[SciPy-User] Sparse matrices and dot product

josef.pktd@gmai... josef.pktd@gmai...
Sun Nov 28 20:56:59 CST 2010

On Sun, Nov 28, 2010 at 9:32 PM, Nathaniel Smith <njs@pobox.com> wrote:
> On Sun, Nov 28, 2010 at 7:16 AM, Pauli Virtanen <pav@iki.fi> wrote:
>> However, I believe 'dot' should be left to be there. `ndarrays` recently
>> gained the same method for matrix products, so it makes sense to leave it
>> be also for sparse matrices. This has also the advantage that it becomes
>> possible to write generic code that works both on sparse matrices and on
>> ndarrays.
> If it's been decided that ndarray's should have a dot method, then I
> agree that sparse matrices should too -- for compatibility. But it
> doesn't actually solve the problem of writing generic code. If A is
> dense and B is sparse, then A.dot(B) still won't work.
> I just spent a few minutes trying to work out if this is fixable by
> defining a protocol -- you need like an  __rdot__ or something? -- but
> didn't come up with anything I'd want to actually recommend.
> (In fact, there are lots of other problems with writing generic code,
> like the behavior of __mul__ and the way sparse matrices like to turn
> all dense results into np.matrix's instead of np.ndarray's. The API
> seems designed on the assumption that everyone will use np.matrix
> instead of np.ndarray for everything, which I guess is fine, but since
> I personally never touch np.matrix my generic code ends up pretty
> ugly. I don't see how to do better without serious API breakage *and*
> a lot more cooperation from numpy. The only full solution might be to
> add sparse matrix support to numpy, and eventually deprecate
> scipy.sparse?)
> In the mean time, maybe it would be a good deed to add this to scipy.sparse?:
> def spdot(A, B):
>  "The same as np.dot(A, B), except it works even if A or B or both
> might be sparse."
>  if issparse(A) and issparse(B):
>    return A * B
>  elif issparse(A) and not issparse(B):
>    return (A * B).view(type=B.__class__)
>  elif not issparse(A) and issparse(B):
>    return (B.T * A.T).T.view(type=A.__class__)
>  else:
>    return np.dot(A, B)

maxentropy has some similar functions that wrap dense and sparse, e.g.


that might be neglected and not up-to-date


> -- Nathaniel
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