[SciPy-user] Numpy/SciPy and performance optimizations

Georg Holzmann grh@mur...
Wed Jan 7 08:23:43 CST 2009


> I have had best luck with boost::ublas.  Limited to 2d though.
> blitz is very nice, but 2 problems:
> suffers from lots of old cruft from supporting ancient c++ compilers
> Poorly maintained - future uncertain IMO.

For me the biggest problem with blitz++ is, that it is very unintuitive 
and slow to write blas-like statements.

> MTL is moving extremely slowly.
> One very active project is eigen.  I haven't used it myself.

Thanks for the hint to eigen (http://eigen.tuxfamily.org/), I did not 
know this library - it looks very promising (although there are no 
benchmarks for sparse operations, I should try that!).

Do you also know if this library is well maintained ?
I am now using a very nice c++ lib (flens: 
http://flens.sourceforge.net/), but with a very unforeseeable future 
(and many dependencies, hard to build) ...

However, what I mainly wanted to ask was, how you use boost::ublas or 
eigen with numpy/scipy - how both systems are combined ?
For me ATM the optimal way would be to use e.g. eigen in weave like now 
blitz++ is used in weave ...


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