[SciPy-user] [Sparse matrix library] csr_matrix and column sum
Mon Apr 28 11:43:26 CDT 2008
On Mon, Apr 28, 2008 at 11:06 AM, Robert Kern <email@example.com> wrote:
> ndarray.sum() accepts a dtype= argument to specify the type of the
> accumulator. You might consider implementing the same thing for sparse
> arrays. Also, ndarray.sum() defaults to int32 (on 32-bit systems,
> int64 on 64-bit systems) as the accumulator dtype for all smaller
> integer types.
I wasn't aware of that feature until now. I've tried to keep the
behavior of scipy.sparse as close to that of numpy matrices, so we
should support user-defined accumulator types.
I've created a ticket for this issue;
It won't require much work to implement, but I can't say when I'll
have the time to carry it out. I think the "right" way is to support
matvec operations y = A*x with different dtypes for A and x/y. This
would allow one to compute A*x for integer A and floating point x
without upcasting A's data array.
Nathan Bell firstname.lastname@example.org
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