[Numpy-discussion] Assignment from a list is slow in Numarray
Nadav Horesh
nadavh at visionsense.com
Mon Sep 20 01:12:02 CDT 2004
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 at e.math.helsinki.fi]
Sent: Sun 19-Sep-04 20:35
To: numpy-discussion at lists.sourceforge.net
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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