Re: [Numpy-discussion] avoiding the matrix copy performance hit

[Ryan K. <rya...@gm...>]

You both seem to have cooler computers than I do:

In [19]: t1.timeit(100)
Out[19]: 4.9827449321746826

In [20]: t2.timeit(100)
Out[20]: 4.9990239143371582


On 2/13/06, Tim Hochberg <tim...@co...> wrote:
> Bill Baxter wrote:
>
> > Is there anyway to get around this timing difference?
> > *
> >   >>> import timeit
> > **  >>> t1 =3D timeit.Timer("a =3D zeros((1000,1000),'d'); a +=3D 1.;",
> > 'from numpy import zeros,mat')
> > **  >>> t2 =3D timeit.Timer("a =3D mat(zeros((1000,1000),'d')); a +=3D
> > 1.;",  'from numpy import zeros,mat')
> >   >>> **t1.timeit(100)
> >   1.8391627591141742
> >   >>> t2.timeit(100)
> >   3.2988266117713465
> >
> > *Copying all the data of the input array seems wasteful when the array
> > is just going to go out of scope.  Or is this not something to be
> > concerned about?
>
> You could try using copy=3DFalse:
>
>  >>> import timeit
>  >>> t1 =3D timeit.Timer("a =3D zeros((1000,1000),'d'); a +=3D 1.;",  'fr=
om
> numpy import zeros,mat')
>  >>> t2 =3D timeit.Timer("a =3D mat(zeros((1000,1000),'d'), copy=3DFalse)=
; a
> +=3D 1.;",  'from numpy import z
> eros,mat')
>  >>> t1.timeit(100)
> 3.6538127052460578
>  >>> t2.timeit(100)
> 3.6567186611706237
>
> I'd also like to point out that your computer appears to be much faster
> than mine.
>
> -tim
>
>
> >
> > It seems like a copy-by-reference version of mat() would be useful.
> > Really I can't imagine any case when I'd want both a matrix and the
> > original version of the array both hanging around as separate copies.
> > I can imagine either 1) the array is just a temp and I won't ever need
> > it again or 2) temporarily wanting a "matrix view" on the array's data
> > to do some linalg, after which I'll go back to using the original (now
> > modified) array as an array again.
> >
> > --bill
>
>
>
>
>
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