[Numpy-discussion] np.longlong casts to int

[Mark Wiebe]

On Thu, Feb 23, 2012 at 10:55 AM, Matthew Brett <matthew.brett at gmail.com>wrote:

> Hi,
>
> On Thu, Feb 23, 2012 at 10:45 AM, Mark Wiebe <mwwiebe at gmail.com> wrote:
> > On Thu, Feb 23, 2012 at 10:42 AM, Matthew Brett <matthew.brett at gmail.com
> >
> > wrote:
> >>
> >> Hi,
> >>
> >> On Thu, Feb 23, 2012 at 10:11 AM, Pierre Haessig
> >> <pierre.haessig at crans.org> wrote:
> >> > Le 23/02/2012 17:28, Charles R Harris a écrit :
> >> >> That's correct. They are both extended precision (80 bits), but
> >> >> aligned on 32bit/64bit boundaries respectively. Sun provides a true
> >> >> quad precision, also called float128, while on PPC long double is an
> >> >> odd combination of two doubles.
> >> > This is insane ! ;-)
> >>
> >> I don't know if it's insane, but it is certainly very confusing, as
> >> this thread the previous one show.
> >>
> >> The question is, what would be less confusing?
> >
> >
> > One approach would be to never alias longdouble as float###. Especially
> > float128 seems to imply that it's the IEEE standard binary128 float,
> which
> > it is on some platforms, but not on most.
>
> It's virtually never IEEE binary128.  Yarik Halchenko found a real one
> on an s/360 running Debian.  Some docs seem to suggest there are Sun
> machines out there with binary128, as Chuck said.  So the vast
> majority of numpy users with float128 have Intel 80-bit, and some have
> PPC twin-float.
>
> Do we all agree then that 'float128' is a bad name?
>
> In the last thread, I had the feeling there was some consensus on
> renaming Intel 80s to:
>
> float128 -> float80_128
> float96 -> float80_96
>
> For those platforms implementing it, maybe
>
> float128 -> float128_ieee
>
> Maybe for PPC:
>
> float128 -> float_pair_128
>
> and, personally, I still think it would be preferable, and less
> confusing, to encourage use of 'longdouble' instead of the various
> platform specific aliases.
>

+1, I think it's good for its name to correspond to the name in C/C++, so
that when people search for information on it they will find the relevant
information more easily. With a bunch of NumPy-specific aliases, it just
creates more hassle for everybody.

-Mark


> What do you think?
>
> Best,
>
> Matthew
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