Hello everybody,
We are organizing a new conference on Python in Chicago (May 29-30) with focus
on Numerical Applications, Machine Learning and Web:
http://mdp.cdm.depaul.edu/DePy2015/default/index
We are looking for participants, speakers, and sponsors. Please register and
submit a subm
coverts to C/JS/OpenCL a common subset of
those languages. But it does what it advertises. It is written in pure python
and implemented and implemented in a single file.
Massimo
On Feb 16, 2013, at 10:13 AM, Ronan Lamy wrote:
> Le 16/02/2013 16:08, Massimo DiPierro a écrit :
>> Sorry for
Sorry for injecting... Which page is this about?
On Feb 16, 2013, at 9:59 AM, Ronan Lamy wrote:
> Le 15/02/2013 07:11, Travis Oliphant a écrit :
>
>> This page is specifically for Compiler projects that either integrate
>> with or work directly with the CPython run-time which is why PyPy is not
On May 22, 2012, at 10:12 AM, Robert Kern wrote:
> On Tue, May 22, 2012 at 4:09 PM, Massimo DiPierro
> wrote:
>> One more questions (since this list is very useful. ;-)
>>
>> If I have a numpy array of arbitrary shape, is there are a way to
>> sequentially
One more questions (since this list is very useful. ;-)
If I have a numpy array of arbitrary shape, is there are a way to sequentially
loop over its elements without reshaping it into a 1D array?
I am trying to simplify this:
n=product(data.shape)
oldshape = data.shape
newshape = (n,)
data.resh
Thank you this does it.
On May 22, 2012, at 9:59 AM, Robert Kern wrote:
> On Tue, May 22, 2012 at 3:47 PM, Massimo DiPierro
> wrote:
>> Thank you. I will look into numexpr.
>>
>> Anyway, I do not need arbitrary expressions. If there were something like
>>
] += c*b[i:i+n]
print time.time()-t0
the second "possible" solution appears 1000x faster then the former in my tests
and uses little extra memory. It is only 2x slower than b*=c.
Any reason not to do it?
On May 22, 2012, at 9:32 AM, Dag Sverre Seljebotn wrote:
> On 05/22/2012 04:2
05/22/2012 04:25 PM, Massimo DiPierro wrote:
>> hello everybody,
>>
>> first of all thanks to the developed for bumpy which is very useful. I am
>> building a software that uses numpy+pyopencl for lattice qcd computations.
>> One problem that I am facing is that I n
hello everybody,
first of all thanks to the developed for bumpy which is very useful. I am
building a software that uses numpy+pyopencl for lattice qcd computations. One
problem that I am facing is that I need to perform most operations on arrays in
place and I must avoid creating temporary arr
