> 
>  Travis Oliphant wrote:
> 
>  > This is the gist of it.  Basically you extend the Python scalars to
>  > include the single precision types (all the types Numeric supports).
> 
>  Would they be recognised as scalars by Python? In particular, could you
>  use one as an index? Personally, this is what has bit me in the past: I
>  could use A[3,2] as an index if A was type "Int" but not if it was
>  "Int16" for example.
> 
>  In any case, the type of A[3,2] should NOT depend on the precision of
>  the numbers stored in A.
> 
>  Frankly, I have no idea what the implimentation details would be, but
>  could we get rid of rank-0 arrays altogether? I have always simply found
>  them strange and confusing... What are they really neccesary for
>  (besides holding scalar values of different precision that standard
>  Pyton scalars)?

With new coercion rules this becomes a possibility.  Arguments against it
are that special rank-0 arrays behave as more consistent numbers with the
rest of Numeric than Python scalars.  In other words they have a length
and a shape and one can right N-dimensional code that works the same even
when the result is a scalar.

Another advantage of having a Numeric scalar is that we can control the
behavior of floating point operations better.

e.g.

if only Python scalars were available and sum(a) returned 0, then

 1 / sum(a)  would behave as Python behaves (always raises error).

while with our own scalars

1 / sum(a)   could potentially behave however the user wanted.


-Travis






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