[SciPy-user] Ubuntu installation requirements, and wetting my feet.

[Stephen Kelly]

Hi. I emailed this list a while ago about possible subject matter for a
final year project in engineering (
http://news.gmane.org/find-root.php?group=gmane.comp.python.scientific.user&article=8498).
There was no project resulting directly from the mailing list, but I have
now started a project concerning the correction of xray diffraction data
using python. It will mainly be concerned with designing a good user
interface, but could also involve interpolation and plotting, so I want to
see what I can do with scipy in a reasonable time to do this.

The installation instructions on the wiki are a bit confusing. I'm inclined
to get the optimised packages, so:

> To build SciPy <http://scipy.org/SciPy> using optimized lapack and blas on
the ubuntu system you should install atlas-3dnow-dev or atlas-sse2-dev or
atlas-sse3-dev depending on your system.

But those packages are not available in the repos available to me. There are
others with similar names, but I'm not certain which to choose. What
characteristics of my system will affect this?

> atlas2            atlas2-sse-dev    atlas3-headers    atlas-dev
> atlas2-3dnow-dev  atlas3-3dnow      atlas3-sse        atlas-doc
> atlas2-base-dev   atlas3-3dnow-dev  atlas3-sse2       atlas-test
> atlas2-dev        atlas3-base       atlas3-sse2-dev
> atlas2-headers    atlas3-base-dev   atlas3-sse-dev
> atlas2-sse2-dev   atlas3-doc        atlas3-test

On an unrelated matter, I'm already using the numpy deb package provided at
astraw.com, and as a learning excercise started making a mechanics of
materials module for tensor calculations. I'm not sure if numpy/scipy
already provides such functions, so I don't know if this is reinventing the
wheel. To calculate the sencond scalar invariant, I thought an easy way
would be to calculate the trace of the adjoint of the stress tensor I
define. When I went to do it though, I couldn't find any functions in numpy
to get an adjoint of a matrix, or get cofactors. Are these functions
available in numpy or scipy? I've got it working now by multiplying the
inverse of the matrix by the determinant, but if there's a better way I'd
like to know. Also, I'd like to assess the validity of such a stress matrix
by checking if it's symmetric, but I haven't seen any way to do that either.
I thought there might be a foo.isSymmetric() bool, but there doesn't seem to
be, so I tried doing a comparison, if foo == foo.T: etc., but comparison of
matrices doesn't seem to work either. Is the only way to compare them to
loop over them using regular python methods?

Thanks for help on this. I may be seen a bit more on this mailing list once
I get into the computation parts of this project. Is there any interest in
using #scipy on freenode?

Thanks,

Steve
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