On Mon, Apr 2, 2012 at 4:45 PM, Chris Barker <chris.bar...@noaa.gov> wrote:
> On Mon, Apr 2, 2012 at 2:25 AM, Nathaniel Smith <n...@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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