[Numpy-discussion] np.longlong casts to int
Thu Feb 23 13:08:48 CST 2012
On Thu, Feb 23, 2012 at 10:55 AM, Matthew Brett <email@example.com>wrote:
> On Thu, Feb 23, 2012 at 10:45 AM, Mark Wiebe <firstname.lastname@example.org> wrote:
> > On Thu, Feb 23, 2012 at 10:42 AM, Matthew Brett <email@example.com
> > wrote:
> >> Hi,
> >> On Thu, Feb 23, 2012 at 10:11 AM, Pierre Haessig
> >> <firstname.lastname@example.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,
> > 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.
> What do you think?
> NumPy-Discussion mailing list
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