[Numpy-discussion] Masking through generator arrays
sransom at nrao.edu
Thu May 10 14:52:03 EDT 2012
On 05/10/2012 02:23 PM, Chris Barker wrote:
> On Thu, May 10, 2012 at 2:38 AM, Dag Sverre Seljebotn
> <d.s.seljebotn at 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
> 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.
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.).
Scott M. Ransom Address: NRAO
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