[Numpy-discussion] float96 on windows32 is float64?
Matthew Brett
Am I right in thinking that float96 on windows 32 bit is a float64
padded to 96 bits? If so, is it useful? Has anyone got a windows64
box to check float128 ?
Python 2.7.1 (r271:86832, Nov 27 2010, 18:30:46) [MSC v.1500 32 bit
(Intel)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import numpy as np
>>> np.__version__
'1.6.1'
>>> info = np.finfo(np.float96)
>>> print info
Machine parameters for float96
---------------------------------------------------------------------
precision= 15 resolution= 1e-15
machep= -52 eps= 2.22044604925e-16
negep = -53 epsneg= 1.11022302463e-16
minexp=-16382 tiny= 0.0
maxexp= 16384 max= 1.#INF
nexp = 15 min= -max
---------------------------------------------------------------------
>>> info.nmant
52
Confirming 52 (+1 implicit) significand digits
>>> np.float96(2**52)+1
4503599627370497.0
>>> np.float96(2**53)+1
9007199254740992.0
float96 claims 15 exponent digits (nexp above), but in fact it appears
to have 11, as does float64
>>> np.float64(2**1022) * 2
8.9884656743115795e+307
>>> np.float64(2**1022) * 4
__main__:1: RuntimeWarning: overflow encountered in double_scalars
inf
>>> np.float96(2**1022) * 2
8.9884656743115795e+307
>>> np.float96(2**1022) * 4
1.#INF
It does take up 12 bytes (96 bits)
>>> np.dtype(np.float96).itemsize
12
Thanks,
Matthew
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David Cournapeau
Hi,
Am I right in thinking that float96 on windows 32 bit is a float64
padded to 96 bits?
If so, is it useful?
Has anyone got a windows64
box to check float128 ?
Charles R Harris
Wait, MSVC doesn't support extended precision, so how do we get doubles padded to 96 bits? I think MINGW supports extended precision but the MS libraries won't. Still, if it's doubles it should be 64 bits and float96 shouldn't exist. Doubles padded to 96 bits are 150% pointless.
Chuck
Matthew Brett
On Thu, Mar 15, 2012 at 9:17 PM, David Cournapeau <cour...@gmail.com> wrote:
>
>
> On Thu, Mar 15, 2012 at 11:10 PM, Matthew Brett <matthe...@gmail.com>
> wrote:
>>
>> Hi,
>>
>> Am I right in thinking that float96 on windows 32 bit is a float64
>> padded to 96 bits?
>
>
> Yes
>
>>
>> If so, is it useful?
>
>
> Yes: this is what allows you to use dtype to parse complex binary files
> directly in numpy without having to care so much about those details. And
> that's how it is defined on windows in any case (C standard only forces you
> to have sizeof(long double) >= sizeof(double)).
I propose then to rename this one to float64_96 .
The nexp value in finfo(np.float96) is incorrect I believe, I'll make
a ticket for it.
>> Has anyone got a windows64
>> box to check float128 ?
>
>
> Too lazy to check on my vm, but I am pretty sure it is 16 bytes on windows
> 64.
Should you have time to do that, could you confirm it's also a padded
float64 and that nexp is still (incorrectly) 15? That would be a
great help,
Matthew Brett
I think David is arguing that longdouble for MSVC is indeed a 96 bit
padded float64 unless I misunderstand him.
If we were thinking of trade-offs I suppose one could argue that the
confusion and wasted memory of float96 might outweigh the simple
ability to read in binary files containing these values, on the basis
that one can do it anyway (by using a structured array dtype) and that
such files must be very rare in practice.
See you,
Val Kalatsky
Benjamin Root
Ben Root
Matthew Brett
On Thu, Mar 15, 2012 at 9:33 PM, Val Kalatsky <kala...@gmail.com> wrote:
>
> I just happened to have an xp64 VM running:
> My version of numpy (1.6.1) does not have float128 (see more below what I
> get in ipython session).
> If you need to test something else please let me know.
Thanks a lot - that's helpful. What do you get for:
print np.finfo(np.longdouble)
?
Best,
Val Kalatsky
Warren Weckesser
I does look like a joke.Here is print np.finfo(np.longdouble)In [2]: np.__version__Out[2]: '1.6.1'In [3]: np.flonp.float np.float32 np.float_ np.floornp.float16 np.float64 np.floating np.floor_divideIn [3]: print np.finfo(np.longdouble)Machine parameters for float64---------------------------------------------------------------------precision= 15 resolution= 1e-15machep= -52 eps= 2.22044604925e-16negep = -53 epsneg= 1.11022302463e-16minexp= -1022 tiny= 2.22507385851e-308maxexp= 1024 max= 1.79769313486e+308nexp = 11 min= -max---------------------------------------------------------------------
In this case (Win64), np.longdouble is just an alias for np.float64:
In [16]: sys.version
Out[16]: '2.7.2 |EPD 7.2-2 (64-bit)| (default, Sep 14 2011, 11:25:00) [MSC v.1500 64 bit (AMD64)]'
In [17]: np.__version__
Out[17]: '1.6.1'
In [18]: np.longdouble
Out[18]: numpy.float64
Warren
Matthew Brett
On Thu, Mar 15, 2012 at 9:41 PM, Val Kalatsky <kala...@gmail.com> wrote:
> I does look like a joke.
> Here is print np.finfo(np.longdouble)
>
> In [2]: np.__version__
> Out[2]: '1.6.1'
>
> In [3]: np.flo
> np.float np.float32 np.float_ np.floor
> np.float16 np.float64 np.floating np.floor_divide
>
> In [3]: print np.finfo(np.longdouble)
> Machine parameters for float64
> ---------------------------------------------------------------------
> precision= 15 resolution= 1e-15
> machep= -52 eps= 2.22044604925e-16
> negep = -53 epsneg= 1.11022302463e-16
> minexp= -1022 tiny= 2.22507385851e-308
> maxexp= 1024 max= 1.79769313486e+308
> nexp = 11 min= -max
> ---------------------------------------------------------------------
Great - much easier on the eye - longdouble is float64 as expected.
Thanks,
Ilan Schnell
EPD test machines. I guess Windows does not support 128
bit floats.
I did some tests a few weeks ago, and discovered that also
on the Mac and Linux long long double is not really 128 bits.
If I remember correctly it was 80 bits: 1 (sign) + 16 (exp) + 63 (mantissa)
- Ilan
Matthew Brett
On Thu, Mar 15, 2012 at 10:17 PM, Ilan Schnell <isch...@enthought.com> wrote:
> I'm seeing the same thing on both (64 and 32-bit) Windows
> EPD test machines. I guess Windows does not support 128
> bit floats.
Do you mean there is no float96 on windows 32 bit as I described at
the beginning of the thread?
> I did some tests a few weeks ago, and discovered that also
> on the Mac and Linux long long double is not really 128 bits.
> If I remember correctly it was 80 bits: 1 (sign) + 16 (exp) + 63 (mantissa)
Yes, that's right, on Intel for linux and OSX longdouble is 80 bit precision.
Ilan Schnell
machines I don't see.float96 as well as np.float128
- Ilan
Matthew Brett
On Thu, Mar 15, 2012 at 10:26 PM, Ilan Schnell <isch...@enthought.com> wrote:
> To be more precise. On both 32-bit and 64-bit Windows
> machines I don't see.float96 as well as np.float128
Do you have any idea why I am seeing float96 and you are not? I'm on
XP with the current sourceforge 1.6.1 exe installer with python.org
2.7 (and same for python.org 2.6 and numpy 1.5.1).
Ilan Schnell
win-64: float96 No, float128 No
win-32: float96 No, float128 No
osx-64: float96 No, float128 Yes
osx-32: float96 No, float128 Yes
rh3-64: float96 No, float128 Yes
rh3-32: float96 Yes, float128 No
rh5-64: float96 No, float128 Yes
rh5-32: float96 Yes, float128 No
sol-64: float96 No, float128 Yes
sol-32: float96 Yes, float128 No
I have no explanation for this, but I'm guessing David C. has.
I'll look more into this tomorrow.
- Ilan
josef...@gmail.com
> I just did a quick test across all supported EPD platforms:
> win-64: float96 No, float128 No
> win-32: float96 No, float128 No
> osx-64: float96 No, float128 Yes
> osx-32: float96 No, float128 Yes
> rh3-64: float96 No, float128 Yes
> rh3-32: float96 Yes, float128 No
> rh5-64: float96 No, float128 Yes
> rh5-32: float96 Yes, float128 No
> sol-64: float96 No, float128 Yes
> sol-32: float96 Yes, float128 No
numpy 1.5.1 MingW, on python 2.6 win32 has float96, float128 no
numpy 1.6.1 Gohlke (MKL I think) on python 3.2 win64 no float96, no float128
Josef
Matthew Brett
On Fri, Mar 16, 2012 at 5:36 AM, <josef...@gmail.com> wrote:
> On Fri, Mar 16, 2012 at 2:10 AM, Ilan Schnell <isch...@enthought.com> wrote:
>> I just did a quick test across all supported EPD platforms:
>> win-64: float96 No, float128 No
>> win-32: float96 No, float128 No
>> osx-64: float96 No, float128 Yes
>> osx-32: float96 No, float128 Yes
>> rh3-64: float96 No, float128 Yes
>> rh3-32: float96 Yes, float128 No
>> rh5-64: float96 No, float128 Yes
>> rh5-32: float96 Yes, float128 No
>> sol-64: float96 No, float128 Yes
>> sol-32: float96 Yes, float128 No
>
>
> numpy 1.5.1 MingW, on python 2.6 win32 has float96, float128 no
> numpy 1.6.1 Gohlke (MKL I think) on python 3.2 win64 no float96, no float128
>
> Josef
>
>>
>> I have no explanation for this, but I'm guessing David C. has.
>> I'll look more into this tomorrow.
>>
>> - Ilan
Oh dear - I completely forgot the previous thread that I started on
this : http://mail.scipy.org/pipermail/numpy-discussion/2011-November/059233.html
You young people, don't laugh, this will happen to you one day.
Anyway, summarizing, it appears that windows float96:
a) Is stored as an 80 bit extended precision number
b) Uses float64 precision for all calculations.
c) Is specific to MingW builds of numpy - I think.
Perhaps David C you'll correct me if I've got that wrong,
Best,