On 21. apr. 2012, at 00:16, Drew Frank wrote: > On Fri, Apr 20, 2012 at 11:45 AM, Chris Barker <chris.bar...@noaa.gov> wrote: >> >> On Fri, Apr 20, 2012 at 11:39 AM, Dag Sverre Seljebotn >> <d.s.seljeb...@astro.uio.no> wrote: >>> Oh, right. I was thinking "small" as in "fits in L2 cache", not small as >>> in a few dozen entries. > > Another example of a small array use-case: I've been using numpy for > my research in multi-target tracking, which involves something like a > bunch of entangled hidden markov models. I represent target states > with small 2d arrays (e.g. 2x2, 4x4, ..) and observations with small > 1d arrays (1 or 2 elements). It may be possible to combine a bunch of > these small arrays into a single larger array and use indexing to > extract views, but it is much cleaner and more intuitive to use > separate, small arrays. It's also convenient to use numpy arrays > rather than a custom class because I use the linear algebra > functionality as well as integration with other libraries (e.g. > matplotlib). > > I also work with approximate probabilistic inference in graphical > models (belief propagation, etc), which is another area where it can > be nice to work with many small arrays. > > In any case, I just wanted to chime in with my small bit of evidence > for people wanting to use numpy for work with small arrays, even if > they are currently pretty slow. If there were a special version of a > numpy array that would be faster for cases like this, I would > definitely make use of it. > > Drew
Although performance hasn't been a killer for me, I've been using numpy arrays (or matrices) for Mueller matrices [0] and Stokes vectors [1]. These describe the polarization of light and are always 4x1 vectors or 4x4 matrices. It would be nice if my code ran in 1 night instead of one week, although this is still tolerable in my case. Again, just an example of how small-vector/matrix performance can be important in certain use cases. Paul [0] https://en.wikipedia.org/wiki/Mueller_calculus [1] https://en.wikipedia.org/wiki/Stokes_vector _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion