[Numpy-discussion] [ANN] Nanny, faster NaN functions

Nathaniel Smith njs@pobox....
Fri Nov 19 12:55:30 CST 2010

On Fri, Nov 19, 2010 at 10:33 AM, Keith Goodman <kwgoodman@gmail.com> wrote:
> Nanny uses the magic of Cython to give you a faster, drop-in replacement for
> the NaN functions in NumPy and SciPy.


Why not make this a patch to numpy/scipy instead?

> Nanny uses a separate Cython function for each combination of ndim, dtype, and
> axis. You can get rid of a lot of overhead (useful in an inner loop, e.g.) by
> directly importing the function that matches your problem::
>    >> arr = np.random.rand(10, 10)
>    >> from nansum import nansum_2d_float64_axis1

If this is really useful, then better to provide a function that finds
the correct function for you?

best_nansum = ny.get_best_nansum(ary[0, :, :], axis=1)
for i in xrange(ary.shape[0]):
    best_nansum(ary[i, :, :], axis=1)

> - functions: nansum
> - Operating systems: 64-bit (accumulator for int32 is hard coded to int64)
> - dtype: int32, int64, float64
> - ndim: 1, 2, and 3

What does it even mean to do NaN operations on integers? (I'd
sometimes find it *really convenient* if there were a NaN value for
standard computer integers... but there isn't?)

-- Nathaniel

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