[Numpy-discussion] ANN: NumPy 1.7.0b1 release

Frédéric Bastien nouiz@nouiz....
Sun Sep 9 12:08:18 CDT 2012


All the PyArray_FLOAT*, ... to NPY_FLOAT*.

PyObject *var;
PyArrayObject * var_arr;
var_arr->{dimensions,strides,nd,descr} to PyArray_{DIMS,...}(var_arr),
need macro

PyArray_ISCONTIGUOUS(var) to PyArray_ISCONTIGUOUS(var_arr)

PyArray_{DATA,STRIDES,GETPTR2}(var) to PyArray_{DATA,STRIDES}(var_arr)

The sed script didn't replace NPY_ALIGNED to NPY_ARRAY_ALIGNED. idem
for NPY_WRITABLE, NPY_UPDATE_ALL, NPY_C_CONTIGUOUS, NPY_F_CONTIGUOUS,

The sed script did change   as well, but I think it should not be
deprecated. This flag NPY_ARRAY_ENSURECOPY is a new one. It was not
existing in numpy 1.6.0. We try to stay compitible with numpy 1.3
(maybe we will bump to numpy 1.4). This is the info on when this line
was introduced:

263df0cc (Mark Wiebe         2011-07-19 17:06:08 -0500  784) #define
NPY_ARRAY_ENSURECOPY      0x0020

In the trunk of Theano, I'll define NPY_ARRAY_ENSURECOPY for older
version of numpy.

PyArray_SetBaseObject


On Tue, Sep 4, 2012 at 6:31 PM, Ondřej Čertík <ondrej.certik@gmail.com> wrote:
> On Sat, Sep 1, 2012 at 2:19 AM, Sandro Tosi <morph@debian.org> wrote:
>> On Fri, Aug 31, 2012 at 8:07 PM, Sandro Tosi <morph@debian.org> wrote:
>>> On Fri, Aug 31, 2012 at 7:17 PM, Ondřej Čertík <ondrej.certik@gmail.com> wrote:
>>>> If you could create issues at github: https://github.com/numpy/numpy/issues
>>>> that would be great. If you have time, also with some info about the platform
>>>> and how to reproduce it. Or at least a link to the build logs.
>>>
>>> I've reported it here: https://github.com/numpy/numpy/issues/402
>>
>> I've just spammed the issue tracker with additional issues, reporting
>> all the test suite failures on Debian architectures; issues are 406 ->
>> 414 .
>>
>> Don't hesitate to contact me if you need any support or clarification.
>
> Thanks Sandro for reporting it! I put all of them into my release issue:
>
> https://github.com/numpy/numpy/issues/396
>
> most of the failures seem to be caused by these two issues:
>
> https://github.com/numpy/numpy/issues/394
> https://github.com/numpy/numpy/issues/426
>
> so I am looking into this now.
>
> Ondrej
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