[Numpy-discussion] Insights / lessons learned from NumPy design
Wed Jan 9 06:59:57 CST 2013
On Jan 9, 2013 11:35 AM, "Mike Anderson" <firstname.lastname@example.org>
> 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
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
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