[Numpy-discussion] NumPy EIG much slower than MATLAB EIG
Mon Apr 2 11:04:36 CDT 2012
On Mon, Apr 2, 2012 at 4:45 PM, Chris Barker <email@example.com> wrote:
> On Mon, Apr 2, 2012 at 2:25 AM, Nathaniel Smith <firstname.lastname@example.org> wrote:
> > To see if this is an effect of numpy using C-order by default instead of
> > Fortran-order, try measuring eig(x.T) instead of eig(x)?
> Just to be clear, .T re-arranges the strides (Making it Fortran
> order), butyou'll have to make sure your ariginal data is the
> transpose of whatyou want.
> I posted this on slashdot, but for completeness:
> the code posted on slashdot is also profiling the random number
> generation -- I have no idea how numpy and MATLAB's random number
> generation compare, nor how random number generation compares to
> eig(), but you should profile them independently to make sure.
While this is true, the cost is most likely negligeable compared to the
cost of eig (unless something weird is going on in random as well).
-------------- next part --------------
An HTML attachment was scrubbed...
More information about the NumPy-Discussion