[Numpy-discussion] Numpy performance vs Matlab.
Fri Jan 9 07:50:29 CST 2009
> I understand the weakness of the missing JITcompiler in Python vs Matlab,
> that's why I invistigated numpy vectorization/broadcast.
> (hoping to find a cool way to write our code in fast Numpy)
> I used the page http://www.scipy.org/PerformancePython to write my code
> efficiently in Numpy.
> While doing it I found one issue.
> To have pretty code, I created p0 and p1 arrays of indexes.
I must admit I don't quite understand what you are trying to do, and what
your problem is.
If you just want to do
Out[:,:] = In[:,:]
there is no need for meshgrids (ogrid), for-loops, or whatever.
It is brain dead to use nested for-loops or ogrid for this purpose in
NumPy. It is equally foolish to use nested for loops or meshgrid for this
purpose in Matlab. If you do, I would seriously question your competence.
By the way, you can index ogrid with more than one dimension:
p = numpy.ogrid[:m, :n]
Out[p] = In[p]
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