On Saturday 26 February 2011 02:58:19 Bruce Southey wrote:
> On 02/25/2011 02:01 AM, Algis Kabaila wrote:
>
> I just build numpy and scipy from source so I do not know how
> you get Python 3 or which Ubuntu versions include recent
> numpy versions (there is a upcoming release that
On Friday 25 February 2011 18:54:13 Scott Sinclair wrote:
> On 25 February 2011 06:22, Algis Kabaila
wrote:
> > On Friday 25 February 2011 14:44:07 Algis Kabaila wrote:
> > PS: a little investigation shows that my version of numpy
> > is 1.3.0 and scipy is 0.7.2 - so ub
On Friday 25 February 2011 14:44:07 Algis Kabaila wrote:
> On Friday 25 February 2011 14:22:04 Bruce Southey wrote:
> > Python 3.1+ support occurred with numpy 1.5 that was
> > released last year (2010-08-31) - 1.5.1 is the current
> > release. scipy 0.9 due very soon (r
On Friday 25 February 2011 14:22:04 Bruce Southey wrote:
>
> Python 3.1+ support occurred with numpy 1.5 that was released
> last year (2010-08-31) - 1.5.1 is the current release.
> scipy 0.9 due very soon (release candidates are available at
> http://sourceforge.net/projects/scipy/) also support
If there is, then its great news (for me). Where can I check it
out?
Thanks for responding -
Al.
On Friday 25 February 2011 13:14:31 Shao Hong wrote:
> Hi correct me if I am wrong, I thought there is package
> ported for python 3.1 already?
>
--
Algis
http://akabaila.pcug.org.au/StructuralAn
Are there plans to port numpy to Python3? In particular, when
will the packages of Linear Algebra (viz matrix inversion) be
available in Python 3 compatible modules.
Because of the importance of numpy in many scientific endeavours
is so great, information of the availability in Python 3 mode is
On Tuesday 01 February 2011 03:27:22 Sturla Molden wrote:
> Den 31.01.2011 03:05, skrev Algis Kabaila:
> > Actually, the structural engineer
> > has no interest in trying to invert a singular matrix.
> > However he/she is interested (or should be interested :)
> >
>
> And if you are trying to solve a least-squares, I think that
> you should be using a ridge (or Tikhonov) regularisation:
> http://en.wikipedia.org/wiki/Tikhonov_regularization
> read in particular the paragraph above the table of content:
> you are most likely interested in Gamma = alpha ident
On Sunday 30 January 2011 16:35:15 Charles R Harris wrote:
> On Sat, Jan 29, 2011 at 10:11 PM, Algis Kabaila
wrote:
> > On Sunday 30 January 2011 09:10:30 Sturla Molden wrote:
> > > Den 29.01.2011 12:40, skrev Algis Kabaila:
> > > > So my question i
On Sunday 30 January 2011 09:10:30 Sturla Molden wrote:
> Den 29.01.2011 12:40, skrev Algis Kabaila:
> > So my question is: how can one reliably detect singularity
> > (or near singularity) and raise an exception?
>
> Use an SVD, examine the singular values.
I gather tha
On Saturday 29 January 2011 22:47:23 Stuart Brorson wrote:
> > So my question is: how can one reliably detect singularity
> > (or near singularity) and raise an exception?
>
> Matrix condition number:
>
> http://docs.scipy.org/doc/numpy/reference/generated/numpy.lin
> alg.cond.html http://en.wiki
Hi,
I am interested in determining if a matrix is singular or
"nearly singular" - very ill conditioned. The problem occurs in
structural engineering applications.
My OS is kubuntu 10.10 (32 bit)
Python 2.6.6
numpy and numpy.linalg binaries from ubuntu repositories.
The attached tar ball has
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