> I vote for CONVERTING and in addition we should implement a common
test suite that checks for input types/shape of our estimators (AFAIR
this was proposed by Mathieu a while ago).
+1
On 20 October 2011 14:15, Peter Prettenhofer
<[email protected]>wrote:
> Thanks for raising this issue Lars.
>
> I vote for CONVERTING and in addition we should implement a common
> test suite that checks for input types/shape of our estimators (AFAIR
> this was proposed by Mathieu a while ago).
>
> best,
> Peter
>
> 2011/10/20 Lars Buitinck <[email protected]>:
> > Dear all,
> >
> > At https://github.com/scikit-learn/scikit-learn/issues/392 there's
> > been some discussion on whether to accept data of type np.matrix or
> > not. I'd like to take that discussion here and resolve it with a quick
> > vote, if possible.
> >
> > The issue is: many modules currently fail when handed an np.matrix. We
> > can resolve this by...
> >
> > CONVERTING to np.ndarray
> > * matrices are obviously array-like
> > * matrices may come about inadvertently, because some NumPy/SciPy
> > routines/methods happen to return them
> > * we loosely use the term "matrix" throughout the docs, so it would be
> > strange to require a matrix not to be an np.matrix
> > * we are (or should be) doing input validation anyway, with
> > utils.{safe_asanyarray, as_float_array, atleast2d_or_csr}
> > * we already need to handle the matrix API in all modules that accept
> > sparse input
> > * backwards compatibility
> >
> > REJECTING np.matrix by throwing a TypeError
> > * mathematical operators may have different meanings than on array (*
> > means dot product on matrix, Hadamard product on arrays)
> > * matrices are always 2-d, so ravel, flatten and reshape don't behave
> > as expected
> > * converting to array is easy enough for the user: just call .A on every
> matrix
> > * explicit is better than implicit
> > * we'd need to test every routine against matrices (but then, we
> > should be testing input validation anyway)
> >
> > Please voice your opinions. I'm willing to write up some docs
> > describing whichever option we choose.
> >
> > TIA,
> >
> > --
> > Lars Buitinck
> > Scientific programmer, ILPS
> > University of Amsterdam
> >
> >
> ------------------------------------------------------------------------------
> > The demand for IT networking professionals continues to grow, and the
> > demand for specialized networking skills is growing even more rapidly.
> > Take a complimentary Learning@Ciosco Self-Assessment and learn
> > about Cisco certifications, training, and career opportunities.
> > http://p.sf.net/sfu/cisco-dev2dev
> > _______________________________________________
> > Scikit-learn-general mailing list
> > [email protected]
> > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
> >
>
>
>
> --
> Peter Prettenhofer
>
>
> ------------------------------------------------------------------------------
> The demand for IT networking professionals continues to grow, and the
> demand for specialized networking skills is growing even more rapidly.
> Take a complimentary Learning@Ciosco Self-Assessment and learn
> about Cisco certifications, training, and career opportunities.
> http://p.sf.net/sfu/cisco-dev2dev
> _______________________________________________
> Scikit-learn-general mailing list
> [email protected]
> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
>
--
He is no fool who gives what he cannot keep to gain what he cannot lose.
- Jim Elliot.
------------------------------------------------------------------------------
The demand for IT networking professionals continues to grow, and the
demand for specialized networking skills is growing even more rapidly.
Take a complimentary Learning@Ciosco Self-Assessment and learn
about Cisco certifications, training, and career opportunities.
http://p.sf.net/sfu/cisco-dev2dev
_______________________________________________
Scikit-learn-general mailing list
[email protected]
https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
