On 07/07/2006, at 6:26 AM, Travis Oliphant wrote:
> 1) .T Have some kind of .T attribute
-1
The meaning of .T is unclear for ndim != 2, as the plethora of sub-
vote options shows. And we already have a matrix object designed
explicitly for the case ndim == 2. Let's make matrix objects more
useful, rather than give up on matrices and hard-wire 2d concepts
into arrays. I'm willing to help with this, and I'll post some ideas
to a different thread.
> If >0 on this then:
>
> a) .T == .swapaxes(-2,-1)
>
> b) .T == .transpose()
>
> c) .T raises error for ndim > 2
>
> d) .T returns (N,1) array for length (N,) array
>
> e) .T returns self for ndim < 2
(Just for the record, I think option (d) is positively evil.)
> 2) .H returns .T.conj()
-1
I'm against this for the same reasons I'm against .T, but more
strongly, due to the extra memory allocation.
> 3) .M returns matrix version of array
-0
This would have the advantage of making .T and .H redundant for 2-d
arrays, since they'd be accessible as matrix attributes anyway. But I
don't see a strong enough case for this as an extra attribute, since
asmatrix() and mat() are available anyway.
I would like to deprecate mat() as an alias for matrix (by moving mat
to the oldnumeric namespace); this would break the expectation that
mat() perform a copy, and allow users to write
>>> from numpy import asmatrix as mat
instead if they need a short, simple syntax that avoids the copy
overhead.
It's also trivial for any serious user of matrices to write wrapper
functions for ones, zeros, etc., such as
def matones(*args):
return asmatrix(ones(*args))
There might be an argument for including these in e.g. the
numpy.matrix namespace. This would make a .M attribute even less
compelling.
> 4) .A returns basearray (useful for sub-classes).
-0
This could be a good idea, but I'm not clear enough on its
implications to vote either way.
-- Ed
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