drife wrote:

Thanks John. Those are the steps I followed, and to no avail.

Interestingly, I downloaded and installed SciPy, and ran the

same eigenvector problem. SciPy greatly speeds up the

calculation...was 1.5 hours using Numeric, now only 15 min

with SciPy.

Unfortunately, SciPy only solves ordinary and generalized

eigenvalue problems of a square matrix. They do not test

to see if the matrix is symmetric, then call the appropriate

routine from LAPACK.

Note that scipy exposes most of lapack, so you could make the call you need

directly:

In [3]: scipy.linalg.lapack.get_lapack_funcs?

Type: function

Base Class: <type 'function'>

String Form: <function get_lapack_funcs at 0x40402c6c>

Namespace: Interactive

File: /usr/lib/python2.3/site-packages/scipy/linalg/lapack.py

Definition: scipy.linalg.lapack.get_lapack_funcs(names, arrays=(), debug=0,

force_clapack=1)

Docstring:

Return available LAPACK function objects with names.

arrays are used to determine the optimal prefix of

LAPACK routines.

If force_clapack is True then available Atlas routine

is returned for column major storaged arrays with

rowmajor argument set to False.

Cheers,

f