I'm doing some tests with operations on numpy matrices in Python. As an
example, it takes about 3000 seconds to compute eigenvalues and eigenvectors
using scipy.linalg.eig(a) for a matrix 6000x6000. Is it an acceptable time? Any
suggestions to improve? Does C++ perform better with matrices? Another thing to
consider is that matrices I'm processing are heavily sparse.
Do they implement any parallelism? While my code is running, one of my cores is
100% busy, the other one 30% busy.
--
https://mail.python.org/mailman/listinfo/python-list
