Charles,
Nothing I've seen so far envisages disturbing the existing, in my
opinion flawed, Matrix Class.
I trust that I have not missed anything.
Compilation is a complex press for a person unfamiliar with the C.
Anything you could do to simplify that would be welcome.
Colin W.
On 12/08/2014 1:50 PM, Charles R Harris wrote:
On Tue, Aug 12, 2014 at 8:26 AM, Nathaniel Smith <n...@pobox.com
<mailto:n...@pobox.com>> wrote:
Hi Matt,
On Mon, Aug 11, 2014 at 10:46 PM, Matti Picus
<matti.pi...@gmail.com <mailto:matti.pi...@gmail.com>> wrote:
> Hi Nathaniel.
> Thanks for your prompt reply. I think numpy is a wonderful
project, and you
> all do a great job moving it forward.
> If you ask what would my vision for maturing numpy, I would like
to see a
> grouping of linalg matrix-operation functionality into a python
level
> package, exactly the opposite of more tightly tying linalg into
the core of
> numpy.
As I understood it (though I admit Chuck was pretty terse, maybe he'll
correct me :-)), what he was proposing was basically just a build
system reorganization -- it's much easier to call between C functions
that are in the same Python module than C functions that are in
different modules, so we end up with lots of boilerplate gunk for the
latter. I don't think it would involve any tighter coupling than we
already have in practice.
I'm trying to think of the correct sequence of moves. Here are my
current thoughts.
* Move _dotblas down into multiarray
1. When there is cblas, add cblas implementations of decr->f->dot.
2. Reimplement API matrixproduct2
3. Make ndarray.dot a first class method and use it for numpy.dot.
* Implement matmul
1. Add matrixmultiply (matmul?) to the numpy API
2. Implement __matmul__ method.
3. Add functions to linalg for stacked vectors.
4. Make sure __matmul__ works with __numpy_ufunc__
*
Consider using blas_lite instead of cblas, but that is now independent
of the previous steps.
<snip>
Chuck
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