[Numpy-discussion] NumPy EIG much slower than MATLAB EIG

[David Cournapeau]

On Mon, Apr 2, 2012 at 4:45 PM, Chris Barker <chris.barker at noaa.gov> wrote:

> On Mon, Apr 2, 2012 at 2:25 AM, Nathaniel Smith <njs at pobox.com> 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).

David
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