On Wed, Jan 26, 2011 at 1:10 PM, Mark Wiebe <[email protected]> wrote:
> On Wed, Jan 26, 2011 at 2:23 AM, Ralf Gommers <[email protected] > > wrote: > >> On Wed, Jan 26, 2011 at 12:28 PM, Mark Wiebe <[email protected]> wrote: >> >>> On Tue, Jan 25, 2011 at 5:18 PM, Charles R Harris < >>> [email protected]> wrote: >>> >>>> On Tue, Jan 25, 2011 at 1:13 PM, Travis Oliphant < >>>> [email protected]> wrote: >>>> >>>>> >>>>> It may make sense for a NumPy 1.6 to come out in March / April in the >>>>> interim. >>>>> >>>>> >>>> Pulling out the changes to attain backward compatibility isn't getting >>>> any easier. I'd rather shoot for 2.0 in June. What can the rest of us do to >>>> help move things along? >>>> >>> >>> >> Focusing on 2.0 makes sense to me too. Besides that, March/April is bad >> timing for me so someone else should volunteer to be the release manager if >> we go for a 1.6. >> > > I think sooner than March/April might be a possibility. I've gotten the > ABI working so this succeeds on my machine: > > If we go with a 1.6 I have some polynomial stuff I want to put in, probably a weekend or two of work, and there are tickets and pull requests to look through, so to me March-April looks like a good time. It sounds like Ralf has stuff scheduled for the rest of the spring after the scipy release. IIRC, there was at least one other person interested in managing a release when David left for Silveregg, do we have any volunteers for a 1.6? If we do go for 1.6 I would like to keep 2.0 in sight. If datetime, the new iterator, einsum, and float16 are in 1.6 then 2.0 looks more like a cleanup the library/inteface and support IronPython release and there isn't as much pressure to get it out soon. Also it is important to get the ABI right so we don't need to change it again soon and doing that might take a bit of trial and error. Does September seem reasonable? * Build SciPy against NumPy 1.5.1 > * Build NumPy trunk > * Run NumPy trunk with the 1.5.1-built SciPy - all tests pass except for > one (PIL image resize, which tests all float types and half lacks the > precisions necessary) > > I took a shot at fixing the ABI compatibility, and if PyArray_ArrFunc was >>> the main issue, then that might be done. An ABI compatible 1.6 with the >>> datetime and half types should be doable, just some extensions might get >>> confused if they encounter arrays made with the new data types. >>> >>> Even if you fixed the ABI incompatibility (I don't know enough about the >> issue to confirm that), I'm not sure how much value there is in a release >> with as main new feature two dtypes that are not going to work well with >> scipy/other binaries compiled against 1.5. >> > > I've recently gotten the faster ufunc NEP implementation finished except > for generalized ufuncs, and most things work the same or faster with > it. Below are some timings of 1.5.1 vs the new_iterator branch. In > particular, the overhead on small arrays hasn't gotten worse, but the output > memory layout speeds up some operations by a lot. > > <snip> Chuck > >
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