[Numpy-discussion] Release of NumPy

[Alan Isaac]

> On 16/04/2008, Alan G Isaac <aisaac@american.edu> wrote:
>> The rule is:
>>  to get a submatrix,
>>  use multiple indices.

On Wed, 16 Apr 2008, Stéfan van der Walt wrote:
> That is not the rule for arrays; you argued the compatibility point yourself. 

Sorry, I do not understand.
I am saying only:
I propose no change in current matrix behavior
in response to nonscalar indexes.


On Wed, 16 Apr 2008, Stéfan van der Walt wrote:
> Are you opposed to fixing the problem the way Tim 
> suggested?

It seems lots of complexity for a payoff I do not see.
My proposal is simpler and stays closer to ndarray behavior.
But having a matrix be a container of such "RowVectors" is 
better than the current behavior.  I do not see that it
gets in the way of anything desirable, as long as the
array attribute of your "vectors" will return a 1d array.


> Why would linear algebra users prefer 1d arrays instead of vectors? 

What is a "vector"?
To me a vector is an element of a vector space.
As far as I can tell, a 1d array *is* a vector.

If you mean by "vector" what people mean when
they say "row vector" or "column vector",
this is just short hand for special matrices.
If I want these special matrices, I can have
them right now.  Of course I cannot index the
elements with a scalar...

Cheers,
Alan Isaac