Re: [Numpy-discussion] treating numpy arrays like lists is slow

[Sasha <nd...@ma...>]

This is so because scalar math is very slow in numpy.  This will
improve with the introduction of the scalarmath module.

> python -m timeit -s "from numpy import float_; x =3D float_(2)" "2.*x"
100000 loops, best of 3: 15.8 usec per loop
> python -m timeit -s "x =3D 2." "2.*x"
1000000 loops, best of 3: 0.261 usec per loop



On 2/3/06, Jeff Whitaker <js...@fa...> wrote:
>
> Hi:
>
> I've noticed that code like this is really slow in numpy (0.9.4):
>
> import numpy as NP
> a =3D NP.ones(10000,'d')
> a =3D [2.*a1 for a1 in a]
>
>
> the last line takes 0.17 seconds on my G5, while for Numeric and
> numarray it takes only 0.01.  Anyone know the reason for this?
>
> -Jeff
>
> --
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