On 10-Apr-2014 3:58 PM, njsmith 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

      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.
        Hope that helps,
        -n
    
    Nathaniel,
    I'm not trying to insinuate anything.  You don't quote the words
    that you are troubled by.
    What I intended to convey was that the scikit material was likely
    developed prior to the Numarray period in the evolution of Numpy.  I
    believe that the Matrix class was introduce during the Numarray
    time.  In about 2007, I think, Travis Olliphant took over
    development, under the original name - Numpy and continued the
    Matrix class.
    I was pleased to see that the Matrix class was introduced and
    continued, as it provides for provides for a different type of data.
    Unfortunately, you provide no examples of how the class failed to
    meet your needs.  I hope to be be able to put together a critical
    analysis of PEP 465.
    Best wishes,
    Colin W.
    Colin W.
      
        On Thu, Apr 10, 2014 at 1:54 PM,
          Colin J. Williams <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 09-Apr-2014 3:38 PM, Lars
          Buitinck 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 I don't think any of the sklearn uses of * is a matrix
          multiplication. — Reply to this email directly or view it on
          GitHub. Perhaps this is because much of the SciPy was
          developed before the the Numarray (Space Telescope) people
          took over the maintenance. It seems to me that there is merit
          in recognizing the Matrix, and perhaps the Vector, as separate
          data types (Classes). Colin W. Colin W. — Reply to this email
          directly or view it on GitHub<https://github.com/numpy/numpy/pull/4351/files#r11482704>

          .
        
        -- Nathaniel J. Smith
          Postdoctoral researcher - Informatics - University of
          Edinburgh
          http://vorpus.org
        
      
      —
        Reply to this email directly or view
          it on GitHub.