On Tue, Mar 20, 2012 at 5:59 PM, Chris Barker wrote:
> Warren et al:
>
> On Wed, Mar 7, 2012 at 7:49 AM, Warren Weckesser
> wrote:
> > If you are setup with Cython to build extension modules,
>
> I am
>
> > and you don't mind
> > testing an unreleased and experimental reader,
>
> and I don't.
>
On 03/20/2012 09:20 PM, Dag Sverre Seljebotn wrote:
> On 03/20/2012 12:56 PM, Francesc Alted wrote:
>> On Mar 20, 2012, at 2:29 PM, Dag Sverre Seljebotn wrote:
>>> Francesc Alted wrote:
>>>
On Mar 20, 2012, at 12:49 PM, mark florisson wrote:
>> Cython and Numba certainly overlap. Howeve
On 03/20/2012 12:56 PM, Francesc Alted wrote:
> On Mar 20, 2012, at 2:29 PM, Dag Sverre Seljebotn wrote:
>> Francesc Alted wrote:
>>
>>> On Mar 20, 2012, at 12:49 PM, mark florisson wrote:
> Cython and Numba certainly overlap. However, Cython requires:
>
>1) learning another l
Hello,
I've reported http://projects.scipy.org/numpy/ticket/2085 and Ralf
asked for bringing that up here: is anyone able to replicate the
problem described in that ticket?
The debian bug tracking the problem is:
http://bugs.debian.org/cgi-bin/bugreport.cgi?bug=664672
Cheers,
--
Sandro Tosi (aka
Warren et al:
On Wed, Mar 7, 2012 at 7:49 AM, Warren Weckesser
wrote:
> If you are setup with Cython to build extension modules,
I am
> and you don't mind
> testing an unreleased and experimental reader,
and I don't.
> you can try the text reader
> that I'm working on: https://github.com/Warr
On Mon, Mar 19, 2012 at 6:45 PM, Andreas H. wrote:
> Hi all,
>
> I have troube installing numpy in a virtual environment on a SuSE
> Enterprise 11 server (ppc64).
>
> Here is what I did:
>
>curl -O https://raw.github.com/pypa/virtualenv/master/virtualenv.py
>python virtualenv.py --distrib
On Mar 20, 2012, at 2:29 PM, Dag Sverre Seljebotn wrote:
> Francesc Alted wrote:
>
>> On Mar 20, 2012, at 12:49 PM, mark florisson wrote:
Cython and Numba certainly overlap. However, Cython requires:
1) learning another language
2) creating an extension module --
I doubt Theano is already as smart as you'd want it to be right now,
however the core mechanisms are there to perform graph optimizations and
move computations to GPU. It may save time to start from there instead of
starting all over from scratch. I'm not sure though, but it looks like it
would be
Sorry, forgot to CC list on this. Lines staring with single greater-than are
mine.
--
Sent from my Android phone with K-9 Mail. Please excuse my brevity.
Dag Sverre Seljebotn wrote:
Francesc Alted wrote:
>On Mar 20, 2012, at 12:49 PM, mark florisson wrote:
>>> Cython and Numba certainly ov
We talked some about Theano. There are some differences in project goals which
means that it makes sense to make this a seperate project: Cython wants to use
this to generate C code up front from the Cython AST at compilation time; numba
also has a different frontend (parsing of python bytecode)
On Mar 20, 2012, at 12:49 PM, mark florisson wrote:
>> Cython and Numba certainly overlap. However, Cython requires:
>>
>>1) learning another language
>>2) creating an extension module --- loading bit-code files and
>> dynamically executing (even on a different machine from the o
Yes, that's the behaviour that I expect setting the 'shrink' keyword to 'False'
> Now, just to be clear, you'd want
> 'np.ma.masked_values(...,shrink=False) to create a maked array w/ a
> full boolean mask by default, right ?
___
NumPy-Discussion mailing
This sounds a lot like Theano, did you look into it?
-=- Olivier
Le 20 mars 2012 13:49, mark florisson a écrit :
> On 13 March 2012 18:18, Travis Oliphant wrote:
> >>>
> >>> (Mark F., how does the above match how you feel about this?)
> >>
> >> I would like collaboration, but from a technical
On Tue, Mar 20, 2012 at 5:13 AM, Matthieu Rigal wrote:
> In fact, I was hoping to have a less memory and more speed solution.
which do often go together, at least for big problems -- pushingm
emory around often takes more time than the computation itself.
> At the end, I am rather interested by
On 13 March 2012 18:18, Travis Oliphant wrote:
>>>
>>> (Mark F., how does the above match how you feel about this?)
>>
>> I would like collaboration, but from a technical perspective I think
>> this would be much more involved than just dumping the AST to an IR
>> and generating some code from the
I didn't try it, but I think that Theano and numexpr should be able to
make them faster.
[1] http://deeplearning.net/software/theano/
[2] https://code.google.com/p/numexpr/
Fred
On Tue, Mar 20, 2012 at 9:05 AM, Matthieu Rigal wrote:
> Auto-answer, sorry,
>
> Well, actually I made a mistake lowe
On 20 Mar 2012, at 14:40, Chao YUE wrote:
> I would be in agree. thanks!
> I use gawk to separate the file into many files by year, then it would be
> easier to handle.
> anyway, it's not a good practice to produce such huge line txt files
Indeed it's not, but it's also not good practice to
I would be in agree. thanks!
I use gawk to separate the file into many files by year, then it would be
easier to handle.
anyway, it's not a good practice to produce such huge line txt files
Chao
2012/3/20 David Froger
> Hi,
>
> I think writing a Python script that convert your txt file to o
Hi,
I think writing a Python script that convert your txt file to one netcdf file,
reading the txt file one line at a time, and then use the netcdf file normally
would be a good solution!
Best,
David
Excerpts from Chao YUE's message of mar. mars 20 13:33:56 +0100 2012:
> Dear all,
>
> I receiv
Auto-answer, sorry,
Well, actually I made a mistake lower... that you may have noticed...
On the faster (your) solution, even with a cleaner use of the out parameter,
the fact that the all has then to be used with parameter axis=0 takes more
time and makes it actually slower than the initial sol
Dear all,
I received a file from others which contains ~30 million lines and in size
of ~500M.
I try read it with numpy.genfromtxt in ipython interactive mode. Then
ipython crashed.
The data contains lat,lon,var1,year, the year ranges from 1001 to 2006.
Finally I want to write the
data to netcdf f
Hi Richard,
Thanks for your answer and the related help !
In fact, I was hoping to have a less memory and more speed solution. Something
equivalent to a "raster calculator" for numpy. Wouldn't it make sense to have
some optimized function to work on more than 2 arrays for numpy anyway ?
At the
Pauli, Chris,
Thanks for your inputs.
Pauli, I think that when f2py encounters a STOP statement, it just
stops the execution of the process. Alas, it's the same process as the
interpreter... So we need a trick not to interrupt the whole process.
I eventually resorted to patching f2py as suggested
Gökhan,
By default, the mask of a MaskedArray is set to the special value
`np.ma.nomask`. In other terms::
np.ma.array(...) <=> np.ma.array(..., mask=np.ma.nomask)
In practice, np.ma.nomask lets us quickly check whether a MaskedArray
has a masked value : if its .mask is np.ma.nomask, then no m
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