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 <njs@pobox.com> wrote:

Hi Matt,

As I understood it (though I admit Chuck was pretty terse, maybe he'll

On Mon, Aug 11, 2014 at 10:46 PM, Matti Picus <matti.picus@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.

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.<snip>

- Move _dotblas down into multiarray

- When there is cblas, add cblas implementations of decr->f->dot.
- Reimplement API matrixproduct2
- Make ndarray.dot a first class method and use it for numpy.dot.
- Implement matmul

- Add matrixmultiply (matmul?) to the numpy API
- Implement __matmul__ method.
- Add functions to linalg for stacked vectors.
- Make sure __matmul__ works with __numpy_ufunc__
Consider using blas_lite instead of cblas, but that is now independent

of the previous steps.

Chuck

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