On Jan 9, 2013 11:35 AM, "Mike Anderson" <mike.r.anderson...@gmail.com> wrote: > But I'm curious: what is the main use case for the alternative data types in NumPy? Is it for columns of data of heterogeneous types? or something else? In my case, I have used 32 bit (or lower) arrays due to memory limitations and some significant speedups in certain situations. This was particularly useful when I was preprocessing numerous arrays to especially Boolean data, saved a lot of hd space and I/O. I have used 128 bits when precision was critical, as I was dealing with very small differences. It is also nice to be able to repeat your computation with different precision in order to spot possible numerical instabilities, even if the performance is not great.l
David.
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
