On Thu, May 10, 2012 at 1:14 PM, Charles R Harris <charlesr.har...@gmail.com > wrote:
> > > On Thu, May 10, 2012 at 12:52 PM, Scott Ransom <sran...@nrao.edu> wrote: > >> On 05/10/2012 02:23 PM, Chris Barker wrote: >> > On Thu, May 10, 2012 at 2:38 AM, Dag Sverre Seljebotn >> > <d.s.seljeb...@astro.uio.no> wrote: >> >> What would serve me? I use NumPy as a glorified "double*". >> > >> >> all I want is my glorified >> >> "double*". I'm probably not a representative user.) >> > >> > Actually, I think you are representative of a LOT of users -- it >> > turns, out, whether Jim Huginin originally was thinking this way or >> > not, but numpy arrays are really powerful because the provide BOTH and >> > nifty, full featured array object in Python, AND a wrapper around a >> > generic "double*" (actually char*, that could be any type). >> > >> > This is are really widely used feature, and has become even more so >> > with Cython's numpy support. >> > >> > That is one of my concerns about the "bit pattern" idea -- we've then >> > created a new binary type that no other standard software understands >> > -- that looks like a a lot of work to me to deal with, or even worse, >> > ripe for weird, non-obvious errors in code that access that good-old >> > char*. >> > >> > So I'm happier with a mask implementation -- more memory, yes, but it >> > seems more robust an easy to deal with with outside code. >> > >> > But either way, Dag's key point is right on -- in Cython (or any other >> > code) -- we need to make sure ti's easy to get a regular old pointer >> > to a regular old C array, and get something else by accident. >> > >> > -Chris >> >> Agreed. (As someone who has been heavily using Numpy since the early >> days of numeric, and who wrote and maintains a suite of scientific >> software that uses Numpy and its C-API in exactly this way.) >> >> Note that I wasn't aware that the proposed mask implementation might (or >> would?) change this behavior... (and hopefully I haven't just >> misinterpreted these last few emails. If so, I apologize.). >> >> > I haven't seen a change in this behavior, otherwise most of current numpy > would break. > > I suspect this rumour comes from some ideas for generator arrays (not mine), but I would strongly oppose anything that changes things that much. Chuck
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion