[Numpy-discussion] Preliminary thoughts on implementing __matmul__
njs at pobox.com
Wed Aug 6 19:51:18 EDT 2014
On 7 Aug 2014 00:41, "Charles R Harris" <charlesr.harris at gmail.com> wrote:
> On Wed, Aug 6, 2014 at 5:33 PM, Nathaniel Smith <njs at pobox.com> wrote:
>> On Thu, Aug 7, 2014 at 12:24 AM, Charles R Harris
>> <charlesr.harris at gmail.com> wrote:
>> > On Wed, Aug 6, 2014 at 4:57 PM, Nathaniel Smith <njs at pobox.com> wrote:
>> >> On Wed, Aug 6, 2014 at 4:32 PM, Charles R Harris
>> >> <charlesr.harris at gmail.com> wrote:
>> >> > Should also mention that we don't have the ability to operate on
>> >> > vectors because they can't be identified by dimension info. One
>> >> > workaround
>> >> > is to add dummy dimensions where needed, another is to add two
>> >> > row
>> >> > and col, and set them appropriately. Two flags are needed for
>> >> > compatibility, i.e., both false is a traditional array.
>> >> It's possible I could be convinced to like this, but it would take a
>> >> substantial amount of convincing :-). It seems like a pretty big
>> >> violation of orthogonality/"one obvious way"/etc. to have two totally
>> >> different ways of representing row/column vectors.
>> > The '@' operator supports matrix stacks, so it would seem we also need
>> > support vector stacks. The new addition would only be effective with
>> > operator. The main problem I see with flags is that adding them would
>> > require an extensive audit of the C code to make sure they were
>> > Another option, already supported to a large extent, is to have row
>> > classes inheriting from ndarray that add nothing, except for a
>> > transpose type function/method. I did mock up such a class just for
>> > also added a 'dyad' function. If we really don't care to support
>> > vectors we can get by without adding anything.
>> It's possible you could convince me that this is a good idea, but I'm
>> starting at like -0.95 :-). Wouldn't it be vastly simpler to just have
>> np.linalg.matvec, matmat, vecvec or something (each of which are
>> single-liners in terms of @), rather than deal with two different ways
>> of representing row/column vectors everywhere?
> Sure, but matvec and vecvec would not be supported by '@' except when vec
was 1d because there is no way to distinguish a stack of vectors from a
matrix or a stack of matrices.
Yes. But @ can never be magic - either people will have to write something
extra to flip these flags on their array objects, or they'll have to write
something extra to describe which operation they want. @ was never intended
to cover every case, just the simple-but-super-common ones that dot covers,
plus a few more (simple broadcasting). We have np.add even though + exists
-------------- next part --------------
An HTML attachment was scrubbed...
More information about the NumPy-Discussion