[SciPy-user] Left hand sparse matrix multiplication
Wed Oct 8 10:41:48 CDT 2008
I'm trying to compute x*A where x is a dense row vector and A is a
sparse CSC matrix. A.rmatvec seems to do what I want but is wasteful
as it computes:
self.transpose().matvec( other )
i.e. it computes A^T * x^T.
It seems there should be a much more efficient overload for csc's
rmatvec which doesn't involve computing the transpose. I hope i'm
understanding things correctly.
On Tue, Oct 7, 2008 at 9:12 PM, Anne Archibald
> 2008/10/7 Neilen Marais <email@example.com>:
>> I have a real sparse matrix that I factorized using
>> scipy.sparse.linalg.dsolve.factorized(). When I solve it with a complex
>> RHS, I always get a real return. Do I need to set the matrix type as
>> complex in this case, or is there a better way?
> If all you're doing is solving y = A*x, then you can simply solve for
> the real and imaginary parts separately, since a real matrix won't mix
> them and the problem is linear.
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