[Numpy-discussion] Anyone have a well-tested SWIG-based C++ STL valarray <=> numpy.array typemap to share?
Wed Sep 5 13:04:37 CDT 2007
On Sep 5, 2007, at 11:19 AM, Christopher Barker wrote:
> Bill Spotz wrote:
>> I have been considering adding some C++ STL support to numpy/doc/
>> numpy.i. Probably std::vector<TYPE> <=> PyArrayObject (and some
>> std::complex<TYPE> support as well). Is this what you had in mind?
> well, std::valarray is not the same as std::vector, though there are
> similarities, so the example would be helpful.
Ah, silly me. Back when I first learned C++, valarray wasn't around
yet (or at least it wasn't taught to me), and it is not in the
(clearly outdated) references I use. But it is a more logical choice
> Of greatest concern to me is the memory management issue -- it
> would be
> nice to be able to share the data black between the valarray and the
> numpy array (rather than copying back and forth), but as the both
> valarrays and vectors are re-sizeable, that might get tricky. I'm
> assuming that you can get the pointer to the data block from both, but
> it might change on you. If you solve that for std::vector, the
> is likely to be similar for std:valarray. (I hope).
Yes, this resizing memory management issue is the main reason I
haven't tried to implement it in numpy.i yet.
<thinking out loud>
A possibly better solution would be to develop a class that inherits
from std::valarray<TYPE> but also implements the array interface
attributes (these attributes would have to be dynamic, in that they
check the std::valarray attributes when accessed rather than storing
copies). We could then write typemaps that utilize the array
interface. So pure input arguments could be numpy.ndarrays (or any
reasonable sequence, really), but output arrays would be a wrapped
version of this new class. (Which would behave both like
std::valarrays and like numpy.ndarrays. I think...)
</thinking out loud>
** Bill Spotz **
** Sandia National Laboratories Voice: (505)845-0170 **
** P.O. Box 5800 Fax: (505)284-5451 **
** Albuquerque, NM 87185-0370 Email: email@example.com **
More information about the Numpy-discussion