[SciPy-dev] Compiling pysparse from the sandbox
Jonathan Guyer
guyer@nist....
Thu Apr 19 07:59:37 CDT 2007
On Apr 18, 2007, at 11:54 PM, Bill Baxter wrote:
> SciPy's sparse matrices also lack any way to operate based on a sparse
> index, which is a fundamental operation in FEM codes. Basically you
> need to be able to do something like
> idx = [1,8,13,15]
> K[ix_[idx,idx]] += node_contribution
>
> pysparse has an update_add_masked function which can do that
> efficiently (although it would obviously be better if regular numpy
> indexing just worked.)
This is one important advantage, although update_add_mask() was not
suitable for our needs (we wanted to build sparse matrices from dense
vectors, rather than building sparse matrices from small dense
matrices). We added (and Roman accepted) an update_add_at() function
that did what we wanted. Either is blindingly faster than what could
be done if SciPy the last time I looked. SciPy's syntax is more
Pythonic, but PySparse can build matrices *much* more efficiently.
More broadly, the advantages of PySparse over SciPy all boil down to
speed. About a year and a half ago, I posted some benchmarking info
to the SciPy wiki, but it went away with the move to the new wiki. I
have no idea where it's gone, and I don't seem to have a copy of it.
It used to be at <http://www.scipy.org/wikis/featurerequests/
SparseSolvers>.
> Sounds great to me. I've toyed with MG, but never got very far.
> Non-power-of-two grids and boundary conditions were too tricksy for
> me. But the O(N) solve time is great if someone else does all the
> hard work for me. :-)
Likewise. We're very interested in multigrid for FiPy, and even more
interested if it doesn't require us to think very hard.
More information about the Scipy-dev
mailing list