There are several packages for matrix algebra. I tried Numeric, numpy andThat argument might have been valid 3 years ago, but as already said
numarray. All three are very good, but each uses different syntax.
by others, Numeric and Numarray are deprecated. Numpy should be the
only thing needed for new users. I suggest you investigate a little
bit more the next time you make such efforts, since this fact should
be widely known among the users of the mentioned packages, see e.g.
the huge warning at the numarray page:
http://www.stsci.edu/resources/softw.../numarray.html
1. Is there any interest in matrix algebra "for the masses" (I mean interestIn my opinion, no. I might be biased, since with my matlab background
in a wrapper for a subset of functions of the packages with a unified
simple syntax)?
I find numpy simple enough as is. But I don't see how A = B*C+D or
E=dot(F,G) is complicated for a beginner of linear algebra.
My OS is Linux (openSUSE 10.3) and my interest in retirement is PythonIf you care about contributing something useful to the community, I
applications to Structural Analysis of Civil Engineering structures,
currently in 2 dimensions only (under GPL). Modern Structural Analysis is
highly matrix oriented, but requires only a few basic matrix operations,
namely matrix creation, transposition, multiplication, invertion and
linear equation solution. For stability analysis one would require
Eigenvalues and Eigenvectors. In 3 dimensions, additionally highly
desirable would be vector algebra. The packages do have all these
functions, but currently only the basic functions are in the wrapper.
think your time and skills are better spent writing some cool
mechanical analysis tool for inclusion in Scipy.
Bas