I know it can be frustrating to feel like you're being ignored, and I'm
trying to be constructive, but if you're going to reply to my post saying
"please engage with the specific points instead of just repeating
assertions over and over" by repeating vague assertions and ignoring
specific points then I've kind of run out of responses.

A PEP which has, in fact, convinced the BDFL and (apparently) the rest of
the Python core team is, by definition, convincing. Maybe we were all
*wrong* to be convinced, it's always possible. But asserting that it isn't
convincing and saying nothing else just makes it sound like you think we're
all idiots.

(To be clear, there's nothing wrong with thinking we're all idiots. That
could be true to. But as a practical matter it's not going to produce any
of the changes in behaviour that you're hoping for.)

On Thu, Apr 10, 2014 at 10:05 PM, Robert Bradshaw
<notifications@github.com>wrote:

> In doc/neps/return-of-revenge-of-matmul-pep.rst:
>
> > +much larger than both projects put together (stdlib: 411575 SLOC,
> > +scikit-learn: 50924 SLOC, nipy: 37078 SLOC). [#sloc-details]
> > +
> > +The **dot** row (marked ``******``) counts how common matrix multiply
> > +operations are in each codebase.
> > +
> > +::
> > +
> > +    ====  ======  ============  ====  ========
> > +      op  stdlib  scikit-learn  nipy  combined
> > +    ====  ======  ============  ====  ========
> > +       =    2969          5536  4932      3376 / 10,000 SLOC
> > +       -     218           444   496       261
> > +       +     224           201   348       231
> > +      ==     177           248   334       196
> > +       *     156           284   465       192
>
> On Thu, Apr 10, 2014 at 12:58 PM, njsmith <notifications@github.com>
> wrote: Hi Colin, I honestly have no idea what you're trying to insinuate
> about the connection between the Space Telescope, SciPy, and scikit-learn
> (??), but I don't think it's helping anything. Nor is simply posting over
> and over in different forums that you like Matrix and Vector classes. We
> know that now :-). But just saying that is not going to convince anyone to
> like them with you. Realistically, my best guess is that nothing you say is
> likely to convince anyone of anything, given that np.matrix has come to its
> present state of poor reputation through years of experience, and it isn't
> clear you even understand why most numpy developers and users are convinced
> that the approach is fundamentally flawed and unfixable. But if you really
> want to try, then the place to do that is the numpy-discussion list, and
> the way to do that is to understand and engage with specific the problems
> people have raised.
> This keeps coming up (and not by just one or two isolated people) because
> the PEP doesn't convincingly show that a better Matrix class than np.matrix
> isn't a viable alternative.
>
> —
> Reply to this email directly or view it on GitHub<https://github.com/numpy/numpy/pull/4351/files#r11506487>
> .
>



-- 
Nathaniel J. Smith
Postdoctoral researcher - Informatics - University of Edinburgh
http://vorpus.org