[EMAIL PROTECTED] wrote:
>Hi,
>
> [TO]: NumPy uses Numeric's old wrapper to lapack algorithms.
> [TO]:
> [TO]: SciPy uses it's own f2py-generated wrapper (it doesn't rely on the
> [TO]: NumPy wrapper).
> [TO]:
> [TO]: The numpy.dual library exists so you can use the SciPy calls if the
> [TO]:
On Wed, 28 Jun 2006 03:22:28 -0500
Robert Kern <[EMAIL PROTECTED]> wrote:
> [EMAIL PROTECTED] wrote:
> > Hi,
> >
> > [TO]: NumPy uses Numeric's old wrapper to lapack algorithms.
> > [TO]:
> > [TO]: SciPy uses it's own f2py-generated wrapper (it doesn't rely on the
> > [TO]: NumPy wrapper).
On Wed, 28 Jun 2006 10:55:36 +0200
Jon Wright <[EMAIL PROTECTED]> wrote:
> Poking around in the svn of numpy.linalg appears to find the same lapack
> routine as Numeric (dsyevd). Perhaps I miss something in the code logic?
It's actually *exactly* the same as the latest Numeric :-) It hasn't been
Jens wrote:
> Dennis V. Perepelitsa wrote:
>>Hi, all.
>>
>>I've run some benchmarks comparing the performance of scipy, numpy,
>>Numeric and numarray vs. MATLAB. There's also the beginnings of a
>>benchmark framework included. The results are online at:
>>
>> http://web.mit.edu/jonas/www/be
Dennis V. Perepelitsa wrote:
>Hi, all.
>
>I've run some benchmarks comparing the performance of scipy, numpy,
>Numeric and numarray vs. MATLAB. There's also the beginnings of a
>benchmark framework included. The results are online at:
>
> http://web.mit.edu/jonas/www/bench/
>
>
It's a lit
Hi,
On Wed, 28 Jun 2006, Jon Wright wrote:
>
> >>This strikes me as a little bit odd. Why not just provide the
> >>best-performing
> >>function to both SciPy and NumPy? Would NumPy be more difficult to install
> >>if the SciPy algorithm for inv() was incorporated?
> >>
> >>
> Having spent a few
>>This strikes me as a little bit odd. Why not just provide the best-performing
>>function to both SciPy and NumPy? Would NumPy be more difficult to install
>>if the SciPy algorithm for inv() was incorporated?
>>
>>
Having spent a few days recently trying out various different
eigenvector ro
[EMAIL PROTECTED] wrote:
> Hi,
>
> [TO]: NumPy uses Numeric's old wrapper to lapack algorithms.
> [TO]:
> [TO]: SciPy uses it's own f2py-generated wrapper (it doesn't rely on the
> [TO]: NumPy wrapper).
> [TO]:
> [TO]: The numpy.dual library exists so you can use the SciPy calls if the
>
Hi,
[TO]: NumPy uses Numeric's old wrapper to lapack algorithms.
[TO]:
[TO]: SciPy uses it's own f2py-generated wrapper (it doesn't rely on the
[TO]: NumPy wrapper).
[TO]:
[TO]: The numpy.dual library exists so you can use the SciPy calls if the
[TO]: person has SciPy installed or the N
Keith Goodman wrote:
> Scipy computes the inverse of a matrix faster than numpy (except if
> the dimensions of x are small). But scipy is slower than numpy for
> eigh (I only checked for symmetric positive definite matrices):
Looks like scipy uses *SYEV and numpy uses the better *SYEVD (the D stan
On 6/27/06, Keith Goodman <[EMAIL PROTECTED]> wrote:
> On 6/27/06, Travis Oliphant <[EMAIL PROTECTED]> wrote:
>
> > The numpy.dual library exists so you can use the SciPy calls if the
> > person has SciPy installed or the NumPy ones otherwise. It exists
> > precisely for the purpose of seamlessly
On 6/27/06, Travis Oliphant <[EMAIL PROTECTED]> wrote:
> The numpy.dual library exists so you can use the SciPy calls if the
> person has SciPy installed or the NumPy ones otherwise. It exists
> precisely for the purpose of seamlessly taking advantage of
> algorithms/interfaces that exist in NumP
Keith Goodman wrote:
> On 6/27/06, Dennis V. Perepelitsa <[EMAIL PROTECTED]> wrote:
>
>
>> I've run some benchmarks comparing the performance of scipy, numpy,
>> Numeric and numarray vs. MATLAB.
>>
>
> I enjoyed looking at the results.
>
> The most interesting result, for me, was that inver
Dennis V. Perepelitsa wrote:
> Hi, all.
>
> I've run some benchmarks comparing the performance of scipy, numpy,
> Numeric and numarray vs. MATLAB. There's also the beginnings of a
> benchmark framework included. The results are online at:
>
> http://web.mit.edu/jonas/www/bench/
>
> They were
On 6/27/06, Dennis V. Perepelitsa <[EMAIL PROTECTED]> wrote:
> I've run some benchmarks comparing the performance of scipy, numpy,
> Numeric and numarray vs. MATLAB.
I enjoyed looking at the results.
The most interesting result, for me, was that inverting a matrix is
much faster in scipy than nu
Dennis V. Perepelitsa wrote:
> Hi, all.
>
> I've run some benchmarks comparing the performance of scipy, numpy,
> Numeric and numarray vs. MATLAB. There's also the beginnings of a
> benchmark framework included. The results are online at:
>
> http://web.mit.edu/jonas/www/bench/
>
> They w
Hi, all.
I've run some benchmarks comparing the performance of scipy, numpy,
Numeric and numarray vs. MATLAB. There's also the beginnings of a
benchmark framework included. The results are online at:
http://web.mit.edu/jonas/www/bench/
They were produced on a Thinkpad T42 with an Intel Pe
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