On 7/20/07, Kevin Jacobs <[EMAIL PROTECTED]> <[EMAIL PROTECTED]>
wrote:
On 7/20/07, Kevin Jacobs <[EMAIL PROTECTED]> <[EMAIL PROTECTED]>
wrote:
>
> On 7/20/07, Charles R Harris < [EMAIL PROTECTED]> wrote:
> >
> > I expect using sqrt(x) will be faster than x**.5.
> >
>
> I did test this at one po
On 7/20/07, Kevin Jacobs <[EMAIL PROTECTED]> <[EMAIL PROTECTED]>
wrote:
On 7/20/07, Charles R Harris <[EMAIL PROTECTED]> wrote:
>
> I expect using sqrt(x) will be faster than x**.5.
>
I did test this at one point and was also surprised that sqrt(x) seemed
slower than **.5. However I found out
On 7/20/07, Charles R Harris <[EMAIL PROTECTED]> wrote:
I expect using sqrt(x) will be faster than x**.5.
I did test this at one point and was also surprised that sqrt(x) seemed
slower than **.5. However I found out otherwise while preparing a timeit
script to demonstrate this observation.
On 7/20/07, Charles R Harris <[EMAIL PROTECTED]> wrote:
[SNIP]
I expect using sqrt(x) will be faster than x**.5.
You might want to check that. I believe that x**0.5 is one of the magic
special cases that is optimized to run fast (by calling sqrt in this case).
IIRC the full set is [-1, 0, 0
On 7/20/07, Kevin Jacobs <[EMAIL PROTECTED]> <[EMAIL PROTECTED]>
wrote:
On 7/20/07, Anne Archibald <[EMAIL PROTECTED]> wrote:
>
> On 20/07/07, Nils Wagner <[EMAIL PROTECTED]> wrote:
> > lorenzo bolla wrote:
> > > hi all.
> > > is there a function in numpy to compute the exp of a matrix, similar
On 7/20/07, Nils Wagner <[EMAIL PROTECTED]> wrote:
Your sqrtm_eig(x) function won't work if x is defective.
See test_defective.py for details.
I've added several defective matrices to my test cases and the SVD method
doesn't work well as I'd thought (which is obvious in retrospect). I'm
goi
On Fri, 20 Jul 2007 14:45:43 -0400
"Kevin Jacobs <[EMAIL PROTECTED]>"
<[EMAIL PROTECTED]> wrote:
> On 7/20/07, Nils Wagner <[EMAIL PROTECTED]>
>wrote:
>>
>> Your sqrtm_eig(x) function won't work if x is defective.
>> See test_defective.py for details.
>
>
> I am aware, though at least on my s
On 7/20/07, Nils Wagner <[EMAIL PROTECTED]> wrote:
Your sqrtm_eig(x) function won't work if x is defective.
See test_defective.py for details.
I am aware, though at least on my system, the SVD-based method is by far the
fastest and robust (and can be made more robust by the addition of a
rela
On Fri, 20 Jul 2007 13:03:09 -0400
"Kevin Jacobs <[EMAIL PROTECTED]>"
<[EMAIL PROTECTED]> wrote:
On 7/20/07, Anne Archibald <[EMAIL PROTECTED]>
wrote:
On 20/07/07, Nils Wagner <[EMAIL PROTECTED]>
wrote:
> lorenzo bolla wrote:
> > hi all.
> > is there a function in numpy to compute the exp o
On 7/20/07, Anne Archibald <[EMAIL PROTECTED]> wrote:
On 20/07/07, Nils Wagner <[EMAIL PROTECTED]> wrote:
> lorenzo bolla wrote:
> > hi all.
> > is there a function in numpy to compute the exp of a matrix, similar
> > to expm in matlab?
> > for example:
> > expm([[0,0],[0,0]]) = eye(2)
> Numpy d
On 20/07/07, Nils Wagner <[EMAIL PROTECTED]> wrote:
> lorenzo bolla wrote:
> > hi all.
> > is there a function in numpy to compute the exp of a matrix, similar
> > to expm in matlab?
> > for example:
> > expm([[0,0],[0,0]]) = eye(2)
> Numpy doesn't provide expm but scipy does.
> >>> from scipy.lina
lorenzo bolla wrote:
> hi all.
> is there a function in numpy to compute the exp of a matrix, similar
> to expm in matlab?
> for example:
> expm([[0,0],[0,0]]) = eye(2)
>
> thanks,
> lorenzo.
>
>
> __
hi all.
is there a function in numpy to compute the exp of a matrix, similar to expm
in matlab?
for example:
expm([[0,0],[0,0]]) = eye(2)
thanks,
lorenzo.
___
Numpy-discussion mailing list
Numpy-discussion@scipy.org
http://projects.scipy.org/mailman/lis
13 matches
Mail list logo
