On 28.07.2014 23:32, Eelco Hoogendoorn wrote:
> I see, thanks for the clarification. Just for the sake of argument,
> since unfortunately I don't have the time to go dig in the guts of numpy
> myself: a design which always produces results of the same (high)
> accuracy, but only optimizes the commo
I see, thanks for the clarification. Just for the sake of argument, since
unfortunately I don't have the time to go dig in the guts of numpy myself:
a design which always produces results of the same (high) accuracy, but
only optimizes the common access patterns in a hacky way, and may be
inefficie
On Mo, 2014-07-28 at 16:31 +0200, Eelco Hoogendoorn wrote:
> Sebastian:
>
>
> Those are good points. Indeed iteration order may already produce
> different results, even though the semantics of numpy suggest
> identical operations. Still, I feel this different behavior without
> any semantical cl
I had to move my development enviroment on different windows box recently
(stilll in progress). On this box I don't have full access unfortunately.
The patch for scipy build was merged into scipy master some time ago, see
https://github.com/scipy/scipy/pull/3484 . I have some additional patches
for
2014-07-28 15:25 GMT+02:00 Carl Kleffner :
> Hi,
>
> on https://bitbucket.org/carlkl/mingw-w64-for-python/downloads I uploaded
> 7z-archives for mingw-w64 and for OpenBLAS-0.2.10 for 32 bit and for 64 bit.
> To use mingw-w64 for Python >= 3.3 you have to manually tweak the so called
> specs file -
Sebastian:
Those are good points. Indeed iteration order may already produce different
results, even though the semantics of numpy suggest identical operations.
Still, I feel this different behavior without any semantical clues is
something to be minimized.
Indeed copying might have large speed i
On Mo, 2014-07-28 at 15:50 +0200, Fabien wrote:
> On 28.07.2014 15:30, Daπid wrote:
> > An example using float16 on Numpy 1.8.1 (I haven't seen diferences with
> > float32):
>
> Why aren't there differences between float16 and float32 ?
>
float16 calculations are actually float32 calculations. I
On Mo, 2014-07-28 at 15:35 +0200, Sturla Molden wrote:
> On 28/07/14 15:21, alex wrote:
>
> > Are you sure they always give different results? Notice that
> > np.ones((N,2)).mean(0)
> > np.ones((2,N)).mean(1)
> > compute means of different axes on transposed arrays so these
> > differences 'cance
On 28.07.2014 15:30, Daπid wrote:
> An example using float16 on Numpy 1.8.1 (I haven't seen diferences with
> float32):
Why aren't there differences between float16 and float32 ?
Could this be related to my earlier post in this thread where I
mentioned summation problems occurring much earlier i
On 28/07/14 15:21, alex wrote:
> Are you sure they always give different results? Notice that
> np.ones((N,2)).mean(0)
> np.ones((2,N)).mean(1)
> compute means of different axes on transposed arrays so these
> differences 'cancel out'.
They will be if different algorithms are used. np.ones((N,2)
On 28 July 2014 14:46, Sebastian Berg wrote:
> > To rephrase my most pressing question: may np.ones((N,2)).mean(0) and
> > np.ones((2,N)).mean(1) produce different results with the
> > implementation in the current master? If so, I think that would be
> > very much regrettable; and if this is a m
Hi,
on https://bitbucket.org/carlkl/mingw-w64-for-python/downloads I uploaded
7z-archives for mingw-w64 and for OpenBLAS-0.2.10 for 32 bit and for 64
bit.
To use mingw-w64 for Python >= 3.3 you have to manually tweak the so called
specs file - see readme.txt in the archive.
Regards
Carl
2014-
On Mon, Jul 28, 2014 at 8:46 AM, Sebastian Berg
wrote:
> On Mo, 2014-07-28 at 14:37 +0200, Eelco Hoogendoorn wrote:
>> To rephrase my most pressing question: may np.ones((N,2)).mean(0) and
>> np.ones((2,N)).mean(1) produce different results with the
>> implementation in the current master? If so,
On Mo, 2014-07-28 at 14:37 +0200, Eelco Hoogendoorn wrote:
> To rephrase my most pressing question: may np.ones((N,2)).mean(0) and
> np.ones((2,N)).mean(1) produce different results with the
> implementation in the current master? If so, I think that would be
> very much regrettable; and if this is
To rephrase my most pressing question: may np.ones((N,2)).mean(0) and
np.ones((2,N)).mean(1) produce different results with the implementation in
the current master? If so, I think that would be very much regrettable; and
if this is a minority opinion, I do hope that at least this gets documented
i
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