On Fri, Jul 4, 2014 at 3:15 PM, Nathaniel Smith <n...@pobox.com> wrote:
> On Fri, Jul 4, 2014 at 9:48 PM, Charles R Harris > <charlesr.har...@gmail.com> wrote: > > > > On Fri, Jul 4, 2014 at 2:41 PM, Nathaniel Smith <n...@pobox.com> wrote: > >> > >> On Fri, Jul 4, 2014 at 9:33 PM, Charles R Harris > >> <charlesr.har...@gmail.com> wrote: > >> > > >> > On Fri, Jul 4, 2014 at 2:09 PM, Nathaniel Smith <n...@pobox.com> > wrote: > >> >> > >> >> On Fri, Jul 4, 2014 at 9:02 PM, Ralf Gommers <ralf.gomm...@gmail.com > > > >> >> wrote: > >> >> > > >> >> > On Fri, Jul 4, 2014 at 10:00 PM, Charles R Harris > >> >> > <charlesr.har...@gmail.com> wrote: > >> >> >> > >> >> >> On Fri, Jul 4, 2014 at 1:42 PM, Charles R Harris > >> >> >> <charlesr.har...@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... ;-). > I can do that ;) Doesn't help with the release though unless we want to document the errors in the release notes and tell folks to wait on the next release of the packages. Chuck
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