[Numpy-discussion] Numpy 1.6 schedule (was: Numpy 2.0 schedule)
Ralf Gommers
ralf.gommers at googlemail.com
Mon Feb 28 10:31:59 EST 2011
On Mon, Feb 28, 2011 at 10:36 PM, Bruce Southey <bsouthey at gmail.com> wrote:
> On 02/28/2011 02:00 AM, Ralf Gommers wrote:
>> Hi,
>>
>> On Fri, Jan 28, 2011 at 7:15 AM, Travis Oliphant<oliphant at enthought.com> wrote:
>>> The reason for a NumPy 1.6 suggestion, is that Mark (and others it would
>>> seem) have additional work and features that do not need to wait for the
>>> NumPy 2.0 ABI design to finalize in order to get out there.
>>> If someone is willing to manage the release of NumPy 1.6, then it sounds
>>> like a great idea to me.
>> This thread ended without a conclusion a month ago. Now I think master
>> is in a better state than a month ago for a release (py 2.4/2.5/3.x
>> issues and segfault on OS X fixed, more testing of changes), and I
>> have a better idea of my free time for March/April. Basically, I have
>> a good amount of time for the next couple of weeks, and not so much at
>> the end of March / first half of April due to an inter-continental
>> move. But I think we can get out a beta by mid-March, and I can manage
>> the release.
>>
>> I've had a look at the bug tracker, here's a list of tickets for 1.6:
>> #1748 (blocker: regression for astype('str'))
>> #1619 (issue with dtypes, with patch)
>> #1749 (distutils, py 3.2)
>> #1601 (distutils, py 3.2)
>> #1622 (Solaris segfault, with patch)
>> #1713 (Solaris segfault)
>> #1631 (Solaris segfault)
>>
>> I can look at the distutils tickets.
>>
>> The other thing that needs to be done is some (more) documentation of
>> new features. Einsum and the new iterator seem to be well documented,
>> but not described in the release notes. Datetime has no docs as far as
>> I can see except for two similar NEPs.
>>
>> Proposed schedule:
>> March 15: beta 1
>> March 28: rc 1
>> April 17: rc 2 (if needed)
>> April 24: final release
>>
>> Let me know what you think. Bonus points for volunteering to fix some
>> of those tickets:)
>>
>> Cheers,
>> Ralf
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> Is this 1.6 or 2.0?
> The title is 2.0 but you talk about 1.6 so some tickets listed as 2.0
> may apply to 1.6.
1.6, and renamed the thread to make it clearer.
> It would be great to do some 'housekeeping' and try to address some of
> the old tickets dealt with before numpy 2.0. For example, I think ticket
> 225 (bincount does not accept input of type > N.uint16) has been
> addressed but it needs to be checked from windows and 32-bit systems.
That would be useful of course, it just requires someone with spare
time and the knowledge and motivation to close those tickets. I listed
only the ones that I think are essential to fix before a release can
be made.
Ralf
> Created 2006:
> #38 strides accepted as an argument to records.array
> #57 ufunc methods need improved BUFFER loop
> #213 SharedLibrary builder for numpy.distutils
> #225 bincount does not accept input of type > N.uint16
> #236 reduceat cornercase
> #237 reduceat should handle outlier indices gracefully
> #244 Build fails with Intel Visual Fortran compiler
> #260 Add mechanism for registering objects to be deallocated and
> memory-to-be freed at Python exit
> #274 Speed up N-D Boolean indexing
> #301 power with negative argument returns 0
> #333 Creating an array from a n-dim dtype type fails
> #338 Valgrind warning when calling scipy.interpolate.interp1d
> #349 Improve unit tests in linalg
> #354 Possible inconsistency in 0-dim and scalar empty array types
> #398 Compatibility loader for old Numeric pickles
> #400 C API access to fft for C scipy extension ?
> #402 newaxis incompatible with array indexing
>
>
> Numpy 1.0
> #450 Make a.min() not copy data
> #417 Numpy 1.0.1 compilation fails on IRIX 6.5
> #527 fortran linking flag option...
> #1176 deepcopy turns ndarry into string_
> #1143 Improve performance of PyUFunc_Reduce
> #931 Records containing zero-length items pickle just fine, but
> cannot be unpickled
> #803 Assignment problem on matrix advanced selection
>
> Numpy 1.1
> #1266 Extremely long runtimes in numpy.fft.fft
> #963 Object array comparisons eat exceptions
> #929 empty_like and zeros_like behave differently from ones_like
> #934 Documentation error in site.cfg.example
>
> Numpy 1.2
> #1374 Ticket 628 not fixed for Solaris (polyfit uses 100% CPU and
> does not stop)
> #1209 Docstring for numpy.numarray.random_array.multinomial is out of
> date.
> #1192 integer dot product
> #1172 abs does not work with -maxint
> #1163 Incorrect conversion to Int64 by loadtxt (traced to _getconv in
> numpy.lib.io)
> #1161 Errors and/or wrong result with reverse slicing in numpy.delete
> #1094 masked array autotest fails with bus error
> #1085 Surprising results from in-place operations involving views
> #1071 loadtxt fails if the last column contains empty value
>
>
>
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