Cython and number it is...
they definitely rule!
But of course I am also interfacing my python code (with all the
structuring and UI and object orientation) with some sse and fortran.
if u can get a grip of programming fortran/sse, they work too
On 12/7/14, Mark Lawrence wrote:
> On 07/12/2014
I have been using Anaconda's (Continnum) conda installation for system
installation (python 2.7) and for python 3
conda lets us maintain diferent environments with different python and
different combinations of other packages like numpy etc...
sure not to disappoint!
On 10/12/14, Albert-Jan Ros
loops and not to
distract us to the operation done inside the loop.
right?
On Wed, Aug 6, 2014 at 6:09 PM, Peter Otten <__pete...@web.de> wrote:
> Gayathri J wrote:
>
> > Dear Peter
> >
> > Yes the f[t] or f[:,:,:] might give a marginal increase,
>
> The spe
Dear Peter
Yes the f[t] or f[:,:,:] might give a marginal increase, but then i need
to do further operations using the indices, in which case this wouldnt help
Dear Wojciech
np.flat() works if u dont care about the indices and only the matrix/array
values matter.
but if the matters, flatten
Dear Peter
Below is the code I tried to check if itertools.product() was faster than
normal nested loops...
they arent! arent they supposed to be...or am i making a mistake? any idea?
**
*# -*- coding: utf-8 -*-*
*import numpy as np*
