On Mon, 2010-03-08 at 13:40 -0500, Stefan Seefeld wrote: > On 03/08/2010 01:30 PM, Neal Becker wrote: > > > > Check out pyublas > > > > Thanks for mentioning that. > > Yes, this looks very useful. In fact, my PyArray wrapper was inspired by > pyublas.
Definitely useful, and from what I've seen from a quick glance, a very nice API. I'm personally using Eigen2 rather than boost.ublas - do you have any comment on whether this could be made more generic so as to support other C++ matrix libraries? Of course, ublas is in boost, so it's clearly the most important target. > I think it would be useful to integrate the PyArray wrapper right into > boost.python. > I generally agree, but I dislike the idea of including the numpy C-API header file in all its preprocessor-macro glory in a file which will be included by users, and I've found it hard to avoid that in a header-only library. What was your solution? > Other libraries which provide more functionality (such as pyublas, or > the one Jim is talking about) can then use that wrapper, instead of > having to provide it themselves. This should notably also improve > interoperability, since the boost.python type registry doesn't (yet) > allow multiple wrappers for the same types. This does seem like the best way to go, if we can find a solution to the numpy header problem that doesn't require building the boost.python library itself against numpy. By the way, here's what I've got - it seems to complement pyublas pretty well: - A few "object manager" types for numpy.ndarray, numpy.dtype, numpy.matrix, and numpy.void scalars, and a pretty easy system for adding more. These present a boost.python interface to the parts of the Numpy C-API, and it sounds like they're pretty similar in spirit to your PyArray. I'll look into putting them into the sandbox. - A tool for creating broadcasting python callables from arbitrary C++ objects that overload operator(). - A multidimensional array template library patterned after numpy; this is definitely not something that belongs in boost.python, but I find that they work very well together: http://code.google.com/p/ndarray/ It would really great if boost.multiarray could fill such a role, but I found it doesn't do everything needed in talking to numpy - particularly the ability to handle shared data. Jim _______________________________________________ Cplusplus-sig mailing list Cplusplus-sig@python.org http://mail.python.org/mailman/listinfo/cplusplus-sig
