RE: Assignment from a list is slow in Numarray

Yo may try the aging module TableIO (http://php.iupui.edu/~mmiller3/python/). 
Just replace "import Numeric" by "import numarray as Numeric". It may give up 
to two-fold speed improvement. Since you have C skills, you might update the 
small C source to interact directly with numarray.

  Nadav


-----Original Message-----
From:   Timo Korvola [mailto:tkorvola@xxxxxxxxxxxxxxxxxx]
Sent:   Sun 19-Sep-04 20:35
To:     numpy-discussion@xxxxxxxxxxxxxxxxxxxxx
Cc:     
Subject:        [Numpy-discussion] Assignment from a list is slow in Numarray
Hello,

I am new to the list, sorry if you've been through this before.

I am trying to do some FEM computations using Petsc, to which I have
written Python bindings using Swig.  That involves passing arrays
around, which I found delightfully simple with
NA_{Input,Output,Io}Array.  Numeric seems more difficult for output
and bidirectional arrays.

My code for reading a triangulation from a file went roughly
like this:

coord = zeros( (n_vertices, 2), Float)
for v in n_vertices:
    coord[ v, :] = [float( s) for s in file.readline().split()]

This was taking quite a bit of time with ~50000 vertices and ~100000
elements, for which three integers per element are read in a similar
manner.  I found it was faster to loop explicitly:

coord = zeros( (n_vertices, 2), Float)
for v in n_vertices:
    for j, c in enumerate( [float( s) for s in file.readline().split()]):
        coord[ v, j] = c

Morally this uglier code with an explicit loop should not be faster
but it is with Numarray.  With Numeric assignment from a list has
reasonable performance.  How can it be improved for Numarray?

-- 
        Timo Korvola            <URL:http://www.iki.fi/tkorvola>


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