On Dec 8, 5:43 am, "David Joyner" <[EMAIL PROTECTED]> wrote:
> On Mon, Dec 8, 2008 at 5:48 AM, Joost Witteveen <[EMAIL PROTECTED]> wrote:
<SNIP>
> > As I saw matplotlib/pylab being mentioned, in combination with slowdowns, I
> > thought I'd mention that plotting in pylab itself goes progressively slower.
> > On a system here, running the following:
>
> > import pylab
> > import time
> > n=300
> > m=100
> > for i in range(n):
> > start=time.time()
> > pylab.plot(range(m), [pylab.sin(pylab.pi*j/(m+0.0)) for j in range(m)])
> > pylab.savefig("name%04i.eps"%i)
> > print "plotting took %f sec"%(time.time()-start)
>
> > Will print "plotting took 0.051967 sec" for the second run (first goes
> > slower), but then the time to plot the next plots goes slowly up, to about
> > 0.55 sec after 300 plots.
>
> Thanks. That is more than a 10-fold increase!
>
> Michael: could this contribute significantly to the slowness of the
> plot Fourier
> series you mentioned in the other thread?
I am not sure. Do we even use pylab? I thought we were using straight
matplotlib. We should investigate *why* pylab gets slower and slower
or at least ping the right people upstream so they can take a look.
Either way, we should either start using _fast_float for those plots
or alternatively use the much fast (30 times IIRC) code that rjf
posted in the other thread. The issue of general slowdown is something
we are doing due to the way we use Maxima, but Simon already opened a
ticket for that.
Feel free to open a ticket to improve the performance of piecewise in
that regard.
Cheers,
Michael
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