[SciPy-Dev] sparse rmatvec and maxentropy

[Ralf Gommers]

On Thu, Jan 20, 2011 at 10:13 PM, Skipper Seabold <jsseabold at gmail.com>wrote:

> On Tue, Jan 18, 2011 at 8:12 PM,  <josef.pktd at gmail.com> wrote:
> > On Tue, Jan 18, 2011 at 8:05 PM,  <josef.pktd at gmail.com> wrote:
> >> I don't know much about these two parts of scipy.
> >>
> >> Running an example for scipy.maxentropy raises an exception after
> >> upgrading to scipy trunk
> >>
> >> I didn't manage to find out with a  Trac search whether rmatvec still
> exists.
> >>
>
It was removed in r6996. I missed this one call to it, will clean it up.


> >
> > 3 of the 4 examples in scipy/maxentropy/examples raise an exception. 2
> > of them with the rmatvec not found error. The other one doesn't find
> > scipy.sandbox
> >
>
> I remember seeing the deprecation warnings for this now, but I never
> worked much with the bigmodel.  I think you can just use * now instead
> of the rmatvec for the sparse matrices.  You can see this in 0.8.0
> where both are still there.
>

A.rmatvec(v) should be A.conj().transpose() * v. But that does not make the
examples work, they just fail later on. The one that imports scipy.sandbox
hasn't worked for a while either.

>
> http://projects.scipy.org/scipy/browser/tags/0.8.0/scipy/sparse/base.py
>
> I picked up the montecarlo code when I was playing around with these.
>
>
> http://bazaar.launchpad.net/~jsseabold/statsmodels/statsmodels-skipper-maxent/files/head:/scikits/statsmodels/sandbox/maxentropy/<http://bazaar.launchpad.net/%7Ejsseabold/statsmodels/statsmodels-skipper-maxent/files/head:/scikits/statsmodels/sandbox/maxentropy/>
>
> I'm curious if the maxentropy stuff as it is in scipy wouldn't find
> more use and maintenance in scikits.learn.  The implementation is
> somewhat use specific (natural language processing), though this is
> not by any means set in stone.
>
> Probably, but wouldn't it need a lot of work before it could be moved? It
has a grand total of one test, mostly non-working examples, and is obviously
hardly used at all (see r6919 and r6920 for more examples of broken code).

Perhaps it's worth asking the scikits.learn guys, and otherwise consider
deprecating it if they're not interested?

Cheers,
Ralf
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