On Mon, Jun 6, 2011 at 10:30 AM, Mark Wiebe <[email protected]> wrote:
> On Sun, Jun 5, 2011 at 3:43 PM, Ralf Gommers > <[email protected]>wrote: > >> On Thu, Jun 2, 2011 at 10:12 PM, Mark Wiebe <[email protected]> wrote: >> >>> On Thu, Jun 2, 2011 at 3:09 PM, Gael Varoquaux < >>> [email protected]> wrote: >>> >>>> On Thu, Jun 02, 2011 at 03:06:58PM -0500, Mark Wiebe wrote: >>>> > Would anyone object to, at least temporarily, tightening up the >>>> default >>>> > ufunc casting rule to 'same_kind' in NumPy master? It's a one line >>>> change, >>>> > so would be easy to undo, but such a change is very desirable in my >>>> > opinion. >>>> > This would raise an exception, since it's np.add(a, 1.9, out=a), >>>> > converting a float to an int: >>>> >>>> > >>> a = np.arange(3, dtype=np.int32) >>>> >>>> > >>> a += 1.9 >>>> >>>> That's probably going to break a huge amount of code which relies on the >>>> current behavior. >>>> >>>> Am I right in believing that this should only be considered for a major >>>> release of numpy, say numpy 2.0? >>> >>> >>> Absolutely, and that's why I'm proposing to do it in master now, fairly >>> early in a development cycle, so we can evaluate its effects. If the next >>> version is 1.7, we probably would roll it back for release (a 1 line >>> change), and if the next version is 2.0, we probably would keep it in. >>> >>> I suspect at least some of the code relying on the current behavior may >>> have bugs, and tightening this up is a way to reveal them. >>> >>> >> Here are some results of testing your tighten_casting branch on a few >> projects - no need to first put it in master first to do that. Four failures >> in numpy, two in scipy, four in scikit-learn (plus two that don't look >> related), none in scikits.statsmodels. I didn't check how many of them are >> actual bugs. >> >> I'm not against trying out your change, but it would probably be good to >> do some more testing first and fix the issues found before putting it in. >> Then at least if people run into issues with the already tested packages, >> you can just tell them to update those to latest master. >> > > Cool, thanks for running those. I already took a chunk out of the NumPy > failures. The ones_like function shouldn't really be a ufunc, but rather be > like zeros_like and empty_like, but that's probably not something to change > right now. The datetime-fixes type resolution change provides a mechanism to > fix that up pretty easily. > > For Scipy, what do you think is the best way to resolve it? If NumPy 1.6 is > the minimum version for the next scipy, I would add casting='unsafe' to the > failing sqrt call. > I've updated the tighten_casting branch so it now passes all tests. For masked arrays, this required changing some tests to not assume float -> int casts are fine by default, but otherwise I fixed things by relaxing the rules just where necessary. It now depends on the datetime-fixes branch, which I would like to merge at its current point. -Mark
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