On Feb 23, 2012, at 10:26 AM, Matthew Brett wrote: > Hi, > > On Thu, Feb 23, 2012 at 4:23 AM, Francesc Alted <franc...@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 <franc...@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 (): >> >> In [5]: 1 / 2**63. >> Out[5]: 1.0842021724855044e-19 >> >> [http://en.wikipedia.org/wiki/Extended_precision] >> >> which is correctly stated by NumPy, while for 128-bit (quad precision), eps >> should be: >> >> In [6]: 1 / 2**113. >> Out[6]: 9.62964972193618e-35 >> >> [http://en.wikipedia.org/wiki/Quadruple-precision_floating-point_format] >> >> If nobody objects, I'll file a bug about this. > > There was half a proposal for renaming these guys in the interests of clarity: > > http://mail.scipy.org/pipermail/numpy-discussion/2011-October/058820.html
Oh, my bad. thanks for pointing this out! > I'd be happy to write this up as a NEP. Or even better, adapt the docs to say something like: float96 96 bits storage, 80-bit precision. Only available on 32-bit platforms. float128 128 bits storage, 80-bit precision. Only available on 64-bit platforms. -- Francesc Alted _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
