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On Fri, Jul 4, 2014 at 9:48 PM, Charles R Harris <cha...@gm...> wrote: > > On Fri, Jul 4, 2014 at 2:41 PM, Nathaniel Smith <nj...@po...> wrote: >> >> On Fri, Jul 4, 2014 at 9:33 PM, Charles R Harris >> <cha...@gm...> wrote: >> > >> > On Fri, Jul 4, 2014 at 2:09 PM, Nathaniel Smith <nj...@po...> wrote: >> >> >> >> On Fri, Jul 4, 2014 at 9:02 PM, Ralf Gommers <ral...@gm...> >> >> wrote: >> >> > >> >> > On Fri, Jul 4, 2014 at 10:00 PM, Charles R Harris >> >> > <cha...@gm...> wrote: >> >> >> >> >> >> On Fri, Jul 4, 2014 at 1:42 PM, Charles R Harris >> >> >> <cha...@gm...> 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