pandas 0.14.1 scheduled for end of next week (was waiting to see schedule for numpy 1.9) but works either way
> On Jul 4, 2014, at 7:41 PM, Nathaniel Smith <n...@pobox.com> wrote: > > On 5 Jul 2014 00:07, "Charles R Harris" <charlesr.har...@gmail.com> wrote: > > > > > > > > > > On Fri, Jul 4, 2014 at 3:33 PM, Nathaniel Smith <n...@pobox.com> wrote: > >> > >> On Fri, Jul 4, 2014 at 10:31 PM, Charles R Harris > >> <charlesr.har...@gmail.com> wrote: > >> > > >> > 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. > >> > >> Oh, I meant, in case they want to fix numpy so that their packages > >> don't break :-). > >> > > > > I've filed issues with all the affected projects. Here is the current > > status. > > > > matplotlib -- Reported, being fixed, should be in 1.4 in a few days. > > skimage -- Reported. > > scikit-learn -- Reported. > > tables -- Reported. > > statsmodels -- Reported, fixed in master. > > bottleneck -- Reported. IIRC, kwgoodman already knew of the changes. > > pyfits -- Reported to astropy. > > milk -- Reported. > > pandas -- Reportedly fixed in master. > > That is a massive pile of affected projects :-(. > > My worry is that if all these projects we know about are broken, then how > many other codebases that we aren't testing are also broken? > > > If the issues are fixed in matplotlib and pandas I'd be inclined to release > > as is with a mention of versions in the release notes. > > Even if it's fixed in pandas master, how long until it's in user's hands? > > -n > > > Chuck > > > > > > _______________________________________________ > > NumPy-Discussion mailing list > > NumPy-Discussion@scipy.org > > http://mail.scipy.org/mailman/listinfo/numpy-discussion > > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion
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