On Fri, May 1, 2009 at 7:24 PM, Neal Becker <ndbecker2@gmail.com> wrote:
Charles R Harris wrote:

> On Fri, May 1, 2009 at 1:02 PM, Neal Becker <ndbecker2@gmail.com> wrote:
>> In [16]: (np.linspace (0, len (x)-1, len(x)).astype (np.uint64)*2).dtype
>> Out[16]: dtype('uint64')
>> In [17]: (np.linspace (0, len (x)-1, len(x)).astype (np.uint64)*n).dtype
>> Out[17]: dtype('float64')
>> In [18]: type(n)
>> Out[18]: <type 'int'>
>> Now that's just strange.  What's going on?
> The  n is signed, uint64 is unsigned. So a signed type that can hold
> uint64 is needed. There ain't no such integer, so float64 is used. I think
> the logic here is a bit goofy myself since float64 doesn't have the needed
> 64 bit precision and the conversion from int kind to float kind is
> confusing. I think it would be better to raise a NotAvailable error or
> some such. Lest you think this is an isolated oddity, sometimes numeric
> arrays can be converted to object arrays.
> Chuck

I don't think that any type of integer arithmetic should ever be
automatically promoted to float.

Besides that, what about the first example?  There, I used '2' rather than
'n'.  Is not '2' also an int?

What version of numpy are you using?