you really think we can't use a band-aid over the new indexing code, though?

Yeah, we can. But Sebastian doesn't have time and I'm unfamiliar with the code, so it may take a while...

Fair enough! I guess that if what are (arguably) bugs in matplotlib and scikit-image are holding up the numpy release, then it's worth CC'ing their mailing lists in case someone feels like volunteering to fix it... ;-). -n -- Nathaniel J. Smith Postdoctoral researcher - Informatics - University of Edinburgh http://vorpus.org