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 -- Christopher Barker, Ph.D. Oceanographer Emergency Response Division NOAA/NOS/OR&R (206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception chris.bar...@noaa.gov _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion