[SciPy-User] [ANN] Bottleneck 0.5.0 released
Sat Aug 13 14:05:10 CDT 2011
found the problem,
I used a too old version of numpy,
( wouldn't it be an idea to replace line 17 in __init__.py with "print 'requires at least numpy 1.5.1"
now the fast routines are working ...
... at least sometimes
... at least on some computers
What I've seen until now:
Computer 1: numpy 1.4, so it uses slow routines: functional ok
Computer 2: exactly the same python + libs: screen starts to "blink" to black a few times (for about
half a second, with an interval about 2 seconds),
after 10 times, the screen is filled with a repeating part of the screen and computer hangs totally.
Computer 2: numpy 1.6.1 : first program run, screen "blinks" black once, the fast bottleneck
routines are use, and they function ok.
Second run of the same program: screen blinks blank once, after a few seconds, the screen is again
filled with a smaal repating part of the screen and the computer hangs totally.
Any ideas ?
Is the GPU used with these routines ?
On 13-08-2011 17:09, Christoph Gohlke wrote:
> On 8/13/2011 6:54 AM, Stef Mientki wrote:
>> is it possible to create a windows executable
>> (a lot of windows users can't compile C-code).
>> I tried the prebuild versions from:
>> but the fast routines are all missing there.
> I don't see anything missing. Tests and benchmarks yield expected
> results using numpy 1.6.1.
> What's the output of `import bottleneck as bn;bn.test()` (requires nose
>> On 13-06-2011 23:35, Keith Goodman wrote:
>>> Bottleneck is a collection of fast NumPy array functions written in
>>> Cython. It contains functions like median, nanmedian, nanargmax,
>>> move_max, rankdata.
>>> The fifth release of bottleneck adds four new functions, comes in a
>>> single source distribution instead of separate 32 and 64 bit versions,
>>> and contains bug fixes.
>>> J. David Lee wrote the C-code implementation of the double heap moving
>>> window median.
>>> New functions:
>>> - move_median(), moving window median
>>> - partsort(), partial sort
>>> - argpartsort()
>>> - ss(), sum of squares, faster version of scipy.stats.ss
>>> - Single source distribution instead of separate 32 and 64 bit versions
>>> - nanmax and nanmin now follow Numpy 1.6 (not 1.5.1) when input is all NaN
>>> Bug fixes:
>>> - #14 Support python 2.5 by importing `with` statement
>>> - #22 nanmedian wrong for particular ordering of NaN and non-NaN elements
>>> - #26 argpartsort, nanargmin, nanargmax returned wrong dtype on 64-bit Windows
>>> - #29 rankdata and nanrankdata crashed on 64-bit Windows
>>> mailing list
>>> mailing list 2
>>> SciPy-User mailing list
>> SciPy-User mailing list
> SciPy-User mailing list
More information about the SciPy-User