[Numpy-discussion] np.longlong casts to int

Charles R Harris charlesr.harris@gmail....
Thu Feb 23 10:28:12 CST 2012


On Thu, Feb 23, 2012 at 5:23 AM, Francesc Alted <francesc@continuum.io>wrote:

> On Feb 23, 2012, at 6:06 AM, Francesc Alted wrote:
> > On Feb 23, 2012, at 5:43 AM, Nathaniel Smith wrote:
> >
> >> On Thu, Feb 23, 2012 at 11:40 AM, Francesc Alted <francesc@continuum.io>
> wrote:
> >>> Exactly.  I'd update this to read:
> >>>
> >>> float96    96 bits.  Only available on 32-bit (i386) platforms.
> >>> float128  128 bits.  Only available on 64-bit (AMD64) platforms.
> >>
> >> Except float96 is actually 80 bits. (Usually?) Plus some padding…
> >
> > Good point.  The thing is that they actually use 96 bit for storage
> purposes (this is due to alignment requirements).
> >
> > Another quirk related with this is that MSVC automatically maps long
> double to 64-bit doubles:
> >
> > http://msdn.microsoft.com/en-us/library/9cx8xs15.aspx
> >
> > Not sure on why they did that (portability issues?).
>
> Hmm, yet another quirk (this time in NumPy itself).  On 32-bit platforms:
>
> In [16]: np.longdouble
> Out[16]: numpy.float96
>
> In [17]: np.finfo(np.longdouble).eps
> Out[17]: 1.084202172485504434e-19
>
> while on 64-bit ones:
>
> In [8]: np.longdouble
> Out[8]: numpy.float128
>
> In [9]: np.finfo(np.longdouble).eps
> Out[9]: 1.084202172485504434e-19
>
> i.e. NumPy is saying that the eps (machine epsilon) is the same on both
> platforms, despite the fact that one uses 80-bit precision and the other
> 128-bit precision.  For the 80-bit, the eps should be ():
>
>
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.

Chuck

> In [5]: 1 / 2**63.
>
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